Home
Search
Collections
Journals
About
Contact us
My IOPscience
Surface runoff estimation from various land use in Mapili Watershed using SCS Curve Number and Geographic Information System
This content has been downloaded from IOPscience. Please scroll down to see the full text. 2017 IOP Conf. Ser.: Earth Environ. Sci. 54 012022 (http://iopscience.iop.org/1755-1315/54/1/012022) View the table of contents for this issue, or go to the journal homepage for more Download details: IP Address: 69.147.248.113 This content was downloaded on 18/02/2017 at 11:17 Please note that terms and conditions apply.
You may also be interested in: Modelling land use/cover changes with markov-cellular automata in Komering Watershed, South Sumatera E Kusratmoko, S D Y Albertus and Supriatna Water balance of Slovenia 1971 – 2000 P Frantar, M Dolinar and B Kurnik A database paradigm for the management of DICOM-RT structure sets using a geographic information system Weber Shao, Patrick A Kupelian, Jason Wang et al. A watershed modeling approach to streamflow reconstruction from tree-ring records Laurel Saito, Franco Biondi, Jose D Salas et al. Coupled impacts of climate and land use change across a river-lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000–2040 Asim Zia, Arne Bomblies, Andrew W Schroth et al. The role of precipitation type, intensity, and spatial distribution in source water quality after wildfire Sheila F Murphy, Jeffrey H Writer, R Blaine McCleskey et al. Characteristics of Summer Runoff Variations in the Yangtze River Basin and its Connections with Asian Summer Monsoons Jian Tang, Qingyun Li and Jin Chen Analyzing temporal changes in maximum runoff volume series of the Danube River Dana Halmova, Pavla Pekarova, Jan Pekar et al.
LISAT IOP Conf. Series: Earth and Environmental Science 54 (2017) 012022
IOP Publishing doi:10.1088/1755-1315/54/1/012022
International Conference on Recent Trends in Physics 2016 (ICRTP2016) IOP Publishing Journal of Physics: Conference Series 755 (2016) 011001 doi:10.1088/1742-6596/755/1/011001
Surface runoff estimation from various land use in Mapili Watershed using SCS Curve Number and Geographic Information System Sri Malahayati Yusuf1*, David Guluda2, Trisumitra Jayanegara3 1 Center for Environmental Research, Bogor Agricultural University, Indonesia 2 Postgraduated Program, University of Tadulako, Central Sulawesi, Indonesia 3 Agency for Watershed Management and Protected Forest of Lariang Mamasa, West Sulawesi, Indonesia E-mail:
[email protected] Abstract. Mapili watershed which is located in West Sulawesi is dominated by secondary forest and agriculture land. The condition of the watershed is affected by land use and soil type. Land use is a form of interaction between man and land in order to meet their needs. Soil is function from organism, climate, topographic, material, and time. This information then will affect the hydrological condition in the watershed, especially surface runoff. The objective of study is to analyze the surface runoff in Mapili watershed. SCS curve number method that integrates with geographic information system was used in the analysis. The highest surface runoff value is about 887.6 mm and the highest of surface runoff coefficient is about 0.31.
1. Introduction Land use is characterised by arrangements, activities, and inputs people undertake in a certain land cover type to produce, change or maintain it [1, 2]. Land as a natural resource is a utilized resource by humans to meet their needs. Land use that does not comply with the carrying capacity and soil and water conservation service will trigger land degradation [3-5]. Land degradation is one of the parameters that affect the hydrological aspects of the watershed, especially runoff [6-8]. Surface runoff is a part of rainfall that flowing on gound surface after the interception, depression storage, and infiltration takes place [9, 10]. The amount of measured runoff is a function of rainfall, soil and land use type [4, 9, 10]. The high of surface runoff is one cause of problems in a watershed [11, 12]. Mapili watershed which is located in Province of West Sulawesi, Indonesia is dominated by steep and very steep slope around 64%. Dominant land uses are upland agriculture mixed with shrub land (42.28%) and secondary forest (43.57%). The combination of these circumstances will contribute to the occurrence of surface runoff [13-15]. Therefore, it is necessary to estimate the surface runoff value in Mapili watershed so that the watershed condition can be determined. Surface runoff value for Mapili watershed was estimated using SCS Curve Number method. The method is able to describe the effect of various type of land use on runoff in a watershed [16-19]. The integration between SCS Curve Number with Geographic Information System is able to provide the
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd 1
LISAT IOP Conf. Series: Earth and Environmental Science 54 (2017) 012022
IOP Publishing doi:10.1088/1755-1315/54/1/012022
information of runoff value spatially in the entire watershed, so the most problematic part of a watershed will be known [20-22]. 2. Methodology 2.1 Watershed description The research was conducted in Mapili watershed which is located in Mamuju and Polewali Mandar Region, Province of West Sulawesi (figure 1). The research area is dominated by secondary forest type (43.57%) and very steep slope (33%). 2.2 Research Procedure The research procedure is described in Figure 2. From the figure, runoff value was estimated for each sub watershed in Mapili watershed base on soil, land use, topographic, and also rainfall data. Hydrology of a watershed is affected by soil data through hydrology soil group (HSG) information. HSG is defined by soil texture and minimum infiltration rate. Effect of combination from various land use and soil type on watershed hydrology is described by curve number (CN). CN is determined based on HSG, land use type, and antecedent moisture condition (AMC).
Figure 1. Study area
2
LISAT IOP Conf. Series: Earth and Environmental Science 54 (2017) 012022
IOP Publishing doi:10.1088/1755-1315/54/1/012022
Figure 2. Procedure to estimate runoff value 3. Results and Discussion Analysis of runoff for Mapili watershed was done in detail for each sub watershed. Sub watershed was divided using hydrological model with input data digital elevation model. Base on the process, there was 25 sub watersheds in Mapili watershed (figure 3). Then, hydrology soil group (HSG) for each sub watershed was defined base on soil texture data. From the data, it is known that Mapili watershed is dominated by HSG A (figure 4), where the soil in the watershed has lowest runoff potential [10, 1618]. But, the total surface runoff also effected by slope in the watershed which is dominated by steep and very steep slope. Before water infiltrate to the soil profile, it will flowing on the ground surface as runoff.
Figure 3. Map of sub watershed in Mapili watershed
3
LISAT IOP Conf. Series: Earth and Environmental Science 54 (2017) 012022
IOP Publishing doi:10.1088/1755-1315/54/1/012022
Figure 4. Map of Hydrology Soil Group in Mapili watershed Data of HSG and land use map were used to define the curve number for each land use type in Mapili watershed. The curve numbers describes the condition of land use, soil and also the moisture condition [4, 18, 20]. The value of curve numbers in Mapili watershed are varies between 25 for forest area to 92 for water body (figure 5). It means that around 25 until 92% from rainfall will transform into surface runoff. The lowest surface runoff is 51.9 mm and the highest is 887.6 mm with the average value is around 398.90 mm (figure 6). The status for each sub watershed can be determined using parameter of surface runoff coefficient. The coefficient of surface runoff is resulted from surface runoff value and rainfall data. From the data, Mapili watershed is dominated by coefficient surface runoff under 0.2 (figure 7). The highest coefficient surface runoff was derived from sub watershed number 4 as 0.31. This sub watershed is dominated by agriculture land and steep slope. Base on the Rule of Minister of Forestry of Republic Indonesia No. P. 61/MENHUT-II/2014, the coefficient surface runoff < 0.2 is categorized as low and very low class, while the highest value in Mapili watershed is categorized into medium class. It is mean that all sub watershed is still in good condition. But, all the stakeholders in watershed should keep this condition so the sustainable watershed can be reached.
Figure 5. Map of curve number in Mapili watershed
4
LISAT IOP Conf. Series: Earth and Environmental Science 54 (2017) 012022
1000
887.6
Surface runoff (mm)
900 800 700 600 500
IOP Publishing doi:10.1088/1755-1315/54/1/012022
695.1 670.8 462.2
719.9
708.6 595.1 540.4 494.6465 411.5 393.2 427.9
642.4 491.5
486.6
400 300 200
66.8
100
51.9
176.5 150.2 113.5 99.8 102.1 61 58.2
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Number of Sub Watershed
Figure 6. Surface runoff value for sub watersheds
Figure 7. Map of surface runoff in Mapili watershed 4. Conclusion The surface runoff value in Mapili watershed is range between 51.9 - 887.6 mm. The highest surface runoff derives the highest of surface runoff coefficient around 0.31. This value is classified into medium class of surface runoff condition. 5. References [1] FAO 1999 Land Resources http:www.fao.org (accessed on July 10, 2016) [2] Vink, A P A 1975 Land Use in Advancing Agriculture (Berlin Heidelberg, New York: SpringerVerlag) [3] Agency for Watershed Management and Protected Forest of Citarum Ciliwung 2009 Management planning of Citarum Ciliwung watershed (Bogor: Agency for Watershed Management and Protected Forest of Citarum Ciliwung) (in Bahasa Indonesia) [4] Arsyad S 2006 Konservasi tanah dan air (Bogor: IPB Press) [5] Berry E and Levy J 1983 Soil degradation problems and soil conservation techniques and management: use and implementation in Africa, Resource Handbook 1 (New York: United State Agency for International Development)
5
LISAT IOP Conf. Series: Earth and Environmental Science 54 (2017) 012022
[6]
[7]
[8]
[9] [10] [11]
[12]
[13] [14]
[15]
[16] [17]
[18] [19]
[20] [21]
[22]
IOP Publishing doi:10.1088/1755-1315/54/1/012022
Ghimire C P 2014 Hydrological impacts of reforesting degraded pasture land in the middle mountain zone of Central Nepal (doctor dissertation) (Netherlands: ITC Printing Department) van Luijk G, Cowling R M, Riksen M J P M and Glenday J 2013 Hydrological implications of desertification: Degradation of South African semi-arid subtropical thicket J. Arid Environ. 91 14-21 Johansson J and Svensson J 2002 Land degradation in the semi-arid catchment of Lake Baringo, Kenya: a minor field study of physical causes with a socioeconomic aspect (Sweden: Earth Science Centre, Goteborg University) Linsley R K, Kohler M A and Paulhus J L H 1982 Hydrology for engineers 3rd Ed. (McGrawHill, Inc) Schwab G O, Frevert R K, Edminster T W and Barnes K K 1981 Soil and water conservation engineering 3rd Ed. (Canada: John Wiley & Sons, Inc) Valentin C, Agus F, Alamban F, Boosaner A, Bricquet JP, Chaplot V, de Guzman T, de Rouw A, Janeau JL, Orange D, Phachomphonh K, Phai DD, Podwojewski P, Ribolz O, Silvera N, Subagyono K, ´Baux JPT, Tran DT and Vadari T 2008 Runoff and sediment losses from 27 upland catchments in Southeast Asia: impact of rapid land use changes and conservation practices J. Agriculture, Ecosystems and Environment 128 225–238 Wang S, Kang S, Zhang L and Li F 2007 Modelling hydrological response to different land use and climate change scenarios in the Zamu River Basin of Northwest China Journal of Hydrological Process (Wiley Interscience) Pawitan H 2006 Land use change and its impact on watershed hydrology (Bogor: Hydrometeorology Laboratory, IPB) (in Bahasa Indonesia) Agency for Climate and Meteorology Research 2007 Analysis of land cover change and its effect on water balance and sedimentation in Lake Tempe http://balitklimat.litbang.deptan.go.id (accessed on 14 Mei 2012) Yusuf S M, Murtilaksono K, Harjianto M and Herlina E 2016 The utilization of satellite imagery data to predict hydrology characteristics in Dodokan Watershed Procedia Environmental Sciences 33 36-43 McCuen R H 1982 A guide to hydrologic analysis using SCS method (New Jersey: Prentice Hall, Inc) United States Department Agriculture, Natural Resources Conservation Service and Conservation Engineering Divison 1986 Urban hydrology for small watersheds TR-55 (Washington: USDA) Natural Resources Conservation Service 1997 Engineering hydrology training series: Module 205-SCS runoff equation (Washington: NRCS) Tedela N H, McCutcheon S C, Rasmussen T C, Hawkins R H, Swank W T, Campbell J L, Adams M B, Jackson C R and Tollner E W 2012 Runoff curve numbers for 10 small forested watersheds in the mountains of the Eastern United States J Hydrol. Eng. 17 11881198 Nayak T, Verma M K and Hema B S 2012 SCS curve number method in Narmada basin International Journal of Geomatics and Geosciences 3 219-228 Gajbhiye S and Mishra S K 2012 Aplication of NRCS-SCS Curve Number model in runoff estimation using RS & GIS IEEE-International Conference on Advances in Engineering, Science, and Management (ICAESM-2012) (March 30-31, 2012) Ahmad I, VermaV and Verma M K 2015 Application of curve number method for estimation of runoff potential in GIS environment 2nd International Conference on Geological and Civil Engineering IPCBEE 80 p 16-20
6
