improvement plant nutrient management

i

Symposium Proceedings of The Water Professionals’ Day

WATER RESOURCES RESEARCH IN SRI LANKA

Editors N.D.K. Dayawansa Ranjith Premalal De Silva

October 01, 2015

Cap-Net Lanka Postgraduate Institute of Agriculture (PGIA) & Geo-Informatics Society of Sri Lanka

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WATER RESOURCES RESEARCH IN SRI LANKA

Panel of Reviewers Prof. Ranjith Premalal De Silva Prof. M.I.M. Mowjood Dr. (Mrs.) N.D.K. Dayawansa

ISBN 978-955-1308-20-9 Copyright © 2015 by GISSL. All rights reserved. Responsibility of the contents of the papers in this proceedings rests with authors.

Water Professionals’ Day Symposium – October 01, 2015


WATER RESOURCES RESEARCH IN SRI LANKA TABLE OF CONTENTS FOREWORD................................................................................................................ v Climate Variability, Water and Society ........................................................................ 1 A Glimpse on Rainfall Regime of Sri Lanka in 2014............................................ 3 A.B. Abeysekera, B.V.R. Punyawardena and K.H.M.S. Premalal Characterization of Alternative Wet and Dry Spells using Rainfall Indices: A Case Study in Awlegama, Kurunegala .............................................. 15 T. Sellathurai, L.W. Galegedara and M.I.M. Mowjood Economic Status of Rural Households with Rainwater Harvesting Systems: A Case Study in Monaragala District .................................................. 25 W.D.P. Sandamali and A. Nanthakumaran Shallow Groundwater Use Through Agro Wells in Dry & Intermediate Zones of Sri Lanka and Present Health Hazards ............................................... 31 C. S. De Silva Water and Ecosystems ................................................... Error! Bookmark not defined. Effects of Construction and Operation of Mini Hydropower Plants on Fish Fauna Endemic to Sri Lanka - A Case Study on Kelani River Basin....... 45 E.I.L. Silva, R.A.S.N. Jayawardhana, N.P.P. Liyanage and E.N.S. Silva

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Variation of Diversity of Dragonfly in Paddy Field Ecosystem, Awlegama, Wariyapola, Sri Lanka with respect to Different Growth Stages and Water Quality ........................................................................................................ 57 G.W.R.W.M.R.M.W.K. Kirinde, R.P.S.P. Chandrasiri, M.I.M Mowjood and N.D.K. Dayawansa Pollution Sources of Negombo Estuary in Negombo Municipal Council Area and the Contribution of Drainage Canal System to Estuary Pollution ... 67 G.D.S. Priyadarshika, N.D.K. Dayawansa and S. Pathmarajah Soil Erosion and Sediment Transport in Bibili Oya Watershed in Kelani River Basin ............................................................................................................. 83 K. Thuraisingham and V.P.A. Weerasinghe Present Status of Eco-units of Micro Tanks in Agbopura Cascade, Kanthale and Their Implications on Hydrology and Other Ecosystem Functions ................................................................................................................ 95 K.M.G.S.R. Senevirathna and H.M.G.S.B. Hitinayake Water Quality and the Environment........................................................................ 115 Water Quality Analysis along Mahaweli River in Upper Mahaweli Catchment Area of Sri Lanka ............................................................................ 117 H.K.I.J. Thilakarathne, N.S. Withanage, R.M.C.W.M. Rathnayake and K.M.A. Kendaragama Phosphorus Removal from Wastewater Using Soil as an Adsorbent ............. 129 H. M. C. M. Jayawardana and D. M. S. H. Dissanayaka, P. P. U. Kumarasinghe and M.I.M. Mowjood Impact of Urban Land Use in Anuradhapura City on Water Quality of Upper Malwathu Oya Stream ............................................................................. 139 R.M.G. Madushanka, J.P.H.U. Jayaneththi, D.M.S.H. Dissanayaka and M.G.T.S. Amarasekara


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FOREWORD Population growth, economic development, increased demand for food and energy have exerted a great pressure on the ecosystems all over the world. More and more agricultural lands are required to cater to the increasing demand for food hence, important ecosystems such as forests, mangroves, wetlands are converted into agricultural lands at alarming rates. Most of these sectors attempt to achieve their goals individually without realizing the existing connectivity between them and the ecosystems. However, it is important that these common development goals should be achieved without compromising the functions of valuable ecosystems which play an important role in ensuring water and food security. Establishment of Inter sectoral linkages is vital for the integrated management of water and other natural resources at local, national and transboundary scales. Identifying the timely importance, the Water Professionals’ Day Symposium 2015 was organized under the theme of ‘Water-Food-Ecosystem Nexus: Understanding the inter-sectoral linkages for sustainable water management’. The Water Professionals’ Day Proceedings - 2015 includes twelve research papers covering three main aspects related to water namely; Climate variability, Water and society, Water and ecosystems and Water quality and the environment. It is a great achievement to publish the proceedings on the day of the symposium. The support extended by Mr. Ajith Jayasekare in compiling and formatting the proceedings is greatly appreciated. Also, the contribution of reviewers, authors, sponsors and others are kindly acknowledged. We sincerely hope that the Water Professionals’ Day Symposium – 2015 will provide an outstanding contribution towards understanding the nexus between different water use sectors in achieving sustainability in water use and management.

Dr. (Ms.) N.D.K. Dayawansa Professor Ranjith Premalal De Silva Editors

Climate Variability, Water and Society

A Glimpse on Rainfall Regime of Sri Lanka in 2014 A.B. Abeysekera, B.V.R. Punyawardena Natural Resources Management Centre, Department of Agriculture, Peradeniya and K.H.M.S. Premalal Department of Meteorology, Colombo

ABSTRACT In the light of high variability of seasonal rainfall in Sri Lanka during the recent past under a changing and variable climate, this study has attempted to examine the spatial and temporal pattern of rainfall anomalies experienced during year 2014 which resulted several negative impacts on the economy. This study has covered all three major climatic zones of the country using 24 rain gauge stations. Monthly rainfall anomaly percentages were calculated using the most recent decade from 2004 to 2013 as the base period. It has revealed that 2014 Yala season has been a drought burdened season in all over the country. Rainfall anomalies during this growing season were more severe during the First Inter Monsoon Season (MarchApril) and early part of the South West Monsoon season. Even though some negative anomalies were evident at the beginning of the 2014/15 Maha season during Second Inter Monsoon period (October - November) especially in Wet and Intermediate zones, it was not as severe as during the first of the year. During the North East Monsoon season (December - February), its first month, December experienced very heavy rains causing severe floods in most parts of the country. However, at the latter of the season, North East Monsoon turned in to relatively weaker resulting below normal rains in most parts of the island. However, due to availability of good water storages in almost all irrigation tanks and reservoirs in the country on account of heavy rains during December, it did not result in severe depletion of water levels. This nature of abnormal rhythm of country's rainfall may continue to occur in future due to intensified hydrological cycle in a warming world.

INTRODUCTION Productivity of agriculture and water resources in Sri Lanka are highly dependent on the spatial and temporal distribution of seasonal rainfall in a given year. The year 2014 was a year where both extremes of seasonal rainfall were evident in a quick succession. Below normal rainfall spanning more than five to six months during first half of the year was reported in certain geographical regions of the country with severe depletion of water levels in reservoirs and with subsequent losses in both irrigated and rainfed agriculture. In certain places, “absolute droughts “ were even evident – is one during which 0.3 mm of rain or more is not recorded on any

A.B. Abeysekera, B.V.R. Punyawardena and K.H.M.S. Premalal

day during a period of at least 15 consecutive days. In contrary, the latter part of the year was abnormally wet especially in the Dry zone with both merits and demerits on water resources and agriculture sector. Due to heavy rains experienced in the eastern flank of the Central Highlands during last few days of October, a massive landslide devastated the Meeriyabeddda at Koslanda resulting 38 villagers either missing or dead after giving an initial toll of more than 300 (ColomboPage, 2014). Heavy flooding was evident in the Dry zone since 19 December 2014 in 18 districts affecting an estimated 675,000 people. Six people had been reported dead due to floods and landslides. It was reported that 3,175 houses were fully destroyed and 11,366 houses were partially damaged due to floods (Sri Lanka Red Cross, 2014). Out of the total 72 major manmade tanks and reservoirs in Sri Lanka, 53 were overspilling for several days exacerbating damages to agricultural lands. Extremely heavy rainfall was observed during 16th -21st December in Eastern and North Central regions (Agro-climatology Division, Department of Agriculture, undated).

Objectives This study was undertaken to examine the anomalies of monthly rainfall during year 2014 covering the entire island. This piece of information is of particular importance to agriculture and water resource planners to explain any departures from their usual performance during the year.

METHODOLOGY To study the variation of the pattern of rainfall during 2014, monthly rainfall data were collected from March 2014 to February 2015, from 24 rain gauge stations covering three major climatic zones in Sri Lanka (Figure 1). This 24 stations were scattered all over the island, as 10 representing Wet zone, 6 representing Intermediate zone and 8 representing Dry zone, including Agro-met stations, Met Stations and Estates. For the comparison, 10 year averages were calculated for each station for the period of 2004 to 2013. Monthly precipitation anomaly percentage is a standard monitoring index to find the drought or flood conditions. Therefore, monthly precipitation anomaly percentage was calculated for the collected data set. The positive and negative anomalies were taken to verify the pattern of rainfall during 2014 Yala season and 2014/15 Maha season.

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A Glimpse on Rainfall Regime of Sri Lanka in 2014

Figure 1: Rainfall observation stations used in the study

RESULTS AND DISCUSSION Tables 1, 2, 3 and 4 show the Monthly Total Rainfall (MRF) values and monthly precipitation anomaly percentages (Anomaly) for the selected locations in the study during First Inter Monsoon (FIM) season, South West monsoon (SWM) season, Second Inter Monsoon (SIM) season and North East Monsoon (NEM) season, respectively.


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First Inter Monsoon (FIM) season Table 1 presents the variation of rainfall pattern during First Inter Monsoon (FIM) period. Table 1: Variation of the rainfall pattern during First Inter Monsoon (FIM) season of the selected locations

Station

AER

Rathnapura

WL 1a

Bombuwela

WL 1b

Labuduwa

WL 2a

Henarathgoda

WL 3

Colombo

WL 3

Kenilworth

WM 1a

Mahavila (Gampola)

WM 2a

Peradeniya

WM 2b

Labookele

WU 2a

Sita-Eliya

WU 3

Batalagoda

IL 1a

Moneragala

IL 1c

Maho

IL 3

Kundasale

IM 3a

Loolecondera (Deltota)

IU 2

Bandarawela

IU 3c

Angunakolapalasse

DL 1b

Maha-Illuppallama

DL 1b

Polonnaruwa

DL 1c

Aralaganwila

DL 2b

Batticoloa

DL 2b

Trincomalee

DL 2b

Jaffna

DL 3

Ambalanthota

DL 5

March MRF Anomaly 144.4 -48.7 109.9 -40.9 61.7 -54.1 170.9 -1.6 144.8 1.0 93.0 -62.8 67.8 -49.6 12.1 -92.7 75.7 -43.8 47.6 -61.2 1.2 -99.1 26.8 -76.5 0.0 -100.0 12.9 -88.3 43.9 -72.0 24.3 -82.4 47.3 -56.0 0.0 -100.0 14.5 -84.6 15.8 -84.3 22.2 -77.7 5.3 -94.5 0.0 -100.0 50.3 -40.8

MRF 498.0 218.4 281.1 222.9 254.7 222.0 174.8 221.3 193.0 169.2 347.3 60.0 443.3 159.5 188.0 301.1 114.7 322.9 39.9 158.1 1.2 1.6 8.5 18.4

April Anomaly 18.6 -32.0 10.4 -0.1 -17.0 -52.6 -31.9 -13.4 -20.1 1.3 63.8 -77.2 97.8 -3.5 -28.7 38.9 -10.3 108.8 -65.0 22.3 -98.7 -98.3 -90.9 -82.0

During the First Inter-monsoon (FIM) season, a negative anomaly of rainfall can be observed in almost all selected locations, irrespective to the climatic zones of the country. This below normal rainfall may have led to frequent insufficient water storage conditions of tanks and reservoirs during Yala season for cultivation, drinking, household use and environmental purposes.

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The negative anomaly of rainfall observed during FIM has extended to the first month of SWM period. But the dry areas of the island have shown above normal rains. This situation has suddenly changed in June resulting heavy rains in the Wet zone. Massive floods which were reported during this period correspond with this above normal rains. But this situation lasted only for a very short period of time and thus in July, again below normal rains have experienced all over the country. However at the tail end of the season, situation has changed in to a mixed trend depending on the geographical location.

South West Monsoon (SWM) season Table 2 presents the variation of the rainfall pattern during South West Monsoon (SWM) season.


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Table 2: Variation of the rainfall pattern during South West Monsoon (SWM) season of the selected locations May Station

AER

Rathnapura

WL 1a

Bombuwela

WL 1b

Labuduwa

WL 2a

Henarathgoda

WL 3

Colombo

WL 3

Kenilworth Mahavila (Gampola)

WM 1a

Peradeniya

WM 2b

Labookele

WU 2a

Sita-Eliya

WU 3

Batalagoda

IL 1a

Moneragala

IL 1c

Maho

IL 3

Kundasale

IM 3a

Loolecondera

IU 2

Bandarawela

IU 3c

8

WM 2a

June

July

August

September

MRF 260.8 249.7 261.0 142.9 83.5 169.0

Anomaly -40.1 -39.7 -10.6 -51.2 -71.2 -79.2

MRF 533.9 446.8 260.2 550.1 238.7 1000.0

Anomaly 27.5 55.2 7.2 185.8 31.9 23.7

MRF 250.9 70.9 91.4 44.2 35.2 516.0

Anomaly -20.9 -62.5 -51.1 -67.5 -71.8 -30.0

MRF 607.5 427.5 512.8 291.4 225.4 684.0

Anomaly 92.3 91.3 135.1 143.5 72.2 20.3

MRF 588.4 300.4 422.5 166.3 312.7 524.0

Anomaly 61.3 5.3 57.1 -20.1 73.0 -19.2

125.6 164.2 134.8 234.6 166.2 73.3 287.3 94.5 147.0 232.0

-37.0 40.5 -38.3 54.6 23.2 -28.5 286.2 24.8 -8.5 83.8

355.4 222.2 474.0 127.2 60.2 0.0 22.0 158.2 169.5 22.2

33.8 42.8 33.1 -11.7 -42.6 -100.0 -41.8 92.9 20.6 -53.2

194.2 88.1 430.7 73.1 47.9 78.4 38.0 28.1 78.9 3.3

-10.1 -38.9 38.8 -40.1 -41.6 74.6 -11.0 -54.5 -49.9 -93.3

261.6 147.9 360.5 91.5 141.3 140.0 105.3 71.9 89.2 72.4

47.9 30.5 70.3 -5.8 95.3 85.7 79.9 4.3 -8.9 15.1

318.8 230.6 332.9 171.8 241.0 88.9 227.9 133.7 227.1 159.6

38.2 69.7 16.8 22.7 124.4 -20.2 259.6 62.4 84.7 44.9



May Station Angunakolapa lasse MahaIlluppallama

June

July

August

September

AER

MRF

Anomaly

MRF

Anomaly

MRF

Anomaly

MRF

Anomaly

MRF

Anomaly

DL 1b

120.9

31.3

37.5

-26.9

14.8

-62.2

16.5

-77.2

55.8

-40.3

DL 1b

195.2 77.8 115.5 174.2 57.0 80.6 77.7

299.2 47.6 87.5 619.8 6.9 42.2 18.8

2.0 0.0 0.0 0.0 4.7 8.1 27.4

-79.6 0.0 -100.0 -100.0 -59.5 -26.4 -41.5

0.0 0.0 0.0 0.0 25.2 1.6 9.6

-100.0 -100.0 -100.0 -100.0 -40.3 -89.6 -61.9

25.8 59.0 125.7 82.7 120.0 107.5 29.8

-32.1 24.6 99.5 90.1 39.3 90.9 -53.4

247.6 30.3 66.3 21.6 108.5

292.4 -40.0 39.3 -74.3 35.2 -48.9 -45.4

Polonnaruwa

DL 1c

Aralaganwila

DL 2b

Batticoloa

DL 2b

Trincomalee

DL 2b

Jaffna

DL 3

Ambalanthota

DL 5


35.7

50.3

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Second Inter Monsoon (SIM) season Variation of rainfall during second inter monsoon is presented in Table 3. Table 3. Variation of the rainfall pattern during Second Inter Monsoon (SIM) season of the selected locations October Station AER MRF Rathnapura WL 1a 878.6 Bombuwela WL 1b 526.4 Labuduwa WL 2a 591.2 Henarathgoda WL 3 47.5 Colombo WL 3 449.6 Kenilworth WM 1a 613.0 Mahavila (Gampola) WM 2a 471.4 Peradeniya WM 2b 519.2 Labookele WU 2a 534.9 Sita-Eliya WU 3 276.9 Batalagoda IL 1a 349.5 Moneragala IL 1c 427.5 Maho IL 3 314.9 Kundasale IM 3a 374.4 Loolecondera (Deltota) IU 2 562.6 Bandarawela IU 3c 391.2 Angunakolapalasse DL 1b 239.4 Maha-Illuppallama DL 1b 257.6 Polonnaruwa DL 1c 242.7 Aralaganwila DL 2b 270.4 Trincomalee DL 2b 160.3 Batticoloa DL 2b 184.1 Jaffna DL 3 262.1 Ambalanthota DL 5 273.7 Note: * indicate missing value in Henarathgoda

Anomaly 94.6 14.1 59.0 -88.6 27.5 -15.7 43.6 58.0 38.8 7.7 5.7 38.5 -14.2 56.2 79.5 27.6 48.9 -6.8 -20.4 -5.2 -42.3 2.8 13.3 85.4

November MRF Anomaly 283.7 -24.6 299.6 -21.4 308.6 -5.1 * * 278.8 -27.4 355.0 -23.5 335.2 19.9 241.4 -17.9 421.6 40.3 209.1 -21.9 287.6 -4.5 292.1 -20.3 309.4 16.7 300.9 27.6 343.0 -5.9 203.5 -26.9 162.2 -34.6 271.3 -2.2 442.7 48.3 629.0 75.7 429.5 21.4 521.1 42.7 496.4 23.8 218.8 -12.2

Rainfall anomaly percentages in the Second Inter Monsoon (SIM) season reveals that there is no strong positive or negative deviations in almost all locations under consideration in this study which pave the way for a promising Maha season.

North East Monsoon (NEM) season Table 4 presents the variation of rainfall during North East monsoon.

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Table 4: Variation of the rainfall pattern during North East Monsoon (NEM) season of the selected locations

Station

AER

Rathnapura

WL 1a

Bombuwela

WL 1b

Labuduwa

WL 2a

Henarathgoda

WL 3

Colombo

WL 3

Kenilworth

WM 1a

Mahavila (Gampola)

WM 2a

Peradeniya

WM 2b

Labookele

WU 2a

Sita-Eliya

WU 3

Batalagoda

IL 1a

Moneragala

IL 1c

Maho

IL 3

Kundasale

IM 3a

Loolecondera (Deltota)

IU 2

Bandarawela

IU 3c

Angunakolapalasse

DL 1b

December MRF Anomaly 425.1 -5.9 209.1 -54.7 342.4 -7.9 * * 476.5 35.2 314.0 -56.8 521.6 58.9 649.7 97.7 943.5 144.9 457.9 78.1 719.5 117.7 408.2 32.3 388.6 5.9 640.1 167.1 829.9 164.8 530.3 73.0 375.4 133.4

January MRF Anomaly 106.2 -71.8 90.1 -76.4 109.0 -66.5 0.0 -100.0 32.7 -91.5 20.0 -95.7 0.0 -100.0 16.0 -94.6 0.0 -100.0 5.4 -98.0 0.0 -100.0 25.0 -93.2 4.0 -98.5 13.5 -94.3 5.7 -98.4 14.9 -94.6 24.2 -90.2


February MRF Anomaly 287.5 -36.3 99.5 -78.4 113.9 -69.4 58.9 -85.9 122.5 -65.2 210.0 -71.1 185.7 -43.4 91.3 -72.2 233.2 -39.5 219.7 -14.6 112.0 -66.1 121.6 -60.6 40.4 -89.0 87.2 -63.6 275.3 -12.1 145.6 -52.5 81.6 -49.3

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Station

AER

Maha-Illuppallama

DL 1b

Polonnaruwa

DL 1c

Aralaganwila

DL 2b

Trincomalee

DL 2b

Batticoloa

DL 2b

Jaffna

DL 3

December MRF Anomaly 603.0 118.2

January MRF Anomaly 3.3 -98.8

February MRF Anomaly 82.0 -70.3

1100.3 1111.6 532.3 1164.2 251.6 431.9

82.7 74.8 36.2 13.6 0.9 12.5

196.1 261.9 184.1 217.7 18.1 71.4

Ambalanthota DL 5 Note: * indicate missing value in Henarathgoda

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260.7 289.6 91.5 550.2 8.7 192.5

-72.3 -79.1 -89.8 -96.3 -99.8 -95.0


-35.7 -8.2 -33.8 21.6 -92.2 -51.6


Northeast monsoon (NEM) season started in December with sharp positive anomalies, especially in the Dry and Intermediate zones. Angunakolapalasse, MahaIlluppallama, Polonnaruwa, Aralaganwila, Batticoloa and Ambalanthota areas have shown over 100% of positive anomalies. This very heavy spells during the month resulted massive floods all over the Dry zone. These rains washed out a large number of paddy tracts in the Dry zone resulting farmers to re-sow their paddy fields or to let abandon their cultivations. Nevertheless, this situation was changed in January and February, 2015 showing below normal rains all over the country.

CONCLUSIONS This study has revealed that 2014 Yala season has been a drought burdened season in all over the country. Rainfall anomalies during this growing season were more severe during the First Inter Monsoon Season (March-April) and early part of the South West Monsoon season. Even though some negative anomalies were evident at the beginning of the 2014/15 Maha season during Second Inter Monsoon period (October - November) especially in Wet and Intermediate zones, it was not as severe as during the first of the year. During the North East Monsoon season (December - February), its first month; December experienced very heavy rains causing severe floods in most parts of the country. However, at the latter of the season, North East Monsoon turned in to a relatively weaker resulting below normal rains. However due to availability of good water storages in almost all irrigation tanks and reservoirs in the country on account of heavy rains during December, it did not result in severe depletion of water levels of those surface water bodies. This nature of abnormal rhythm of country's rainfall may continue to occur in future due to intensified hydrological cycle in a warming world.

REFERENCES ColomboPage (2014). http://www.colombopage.com/archive_14B/Nov01_1414856657CH.php Sri Lanka Red Cross (2014). http://www.redcross.lk/news/over-675000-affected-ininclement-weather-in-sri-lanka/


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Characterization of Alternative Wet and Dry Spells using Rainfall Indices: A Case Study in Awlegama, Kurunegala T. Sellathurai Postgraduate Institute of Agriculture, University of Peradeniya L.W. Galegedara Grenfell Campus, Memorial University of Newfoundland, NL, Canada and M.I.M. Mowjood Faculty of Agriculture, University of Peradeniya

ABSTRACT The climate variability can be explained by using climatic indices. The strength of alternative wet and dry spells can determine the aerobic and anaerobic conditions which affect the soil biological, chemical and physical processes. Dry and wet spells were quantified using rainfall indices and non-rainy days in Awlwgama area in Kurunegala district. Fifteen rainfall indices were estimated to find out the extreme events using 30 years of rainfall data from the study area. The occurrences of wet and dry spell mostly range between 1-5 and 26–30, respectively. The intensity and number of dry spell increases during Maha season. In Yala season, continuous dry days per dry spell increases. The probabilities for 4, 12 and 20 days of dry spells were 49%, 17% and 8%, respectively. This alternative wetting and drying (AWD) cycle may alter the soil processes.

INTRODUCTION The physical, chemical and biological processes in an agricultural field are determined basically by the biotic and abiotic environments. The biotic variables are related to microbes, plants and animals while abiotic factors are related to physical, chemical and climatic conditions such as precipitation, temperature, CO2 enrichment, pH, etc., These components are interacted each other and collectively determine the system performance. The mobility and availability of plant nutrients are greatly influenced by biotic and abiotic components. The water regime in the paddy field depends on rainfall and/or irrigation and plays a major role on nutrient availability. Drying or wetting result in aerobic and anaerobic conditions in the field, respectively. The amount of water added at a time, irrigation interval, water holding capacity of soil, infiltration rate, and plant factors (uptake) determine the wet and dry conditions in the soil. All these factors are directly or indirectly related to rainfall variability.

T. Sellathurai, L.W. Galegedara and M.I.M. Mowjood

Studying the prevailing climate variability is important to elucidate the processes caused by alternate drying and wetting. Understanding the climate change induced variation of extreme events that are directly influencing the paddy cultivation would be of important in deciding the agronomic practices. Therefore, a study was conducted to characterize the wet and dry spells by assessing the rainfall variability using rainfall indices.

MATERIALS AND METHODOLOGY Location and rainfall data collection This study was conducted in Bayawa which comes under Awlegama agrarian service division in Kurunegala district. The area belongs to the IL3 agro ecological zone. Rainfall data for 30 years (1981-2010) were collected from the Agrarian Services office in Awlegama.

Rainfall indices The aerobic and anaerobic condition in paddy fields is created by dry and wet spell of the climate. The dry conditions and the duration can be described using non rainy days and the number of non rainy days. Wet days can be explains by using rainfall indices. In this study, 15 extreme rainfall indices listed in the Table 1 were calculated. In addition to classic indices such as annual total precipitation (RTOT) and annual total rainy days with rainfall >= 1 mm (Rd), the single day intensity index (SDII) was calculated as the average rainfall from wet days. Two other indices considered were annual maximum rainfall recorded during 1 and 5 day period (R x 1day and R x 5 day). R95p, R 99p, R95pSUM, R99pSUM, R95pTOT and R99pTOT are based on the 95th and 99th percentiles. These percentile values were calculated from the daily rainfall data over the period of 1981-2010. On average, the thresholds calculated from percentile were 29 mm and 67.1 mm to define a very wet day and an extreme rainfall event, respectively for 95th and 99th percentile. Based on percentile, three extreme rainfall indices were chosen. Very wet day and extreme rainfall frequency were based on annual count of days with rainfall >= 95th (R95p) and 99th percentile (R99p) of 1981-2010. Very wet and extreme rainfall intensity corresponds to the annual total rainfall records from days with rainfall >= 95th percentile (R95pSUM) and 99th percentile (R99pSUM) of 1981-2010 and gives an indication on the rain received as very wet or extreme rainfall. Very wet day and extreme rainfall proposition is the percentage of annual total rainfall recorded from the day with rainfall >= 95th percentile (R95pTOT) and 99th percentiles (R99pTOT) of 19812010 and measures how much of the total rain comes from very wet or extreme events.

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Characterization of Alternative Wet and Dry Spells using Rainfall Indices: A Case Study in

Awlegama, Kurunegala

Table 1: Rainfall indices with their definitions and units ID RTOT R 10 R 20 Rd

Index name Precipitation total Rainfall greater than 10 mm Rainfall greater than 20 mm

Definition Annual total precipitation Number of rain day with rainfall larger than or equal to 10 mm Number of rain day with rainfalls larger than 20 mm

Unit mm days days

Rainfall days

Annual total of wet days days (A wet day has rainfall >= 1 mm) SDII Single day intensity Average rainfall for wet days mm/day index R x 1 day Maximum 1 day Annual maximum 1 day rainfall mm rainfall R x 5 day Maximum 5 day Annual maximum 5 day rainfall mm rainfall R95p Very wet day Annual count of days with days frequency rainfall>=95th percentile of 1981-2010 R 99p Extreme rainfall Annual count of days with days frequency rainfall >=99th percentile of 1981-2010 R95p Very wet day Annual precipitation from days mm SUM intensity with rainfall >= 95th percentile of 1981-2010 R99pSUM Extreme rainfall Annual precipitation from days mm intensity with rainfall >= 99th percentile of 1981-2010 R95pTOT Very wet day Percentage of annual total % proportion rainfall from days with rainfall >= 95th percentile of 1981-2010 R99pTOT Extreme rainfall Percentage of annual total % proportion rainfall from days with rainfall >= 99th percentile of 1981-2010 CDD Consecutive dry Maximum number of days days consecutive days with the rainfall < 1mm CWD Consecutive wet Maximum number of days days consecutive days with the rainfall >= 1mm All indices were calculated as an annual number or annual value. The rainfall value of 1 mm is commonly applied to define a rain event or a rainy day (Hountondji, et al., 2011; Sheikh et al., 2014). Above indicators can be categorized into frequency indicators and intensity indicators as below. Climate Variability, Water and Society

17


Frequency indices Rd, R10, R20, R95pSUM, R99pSUM, CWD, CDD,R95p and R99p. Intensity indices R x 1 day, R x 5 day, RTOT, SDII, R95pTOT and R99pTOT. The probabilities for the consecutive dry days and consecutive wet days for the period of 1981-2010 were estimated using normal distribution method in order to identify the frequency and return period of the occurrence of extreme events for Maha and Yala seasons. Return period or recurrence interval is the average interval of time within which any extreme event of given magnitude will be equaled or exceeded at least once (Patra, 2001). Frequency or probability distribution helps to relate the magnitude of extreme hydrologic events like floods, droughts and severe storms with their number of occurrences such that their chance of occurrence with time can be predicted successfully.

RESULTS AND DISCUSSION Rainfall indices Table 2 describes the decade vise analysis of indices. The R20 value decreases during the last decade while R10, R x 1 day and R99pSUM shows considerable differences. These indices increase considerably with time. It reveals that number of daily rainfall more than 10 mm are increasing in this area. Daily rainfall higher than 1 mm, Rd is increasing and the extreme rainfall intensity also increasing in this area. The SDII, R95 and R99 do not show much difference with time. The wet condition of the area can be explained by using Rd, SDII, R10 and R99p for understanding of the field conditions. These indices explain the field scenario in a shorter period, which will be useful in irrigation and fertilizer management practices.

18


Characterization of Alternative Wet and Dry Spells using Rainfall Indices : A Case Study in


Table 2: Rainfall indices with different periods 1981-1990 precipitation 1145.4 - 2085.5

Annual (mm) R10 (days) R20 (days) Rainfall day (days) SDII (mm/day) R x 1 day (mm) R x 5 day (mm) R 95 (days) R 99 (days) R95pSUM (mm) R99pSUM (mm) R95pTOT (%) R99pTOT (%)

36-55 22-37 53-80 20.3-3002 65.2-233 144.6-255 13-25 0-8 613.9-1326.1 0-942.5 53-6-75 0-45.2

1991-2000 1324.1-2293.4

2001-2010 1276.3 - 2072

34-73 22-45 73-108 14.4-24.7 69.5 - 150.6 118.1-211.2 13-27 1_7 595.5-1292.7 69.5 - 567.6 42.9-68.9 5.24 - 36.74

38 - 57 18 - 40 76-106 13.5 - 24.9 81.7 - 207 107.6 - 259.9 12_27 1_6 612.3 - 1380.4 103-603.4 43. 2_66.6 7.2-38.0

Frequency of dry and wet spells during Maha and Yala cropping seasons The variability of daily rainfall statistics such as the frequency distribution and intensity of rainfall within a season can be more informative than the seasonal mean variability. Studies of the frequency distribution of daily rainfall have found that heavy and extreme events of the distribution are more sensitive than the mean to explain the climate variability (Becker, et al., 2013). The number of dry days is usually higher than the number of wet days therefore a higher accuracy of predicting dry days can be expected than that of wet days. Table 3 describes the occurrence of dry and wet spells. Most of the events fall into the first categories (1 – 5 range) up to 26 - 30.


19


Table 3: Occurrence of wet and dry days Range 1–5 6 – 10 11 – 15 16 – 20 21 – 25 26 - 30 31 -35 36 – 40 41 – 45 46 – 50 51 – 55 56 – 60 61 – 65 66 – 70 71 – 75 76 – 80 81 – 85 86 – 90 91 – 95 96 – 100 101 – 105 106 – 110 111 – 115 116 – 120 121 – 126

Maha Yala No of Wet No of Dry No of Wet No of Dry days days days days 628 441 364 213 38 111 9 79 5 63 0 48 0 23 0 23 0 20 0 11 0 11 0 7 0 5 0 3 0 3 0 2 0 4 0 2 0 0 0 1 0 2 0 2 0 2 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0

Figure 1 explains the decade vise occurrence of wet and dry spells during Maha and Yala seasons for the period of 1981 – 2010. Number of days receiving rainfall greater than 1 mm and less than 1 mm continuously considered as wet spell and dry spell, respectively. In the Maha season, the dry spell increases with the decades. Most of the occurrences fall in the range of 1-10 days (Figure 1a). There is a considerable increase of continuous dry days between 21-30 days, which has increased from 6 to 16 in the last decade. The wet day frequency also shows an increasing trend in the Maha season and most of them fall into the range of 1-10 days similar to dry days (Figure 1c). The annual rainfall also shows in increasing trend over the period from 1981to 2010. At the same time, the frequency distribution of continuous dry days also shows an increasing trend with respect to number of occurrences For Yala season, the dry and wet days have changed in the second decade (1991 – 2000) as shown in Figure 1b & d.

20




240

Occurance

200

1981-1990 1991-2000 2001-2010

160 120 80 40

200 Occurance

240

120 80 40

0

0

1_10 11_20 21_30 31_40 41_50 51_60

(a)

1_10 11_20 21_30 31_40 41_50 51_60 Continuos dry days (b)

Continuos dry days

240

240

200

200 1981-1990 1991-2000 2001-2010

120 80 40

160

Occurance

160

Occurance

1981-1990 1991-2000 2001-2010

160

1981-1990 1991-2000

120 80 40 0

0 1_10 11_20 21_30 31_40 41_50 51_60 Continuos wet days

(c)

1_10 11_20 21_30 31_40 41_50 51_60 Continous wet days

(d) Figure 1: The decade vise frequency distribution for the wet and dry spell during Maha and Yala seasons (a – Maha dry days, b – Yala dry days, c – Maha wet days, d – Yala wet days)

Probabilities of occurring dry and wet spells during Maha and Yala cropping seasons Probability analysis is a very useful tool in decision making in agricultural operations. It enables to determine the expected rainfall at various chanceprobabilities (Bhakaret al., 2008). Daily values of rainfall can be analysed to provide an accurate account of real or potential occurrence of dry and wet spells. According to De Silva (2008) any period of at least 15 consecutive days, to none of which creates 0.25 mm of rain is considered an absolute drought. Further, any period of at least 29 consecutive days, the mean daily rainfall of which does not exceed 0.25 mm is considered as partial drought. Furthermore, any period of at least 15 consecutive days, to none of which is credited 1 mm rain or more, is called a dry spell. In this study normal distribution method was applied to obtain the probabilities of wet and dry spells in the study area. Many agricultural activities such as land preparation, sowing of seeds, application of fertilizer, irrigation amount and time are a few weather sensitive operations which require specific rainfall conditions for Climate Variability, Water and Society

21


their most successful and economic completion. Therefore, this analysis will help the farmers and managers to make decision in the cultivation process. Figure 2 shows the probabilities of daily rainfall records for the Awlegama agrarian service region for both Yala and Maha seasons. Bayawa located at Intermediate zone of the country, has long spell of dry days than the wet days. The probability of having long dry spell is less both in Yala and Maha season. The probability to have 15 days or above continuous dry days falls into 12.7% and 14.9% for Mahaand Yala season respectively. The highest spell of continuous wet days falls into 8 and 14 for Yala and Maha season respectively and their probability of having those spells are 0.26 % and 0.15 % respectively.

100

100 R² = 0.8865

Probability %

Probability (%)

80 60 40

80

40 20

20

0

0 0

15

30

45

(a)

0

60 75 90 105 120 Continous dry days

15

(b)

30

45

60

75

90 105 120

Continuous dry days

100

100

R² = 0.9755

80

80 R² = 0.996

Probability (%)

Probability (%)

R² = 0.9236

60

60 40 20 0

60 40 20 0

0

2

4

6

(c)

8 10 12 continuous wet days

14

0

2

4

6

(d)

8

10

12

14

Countious wet days

Figure 2: The probability curve for the wet and dry spells during Maha and Yala season (a – Maha dry days, b –Yala dry days, c – Maha wet days, d – Yalawet days)

CONCLUSIONS The climate variability can be explained by using climatic indices. Dry and wet spells were quantified using rainfall indices and non-rainy days. Significant increase

22


16



in R10 with time indicates that the number of daily rainfall more than 10 mm is increasing in the study area. For wet spells, R 10 and R99p are good indices to explain the wet condition at the field level. These indices will assist in the irrigation management practices. The proportion of R95p ranges from 42.9 to 75.1 % and the proportion of R99p range from 0 to 45.2 %. The probability of having long dry spell is low in both Yala and Maha seasons. The probability to have 15 days or above continuous dry days falls into 12.7% and 14.9% respectively for Maha and Yala seasons. The highest spell of continuous wet days falls into 8 and 14 for Yala and Maha season respectively and their probability to having those spells are 0.26 % and 0.15 %, respectively. During Maha season, the irrigation interval can be maintained as 10 – 15 days and for the Yala season it should be reduced to 6 – 10 days. From the frequency analysis, intensity of rainfall as well as dry spell increases during the Maha season. In the Yala season, wet days falls into the frequency range of 1 – 5 consecutive days and the dry spells moves towards a higher probability interval. The most frequent dry spells was at 1 day interval with a probability of 75% and above and 4, 12 and 20 days dry spells occurs with the probabilities of 49, 17 and 8 % respectively.

REFERENCES Becker, A. Finger, P., Meyer-Christoffer, A., Rudolf, B., Schamm, K., Schneider, U. and Ziese, M. (2013). A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present. Earth Syst. Sci. Data 5, 71–99. Bhakar, S. R., Mohammed Iqbal, M, Devanda, M., Chhajed, N. and Bansal, A.K.(2008). Probability analysis of rainfall at Kota. Indian Journal of Agric. Res., 42 (3): 201 -206. De Silva. R. P. (2008). Understanding Drought, its Implications and Mitigation Strategies and Policies in Sri Lanka - Issues, Alternatives and Futures, Droughts and Integrated Water Resources Management in South Asia – Issues, Alternatives and Futures, Eds: J. Jairath & V. Ballabh, Sage Publication India Pvt. Ltd, pp 125-155. Evans, A. and Jinapala, K. (Eds.) (2010). Proceedings of the National Conference on Water, Food Security and Climate Change in Sri Lanka, BMICH, Colombo, Sri Lanka, 9-11 June 2009. Vol. 2: Water quality, environment and climate change. Colombo, Sri Lanka: International Water Management Institute. 186p. doi:10.3910/2010.205 Hountondji,Y., De Longueville, F. and Ozer, P. (2011).Trends in extreme rainfall events in Benin (West Africa), 1961-2000. Submitted to the 1st International Conference on Energy, Environment and Climate changes.Availableat http://orbi.ulg.ac.be//bitstream access on 27th January 2015. Patra, K.C. (2001). Hydrology and water resources engineering. Narosa Publishing House, New Delhi. Climate Variability, Water and Society

23


Sheikh, M.M., Manzoor, N., Ashraf. J., Adnan, M., Collins, D., Hameed, S., Manton, M.J., Ahmed, A.U., Baidya, S.K., Borgaonkar, H.P., Islam, N., Jayasinghearchchi. D., Kothawale, D.R., Premalal, K.H.M.S., Ravadekar, J.V. and Shrestha, M.L. (2014).Trends in extreme daily rainfall and temperature indices over South Asia. International Journal of Climatology. Published online in Wiley Online Library.DO:10.1002/joc.4081. WMO, (2009). Guide to Hydrological Practices, WMO no. 168, 6th Edition. World Meteorological Organisation (WMO), Geneva, Switzerland.

24


Economic Status of Rural Households with Rainwater Harvesting Systems: A Case Study in Monaragala District W.D.P. Sandamali and A. Nanthakumaran Faculty of Applied Sciences, Vavuniya Campus

ABSTRACT Water scarcity is one of the major problems particularly for the rural households in the dry zone of Sri Lanka. Considering that the rain water harvesting as a solution for this problem, the rural households were provided the Rain Water Harvesting Structures (RWHS) to collect and store the rain water by various organizations which promote RWH. The objective of this study was to assess the economic benefit of rain water harvesting. Questionnaire survey was conducted among randomly selected forty five rural households at Siripuragama GN division in Monaragala district during September to December, 2014. The data on time taken for water collection during non rainy season, usage of RWHS, quantity of harvested rain water and the income earned by cultivating crops using rain water harvesting were collected from the respondents. The results revealed that the women saved 26 man days while saving of men is 16 man days and the children saved 70 hours per annum by using RWHS. Further, an income earned by cultivating crops using harvested rain water and the reduction in the charges for the electricity due to rain water harvesting were assessed and considered to be an additional income for the households due to RWH. Well water consumers who had RWHS saved Rs. 30505 (US$ 227) while pipe born water consumers who are non-‘Samurdhi’ beneficiaries saved Rs.13046 (US$ 97) and pipe born water consumers who are ‘Samurdhi’ beneficiaries saved Rs.12341 (US$ 92) per annum. Installation of RWHS not only improve the economic status of the rural households but also conserve the water resource, hence it could be a win-win solution to the society and the environment.

INTRODUCTION The definition of the rainwater harvesting includes collecting run-off water from a structure or other impervious surface and stored for later use (Weeraratna & Ariyananda, 2009). Sri Lanka has a greatest history of rain water harvesting as evident by King Parakramabahu who is one of greatest kings in Sri Lankan stated that “one drop of rain water that falls from the sky should not allow flowing to the ocean without using it for human being”. His statement is clearly illustrated by the ancient networks of reservoir system which mainly helps to develop the economic profile of Sri Lanka. The government of Sri Lanka passed a national policy on rainwater harvesting in 2005 with the objective of encouraging communities to control water near its source by harvesting rainwater. In recent years, there has been a revival of domestic rainwater harvesting using RWHS and much research has been conducted to improve the technology. Ariyananda (2010) reported that there

W.D.P. Sandamali and A. Nanthakumaran

are more than 23 institutions and organization implementing rainwater projects and there were more than 31,000 systems constructed in Sri Lanka. It is believed that these rain water harvesting systems improve the economic status of the rural households.

Objectives The objective of this study was to assess the economic benefits of having rainwater harvesting.

MATERIALS AND METHOD Nearly 1944 RWHS in Monaragala district and 120 RWHS in Siripuragama GN division were recorded by Ariyananda & Aheeyer (2011). Among them 45 households were randomly selected for this study. Data such as time taken for water collection during non-rainy season and rainy season, usage of RWHS, quantity of harvested rain water and the income earned by cultivating crops using rain water harvesting were collected using pre-tested questionnaire. The survey was conducted during September to December 2014. MS Excel software was used to analyze the data. Monthly water bill charged by National Water Supply and Drainage Board and monthly electricity bill charged by Sri Lanka Electricity board were used to value the harvested rain water annually (Value of harvested rain water per annum is considered to be a product of value of average monthly harvested RW based on the water bill and the number of month in which harvesting rain water was used) and the amount of electricity used to fill RWHS by electric water pump (Appendix 1), respectively. In addition, the time spent for manual water collection during dry season was considered as time saving due to RWH and it was estimated as the average time saving by men and women by valuing the time saving by men and women using the concept of opportunity cost i.e., respective day labour charges.

RESULTS AND DISCUSSION The study revealed that 57% of households consumed well water while remaining 43% of households consumed pipe born water as a major water source. The well water consumers consumed well water during dry season by the water supply using electric water pumps or by through water bowsers and filling rain water in the RWHS during rainy season. Pipe born water consumers fill the RWHS with well water or pipe born water due to irregular supply of pipe born water and also harvest rain water during rainy season. Hence the respondents obtained the economic returns from rain water harvesting through saving the time spent on fetching the water, money spent for filling the RWHS using electric water pumps or by water bowser, reducing the water bill, and also through the income generated by crop cultivation activities using RWHS.

26


Economic Status of Rural Households with Rainwater Harvesting Systems: A Case Study in

Monaragala District

Valuation of time saving from manual collection of water About 88% of well water consumers collected water manually. Table 1 revealed the economic returns from saving time from manual collection of water. Table 1: Valuation of time saving from manual collection of water Clusters Average time saving/capita/year

Women

Men

Children

26.25 man day (210 hour)

70 hour

Labor charge per working day

SLRs. 800

15.75 man day (126 hour) SLRs. 1000 (US$ 7.46) SLRs. 15750 (US$ 117)

(US$ 5.97) Saving amount SLRs./capita/year SLRs. 21000 (US$ 156) Average money saving per a SLRs. 31500 households (US$ 235)

cannot be valued

According to the Table 1, women saved nearly 210 hours annually which is equivalent to SLRs. 21000 (US$ 156) while the men saved nearly 123 hours equivalent to SLRs. 15750 (US$ 117) and children saved 70 hours. Finally, average money saving per household was SLRs.31500 (US$ 235). The women can utilize the time saved for child education, household work, agricultural work and social work whereas the men for the income generation activities and the children for education and for playing.

Total economic returns from rain water harvesting About 46% of pipe born water consumers used the harvested rain water for watering plants such as chilies, leafy vegetables, brinjal, pea, coconut, lemon and ornamental plants in home gardens, nurseries and green houses. The respondents reported that the pipe borne water was collected, stored and then used to watering the plants. RWHS were used to store the pipeline water for watering the plants in dry season. During rainy season no need to fill the RWHS hence the electricity charge for pumping water using electric motor or the bowser charges would be saved. Table 2 summarises the total economic returns from rain water harvesting. Well water consumers who had rain water harvesting systems saved SLRs. 30505 (US$ 227) while non ‘Samurdhi’ beneficiaries of pipe born water consumers saved the SLRs.13046 (US$ 97) and ‘Samurdhi’ beneficiaries of pipe born water consumers saved SLRs.12341 (US$ 92) per annum (Table 2). Since the charges for electricity consumption vary for ‘Samurdhi’ and non ‘Samurdhi’ beneficiaries the economic return due to RWH was computed and presented separately.


27

W.D.P. Sandamali and A. Nanthakumaran

Table 2: Total economic returns from rain water harvesting Well water consumers (57%) Percentage Average annual saving amount Time spent for 88 % SLRs. 31500 manual (US$ 235) collection of water Money spent 35 % SLRs. 7500 for the bowser (US$ 56) Electricity 24 % SLRs. 270 charge (US$ 2) for the motor Reduction in water bill

Pipe born water consumers (43%) Percentage Average annual saving amount

-

46 %

SLRs. 270 (US$ 2)

100%

SLRs. 2566 (US$ 19) (for non ‘Samurdhi’ beneficiaries) SLRs. 1861 (US$ 14) (for ‘Samurdhi’ beneficiaries) SLRs. 10355 (US$ 77)

-

Income generation project (crop cultivation) Average total SLRs. 30505 saving (US$ 227) per household

-

46%

SLRs. 13046 (US$ 97) (for non ‘Samurdhi’ beneficiaries) SLRs. 12341 (US$ 92) (for ‘Samurdhi’ beneficiaries)

CONCLUSIONS AND RECOMMENDATIONS Rain Water Harvesting plays a significant role in the economic status of the households. It saved a substantial amount of economic returns to the well water consumers and to the pipe born water consumers. Well water consumers saved nearly 2.5 times of higher savings than that of pipe borne water consumers. This research outcome could encourage the rural households to install RWHS. Use of

28


Economic Status of Rural Households with Rainwater Harvesting Systems: A Case Study in

Monaragala District

RWHS not only improves the economic status of the households but also conserves the water resource.

REFERENCES Ariyananda, T. (2010). Domestic Rainwater Harvesting as a Water Supply Option in Sri Lanka. HYDRO NEPAL. ISSUE NO. 6, 27. Ariyananda, T. and Aheeyer, M.M.M. (2011). Effectiveness of Rain Water Harvesting (RWH) Systems as a Domestic Water Supply Option. Sri Lanka. Water Supply & Sanitation Collaborative Council. Weeraratna, C.S. and Ariyananda, T. (2009). Importance of Rainwater Harvesting in Human Health, 14th IRCSA Conference, Kula Lumpur, Malaysia, 3-6th August 2009.

Appendix 1 (1) Kilowatts (kW ) of motor = Horse Power (HP) of motor × 0.746 kW (1HP = 0.746 kW) (2) Electricity (kWh) spent /month = (1) × pumping hours per month Capital saving / year = electricity charge for (2) × number of month used rain water


29

Shallow Groundwater Use Through Agro Wells in Dry & Intermediate Zones of Sri Lanka and Present Health Hazards C. S. De Silva Faculty of Engineering Technology, Open University of Sri Lanka

ABSTRACT Major aquifer type of the dry and intermediate zone of Sri Lanka is Crystalline Hard rock. Agro wells are being designed on the upper 5-6 m regolith of the aquifer with the diameter of 6 m as digging further is rather difficult. Agro wells are considered as a household asset and ideal supplementary water source to overcome the water shortage problem. With the success and proliferation of the agro wells since early nineties, the health hazards are also at an increasing trend. Major health concern during this period of time is the Chronic Kidney Disease with unknown etiology. Shallow groundwater behavior and quality aspects of the agro wells in selected case study areas (Jaffna, Vavuniya, Anuradhapura, Kurunegala and Hambantota) to represent the dry and intermediate zone of Sri Lanka were studied for the last ten years. Findings revealed that the agro wells behave like a storage tank to hold the shallow groundwater generated during wet season rains due to its poor transmissibility and recovery performance after several hours of pumping. Shallow groundwater stored during wet season is used for supplementary irrigation in the dry season and these wells are ideally suited for only supplementary irrigation purposes. Water quality parameters such as Nitrate, Ammonium Nitrate, Sulphate, Fluoride and Phosphate exceeds the World Health Organization limits during wet season from October to February as the wet season rains flush out the mineral, fertilizers and chemicals in the soil zone to the shallow groundwater and the agro well water becomes a highly concentrated chemical nutrient solution during the wet season. Unfortunately, the rural population engaged in agricultural activities using agro wells has failed to understand that agro wells are only suitable for irrigation purposes. Being a convenient household asset and the clear water in the agro wells tempt them to use it for drinking purposes as there is no other drinking water source. Hospital admission records with kidney diseases are high during wet season. Therefore, farmers should be made aware that agro well water should not be used for drinking and an alternative source such as rainwater harvesting must be encouraged until safe and clean supply water is provided.

INTRODUCTION In Sri Lanka, competing demands by non-agricultural sectors are already causing water deficits in traditional agricultural areas especially in the dry and intermediate zones. Unfortunately, more than two thirds of the country‘s land area comes under

C. S. De Silva

the dry and intermediate zones where agricultural production is the major activity. The major aquifer type in these zones is the Hard Rock Aquifer. Low storage, low transmissivity and low infiltration of this soil above are the inherent nature of these aquifers. Realizing this reason from time immemorial, priority was given to irrigation projects in the dry and intermediate zone as a necessary basis for villages. Our history shows that from around 414 BC our ancestors have constructed over 30000 small village reservoirs in the dry zone in addition to the massive reservoirs like Tisawewa, Thopawewa, Kalawewa to collect rainfall runoff for later use in agricultural production. During this period, farmers cultivate two-season paddy, wet season paddy as rainfed and the dry season paddy with tank water. This small reservoir-village agricultural system seems to have flourished from about 500 BC to 1500 AD. The effectiveness of storage-based irrigation systems was such that, over time, more people were attracted to the command areas of the tanks and many of the systems became unsustainable due to overcrowding. With that the farmers in the command area of the tank were unable to cultivate two season of paddy without supplementary irrigation. It was partially due to the poor maintenance of the tanks, which caused siltation leading to poor storage capacities. To overcome this water shortage problem, the Government of Sri Lanka had also diverted a major river, the Mahaweli to the dry zone under the Accelerated Mahaweli Development Programme. Even after the diversion of this river, more than 50% of irrigable lands cannot be cultivated in the Yala season due to scarcity of water. Expansion of irrigated agriculture in Sri Lanka during the recent past is closely associated with the increase of tank irrigation schemes and the rehabilitated village tanks. Despite the significant rise in the irrigated area, the total extent covered by all surface gravity irrigation systems do not still exceed 50 percent of the cultivated area of the country. Therefore, the farmers in the areas where Mahaweli water is not available had to seek an alternative resource for irrigation. In addition, there are vast stretches of land with favorable soil and terrain characteristics lying outside the command areas of the existing irrigation systems in the island’s dry and intermediate zones where water remains the major constraint for agricultural development. If the rainfall and surface water resources are not adequate, the only alternative is to use groundwater resources to supplement the rainfall. Hence, there has been increasing emphasis on the utilization of the groundwater resources with a view to tap the agricultural potential of these lands. Except in the Jaffna Peninsula in the extreme north of the island, where the rich aquifers are associated with Miocene limestone, groundwater was never used on a large scale elsewhere in the dry zone. Nonetheless, many studies have indicated the potential of groundwater resources for improved cropping and livestock farming in the dry zone (Sirimanne, 1952; Sakthivadivel & Panabokke, 1996) As an option to the ever-increasing water demand, use of shallow groundwater for cultivation was thought as an alternative, In 1986, a cabinet paper was presented by the Ministry of Agriculture to obtain a subsidy for development of agricultural wells

32


Shallow Groundwater Use Through Agro Wells in Dry & Intermediate Zones of Sri Lanka and

Present Health Hazards

(popularly known as agro wells) through Agro well programme in the North Central province of Sri Lanka. The most significant development that has taken place in the dry zone during the recent decade has been that of the construction of agro-wells under the numerous small tanks. In order to exploit the shallow groundwater for supplementary irrigation, agro wells are being used. Since then the number of agro wells has been increased at a steady rate. According to the recent estimates, there are over 100,000 such agro wells scattered across the intermediate and dry zones of Sri Lanka. The main reason behind this proliferation is that the agro wells have become a household asset and several subsidies and grants had been given by the government and nongovernmental organizations since late 80s. Currently, out of every 10 households, at least 7 or 8 households have their own agro wells.

AGRO WELLS FOR SUPPLEMENTARY IRRIGATION An agro well is a large diameter well of 6 m diameter on average and having 03-12 m in depth. This well is much larger than normal domestic wells. Similarly, the agro well is shallower than the domestic well. As mentioned earlier these agro wells are in weathered over burden above the crystalline hard rocks. These wells just reach the first top 6 m of the overburden and some agro wells are much shallower up to 3-4 m in depth. Whereas the small diameter wells and tube wells are much deeper and tap water from the fractures of the crystalline hard rocks. Agro wells are mainly designed for supplementary irrigation purposes in the dry and intermediate zones of Sri Lanka where water shortage is the major problem during dry (yala) season. In addition, spacing between wells, well depth, well radius and location of wells are also important factors to be considered for successful agro well irrigation. The minimum spacing in between two adjacent wells in these zones is identified as 200 m (De Silva & Weatherhead, 1997).

Chronic Kidney Disease of Unknown Etiology It is a major health issue, which needs to be attended seriously and have to find a remedial measure to safeguard the rural poor in the dry and intermediate zones. Identifying the real cause for this disease is not so far successful. Some studies suggested Cadmium may be the problem (Ananda Jayalal-pers comm.) and others suggested heavy metals and interaction between heavy metals and other cations and anions known to be nephrotoxicants. Number of studies have presented a multitude of factors identified may be the cause but there is no conclusive evidence to prove the real cause (Jayasumana et al., 2013; Wanigasuriya et al., 2011). Now it has become a political issue and various sectors are being blamed and agrochemicals and fertilizers are thought to be the main culprits. Based on the unconcluded findings/ suggestions, the use of Glyphosate is also banned. It is also to be understood that agricultural activities need fertilizer and agro chemical use to achieve the potential yield to feed the growing population. Further, due the global warming and climate change the insect pest infestation and the growth and proliferation of invasive weeds are believed to more virulent and threatening for the agricultural activities. Therefore, the use of agro chemicals and fertilizers also will


33

C. S. De Silva

be essential to ensure sustainable food production. It is also noted that the people in these regions use agro well water for domestic purposes as they do not have alternative source of drinking water and the disease incidence has increased with the increase in number of agro wells (Manthrithileka, 2015). This paper intends to analyze the agro wells based on the aquifer behavior, groundwater fluctuations and the water quality over a year period ten years to understand the situation and suggest suitable remedial measures to overcome the health hazards. Therefore, a series of studies have been conducted in agro wells being in use for intensive agricultural production areas namely Jaffna, Vavuniya, Anuradhapura, Kurunegala and Hambantota representing dry and intermediate zones of Sri Lanka to understand the groundwater quality over the years of 2004 to 2014.

METHODOLOGY Analysis of chemical parameters of shallow groundwater in Jaffna Peninsula in forty drinking water wells at monthly interval was carried out from 2007 to 2009. Water quality assessments were also done on randomly selected 30 wells in the Thandikulum, Kurumankadu in Vavuniya and Thirappane in Anuradhapura during 2004 to 2006 at monthly intervals. Malsiripura in Kurnagala also engaged in intensive agricultural activity and 10 randomly selected wells were taken for this study during 2004 to 2005 at monthly intervals. The study in Hambantota district was carried out to assess water quality and sanitation for wells used for domestic purposes after the complaint made by the Medical Officer of Health (MOH) of the area for calculi in the urinary tract leading to renal failure and diarroheal diseases in 2006 and 2014 at monthly intervals. Accordingly, water quality assessments were done in Hambantota on randomly selected 15 wells in GN divisions of Bataatha North, Kivula South and Welipatanvila. pH, turbidity, conductivity, and fecal coli form were analyzed using the water quality microbial analysis kits (Dealgua) while nitrate-N, nitrite-N, ammonium-N, chloride, fluoride, calcium, magnesium, sulphate, iron, arsenic and phosphate were analyzed using the UV/Visible Spectrophotometer. The study areas are presented in Figure 1.

RESULTS AND DISCUSSION Shallow Groundwater Fluctuation in Agro wells and Recharge Characteristics The dry and intermediate zones of Sri Lanka receive a considerable amount of rainfall during the second inter monsoon and the Northeast monsoon during October to January (wet season). During the monsoon period from October to January, the soil profile and the weathered rock also get filled with water. This water is called shallow groundwater. Most of the agro wells get water from this shallow groundwater unless they have deepened enough (30-40m) to tap deep groundwater through fractures in the hard rock. More than 99% of the Agro wells store the

34




shallow groundwater during wet season and it can be noticed by the quick rise in shallow groundwater table with the onset of wet season rains in October and reach the ground surface in one or two weeks time. During that time shallow groundwater aquifer gets filled to the maximum and any excess rainfall will be removed as runoff to the surface tanks/ wewa. During this process all the salts, irons and chemicals applied to the soil during dry season for intensive agriculture wash off to the shallow groundwater and the water in agro wells becomes a concentrated solution of all chemical and salts. Therefore, during this period the use of water in agro wells for domestic purposes will cause serious health hazards. From January onwards the groundwater table dropped and in October (prior to the wet season rains) the groundwater table was nearly 3 to 4 m below ground level due to pumping, evaporation by small and big trees and seepage losses. Abstraction from agro-wells during the dry season (February to September) is mainly from the wet season recharge. For sustainable use of groundwater resources the abstraction should not exceed the recharge to the aquifer. Estimated average annual recharge for Northwestern and Northcentral provinces were 250 mm and 230 mm respectively (De Silva & Rushton, 1996).


35

C. S. De Silva

Jaffna

Study Area Trincomalee

• Vavuniya

Anuradhapura

Puttlam

study area

A dry zone B intermediate zone C wet zone

A

Kurunagala

B C Colombo

deep sedimentary rocks Hambantota 0

100 km

shallow sedimentary strata crystaline hard rocks

Figure 1: Aquifer Types, Climate zones and the study areas

Aquifer Flow Mechanisms in Hard Rock Aquifer Most of the agro wells in the small tank systems reach only 6 m to 8 m depth of the regolith or weathered overburden of the hard metamorphic rocks or crystalline basement rocks (Figure 1). This regolith has very low storage and transmissivity. The estimated hydraulic conductivity and specific yield were 6 m/day and 0.065 respectively (De Silva, 1995). The large well storage in the agro-wells contributes nearly 70%-80% of the total abstraction during pumping. Due to the poor aquifer properties, these wells have to be left for recovery in between pumping activities. Recovery rates vary depending on the aquifer properties. Results indicated that after four hours of pumping at the rate of 300 m3/day during the latter part of the dry season, 75% recovery occurred at the end of 3-day rest period (De Silva & Weatherhead, 1996; De Silva & Rushton, 1996). Therefore, pumping should be planned according to the aquifer parameters and recovery patterns of the agro wells. Mainly agro wells play a role as storage tanks and allow for long duration pumping

36




during early wet season for supplementary irrigation. Since there is very low aquifer flow to replenish the water and recovery, the water quality remains same which may cause serious health impacts if water from these agro wells is consumed.

Water Quality of Agro Wells According to the results in Jaffna peninsula, the total iron, phosphate, manganese, arsenic, pH did not reach harmful levels even though the aquifer is highly porous and heavy fertilizer use for intensive agricultural activities was adopted. Salinity developments, high level of nitrate –N, low level of fluoride were identified as major health hazards in the study area (Figure 2). Figure 2 shows that some public, domestic and farm wells exceed the permissible limit of 10 mg/l of Nitrate Nitrogen. The health hazards of consumption of high nitrate contaminated drinking water was studied and emphasized by number of scientists. Nitrate is associated with diseases like methaemoglobinemia, gastric cancer, thinning of blood vessels, aggressive behavior and hypertension (Kuruppuararachi, 1995). Sivarajah (2003) supported this and reported that high nitrate content in water could be related to the high prevalence of cancer of the gastrointestinal tract in the people of Jaffna. It could be converted into carcinogenic substances such as nitrosamines within the body and is of importance in the incidence of esophageal cancer in Jaffna district (Mikunthan & De Silva, 2008). Correlation between agricultural land use and high nitrate concentrations in ground water have been documented at least since 1970s (Paul et al., 1997). Studies conducted in Jaffna by Nagarajah et al. (1982) and in Kalpitiya by Kurippuarachchi (1995) reported about high concentration of nitrate in ground water under different soil conditions. The high concentration of nitrate may also be due to the characteristics of the soil in the study area having sandy loam nature with high porosity compared to clayey soils restricting leaching of nutrients to the shallow ground water (De Silva & Ayomi, 2004). In Vavuniya and Anuradhapura, all samples showed lesser turbidity below 5 NTU. pH of all the wells was in the range of 6.4-7.4. All the wells can be categorized as low salinity water. The thermo tolerant fecal coli form was much higher in some wells near residential areas. Nitrate-N was higher in 20% of the wells above the recommended level of 10 mg/l for drinking water and nitrate-N was low until the beginning of October and has increased after wet season rains in November/ December. The ammonium concentration increased after rainfall and it exceeded the World Health Organization (WHO, 1995) recommended level of 0.2 mg/l. In all wells sulphates were below recommended level (WHO, 1995) of 600 mg/l for drinking water. Chloride ions were within the permissible limit. The maximum limit of fluoride (1.5 mg/l) exceeded slightly by some of the wells (range of 0.28 mg/l to 1.74 mg/l) especially in Anuradhapura (Figure 3). Concentrations above this value carry an increasing risk of dental fluorosis, and much higher concentrations lead to skeleton fluorosis. Research findings show that the higher concentration of fluoride may cause even kidney diseases (Sivarajah, 2003). In most of the study areas, there are several complains about the hardness of water and kidney ailments, especially


37

C. S. De Silva

during the wet season. Eventhough Malsiripura in Kurunegala is an intensively vegetable cultivated area, all the measured parameters were within the permissible limit except for the nitrate concentration. The wells within the cultivated areas showed a higher value of 11 mg/l during wet season where the permissible limit is 10 mg/l (Amarasinghe & De Silva, 2006).

20 18

Public

Farm

Domestic and Home gardening

16

Permissible Limit

Nitrate-N (mg/l)

14 12 10 8 6 4 2 0 1

10

19

28

37 Well No

Permissible limit

Date

NH4+-N (mg/L)

F- (mg/L)

Figure 2: Average concentration of NO3- N with standard deviation in Jaffna Peninsula (Source: Mikunthan & De Silva, 2008).

Permissible limit

Date

Figure 3: Fluoride and Ammonium Nitrogen Concentrations in Agro wells in Vavuniya and Anuradhapura (Amarasinghe & De Silva, 2006). Also in Hambantota, all the measured parameters were within the permissible limit except for ammonium, nitrate, phosphate and sulphate (Figure 4). The study results showed that 26 % of the wells in the study areas exceeded the permissible limit of 0.2mg/l of ammonium. In addition 20% of the wells exceeded the 2mg/l permissible limit of phosphate (2.97 mg/L) and 20% of the wells exceed the permissible limit of sulphate during the study period (487 mg/l). The maximum permissible level of sulphate is 400 mg/l. Similarly, 30% of the sample well water exceeded the permissible limit of 10mg/l (as N) in January at the end of the rainy season (11.1 mg/l).

38




December

Permissible limit

Well Number

August Sulphate concentration (mg/L)

Phosphate concentration (mg/l)

August

December

Permissible limit

Well Number

Figure 4: Sulphate and Phosphate Concentrations in Agro wells in Hambantota

Use of Agro Well Water for Domestic Use and Possible Health Hazards CKDu is a common disease prevailing in the dry zone areas such as Jaffna, Anuradhapura, Polonnaruwa, Kurunegala and Hambantota where farming community mainly depend on agro well water for their irrigation and domestic use. This may be due to the ignorance of the rural population of the fact that the agro wells are constructed only for supplementary irrigation and not for domestic purposes as it is shallow in depth and get highly concentrated washed off material from farm land during wet season which is harmful for health. Findings of the water quality of agro wells discussed above in the areas where CKDu is prominent indicated very clearly that the nitrate, phosphate, sulphate, fluoride and ammonium nitrate concentrations exceed the permissible limits especially during wet season due to the flushing out of minerals and chemicals from the farm lands. It is also recorded from the Vavuniya Base Hospital that the urinary and kidney patient admissions are high during wet season (Amarasinghe & De Silva, 2006). It shows that there is clear correlation between water quality of agro wells and the health consequences during wet season. People using water from these agro wells for drinking purposes may tend to think that this water source is very convenient and that the quality of water is good as they see it clear and got used to the taste. But, they may not see the serious degradation of the quality of water in agro wells during wet season as they are so used to it. In addition to CKDu there are several other diseases such as esophageal cancer, methaemoglobinemia, gastric cancer, thinning of blood vessels and aggressive behavior and hypertension reported in most of the dry zone areas. Even then some people use the water from agro wells for domestic purposes may not get the health problems, because those wells may be located in high land or much deeper than the normal agro wells so that tap the fresh deep groundwater through fractures of the hard rock.


39

C. S. De Silva

CONCLUSIONS Assessments of groundwater quality and quantity were carried out in intensive agricultural activity areas in Jaffna, Vavuniya, Anuradhapura, Kurunegala and Hambantota to understand whether there is any impact of water quality of agro wells with the present kidney related ailments such as Chronic Kidney Disease (CKDu). Results of all the study areas on several parameters showed that the agro well or shallow well (100 household Fish wash off water level (>20 kg/day) Fish offal >10 large scale Concentrated salt (> 100 kg/day) water Export oriented fish 02 Fish wash off water processing Fish offal industries Boat anchorages 40 Burnet fuel Polythene and plastics Styrofoam Ice manufacturing 06 Ammonia plants

of

Discharge to the estuary


Discharge to the estuary Discharge to the estuary


Accordingly, it is clear that there is no established mechanism for disposal of waste generated from fishery related activities. Therefore, Negombo estuary is at a severe threat from various kinds of pollutants from fishing industry.

Water and Ecosystems

75

G.D.S. Priyadarshika, N.D.K. Dayawansa and S. Pathmarajah

Other economic activities and associated pollution sources Among the other economic activities except fishing industry, boat manufacturing and repairing stations, service stations, garages, filling stations, food stalls, restaurants, piggery farms and shrimp farms are at significance. Table 5 presents the possible pollutants from those activities and currently practiced disposal methods. Table 5: Types of pollutants from other economic activities Source pollution

of Number sources

of Types of waste Method generated disposal

Boat manufacturing 04 and repairing stations

Fibre Painting chemicals

Vehicle service >10 Fuel stations, filling Grease stations, garages Piggery farms 30 (small scale Animal excreta >30) Shrimp farms 5 Used water with food and excreta Hotels and >15 Food waste, grey restaurants water

of

Dispose to the lagoon boundary and adjacent environment Discharge to the environment Flushing towards the water body Discharge to the estuary Discharge to the water body or directed to a canal

Above details provide evidences of estuary pollution from other economic activities around the lagoon.

Improper domestic waste disposal practices According to the survey conducted, Tables 6 and 7 present the grey water and black water disposal methods practiced in each GN division and associated problems.

Table 6: Grey water disposal methods and associated problems GN Division

Method of Grey water disposal Siriwardhana Pedesa, Disposed to the Munnakkaraya North, lagoon directly or Pitipana North indirectly Pitipana South Thalahena

76

and Disposed garden

to

Associated problems

Cannot be reused for the garden mainly due to land scarcity and high salinity level of the soil the Not used for gardening as no home garden maintained due to high salinity level of the soil even though land is not comparatively scare


Pollution Sources of Negombo Estuary in Negombo Municipal Council Area and the Contribution

of Drainage Canal System to Estuary Pollution

The following factors can be identified as reasons for disposal of black water into the estuary and improper solid waste disposal practices around the lagoon environment.      

limited land area for the households absence of accessible routes to approach the NMC gully tankers to the required places reluctance to pay tariff involved in black water removal process haphazard construction of housing schemes by government and nongovernment organizations without proper environment feasibility studies under-capacity of NMC to properly maintain the black water disposal system in the area and solid waste management mechanism Lack of awareness on environmental damage caused by haphazard waste disposal practices

Table 7: Black water disposal methods and associated problems GN Division Siriwardhana Pedesa

Munnakkaraya North

Pitipana North

Pitipana South Thalahena

Method of Black water disposal Household level septic tanks are de-slugged through NMC Gully tankers Common collection tanks are de-slugged through NMC Gully tankers

Associated problems Septic tanks are overflowing in rainy seasons

Collection tanks are yet to be connected to a common treatment plant Household level septic Septic tanks are tanks are de-slugged overflowing in rainy through NMC Gully seasons tankers and By means of soakage pits Overflowing of soakage pits located at the lagoon boundary

Assessment of drainage network in the study area Drainage system of the NMC area is flowing towards the lagoon due to the topography of the land. Hamilton canal and Diyahonda Ela are the main contributors for a large quantity of discharge based on the dimensions of the canals. These drainage canals carry solid and liquid waste into the estuary. Table 8 presents the measured water quality parameters in Hamilton canal and Diyahonda Ela with the permissible discharge limits to coastal and marine areas. Figure 4 illustrates the variation of flow rates of these two canals with the daily rainfall at Katunayake meteorological station three days prior to sampling.


77


Table 8 : Permissible limits for quality parameters for discharge into coastal and marine waters and average values of tested physico-chemical parameters of Hamilton canal and Diyahonda Ela Parameter

Permissible limit 0 Temperature/ C 45 pH 5.5-9.0 Salinity/ppt No upper limit Coductivity/(mS/cm) No upper limit TDS(mg/L) No upper limit Turbidity/NTU No upper limit DO/(mg/l) 5 BOD/(mg/L) 100 Oil and grease/ (mg/L) 20 TSS/(mg/L) 150 Total Phoshates/ (mg/L) 1 Faecal colifroms 60 /(MPN/100 mL)

Hamilton canal Diyahonda Ela 30.8 31.4 7.3 7.5 0.4 3.9 7.3 10.81 110.3 454.0 18.4 20.2 4.9 4.3 34.5 29.5 11.25 28.5 67.8 124 2.1 1.2 Too numerous Too numerous to count to count

Accordingly DO, faecal coliform, total phosphates and oil and grease amount exceed the prescribed dischage limits to coastal and marine areas. This indicates the addition of sewage, organic waste and other pollutants to both canals from different sources.

78




4.0

60.0

3.5

50.0

3.0 Flow rate(m3/S)

Rainfall/mm

40.0

Flow rate of Hamilton canal /(m3/S)

2.5 2.0

30.0

1.5

20.0

1.0 10.0

0.5 0.0

0.0 8-Oct 13-Oct 18-Oct 23-Oct 28-Oct 2-Nov 7-Nov 12-Nov

Date

(a) 1.2

60.0

Flow rate(m3/S)

Rainfall/mm 50.0

1.0

40.0

0.8

30.0

0.6

20.0

0.4

10.0

0.2 0.0

0.0 8-Oct

13-Oct

18-Oct

23-Oct

28-Oct

2-Nov

7-Nov

12-Nov

Date

(b) Figure 4: Rainfall and daily discharges of Hamilton canal (a) and Diyahonda Ela (b)


79


According to Figure 4 it is clear that the flow rates of two main canals are highly influanced by the rainfall. Accordingly, non point sources can activate during high flow periods.

Daily pollution loads to the lagoon by Hamilton canal and Diyahonda Ela The estimated daily pollution loads of Hamilton canal and Diyahonda Ela are presented in Figure 5. 35.0

Pollution Load (tons/day)

30.0 BOD Load(tons/day)

25.0 20.0

Oil & grease Load (tons/day)

15.0

TSS load(tons/day)

10.0 5.0

Total Nitrate as N load(tons/day)

Diyahonda Ela

2012.11.14

2012.11.07

2012.10.24

2012.10.10

2012.11.14

2012.11.07

2012.10.24

2012.10.10

0.0 Total Phosphate as PO4 3-(tons/day)

Hamilton Canal

Figure 5: Estimated daily pollution loads of Hamilton canal and Diyahonda Ela According to Figure 5, Hamilton canal transport a higher pollution load compared to Diyahonda Ela. Total Suspended Solids, BOD and Oil and Greexe are the three main pollutants coming through these canals. Mallawaarachchi et al. (2003) have estimated the total BOD load entered through Attanagalu Oya to Negombo estuary as about 2500 t/y. Assuming that the pollution loads will be constant throughout the year, the estimated BOD load to the estuary from Hamilton canal and Diyahonda Ela are 1700 t/y and 700 t/year, respectively. However, these amounts can vary considerably with rainy and dry seasons with changing flow rates and due to activation of pollution sources during wet periods.

80




Impact of tidal movement on estuarine water quality Negombo estuary is a dynamic ecosystem which governs by a number of physical processes (CCD, 2008). Tidal movement is the most significant process that affects the properties of water in the estuary as it is important for circulating pollutants within the estuary. Figure 6 shows the velocity vector plot of the lagoon entrance channels at maximum flood discharges and the points of pollutant discharges into the estuary from different sources. The size of the arrow heads of the figure is positively related with the number of pollution sources and the observed flow rate from each point.

(a)

(b)

Figure 6: Velocity vector plot of the lagoon entrance channels – (a) Maximum flood velocity (Source: University of Moratuwa, 2003) (b) Pollutant inflows into the estuary According to Figure 6, pollutants discharged from fishery harbour and Pitipana areas will tend to flow towards the southern direction due to the current speed (>0.35 m/S) with the high tide. Pollutants added through Hamilton canal and from Munnakkaraya areas will tend to flow towards southern direction slowly and circulate around nearby areas due to low tidal velocity (0.2-0.15 m/S) in these areas. Cross Church area also has a higher flow velocity (0.25-0.35 m/S) and therefore the pollutants added from these areas will flow towards the southern direction during high tide period. The same velocity transverse for low tide periods and therefore pollutants added to the places where high current speed is prominent at low tide periods will flow towards the estuary mouth. However, Kadolkele area having zero (or very low) tidal velocity will retain pollutants in the area for a longer time period. Munnakkaraya and adjacent area will also be expected to follow the same scenario having low current velocities.


81


CONCLUSIONS Negombo estuary is an important coastal ecosystem which is in the threat of degradation due to pollutants discharging from its surrounding which is dominated by the Negombo municipal council area. According to this study both point and non point sources contribute to the lagoon pollution. Main pollution sources include fishing industry, households, drainage canals and other economic activities such as boat manufacturing, pig farming, hotels and restaurants, vehicle service stations. Grey and black water from the surrounding households are also discharge to the system due to lack of space for grey water discharge, inability to maintain a home garden due to high salinity and discharge of septic tanks during rainy season. Hamilton canal and Diyahonda Ela are the two main canals which carry wastewater to the estuary. According to the estimations made in this study, Hamilton canal carried relatively high pollutant loads to the estuary. The current circulation pattern plays an important role in mixing and circulating pollutants in the lagoon.

REFERENCES CCD (2008). Development of a coastal water quality program for Negombo estuary, CCD, Colombo. pp.2-9. CEA (1994). Management Plan for Muthurajawela Marsh and Negombo Lagoon, CEA, Colombo. pp.19-27. Mallawaarachchi, R.N., Rathnayake, N. and Samarawickrama, S.P. (2003). A Study of the Negombo lagoon with respect to the salinity variation and pollution of the lagoon water and effects of proposed dredging activities, Unpublished thesis, University of Moratuwa, pp.1-3. NARA (2004). Technical report on assessment of water quality in Negombo Lagoon, Environment Studies Division, NARA, Colombo. pp.1-5. NMC (2008). Annual Report of Negombo Municipal Council, Negombo. pp.1-34 Rajapaksha, J.K. (1997). Low frequency tidal response and water exchange in a restricted lagoon, The Negombo lagoon-Sri Lanka, Unpublished M.Sc. Thesis, University of Gothenburg, Sweden. Samarakoon, J. (2010). Delusion, Ecosystem Biodiversity and Mangroves, Sunday Leader, 14 August 2011. Strömquist, L., Haag, F., Ratnayake, R.M.K. and Gunaratne, A.B.A.K. (2000). Integrated landscape analysis as a tool to structure and analyze environmental information; Exemplified by the Negombo Lagoon Catchment, Sri Lanka. Uppsala University, Sweden. pp.1-21. University of Moratuwa (2003). Feasibility of Dredging the Negombo lagoon to improve water flow and water quality; Part II: Engineering Feasibility, Sri Lanka Hydraulic Institute, Colombo. pp.42-72.

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Soil Erosion and Sediment Transport in Bibili Oya Watershed in Kelani River Basin K. Thuraisingham and V.P.A. Weerasinghe Faculty of Science, University of Kelaniya

ABSTRACT Soil erosion is one of the serious environmental issues in watersheds in Sri Lanka and it is a severe problem in the up and mid country where steep slopes, high intensity rainfall and inappropriate land uses prevail. Bibili Oya watershed is located in Kegalle district. The objective of this study was to use Geographical Information Systems (GIS) to estimate soil loss and sediment transport in Bibili Oya watershed using RUSLE. Maps of contours, land use along with soil and rainfall data were used to create RUSLE factors. Average annual sediment yield was estimated using sediment delivery ratio and average annual soil loss. Soil erosion hazard map of the watershed was prepared according to five hazard categories. Annual sediment load of the Bibili Oya was determined from measured daily suspended sediment load using discharge-sediment load relationship. Bibili Oya watershed has estimated mean average annual soil loss of 12.96 t/ha. The estimated average annual sediment yield was 5.90 t/ha using GIS. Annual sediment load of Bibili Oya is 4.84 t/ha/yr. Majority of the watershed (56.7%) is under low erosion hazard category. Presence of good vegetation cover contributes immensely to this situation. Nearly 16% of the land area is fallen under very high and extreme high erosion category. Severity of soil erosion is associated with the steep river banks and agricultural land uses along the slopes. It was not possible to obtain a good agreement between measured and estimated sediment transport. Deposition of sediment within the watershed can be a major reason for this situation. The produced erosion hazard map can be used as a guide to identify the erosion hazard areas to apply conservation measures efficiently.

INTRODUCTION Soil erosion is a critical global environmental issue and it adversely affects the productivity of ecosystems (Pimental, 2006). Population growth, deforestation, agriculture in marginal lands, poor land management practices, construction activities, urbanization, climate change and overgrazing are the main factors which accelerate this natural process (Sisay et al., 2014). Severity of watershed degradation affects the sustainable development of a country. Watershed erosion causes serious off-site effects such as siltation of reservoirs consequently affecting the hydropower generation. Capacity of reservoirs, river and drains are reduced due to sedimentation. Stream channels get clogged with sediment and water shortage for downstream irrigation, widening of flood plains during floods, additional cost to treat the water for drinking purposes, etc. will be the results. On- site effects include declining land productivity, soil fertility, crop production and loss of lives, etc. (Wimalasinghe & Wijeyaratna, 1998). Sediment is the largest nonpoint source

K. Thuraisingham and V.P.A. Weerasinghe

pollutant and the primary factor for deterioration of surface water quality. Eutrophication, low oxygen levels, high nutrient and organic matter concentrations in reservoirs, canals, and other water bodies are the most common sediment associated water pollution problems (Noor et al., 2013). Sediment causes turbidity in water which limits the light penetration and prohibits healthy plant growth on the river bed. The accumulation of sediments on the river bed can smother or disrupt aquatic ecosystems, degrade spawning grounds and habitats of desirable fish species (FAO, 2000). Quantitative estimation of soil erosion is important to manage the land. Erosion models are particularly useful instruments in predicting soil erosion. Universal Soil Loss Equation and its derivative, the Revised Universal Soil Loss Equation (RUSLE) are commonly used to estimate average annual soil loss resulting from rill and sheet erosion. Other process-based erosion models need intensive data and computation requirements. USLE model was originally developed for gently sloping cropland situations, and RUSLE expanded the applicability of the model to include soil loss estimation for rangeland, forests, disturbed sites, and steep slopes because there is a modification in slope steepness factor (Remortel et al., 2001). Geographical Information System is a tool which helps in creation of a database for the watershed and it is very much useful for carrying out spatial analysis thus helping the land managers to make decisions for critically affected areas. Bibili Oya watershed located in upper catchment of Kelani river basin was selected for this study. Water erosion is the main cause of soil loss in the watershed due to high rainfall and steep topography. Due to agriculture production without proper land management, reduction of land productivity and subsequent abandoning of land are observed. Recreation activities like swimming, water drafting, boating in Kelani river are famous among local and foreign visitors but have been threatened by deposit of sediments in river during rainy season.

Objectives This study was carried out to determine the average annual soil loss and average annual sediment yield in Bibili Oya watershed and to develop a soil erosion hazard map using Geographical Information Systems (GIS).

METHODOLOGY Study area Bibili Oya watershed is located in Kegalle district in Sabragamuwa province and belongs to Yatiyantota Divisional Secretariat division. It covers an area of 14.5 km2. Figure 1 shows the location of Bibili Oya watershed in Kelani river basin.

84


Soil Erosion and Sediment Transport in Bibili Oya Watershed in Kelani River Basin

Figure1: Location map of Bibili Oya watershed

Average annual soil loss using GIS RUSLE soil erosion model was used to estimate the average annual soil loss. RUSLE is given by Equation 1. RUSLE differs from USLE due to the modifications in slope steepness factor. ArcGIS 10.0 was used to extract Bibili Oya watershed and to develop other spatial data layers. Watershed was delineated from contour map of 4m interval.

(Equation 1) Where, A LS K R C P

Computed soil loss per unit area per year (t ha−1 yr−1) Slope length and steepness factor (dimensionless) Soil erodibility factor (t h MJ−1 mm−1) Rainfall erosivity factor (MJ mm ha−1 h−1yr−1) Cover and management factor (dimensionless) Support practice factor (dimensionless)

Slope length and steepness factor (LS-Factor) Surface slope of the cell (in degrees) was determined from Digital Elevation Model (DEM) using the slope function available in spatial analyst in ArcGIS. The slope steepness factor was calculated based on the relationship given by McCool et al. (1987) (Equations 2a and 2b). (Equation 2a) (Equation 2b) Where

S=slope steepness factor

θ=slope angle in degrees


85


Slope Length factor is given by Equation 3 (Wischmeier & Smith, 1978).

(Equation 3) Where, L = slope length factor = horizontal projected slope length (m) m = slope length exponent. Horizontal projected slope length was calculated using flow accumulation map. Threshold drainage area (number of cells) was applied to extract stream networks from flow accumulation map (Maathius & Wang, 2006). Cell values assigned as zero for streams. Then slope length factor was calculated by multiplying flow accumulation map into cell size. Cell size means resolution of the DEM and it is equal to four. Equation 4 explains substitution of horizontal projected slope length and slope length factor calculation (Tirkey et al., 2013; Sisay et al., 2013).

(Equation 4) Slope length and steepness factor for each grid cell within the entire watershed area was calculated by multiplying L and S factors. Soil erodibility factor (K-Factor) Soil type in Bibili Oya watershed is Red Yellow Podzolic (Alwis & Panabokke, 1972). Soil erodibility factor for Red Yellow Podzolic soil is 0.22 (Joshua, 1977). Vector data layer was produced with the soil erodibility factor and was converted to raster. Rainfall erosivity factor (R-Factor) Rainfall isohytes for BibiliOya watershed were generated using point rainfall data by applying Kringing interpolation technique.Rainfall erosivity factor for each grid cell was determined from the average annual rainfall value using correlation developed for Sri Lanka by Premalal (1986) (Equation 4). (Equation 4) Cover and Management factor (C-Factor) Land use map was used for analyze the C-factor. C-factor was assigned by field observation and literature (FAO, 2010; Wijesekera & Samarakoon, 2001) to different land uses. Artificial structures like roads were given zero (0) values. Wetland was given zero (0). Cover and management factor data layer was converted to raster for further analysis. Conservation practices factor (P-Factor)

86



Management practices applied on each land use was identified by field observations. P values were assigned to land uses by field observation and literature (FAO, 2010; Wijesekera & Samarakoon, 2001; Kuok et al., 2013). Forest area and artificial structures were given value one (1.0). Conservation practices factor data layer was converted to raster for further analysis. Table 1 presents the C and P values used for the analysis. Table 1: C-factor and P-factor for land uses in BibiliOya watershed Land use types Forest

Management practices Thick cover plant and Built -up rural areas natural mulch, Strip with home gardens cropping Rock Thick layer of mulch and Rubber cover plant Contour with strip Tea cropping and terraces Coconut with annual Thick cover plant, Strip crops as inter crop cropping Chena Strip cropping Wetland, Building, road, stream

C-Factor 0.001

P-Factor 1.0

0.05

0.25

0.0001

1.0

0.1

0.2

0.2

0.15

0.03

0.2

0.3

0.4

0

1.0

Using the RUSLE, soil loss was estimated for the watershed using above data layers.

Estimation of average annual sediment yield using GIS Average annual sediment yield was calculated using sediment delivery ratio and average annual soil loss. Sediment Delivery Ratio was calculated using Equation 6 (Bhattarai & Dutta, 2006; Jain & Kothyari, 2000). (Equation 6) Where DR Sediment Delivery Ratio li/aiSi0.5 travel time of the cell to the nearest channel (s) aiSi0.5 flow velocity of the cell (m/s) li length of a diagonal side in the cell according to flow direction (m) Si slope of the cell (degree) ai coefficient for land uses γ coefficient for a given catchment and γ value is equal to 1


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Coefficient for each land use (Bhattarai and Dutta, 2006) was added to each grid cell in land use by reclassification. Length of a diagonal cell is equal to . Coefficient for a given catchment was considered as constant and was equal to one (Bhattarai & Dutta, 2006). Sediment yield for the watershed was obtained using Equation 7 (Jain and Kothyari, 2000). (Equation 7) Where Sy DR SE N

Average annual sediment yield (t/ha/yr) delivery ratio of a cell amount of average annual soil loss produced within the cell (t/ha/yr total number of cells over the catchment

Sediment delivery ratio and average annual soil loss layers were multiplied using raster calculator. Then sediment yield for watershed was calculated by adding all cell values.

Development of soil erosion hazard map Average annual soil loss map was quantitatively classified into five erosion hazard classes. Table 2 describes the erosion hazard classes and their values. Table 2: Erosion hazard classes (Bergsma, 1984, Senanayake et al., 2013) Erosion hazard classes Low Moderate High Very High Extremely high

Average annual soil loss(t ha-1yr-1) 0-5 5-12 12-25 25-60 >60

The low class is within the range of soil loss tolerance values. The moderate class is expected to cover the hazard in situations where erosion is somewhat high but needs to be accepted on most farms. The class of high, very high and extremely high erosion is unacceptable for any land use aiming at sustained productivity. The erosion in the class extremely high is destructive for the land in a short period for instance less than 10 years (Bergsma, 1984).

Annual suspended sediment load in Bibili Oya Annual suspended sediment load of Bibili Oya watershed was determined using sediment load and discharge relationships. Sediment samples were collected at stream gauging station at different times for this purpose. Stream discharge at different times in a particular day was computed using stage –discharge

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relationship. Suspended sediment load in a particular time was calculated using Equation 8 (Ongley, 1996). e (Equation 8) Suspended sediment load (Qs) and stream discharge (Q) relationship was built by Equation 9 (Raghunath, 2006). Then annual sediment load was calculated using this relationship.

(Equation 9) There is a power relationship between suspended sediment load and stream discharge. When converted into log to get a linear relationship, Equation 10 was derived. (Equation 10) Where Qs Suspended Sediment load (g/sec) Q Discharge (m3/sec) K, n Constants Graph was plotted and average suspended sediment load in g/s for a particular day was calculated. Then it was converted into tonnes/day using Equation 11. After annual sediment load was calculated by adding all daily suspended sediment load. (Equation 11)


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RESULTS AND DISCUSSION Average annual soil loss from the watershed area is presented in Figure 2. The spatial variation of soil loss within the watershed varies between 435.42 t/ha/yr to 0 t/ha/yr. Mean average annual soil loss was estimated as 12.96 t/ha/yr and the estimated total soil loss was 18,779.04 t/yr.

Figure 1: Average annual soil loss map of Bibili Oya watershed Bibili Oya watershed has maximum average annual sediment yield of 261.35 t/ha/yr. The estimated total sediment yield was 8,549.10 t/yr. Mean average annual sediment yield at the stream gauging station was 8.18 t/ha/yr estimated using GIS. The measured sediment load at the gauging station was 4.84 t/ha/yr. This significant difference between the measured and estimated sediment discharge values can be due to trapping of sediment within the watershed in topographic depressions, and also by the vegetation roots along the river as well as the limitations of the data used in the study.

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Figure 2: Average annual sediment yield map of Bibili Oya watershed Bibili Oya watershed has maximum average annual sediment yield 261.35 t/ha/yr, minimum average annual sediment yield 0 t/ha/yr, mean average annual sediment yield 5.90 t/ha/yr and total sediment yield 8,549.10 t/yr. mean average annual sediment yield at stream gauging station is 8.18 t/ha/yr using GIS. The soil erosion hazard map is given in Figure 4. According to the erosion hazard map, 56.7% of the watershed area is under low erosion hazard and nearly 14% of the land area is under moderate erosion hazard. Low soil erosion areas were mainly covered with a good vegetation cover such as forests and home gardens. Tea plantations also have very good soil conservation practices such as contour cultivations and terraces. Therefore, erosion is low and moderate. High and very high erosion hazard categories account for 10.38% and5.23% areas respectively. Severe soil erosion risk was evident along steep slopy banks of the tributaries and agricultural land uses in steep slopes. Field investigations can be carried out in high and very high erosion hazard areas to identify the actual situation and suitable soil conservation measures can be applied to control the erosion.


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Figure 3: soil erosion hazard map of Bibili Oya watershed

CONCLUSIONS AND RECOMMENDATIONS RUSLE combine with GIS can be used to identify the spatial variation of erosion hazard in a given watershed. However, it is difficult to obtain very accurate estimations of soil loss and sediment yield using data with poor spatial resolution. High resolution Digital Terrain Model and satellite images will improve the estimations. Majority of the area in Bibili Oya watershed is under low erosion risk. Area under severe erosion risk is 29.2%. Soil conservation practices should focus on severe erosion areas to protect them from further degradation. Long term monitoring of sediment transport will help to establish relationships between stream discharge and sediment transport. It will also help to identify any changes within the watershed area which contribute to increase soil erosion and sediment transport.

REFERENCES Alwis, K.A. and Panabokke, C.R. (1972). Handbook of the soils of Sri Lanka, Soil Science Society Ceylon Vol 2. p. 83-85. Bergsma, E. (1984). Aspects of mapping units in the rain erosion hazard catchment survey: Available from http://www2.alterra.wur.nl /Internet/webdocs/ilripublicaties/publicaties/Pub40/pub40-h7.pdf [Accessed: 10th September 2014] Bhattarai, B. and Dutta, D. (2006). Estimation of soil erosion and sediment yield using GIS at catchment Scale: Available from Error! Hyperlink reference not valid. at_catchment_scale [Accessed: 2nd June 2014]

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FAO (2000). pollution by sediments: Available from http://www.fao.org/docrep/w2598e05.html [Accessed :6th july 2014] FAO (2010). On-site effects of cassava cultivation and soil erosion on the environment: Available from http://www.fao.org/docrep /007/y2413e/y2413e09.html [Accessed: 20th May 2014] Jain, K. and Kothyari , C. (2001). Estimation of soil erosion and sediment yield using GIS, Hydrological Science, 45:771-786. Joshua, W.D. (1977). Soil erosive power of rainfall in the different climatic zones of Sri Lanka: Available from https://www.itia.ntua.gr /hsj/redbooks /122/iahs_122_0051.pdf [Accessed : 13th May 2014] Kuok, K. K.K., Mah, Y. S.D, and Chiu, P.C. (2013). Evaluation of C and P Factors in Universal Soil Loss Equation on Trapping Sediment: Case Study of Santubong River Water Resource and Protection 1149-1154. Noor, H., Fazli, S., Alibakhshi, S.M. (2013). Evaluation of the relationships between Runoff-Rainfall-Sediment related nutrient Loss (A case study: Kojour Watershed, Iran) Soil & Water Research, 8:172–177. Maathuis. B.H.P. and Wang. L (2006). Digital Elevation Model Based Hydro processing Available from http://www.geocarto.com.hk/cgibin/pages1/mar06/3_Maathuis.pdf [Accessed : 18th May 2014] McCool,D.K., Brown,L.C., Foster,G.R., Mutchler , C.K. and Meyer,L.D. (1987). Revised slope steepness factor for the USLE.USA Ongley, E. (1996). Sediment measurement, Water quality monitoring - a practical guide to the design and implementation of freshwater quality studies and monitoring programmes, UNEP and FAO [online].Available from http://www.who.int/water_sanitation_health/resourcesquality/wqmchap13.pdf [Accessed : 5th May 2014] Premalal, W.P.R.P. (1986). Soil and water conservation assessment: Available from www.academia.edu/soil and water conservation [Accessed 9thjuly 2014] Pimental, D. (2006). Soil erosion: A food and environmental threat Environment Development and sustainability, 8:119-137. Raghunath, H.M. (2006). Hydrology Principles, Analysis, Design.2nd Ed. India. Remortel, V. Hamilton,R.M., and Hickey, R. (2001) Estimating the LS factor for RUSLE through iterative slope length processing of Digital Elevation data within ArcInfo grid, Cartography, 30:.27-35. Senanayake, S.S., Munasinghe, M.A.K., and Wickramasinghe, W.M.A.D.B. (2013). Use of erosion hazard assessments for regional scale crop suitability mapping in the Uva province, Annals of Sri Lanka Department of Agriculture, 15:133-147. Sisay, A., Chalie, N., Girmay,Z. , Takele, G. , and Tolera, A. (2014). Landscape– scale soil erosionmodelling and risk mapping of mountainous areas in eastern


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escarpment of Wondo Genet watershed, Ethiopia Agricultural Science and Soil Science 4: 107-116. Tirkey, A.S., Pandey, A.C., Nathawat, M.S.(2013). Use of Satellite Data, GIS and RUSLE for Estimation of Average Annual Soil Loss in Daltonganj Watershed of Jharkhand (India), Remote Sensing Technology 1:20-30. Wijesekera, S. and Samarakoon, L. (2001). Extraction of parameters and modeling soil erosion using GIS in a GRID environment Available from http://www.crisp.nus.edu.sg/~acrs2001/pdf/169wijes [Accessed: 11th July 2014] Wimalasinghe, H.M. and Wijayaratna, C.M. (1998). Participatory watershed management: present status and future prospects, Available from http://publications.iwmi.org /pdf/H023525.pdf [Accessed : 11th May 2014] Wischmeier, W.H. and Smith, D.D. (1978). Predicting rainfall erosion losses – a guide to conservation planning: United States Department of Agriculture, Agricultural handbook No 537.

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Present Status of Eco-units of Micro Tanks in Agbopura Cascade, Kanthale and Their Implications on Hydrology and Other Ecosystem Functions K.M.G.S.R. Senevirathna Postgraduate Institute of Agriculture, University of Peradeniya and

H.M.G.S.B. Hitinayake Faculty of Agriculture, University of Peradeniya

ABSTRACT Dry zone agriculture system of Sri Lanka mainly depends on tank based hydraulic system and their interconnected water bodies of different types. It is called as a cascade system and this ecosystem consists of many units. The eco-units around a tank control siltation of tank, conservation of collected water and purification of collected water and release from the tank. The objective of this study is to evaluate the present status of the eco-units and identify their implications on hydrology and other ecosystem functions. The study was conducted at three tanks Diulgas wewa, Thalgas wewa and Palugas wewa in the Agbopura cascade. The present status of eco-units was evaluated by developing historical diagrams of the tanks with the participation of the local farmers in the area. Vegetation study was conducted to evaluate species composition and diversity of different eco-units. Shannon-wiener index was used to estimate the species diversity. Results of the study indicated that Gasgommana and Perahana were found in all three tanks. Iswetiya and Kattakaduwa were recorded only in Diulgaswewa and Thalgaswewa tanks. The eco-units of Agbopura Tank Cascade recorded a Floristic Richness Index value of 63. Twenty five species belong to twenty two genera and sixteen families were recorded from the ecosystem. Korakaha and Maila were the dominant species in Gasgommana eco-unit and it was Atteriya, korakaha and Galweera in the Iswetiya eco-unit. Perahana eco-unit mainly consists of Korakaha, Kalu habara and Kumbuk. Kambu, Wetakeiya and Rattan were the dominant species in Kattakaduwa. The Iswetiya eco-unit recorded the highest species diversity (H = 2.12) and the lowest diversity by the Kattakaduwa eco-unit (H=1.001). The Diulgaswewa tank showed the highest species diversity (H = 2.52) among the three tanks and the lowest diversity by the Palugaswewa tank as it is highly degraded due to human activities. The study shows that the extents of the eco-units have reduced due to the expansion of agricultural activities especially rice cultivation and also village settlements. The remaining areas of eco-units are in a degraded state due to tree felling, brick making and other human activities. In case of most eco-units, only remnants can be

K.M.G.S.R. Senevirathna and H.M.G.S.B. Hitinayake

observed. This situation has caused siltation of the tanks and negative effects on the quality of water stored and released by these tanks. Also this has caused deterioration of the quality of habitats of many important aquatic species. Awareness creation on importance of these eco-units, planting suitable species to restore the eco-units and setting up suitable institutions to manage cascades are suggested to improve the hydrology and other ecosystem functions performed by this tank cascade ecosystem.

INTRODUCTION Dry zone agriculture system of Sri Lanka largely depends upon the tank based hydraulic system. Within this irrigation system an agricultural pattern flourished resulting in self-sufficiency in food in a dry and yet fertile soil. Madduma Bandara (1985) stated that there are 20,000 small and large tanks in the Dry Zone of Sri Lanka. The general condition in the Dry Zone necessitated a continuous maintenance of a systematic irrigation system. The environment of the Dry Zone was naturally water poor due to annual and prolonged droughts. The tank system was a positive response to the challenge demanded by the natural phenomenon. Today, this well-developed water management system is erroneously named as an irrigation system. However, according to most of the renowned authorities in this field this was a sustainable water-soil-flora-fauna-human ecosystem (Mendis, 2000). This ecosystem functions to support water conservation, better utilization of storage and purification of drainage. The backbone of the tank ecosystem was its ability to store the rainfall water within the system and was focused on the water requirement of the entire ecosystem, unlike in modern irrigation systems, which are focused only on supplying the crop water requirement for the root-zone. To fulfill this requirement, various types of structures and ecological units have been constructed. Small tanks do not exist as individuals. Natural drainage system in the undulating topographic formation in a watershed is blocked by earth bunds in appropriate locations to store water forming a series of tanks along the drainage line. This ramifying nature of the drainage system has led to form clusters of small tanks found in series, which are connected to form a system known as 'tank cascades' (Madduma Bandara, 1985). The components of the tank cascade and their functions have been reviewed by many authors (Dharmasena, 2000; Geekiyanage & Pushpakumara, 2013). Existence of small tanks in a cascade pattern is an advantageous feature in many ways. Surface water bodies spread over an area can maintain the groundwater level closer to the land surface at least on lower areas adjacent to tank basins. It can be stipulated that absence of such a branched system of tanks could lead to rapid depletion of groundwater due to natural gradient of the drainage system (Vidanapathirana, 2009). Therefore, the presence of tank cascade system has contributed to maintaining mosaic of natural vegetation with deep-rooted large tree species where the composition is depend upon the level of the ground water table along various positions in the catenary slope.

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Present Status of Eco-units of Micro Tanks in Agbopura Cascade, Kanthale and Their

Implications on Hydrology and Other Ecosystem Functions

Upper tanks in a tank cascade system act as buffer reservoirs to absorb floodgenerating rainfall, which would otherwise bring the risk of breaking lower tanks. Similarly, these upper tanks are buffer reservoirs to supply water to the lower tanks when they are in short of water to save the crops. Sustainability of traditional tankvillage system had been maintained in the past simply not only from structural maintenance. Each and every component of the ecosystem was given due consideration. The attention was paid not only on macro land uses such as paddy land, settlement area, chena lands and tank bed but also on micro-land uses such as godawala, iswetiya, gasgommana, perahana, kattakaduwa, tisbambe and kiul-ela (Annexure 1).

Objectives The objective of present study is to evaluate the historical changes and present status of the eco-units and identify their implications on hydrology and other ecosystem functions.

METHODOLOGY This study was conducted at the three tanks Diulgaswewa, Thalgaswewa and Palugaswewa in the Agbopura cascade in Kantale. Direct observations were carried out to identify the presence of eco-units in the village tank ecosystems. The historical changes and present status of the eco-units were evaluated during the study using historical maps of the tank ecosystems developed with local farmers. Ten farmers who live in the village settlement or vicinity of each tank were participated in developing the historical diagrams. Farmers above 60 years of age were selected for this study. Vegetation survey was conducted to evaluate the species composition of different eco-units. All species belong to growth forms trees, shrubs and perennial herbs (other than annual herbs) were recorded during the survey. Three samples plots (5 m x 5 m) per each eco-unit in each tank were used to sample the vegetation. Shannon-wiener index were used to estimate the species diversity. Shannon-Wiener Index denoted by H = -SUM [(pi) × ln(pi)] Where SUM - Summation, pi - Number of individuals of species i/ total number of individuals in all samples, S - Number of species or species richness Maximum diversity possible Hmax = ln (S) Evenness E = H / Hmax Relative density = No. of individuals of a given species / No. of individuals of all species x100


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RESULTS AND DISCUSSION Historical changes in the eco-units of the three micro-tanks The historical diagrams of the three tanks are presented in Annexure 02, 03 and 04. These diagrams show the changes that have taken place during past 25-30 years. Table 1 shows the main findings revealed from historical diagrams and discussions with the local communities. Table 1: Summary of main land use changes taken place in past 25-30 years in the three tanks Tank

Changes during past 25-30 years

Divulgaswewa

This is the biggest and lowest tank in the Cascade. The sizes of these ecounits have reduced mainly due to expansion of rice cultivation after rehabilitation of the tank to increase its capacity. Normally soils of these eco-units are rich in soil fertility and are highly suitable for rice cultivation as they are covered with silt due to fluctuations of the water levels in the tank. Village settlement (gangoda area) also has shifted to another place to make room for rice cultivation. Some areas earlier used for chena cultivation also have converted to rice cultivation after the increase in the capacity of the tank. The shape of the tank has changed from fluted to conical. This is the second largest tank in the cascade and located between other two tanks along the valley. Most of the kattakaduwa area has been encroached for rice cultivation. Also forest areas have been converted to rice fields. The areas of other eco-units also have reduced mainly due to expansion in rice cultivation and village settlement. This is the smallest tank in the cascade and located above other two tanks in the valley. A temple has been established near the tank. As a result people have abandoned the chena cultivation took place in the area around the temple creating tree vegetation very similar to “Gasgommana”. The village settlement and rice cultivation has expanded at the expense of forest cover that was around the tank. The kattakaduwa area has been completely encroached for rice cultivation.

Thalgaswewa

Palugaswewa

Presence of eco-units Presence of different eco-units in the three tanks is given in Table 2. It shows that some eco-units such as Godawala and Tisbambe are absent in all three tanks and any of the informants participated in drawing the historical diagrams could not recall their presence. Also it became evident that the informants had little or no knowledge on their structure, composition or their hydrological functions. Gasgommana and Perahana eco-units were recorded in all the tanks. The eco-units of the Palugaswewa tank is in a highly degraded state due to human activities where both Kattakaduwa and Iswetiya have been completely converted to other land uses.

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Table 2: Presence and extents of Eco-units in the micro tanks Eco unit Gasgommana Perahana Iswetiya Godawala Thisbambe Kattakaduwa

Divulgaswewa

Thalgaswewa

Palugaswewa

X X

X X

X X X X

(c) Species composition of the different eco-units Gasgommana Species composition of the Gasgommana eco-units in the three tanks is given in Table 3. Seven plant species were recorded from the Gasgommana eco-units of tank cascade. Results show that Korakaha and Maila are the most common species recorded from the Gasgommana eco-unit. The species Madan, Keliya and Eraminiya were reported from all three tanks. Table 3: Species composition of Gasgommana eco-units in the three tanks Species

Divulgaswewa Thalgaswewa tank tank

Korakaha Maila Palu Madan Eraminiya Keliya Kumbuk Total

02 03 02 01 01 01 01 11

02 03 00 02 01 01 00 09

Palugaswewa Total no. tank of individuals 6 02 8 02 2 00 4 01 3 01 3 01 2 01 28 08

RD

21.43 28.57 7.14 14.29 10.71 10.71 7.14

Key: RD - Relative Density, Botanical names are given in Annexure 05.

Iswetiya Species composition of the Iswetiya eco-units in the three tanks is given in Table 4. As mentioned earlier, Iswetiya was absent in the Palugaswewa tank. Nine plant species were recorded from the Iswetiya eco-units of the tank cascade. Atteriya, Madan, Palu, Korakaha, Timbiri, Galweera and Keliya were recorded on other two tanks. Of them Atteriya, Korakaha and Galweera were the most common species.


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Table 4: Species composition of Iswetiya eco units among three tanks Species Atteriya Madan Palu Weera Korakaha Thimbiri Galweera Nithul Keliya Total

Divulgaswewa Thalgaswewa Palugaswewa Total no. of tank tank tank individuals 4 02 02 00 2 01 01 00 3 02 01 00 2 02 00 00 4 01 03 00 2 01 01 00 4 01 03 00 1 01 00 00 2 01 01 00 24 12 12 00

RD 16.67 8.33 12.50 8.33 16.67 8.33 16.67 4.17 8.33


Perahana Species composition of the Perahana eco-units in the three tanks is given in Table 5. Seven plant species were recorded from the Perahana eco-units of the tank cascade. Korakaha, Kaluhabara and Kumbuk were the most dominant species recorded in the Perahana eco-unit. Korakaha produces a root mat which acts as the strainer. Table 5: Species composition of Perahana eco-units in the three tanks Species

Divulgaswew a tank

Thalgaswew a tank

Palugaswew a tank

Korakaha Kaluhabara Kumbuk Thibiri Mee Keliya Kalawel Total

05 02 02 02 02 02 00 15

03 02 03 02 01 01 01 13

04 03 02 01 00 02 01 13

Total no. of individuals 12 7 7 5 3 5 2 41

RD

29.27 17.07 17.07 12.20 7.32 12.20 4.88


Kattakaduwa Species composition of the Gasgommana eco-units in the three tanks is given in Table 6. Seven plant species were recorded from the Kattakaduwa eco-units of the tank cascade. It is found that most of the large trees that were there earlier have

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been felled illegally leaving only few medium sized trees and the shorter vegetation such as Kambu, Wetakeiya and Rattan. Table 6: Species composition of Kattakaduwa eco-units in the three tanks Species

Divulgaswewa Thalgaswewa Palugaswewa Total no. tank tank tank of individuals Karada 1 01 00 00 Thimbiri 1 00 01 00 Kumbuk 2 02 00 00 Mee 3 02 01 00 Vetakeyya 04 7 03 00 Kambu 54 23 31 00 Rattan 6 03 03 00 Total 74 35 39 00

RD

1.35 1.35 2.70 4.05 9.46 72.97 8.11


Plant diversity in the micro tanks Divulgaswewa tank Species composition of the Divulgaswewa tank is given in Table 7. Eighteen plant species were recorded from the eco-units of the tank. Korakaha and Keliya were reported from all eco-units except Kattakaduwa. Kumbuk, Karanda and Mee were reported as the upper story tree species and Kambu, Rattan and Vetakeya as the ground vegetation from Kattakaduwa.


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Table 7: Species composition of Divulgaswewa tank Species Atteriya Eraminiya Gal weera Karada Kaluhabara Keliya Korakaha Kumbuk Madan Maila Mee Nithul Palu Thimbiri Weera Rattan Kambu Vetakeyya Total

Gasgommana 00 01 00 00 00 01 02 01 01 03 00 00 02 00 00 00 00 00 11

Iswetiya 02 00 01 00 00 01 01 00 01 00 00 01 02 01 02 00 00 00 12

Perahana 00 00 00 00 02 02 05 02 00 00 02 00 00 02 00 00 00 00 15

Kattakaduwa 00 00 00 01 00 00 00 02 00 00 02 00 00 00 00 03 23 04 35

Total no. of individuals

RD

02 01 01 01 02 04 08 05 02 03 04 01 04 03 02 03 23 04 73

2.74 1.37 1.37 1.37 2.74 5.48 10.96 6.85 2.74 4.11 5.48 1.37 5.48 4.11 2.74 4.11 31.51 5.48


Thalgaswewa tank Species composition of the Thalgaswewa tank is given in Table 8. Sixteen plant species were recorded from the eco-units of the tank. Korakaha and Keliya was reported from all eco-units except Kattakaduwa. Timbiri was reported from all ecounits except Gasgommana. Timbiri and Mee were reported as the upper story tree species and Kambu, Rattan and Vetakeya as the ground vegetation from Kattakaduwa.

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Table 8: Species composition of Thalgaswewa tank Species Atteriya Eraminiya Gal weera Kaluhabara Keliya Korakaha Kumbuk Madan Maila Mee Thimbiri Palu Rattan Kambu Kala wel Vetakeyya Total

Gasgommana 00 01 00 00 01 02 00 02 03 00 00 00 00 00 00 00 09

Iswetiya 02 00 03 00 01 03 00 01 00 00 01 01 00 00 00 00 12

Peraha na 00 00 00

Kattaka -duwa 00 00 00 00 00 00 00 00 00 01 01 00 03 31 00 03 39

02 01 03 03 00 00

01 02 00 00 00 01 00 13

Total no. of individuals

RD

02 01 03 02 03 08 03 03 03 02 04 01 03 31 01 03 73

2.74 1.37 4.11 2.74 4.11 10.96 4.11 4.11 4.11 2.74 5.48 1.37 4.11 42.47 1.37 4.11

Key: RD - Relative Density; Botanical names are given in Annexure 05.

Palugaswewa tank Species composition of the Palugaswewa tank is given in Table 9. Nine plant species were recorded from the eco-units of the tank. Again Korakaha was the most common species followed by Kaluhabara, Keliya and Kumbuk. Table 9: Species composition of Palugaswewa tank Species Eraminiya Kala wel Kaluhabara Keliya Korakaha Kumbuk Madan Maila Thimbiri Total

Gasgom mana 01 00 00 01 02 01 01 02 00 08

Iswetiy a 00 00 00 00 00 00 00 00 00 00

Peraha na 00 01 03 02 04 02 00 00 01 13

Kattakadu wa 00 00 00 00 00 00 00 00 00 00

Total no. of individuals 01 01 03 03 06 03 01 02 01 21

RD 4.76 4.76 14.29 14.29 28.57 14.29 4.76 9.52 4.76

Key: RD - Relative Density; Botanical names are given in Annexure 05.


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Species diversity of the eco-units Species diversity of the eco-units is given in Table 10. The Iswetiya eco-unit recorded the highest species diversity (H = 2.12) and the lowest diversity was recorded by Kattakaduwa eco-unit (H=1.001). That means (H=2.12) this plant community has diversity equivalent to a community with 08 equally-common species. Table 10: Species diversity of the eco-units Eco-unit Gasgommana Iswetiya Perahana Kattakaduwa

H 1.82 2.12 1.82 1.001

Hmax 1.95 0.24 1.95 1.95

Evenness 0.93 0.67 0.93 0.51

Species diversity of the three tanks Species diversity of the three tanks is given in Table 11. The Divulgaswewa tank showed the highest species diversity (H = 2.52) among the three tanks and the lowest diversity was recorded from Palugaswewa as it is highly degraded due to human activities. That means (H=2.52) this plant community has diversity equivalent to a community with 12 equally-common species. Table 11: Species diversity of the three tanks Tanks Divulgaswewa Thalgawewa Palugaswewa

H 2.52 2.16 2.00

Hmax 2.94 2. 77 2.20

Evenness 0.86 0.78 0.91

Causes for loss and degradation of eco-units Discussions with local people have revealed the factors that have contributed to the decline in size and degradation of the eco-units. During the war, authorities (Agrarian Services Department and Forest Department) have not been able to carry out their regular monitoring and supervision of the micro tanks and irrigation structures. Due to the land pressure and high availability of water, common lands within the micro tank ecosystem has been encroached by local people mainly for rice farming and establishing village settlements (i.e. homegardens). Soil in upper inundation area (Wew Thaulla) of some tanks have been cut and removed for brick making (e.g. Palugaswewa tank). Trees have been fallen for various purposes including use for small construction work, firewood for brick making and domestic uses. Further, it is found that local people especially new generation have little or no knowledge about the importance of eco-units in providing hydrological and other ecosystem services.

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CONCLUSIONS The eco-units of Agbopura Tank Cascade recorded a Floristic Richness Index value of 63. Twenty five species belong to twenty two genera and sixteen families were recorded from the ecosystem (Annexure 5). Of the species Kora Kaha was recorded in all eco-units except at Kattakaduwa. Kora Kaha produces a system of adventitious roots from the base of the tree which acts as a strainer and barrier for water in addition to supporting the plant to stand in muddy water. Kumbuk, Kora Kaha and Karada create water cages around their bases. They retain silt that comes with water, provide breeding grounds for some indigenous fish and other aquatic biota and habitats for small animals such as otters. Most plant species recorded in this ecosystem (especially, Kora Kaha, Mee, Timbiri, Kumbuk and Karanda) are considered as species that can perform phytoremediation function very effectively. The study clearly shows that all eco-units which are of high hydrological and ecological importance have reduced in size and quality. This trend is more prominent with upper most tank, Palugaswewa. Kattakaduwa is completely absent and only some remnants of Perahana and Iswetiya are there. The forest areas around Thalgaswewa tank and most of Kattakaduwa have been converted to rice tracts. Some control to the destruction is observed in the Divulagaswewa, the main tank of the cascade despite some land use changes took place after tank rehabilitation to increase its capacity. Unplanned expansion of rice cultivation, poverty driven environmental destruction, lack of knowledge about the importance of eco-units and poor institutional (both local and Government) set up to manage the natural resources can be attributed the destruction of this valuable ecosystem. This highly degraded state of the eco-units of Agbopura tank cascade has caused malfunctioning of the tank village ecosystem leading to many negative impacts on the hydrology of the cascade and other ecosystem functions. Hence, as measures to conserve and improve functioning of these eco-units awareness creation about the importance of eco-units, improving institutional set up to manage the system better, planting species typical to the eco-units and facilitating natural regeneration of species are suggested. In this regard all species recorded from the ecosystem especially Kora Kaha, Mee, Timbiri, Kumbuk and Karanda are suggested to be planted to restore this ecosystem. In addition, Kambu, Vetakeya and native sedge species are suggested to be planted in Kattakaduwa areas.

REFERENCES Darmasena, P.B. (2000). Towards efficient utilization of surface and ground water resources in food production under small tank system, Proceedings of the workshop on Food security and small tank system in Sri Lanka held on 9th September, 2000, National Science Foundation, Colombo. Geekiyanage, N. and Pushpakumara, D.K.N.G. (2013). Ecology of ancient Tank Cascade Systems in island Sri Lanka, Journal of Marine and Island Cultures. 2: 93-101.


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Madduma Bandara, C.M. (1985). Catchment Ecosystems and Village Tank Cascades in the Dry Zone of Sri Lanka: A Time-Tested System of Land and Water Management in Strategies for River Basin Management, Linkoping, Sweden. Mendis, D.L.O. (1986). Evolution and Development of Irrigation Ecosystems and Social Formations in Ancient Sri Lanka, Transactions of the Institute of Engineers, Sri Lanka. Vidanapathirana, P. (2009). Catchment morphometry and tank distribution pattern in the Dry Zone of ancient Sri Lanka with Special reference of the Malvatu Oya and Kalā Oya basins, Available in http://www.irrigation.gov.lk

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Annexure 1: Eco-units in small tank ecosystems (Dharmasena, 2000; Geekiyanage & Pushpakumara, 2013). Eco-unit Descriptions Gasgommana It is the upstream of the land strip located above the tank bed and (tree belt) water is accumulated in Gasgommana only when the tanks spill out. Naturally grown large trees such as Kumbuk, Nabada, Maila and Damba and climbers such as Kaila, Elipaththa, Katukeliya, Kalawel and Bokalawel are found in this area. The Gasgommana acts as a wind barrier and at the same time it helps to reduce evaporation from the tank and to lower the water temperature. It gets closer to the bund from either side where roots of large trees make water cages creating breeding and living places for some fish species. This strip of trees demarcates the territory between human and wild animals. Perahana It is the meadow developed under Gasgommana and filters the (Silt trap) sediment flow coming from the upstream chena lands. Large amount of sediments with flow water retain on that area and water release to the tank. Iswetiya or It is the constructed soil ridge in the upstream of the tank at either potawetiya side of the tank bund to prevent entering the eroded soil from (Check dam / upper land slopes. Soil ridge) Godawala A manmade water hole to trap sediment and it provides water to (Water hole) wild animals. This might be a strategy used to evade man-animal conflict. Kuluwewa A small tank constructed above relatively large tanks only to trap (Silt trapping sediment and not for irrigation purposes. It provides the water small tanks) necessary for cattle and wild animals. Tisbambe It is a fertile land strip found around the settlement area (Hamlet (Gangoda) and does not belong to any body. Tree species such as buffer) mee, mango and coconut are grown in scattered manner. Mostly this area was used for the sanitary purposes and also it acts as the resting place of buffaloes. Buffaloes were used as a protection mechanism from wild animals and malaria. Kiulela This is the old natural stream utilized as the common drainage. (Drainage Tree species such as karanda, mee, mat grass, ikiri and vetakeya channel) and few rare small fish species are also found in water holes along the kiulela. Most importantly it removes salts and iron in polluted water and improves condition of the drainage water from the paddy tract.


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Kattakaduwa (Intercepter)

108

This is a reserved land below the tank bund. It consists of three micro-climatic environments: water hole; wetland; and dry upland, therefore, diverse vegetation is developed. This land phase prevents entering salts and ferric ions into the paddy field. The water hole referred to as 'Yathuruwala' minimizes bund seepage by raising the groundwater table. Villagers plant vetakeya along the toe of the bund to strengthen stability of the bund. It appears to be the village garden, where people utilize various parts of the vegetation for purposes such as fuelwood, medicine, timber, fencing materials, household and farm implements, food, fruits and vegetables. Specifically they harvest row materials from this vegetation for cottage industries.


Present Status of Eco-units of Micro Tanks in Agbopura Cascade, Kanthale and Their Implications on Hydrology and Other Ecosystem Functions


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110


Present Status of Eco-units of Micro Tanks in Agbopura Cascade, Kanthale and Their Implications on Hydrology and Other Ecosystem Functions


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Annexure 5: List of plants recorded in the eco-units of the three tanks. Common name Atteria Bokala wel Damba Elipaththa Eraminiya Gal weera Geta Nitul Ikiri Kaila Kalawel Kalu habara Kambu Kelia wel Ketakala Korakaha Kumbuk Madan Maila Mee Nabada Palu Timbiri Weera Wetake Wewel

Family Rutaceae Fabaceae Myrtaceae Ebanaceae Rhamnaceae Euphorbiaceae Moraceae Acanthaceae Euphorbiaceae Fabaceae Ebanaceae Poaceae Tiliaceae Euphorbiaceae Memecylaceae Combretaceae Myrtaceae Fabaceae Sapotaceae Verbanaceae Sapotaceae Ebanaceae Euphorbiaceae Pandanaceae Aracaceae


Botanical name Murraya paniculata Derris scandens Syzygium gardneri Maba buxifolia Zizyphus napeca Drypetus gardneri Striblus aspera Acanthus ilicifolius Phyllanthus reticulatus Derris scandens Diospyros ovalifolia Pennisitum glucum Grewia spp. Bridelia retusa Memecylon umbellatum Terminalia arjuna Syzygium cumini Bauhinia racemosa Madhuca longifolia Vitex leucoxylon Manilkara hexandra Diospyros embryopteris Drypetus sepiaria Pandanns spp. Calamus spp.

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Water Quality and the Environment


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Water Quality Analysis along Mahaweli River in Upper Mahaweli Catchment Area of Sri Lanka H.K.I.J. Thilakarathne, N.S. Withanage, R.M.C.W.M. Rathnayake Faculty of Animal Science and Export Agriculture Uva Wellassa University of Sri Lanka, Badulla and K.M.A. Kendaragama Natural Resources Management Centre, Department of Agriculture, Peradeniya

ABSTRACT Mahaweli is a multipurpose river which provides water for drinking, irrigation, hydropower generation, recreation, environmental use etc. Hence, its quality is very important to provide an uninterrupted water supply to these water use sectors. Upper Manahaweli catchment area is considered as the heartland of the nation since the quantity and quality of water of Mahaweli is highly dependent on this catchment area. The water quality of a flowing river is a matter of prevailing land use conditions in its catchment area. Hence, the objective of this study was to assess the water quality along the Mahaweli river in Upper Mahaweli catchment area with respect to available land use types and to investigate the suitability of its water basically for drinking and other uses. Thus, water quality parameters viz, pH, electrical conductivity at 25oC and turbidity were assessed at 11 different locations along Mahaweli river within Upper Mahaweli catchment area and its immediate downstream. The results revealed that comparatively lower turbidity, EC and pH levels can be seen in the Mahaweli water at upstream areas of the catchment where land use types with good vegetation cover are available. Further, turbidity, EC and pH levels are gradually increasing from upstream to downstream, as the land use types are changing from natural/ well managed plantations to human induced land uses such as homesteads, paddy and urban. Therefore, it was alarmed that, although the tested EC and pH levels are still within the safe limits for drinking as per the Sri Lankan Standards, there is a threat of degrading water quality of Mahaweli river especially in terms of turbidity which may resulted in sedimentation of river bed and the reservoirs.

INTRODUCTION The water quality of the rivers in Sri Lanka is of vital importance since they are the major sources of portable water supply. The deterioration of water quality of rivers creates adverse impacts on human health and subsequently the socio economic development of the country. Due to rapid development and growth of population in the country, most of these water bodies are being continuously polluted by different sources at an alarmingly increasing rate. These sources mainly include point sources such as industrial discharges, and uncontrolled sewerage discharges and non-point

H.K.I.J. Thilakarathne, N.S. Withanage, R.M.C.W.M. Rathnayake and K.M.A. Kendaragama

sources of pollution which primarily include the storm water runoff from residential, industrial, commercial and agricultural land uses (Welagedara et al., 2014). According to the Ministry of Forestry and Environment (2000) water of river Mahaweli is polluted mainly by soil erosion, chemical and agricultural pollutants, industrial pollution and solid waste disposal. Mahaweli is the longest river in Sri Lanka with a length of 335 km and a catchment area of 10,448 km2. The drainage basin for this river is incredibly large which is almost equal to one fifth of the island’s entire size. The Upper Mahaweli Catchment Area (UMCA) is considered very important to the Sri Lankan economy as it provides water to generate hydropower and to cultivate a large extent of paddy and other field crops in the Dry Zone of the country. The upper part of the UMCA has subjected to intensive cultivation since the climatic and soil conditions are highly favourable for exotic vegetables. Moreover, there are many reported problems of excessive fertilizer application, soil erosion and water quality deterioration in this area (Rajakaruna et al., 2005). It can be observed that continuous cultivation with minimum soil conservation measures and without adopting required fallow period has contributed signiﬁcantly to land degradation in these areas (Rajakaruna et al., 2005). It is a well known fact that leaching of excess water soluble nutrients from agricultural systems adversely affects the quality of drainage water and can impact on downstream water quality (Stocking, 1992). The requirement of freshwater will continue to rise significantly over the coming decades to meet the needs of increasing populations, growing economies, changing lifestyles and evolving consumption patterns. Hence, this will greatly amplify the pressure on limited natural resources and ecosystems (Fewtrell et al., 2007). Land use activities have direct impacts on water resources, while water quality and quantity also greatly influence on land use activities (Silva et al., 2008). Hence, rivers, streams and wetlands are highly prone for deterioration and thus the reduction of amenity and aesthetic value of such water bodies would be a great threat.

Objective As Mahaweli River is a source of water for domestic, industrial and agricultural activities, quality of water in Mahaweli river partly determines how efficiently it can provide the intended services to the people. Therefore, this study was conducted to examine the water quality at several locations along Mahaweli River within the Upper Mahaweli river basin of Sri Lanka with respect to surrounding land use types at these locations.

MATERIALS AND METHODS This study was conducted by collecting water samples from 11 different locations (Figure 1) along the Mahaweli river within the Upper Mahaweli river basin and immediate downstream area (Mahiyanganaya).

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Water Quality Analysis along Mahaweli River in Upper Mahaweli Catchment Area of Sri Lanka

Figure 1: Water Sampling Locations along the Mahaweli River Water samples were collected at 4 weeks interval from April to July 2015 from the selected locations. Five hundred ml of river water was collected to plastic bottles, treated with two drops of toluene, immediately transported and stored until laboratory analysis. The water samples were tested for turbidity, electrical conductivity (EC) at 25oC and for pH at the laboratory of the Natural Resources Management Centre, Peradeniya. Turbidity was measured using 2100P turbid meter. Before turbidity determination, samples were shaken thoroughly to remove the air bubbles. EC and pH were tested using portable pH/EC meter. In addition, major land use types in the catchment areas around the sampling locations were also observed and recorded (Table1). Total monthly rainfall during the study period (Table 2) and amount of rainfall received on the sampling date and on the day before sampling (Table 3) were also obtained at the nearby gauging stations of studied sampling locations from the Meteorological Department of Sri Lanka.


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Table 1: Major land use types observed around the sampling locations Sampling Location Dikoya Hatton Watawala Ginigathhena Nawalapitiya Mawathura Gampola Peradeniya Katugastota Tennekumbura Mahaweli River at Mahiyanganaya

Observed Major Land use Type Tea Tea Tea, and Other plantations Tea and Other plantations Tea and Homestead Tea and Homestead Homestead and Other plantations Homestead Homestead Homestead Scrub and Paddy

Table 2: Total Monthly Rainfall at nearby Gauging Stations of Studied Sampling Locations Sampling Location Hatton/ Dikoya Watawala Ginigathhena Nawalapitiya Mawathura/ Gampala Peradeniya Katugasthota Thannekubura Mahiyanganaya

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Gauging Station

Total Monthly Rainfall (mm)

Kotagala

April 385.5

May 108.5

June 330.5

July 379.8

Watawala Samanala Power Station Nawalapitiya Kothmale

195.1 232.4

370 640

636 476

425 359

336.1 388

345.6 187

148

160

Peradeniya Katugasthota Kundasale Aluthnuwara

312.3 157.3 258 91.3

165.3 141.5 142.8 27

138.2 106.1 77.5 87.9

68.5 54.1 26.2 0


Table 3: Amount of Rainfall Received at nearby Gauging Stations of Studied Sampling Locations on and before Sampling Date Sampling Location

Gauging Station

Amount of Rainfall Received (mm) April

Dikoya/ Hatton Watawala Ginigathhena Nawalapitiya Mawathura/ Gampala Peradeniya Katugasthota Thannekumbura Mahiyanganaya

May

June

July

Day before sampling date

Sampling day


Sampling day


Sampling day


Sampling day

Kotagala Watawala Samanala P.S. Nawalapitiya Kothmale

0.8 11.2 2.6

14.5 33.2 23

0 0 1.7

0 0 0

0 0 0

0 8.2 3.8

10 7.5 12.2

16.7 11.7 12.8

24.4 25

4.2 0

0 0

0 0

_ 0

_ 0

_ 7

_ 7

Peradeniya Katugasthota Kundasale Aluthnuwara

16.1 1 0 0

0 1.3 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

1 5.8 0 0

6.5 3.7 0 0

RESULTS AND DISCUSSION Variation of Turbidity along Mahaweli River in Upper Mahaweli Catchment Area Turbidity of river water is an indication of sediment contribution from its different land use types prevailing in the catchment area. Turbidity and water flow are causally related. High flow rates keep particles suspended instead of letting them settle to the bottom. Thus, in rivers and other naturally-occurring high flow environments, turbidity is constantly present. Heavy rainfall affects water flow, which in turn affects turbidity. Rainfall can increase stream volume and thus stream flow, which can re-suspend settled sediments and erode river banks. Rain can also directly increase the level of total suspended solids through runoff. Runoff can also wash away topsoil and contribute to river bank erosion. Other than land use and rain fall, point and nonpoint sources of pollution can be considered as causal factors of turbidity (Kemker, 2014). According to Figure 2, mean turbidity at DikOya is 9.94 NTU and its major land use is tea. In Hatton also the major land use is tea. But, the turbidity at Hatton is slightly lower (7.57 NTU) compared to DikOya. When river flows through Watawala and Ginigathhena areas where tea and other plantations (Pinus) could be observed as the major land use types, somewhat higher turbidity values can be seen. According to the observations, there is no very good undercover in Pinus plantations and thus soil erosion can be considerably high. This can be a possible reason for relatively high turbidity values in Watawala (8.04 NTU) and Ginigathhena (10.6 NTU). From Nawalapitiya to Mawathura, the major land use is tea and there is a decrease in turbidity. It is 5.1 NTU in Nawalapitiya and 7.37 NTU in Mawathura. Mean turbidity in Gampola, Peradeniya, Katugastota and Thennekumbura are 24.6 NTU, 12 NTU, 25.4 NTU and 41.4 NTU, respectively. From Gampola to Thennekunbura, the major land use is homestead which is with relative sparse vegetation cover. There is a possibility for high loads of sediment coming from these areas to increase the turbidity levels in river water. Mahiyanganaya with scrub and paddy as the major land use types shows low turbidity (17.01NTU) comparative to urban (homestead) areas. Further, it was a dry period for the downstream area (Mahiyanganaya) during the whole study period (Table 2). Therefore, there was a less chance of receiving sediment from the surrounding areas. There is a less chance of getting sediments from the upstream also to this location since number of alarge reservoirs are located in the upstream which trap the sediments. Tennekumbura shows the highest turbidity out of all studied 11 sampling locations. However, it cannot be resulted from soil erosion associated with the rainfall received at the surrounding area as Kundasale gauging station (representing Tennekumbura) has not received any rainfall on and before the sampling date (Table 3). Therefore, high sediment concentrations observed in this location could have contributed from the upstream areas which have received high amounts of rainfall (Table 2 and 3) during the sampling period.


Permissible level for Drinking

Figure 2: Turbidity of water at studied locations along the Mahaweli River According to the SLS standards, the maximum permissible value of turbidity for drinking water is 8 NTU. In this study, the water samples taken from 6 locations out of 11 locations have mean turbidity values exceeding this maximum permissible level (Figure 2). As, the upper catchment area of Mahaweli river is heavily utilized for drinking water extraction, turbidity removal will be a prime activity in the water purification process. Figure 2 shows an increasing trend of turbidity in river water towards the downstream especially after Mawathura sampling location. It is a well known fact that when the river is flowing through forest/scrub areas, turbidity level in water is low and it is high in urban areas. When the areas get urbanized, construction sites and other development activities can accelerate soil erosion due to removal of vegetation cover disturbing the soil stability. Also, high rainfall also leads to increase the surface runoff, causing soil erosion which brings particles to the rivers to increase the water turbidity (Welagedara et al., 2014). Hatton and Nawalapitiya areas located in the upper part of the catchment are consisted mainly with tea plantations. Soil erosion is generally well controlled in tea plantations by adopting good soil conservation measures and thus the turbidity level of water in these areas has become low. Hence, the high turbidity levels in river water shows the need of strengthening soil conservation measures in the Upper Mahaweli Catchment Area.


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Variation of Electrical Conductivity along Mahaweli River in Upper Mahaweli Catchment Area Electrical conductivity is a measure of the salt content of water. It is an important measurement for irrigation water as saline irrigation water can lead to salinity development in soils (Pierzynski et al., 2000). In agricultural settings where agrochemicals are heavily used, the EC of surface waters is found to be significantly higher than that of surface waters surrounded with natural vegetation (Tong & Chen, 2002). Figure 3 also shows an increasing trend of EC levels towards the downstream. As per the Figure 3, only at Peradeniya, Tennekumbura and Mahiyanganaya mean EC levels are comparatively higher than at other 8 locations and all these values are much lower than the desirable level for both drinking (0.75 dS/m) and agriculture (2.2 dS/m) as specified by the Sri Lanka Standards Institution. According to USDA classification, irrigation water with 0-0.25 dS/m EC level is considered as class-1 or low salinity water. Accordingly, the Mahaweli river water in this upper part of the catchment is fallen under class one category and well suitable for irrigation purposes.EC towards downstream. Levels tend to increase from Mawathura sampling station. From Dikoya to Peradeniya, the EC values of Mahaweli water are ranging in between 0.073 dS/m to 0.087 dS/m may be owing to the availability of more vegetative land use types. However, at Peradeniya and Tennekumbura the EC levels are 0.15 dS/m and 0.12 dS/m, respectively may be due to the occurrence of more homesteads with in these areas. Mahiyanganaya shows the maximum EC of 0.16 dS/m and this may have been resulted from the usage of more agro chemicals in paddy lands and also washing off of ion rich water from the upstream areas which are subjected to intensive agriculture. Dry weather was experienced for this area during the sampling period hence direct contribution of pollutants from the immediate surrounding cannot be expected of there is no irrigation runoff water coming from the surrounding.

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Figure 3: Electrical Conductivity of water at studied locations along the Mahaweli River

Variation of pH along Mahaweli River in Upper Mahaweli Catchment Area As shown in Figure 4, all resulted pH levels are within 6.61 and 7.63 except at Dik Oya (6.41with acidic soils). As the permissible ranges of pH of water for drinking and agriculture are 6.5 to 9.0 and 6.5 to 8.5, respectively as per the Sri Lanka Standards Institution, the river water at these locations is suitable for both drinking and agriculture. The maximum pH value in river water is reported from Mahiyanganaya (7.63) and it may also be due to the surrounding paddy lands where more agro chemicals (probably with basic ions) are used. Tong & Chen (2002) has reported that pH was found to increase significantly in surface waters adjacent to agricultural lands as compared to urban and natural lands.


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Figure 4: pH of water at studied locations along the Mahaweli River

CONCLUSIONS The study revealed that comparatively lower turbidity, EC and pH levels in the Mahaweli river water at upper most areas of the catchment where land use types with rich vegetative cover are available. However, turbidity, EC and pH levels are gradually increasing from upstream to downstream, as land use types are changing from natural or plantations with good soil conservation practices to human influenced land uses such as paddy, homesteads and urban settings. Therefore, it can be said that, although the tested EC and pH levels are still within the safe limits as per the Sri Lanka Standards Institution, there is a threat of degrading water quality of Mahaweli river with increasing urbanization, agriculture and other alterations to the land. Though this study was limited to a short period of time and only measured the concentrations of sediment in the water, it is useful to identify the sediment load transported along the river to have a better understanding about soil erosion threat and possible problems associated with high sediment loads such as deposition of sediment in river bed, sedimentation of reservoirs and pollutant transport associated with sediments. This study ascertained the usefulness of good land use and management practices to safeguard the river water quality.

REFERENCES Fewtrell, L., Pruss-Ustun, A., Bos, R., Gore, F. and Bartram, J. (2007). Water Sanitation and Hygiene: Quantifying the Health Impact at National and Local Levels in Countries with Incomplete Water Supply and Sanitation Coverage, Environmental Burden of Disease Series, No. 15.

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Pierzynski, G., Sims, J., and Vance, G. (2000). Soils and Environmental Quality, Ed. 2, CRC Press LLC. Danvers, MA. Rajakaruna, R.M.P., Nandasena, K.A. and Jayakody, A.N. (2005). Plant nutrient contamination of shallow groundwater in intensive vegetable gardens of Nuwara Eliya, Tropical Agricultural Research. Silva, A.M., Rosa, A.H., Antunes, F.M., Nogueira, D.P. and Lessa,S.S. (2008). Relationship between water quality and land use along a Stretch of the Sorocaba River, Departamento de Engenharia Ambiental, Campus Experimental de Sorocaba, Universidade Estadual Paulista. Stocking, M.A. (1992). Soil erosion in UMC forest land use mapping project, Technical Report No.14, Environment and forest conservation division, Mahaweli Authority of Sri Lanka, Polgolla. Tong, S. and Chen, W. (2002). Modeling the relationship between land use and surface water quality. Journal of Environmental Management, Vol. 66, pp 377-393. Kemker, C. (2014). Turbidity, Total Suspended Solids and Water Clarity: Fundamentals of Environmental Measurements, Fondriest Environmental, Inc. 13 Jun. 2014. Web. < http://www.fondriest.com/environmentalmeasurements/parameters/water-quality/turbidity-total-suspended-solids-waterclarity/ >. Welagedara, S.D.L.M., De Silva, W. N. C., Ilangasinghe, U.K., Iqbal, S.M.,.Araliya, R.M.V. and Miguntanna, N.P. (2014). Comparison of water quality status of major rivers in Sri Lanka, SAITM Research Symposium on Engineering Advancements, South Asian Institute of Technology and Medicine (SAITM), Sri Lanka, pp 137- 145. Ministry of Forestry and Environment (2000). State of the Environmental Report Sri Lanka, Development, Environment and Management Associates/ NORAD UNEP, SACEP.


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Phosphorus Removal from Wastewater Using Soil as an Adsorbent H. M. C. M. Jayawardana and D. M. S. H. Dissanayaka Faculty of Agriculture, Rajarata University of Sri Lanka P. P. U. Kumarasinghe Postgraduate Institute of Agriculture, University of Peradeniya

and M.I.M. Mowjood Faculty of Agriculture, University of Peradeniya

ABSTRACT Algal blooms are observed in most of the water bodies due to nutrients loading from agricultural, urban and industrial sources. Excess nutrients, especially Phosphorus (P) and Nitrogen (N) are the major factors lead to excess algal growth. A study was conducted to identify sorbents to remove P in water. Five soils were tested based on their clay structure. Montmorillonite and Kaolinite mix soil in Murunkan, acidic clay soil in Baduluoya river basin, Low Humic Glay soil and soil from ant hole in Anuradhapura were collected, air dried and sieved (2 mm). Based on the physio-chemical characteristics, Murunkan soil was selected out of all soils for further experiment on adsorption characteristics. Phosphorous removal efficiency was measured at different pH (1-11), soil dosage (5 – 125 gl-1), initial P concentration (1 – 24 mgl-1) and contact times (1 – 5 hour). Sorption data was modeled using Langmuir and Freundlichadsorption isotherms. Results showed that the best performances of adsorption of P into Murunkan soil was obtained under pH 4 and pH 8 - 9at 50 gl-1 soil dosage with 3 hour contact time up to 5 mg l-1 of PO43-concentration. About 90% of P had removed at pH 4 and pH 8 - 9. Sorption of phosphorus in to Murunkan soil was better represented by Freundlich Isotherm model. Murunkan clay soil was the most suitable to remove P in runoff and wastewater. Further studies are needed for field implementation such as constructed wetland and permeable reactive barrier to reduce the P load in water bodies.

INTRODUCTION Rapid industrialization, urbanization, agricultural activities in many countries lead to generation of large quantities of waste materials, which may be toxic, carcinogenic or mutagenic and cause problem to the environment. Eutrophication of water bodies is one of the most serious environmental problems that occur in water bodies due to rapid increase of the population of algae. Solar radiation and nutrients are the main two factors causing algal growth. Excess nutrients, especially P and N are the main contributors to algal growth. Phosphorus acts as the limiting factors for

H. M. C. M. Jayawardana and D. M. S. H. Dissanayaka, P. P. U. Kumarasinghe and M.I.M. Mowjood

algal growth in fresh water bodies. Therefore, removal of P in the wastewater and urban runoff is one of the major remedial strategies to control eutrophication. It can be achieve through physical, chemical, and biological methods. However, physical methods are generally much more expensive. Hence, biological and chemical methods are commonly used. Biological treatments; especially constructed wetlands have the potential to remove 40 and 60% total P from wastewater (Vymazal, 2005). Natural wetland located along river bank has a high capacity for phosphorus adsorption due to clay, Aluminium and Iron (Tanaka et al., 2011). In the erosion process, P is transported to water bodies with silt and clay due to its absorption characteristics. Therefore, silt and clay can be used as sorbents to remove P in wastewater. A study was conducted to characterize the local soils for P adsorption and removal.

MATERIALS AND METHODS Location Laboratory experiments were conducted in the Soil science laboratory, Faculty of Agriculture, Rajarata University of Sri Lanka.

Collection and Preparation of Soil Samples Soil samples were collected from Murukkan (M), Badulu Oya riverbank (B), Farm land, Rajarata University Faculty of Agriculture (F and W), and Ant hole soil (H). Soils were air dried, crushed and sieved through 2 mm sieve.

Sorption Performance The sorption performance of each soil was evaluated by means of percent phosphorus removal (R %) as shown below. R %=[( C0-C/C0].100 Where: C0 and C are the initial and equilibrium phosphorus concentration, respectively. Phosphorus levels were measured using ascorbic acid method.

Identification of Suitable Sorbent Material Total P,pH, CEC and EC in the soils were measured prior to identify the suitable sorbent material. A 20g of each soil was added in to 200ml of KH2PO4 solution. It was stirred for 3hours in 375 rpm at room temperature. Four milliliters of sample was taken in every one hour for eight hour from suspension. Phosphorous levels of filtrate were measured colorimetrically (Watanabe, 1965).

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Phosphorus Removal from Wastewater Using Soil as an Adsorbent

Adsorption experiment with selected soil Adsorption experiments were carried out with selected soil, Murunken soil with different pH levels, dosage rates, initial concentration and contact times. In each test twenty (20g) of soil was added into 200ml of distilled water. Sample was stirred for 3 hours at 375 rpm at room temperature for the proper mixing of clay soil and distilled water. KH2PO4 solution (5 ppm) was added and the following tests were conducted. pH levels: The pH of stirred sample was adjusted from pH 1 to 11 using 1 M NaOH and 1M H2SO4. Dosage : Eight dosage levels, 1, 2.5, 5, 7.5, 10, 15, 20 and 25g of soil was tested Initial P concentration: Eleven levels of initial concentrations, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 22, 24 ppm were maintained by adding KH2PO4 solution. Four milliliters of samples were taken from each suspension with one hour interval. Suspension was filtered through Whatman No. 5 filter paper and measured for P (Watanabe, 1965).

Effect of Contact Time on Adsorption In the all above experiments, samples were collected at 0, 1, 2, 3, 4 and 5 contact hours and measured for P.

Isotherm Studies Murunken soil was used to develop Freundlich and Langmuir isotherms, expressed by the linearized equations (Equations 1 and 2) (Suteu et al., 2011).

Freundlich isotherm: log q = log KF+ 1/n log C

(Equation 1)

Langmuir isotherm: 1/q = 1/qo + 1 / (KL – q0).

1/C

(Equation 2)

Where: Kf is a parameter related to the adsorption capacity and n is a measure of sorption intensity; a favorable sorption corresponds to a value of 1

improvement plant nutrient management

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