Journal of Indian Water Resources Society, Vol 33, No.4, October, 2013
REVIEW OF COMPUTER BASED SOFTWARE TOOLS FOR SALINITY MANAGEMENT IN AGRICULTURAL LANDS Arun Goel1 and Priyanka Tiwari2 ABSTRACT Irrigation water management and subsurface drainage techniques are very old art to control of water logging and soil salinization problems in the arid and semi-arid regions. The developments in computer science and technologies have proved beneficial to the agriculture. In this research paper included all drainage simulation models/ software packages namely HYDRUS, DRAINMOD, UNSATCHEM, LEACHC, SWAP, SALTMOD and SOWACH are used as a research tool to check the performance of drainage-aquifer systems and their effects on water use, crop response, reuse of saline drain water in crop production, ground water table balance, and pollutants transport from the agricultural fields. The outcome of the review paper will be quite useful in choosing a particular simulation model on input parameters & reviewed application under given condition. Keywords: simulation models, water logging, soil salinity, irrigation and sub surface drainage.
INTRODUCTION Agricultural production is basic need for fulfillment of five basic requirements of human beings such as food, fiber, fuel, fruit and flowers. Which are increasing day by day. The adverse effect of climate change on agricultural lands is directly reflected by decrease rate of agricultural production. The twin problems of water logging and soil salinity are widespread in the irrigated lands of developing countries. Water logging is occurs due to rising water table ( due to canal seepage and over irrigation / flood) and salinization (evaporation of rising water table water by heat or increasing temperature ) also serve by rising water table. Generally the water logging and soil salinity problems occur in arid and semi arid regions because the areas are not received sufficient rainfall for leaching the salts. The millions hectare productive lands have lost every year several quintal of crops yield because of salinization and alkali soils. About 20 to 30 million ha of the world’s 260 million ha irrigated area is severely affected by water logging, soil salinity and sodicity; additional 60 to 80 million hectare are slightly to moderately affected (Umali, 1993; Ghassemi et al. 1995; FAO, 2000). Amongst the key irrigated countries, India, China, USA and Pakistan have the maximum salt affected area (ICID, 2003). The threat to global crop production due to irrigation induced salinity is serious (Postel 1999) and losses at more than US$10 billion per year are substantial. Of 6.74 million hectare salt affected lands in India, severely waterlogged saline soils occur in about 2 million hectare areas in the arid/ semi- arid parts in the north western states of Haryana, Punjab, Rajasthan and Gujarat (Kamra, 2010). Similarly more than 1 million salt affected soils each in coastal and black cotton heavy soils (vertisol) regions of India have specific moisture stress and salinity problems which need special preventive and curative interventions. It is projected that about 13 million ha area in irrigation commands of India 1
Professor, CED NIT Kurukshetra E-mail:
[email protected]; Ph.: +91 1744233349(O) Fax: +91 1744 238050
2
Research Scholar, CED NIT Kurukshetra, E-mail:
[email protected]; Manuscript No.: 1354
will be affected by waterlogging and soil salinity by 2025. Use of saline/ alkali groundwater for crop production and climate change induced warming are likely to further accentuate the soil salinity/ alkalinity problems in the country. All over the world, the only common practice of controlling the rising water-table was by a system of subsurface drainage. In modern agriculture many these systems have been or are now being replaced by pipe drains for solving the waterlogged saline soil problem in the areas of arid and semi-arid region. Unlike many other fields of scientific endeavor, modern irrigation and drainage engineering has been and remains to a large extent based on experiment. A study of history of soil and water (see, karma et al 1991) indicates that periods of experimental investigation with simulation modeling have alternated with periods of analysis. It was not until the eighteenth century that sufficient experimental data had been accumulated to permit the foretelling of future progress, and another 100 years passed before the results marking the achievement of this progress were available. To overcome two most environmental hazard causes likewise saline soil and water problems, various methods have been categories, such as physical management, chemical practices, biological practices, and human efforts in terms of modeling. The continuous advancement in computer technology there are so many numerous simulation models have been developed for the making decision support as tools for desire level of salinity management. The use of simulation model is that it can be used to fill data gaps in measurements in terms of spatial and temporal resolution and to analyze different leaching and management scenarios (Droogers, P. et al., 2001a). The different simulation computer models used for salinity management like are another classified in terms of basin scale model (Walker, 1970; Tanji, 1977; Tedeschi et al., 2001) and WSBM model (Droogers, P. et al., 2001a). The water flow and solute transport equation or mass balance equation, are based on field-scale models such as LEACHC model (Wagenet and Hutson, 1987), SWAP model (Feddes et al., 1978; van Dam et al., 1997), SOWACH model (Dudley and Hanks, 1991), HYDRUS model (Šimunek et al., 1998), UNSATCHEM model (Šimunek et al., 1996) DRAINSAL( Kamra et al 1991), DRAINMOD , SALTMOD (Pakorn Ditthakai 2011). The
24
J. Indian Water Resour. Soc., Vol. 33, No 4, October, 2013
Table 1: Simulation models Capabilities and their limitation Software Name SOWACH (Soil-Plant-AtmosphereSalinity Management Model)A third generation salinity management model developed by Nimah &Hanks (1973a,b) and futher modified by Childs &Hanks (1975) and Robbins et al. (1980a,b) DRAINMOD (DRAINMOD Software is a computer simulation model developed by Dr. Wayne Skagge at the Department of Biological & Agricultural Engineering, North Carolina State University Raleigh, NC in 1980.)
Capabilities The model applicable to simulate water flow process (Infiltration, redistribution, root uptake of water, soil evaporation or plant transpiration, percolation, monitoring ground water table fluctuation).
Limitations SOWACH model cannot simulate crop growth or crop yields, describe surface runoff and erosion, and account for the effects of regional, surface and groundwater flows and its DOS based version is currently totally useless.
The model conducts a water balance on a day- to- day, hour- to- hour basis and calculates infiltration, ET, drainage, surface runoff, sub-irrigation, deep seepage, water table depth, and soil water status at each time step.
LEACHC (Leaching Estimation And solute transport Chemistry Model) is the salinity version in LEACHM developed by Wagenet and Hutson in the year 1987. DRAINSAL (A 2- dimensional finite element model (DRAINSAL) of solute transport in tile drained soil-aquifer system has been developed at CSSRI (Kamra et al., 1991a&b) and tested in the field Sampla (Distt. Rohtak).
The agricultural applicable modules of LEACHC having water flow module, solute transport module, and soil chemistry module.
The software has limited capability to simulate salt distribution in irrigated soils with or without drainage systems in arid or semi-arid soils. It is prone to errors in deep groundwater regions, in heavy textured soils and periods of long dry spells.The DRAINMOD model simulates neither surface nor subsurface flows. The major outputs of DRAINMOD are watertable depth and drainage rate (Madramootool, and Broughtonl 1987). LEACHC model cannot simulate crop growth or crop yields, describe surface runoff and erosion, and account for the effects of regional, surface and groundwater flows (Hutson, 2003).
UNSATCHEM Simunek et al.,(1996)
It uses for simulating water, heat, carbon dioxide, and solute transport movement in one-dimensional variably saturated media, including horizontal, vertical and inclined flow Interaction between water flow, solute transport, heat flow and plant growth Long term simulations (70 years), with multiple crops in a year
SWAP Kroes and Van Dam(2003).The program has developed by Alterra and Wageningen University SALTMOD
The model considers steady state water movement in the unsaturated and saturated zones, and includes the effect of convective transport, dispersion and linear adsorption. It is a field scale model that provides long-term predictions of desalinization of a tile- drained soil and of the associated changes in the quality of groundwater and the drain effluent.
The model developed and updated by from the year 2000 to 2012 by M. Jurriens, D. Zerihun, J. Boonstra and R. A. L. Kselik. The model aims at sustainable land use and environmentally sound optimal water management for sustainability and can be use for the modeling of reclamation, (remediation, rehabilitation, restoration) of saline soil.
DRAINSAL Software is a DOS based model so cannot be used in latest window based software. It has preliminary menu driven interfaces which management of input data files using NORTON EDITOR. The code is not user friendly and graphical outputs are not comparable to the recent window based codes but there are a few flags which convey the progress of computations. It is not used to use root water uptake problems
(1)A continuous supply of water. (2)Energy available to change liquid water into vapour;(3) A vapour gradient to maintain a flux from the evaporating surface to the atmosphere. In October 2012, a simple version was made by the name SaltCalc which lacks the crop rotation and farmers response option but permit monthly instead of seasonal calcutation.
25
J. Indian Water Resour. Soc., Vol. 33, No 4, October, 2013
HYDRUS
The program uses linear finite elements to numerically solve the Richard’s equation for saturated–unsaturated water flow and advection–dispersion equations for both heat and solute transport. The flow equation also includes a sink term to account for water uptake by plant roots as a function of both water and salinity stress.
The modeling from HYDRUS model only by skilled operator or expert, and that person can used this model who can understand finite element mathematics.
Table2: The detail descriptions about models Sr. No. 1
Name Simulation Model SOWACH
of
2
DRAINMOD
3
LEACHC (Leaching Estimation And solute transport Chemistry Model)
4
UNSATCHEA M
5
HYDRUS
6
SWAP (Soil-PlantAtmosphereSalinity Management Model)
Descriptions of Model Features Developer - Nimash and Hanks (1973a,b), Childs and Hanks (1975) and Robbins et al. (1980a, b) Dimension - 1D Operating System - QuickBASIC DOS and WINDOW Operating Language- C++ and Fortran Numerical Solution – Finite Difference Modules -water flow, solute transport, soil Chemistry, Drainage, ion exchange Water table monitoring, Subsurface drainage, irrigation etc. Cost - 1D and 2D = Freeware Developer - Dr. Wayne Skagge (1980) Dimensions - 1D Operating System - DOS and WINDOW Operating Language- C++ and Fortran Numerical Solution – Finite Difference Modules -infiltration,ET,Soil water status, solute transport, Deep seepage, Water Table Depth, Drainage, Water table monitoring, Sub-irrigation , surface-runoff etc. Cost - 1D = Freeware Developer - Wagenet& Hustson (1985) Dimension - 1 D , Operating System - Version 3.03 DOS based and Version 2007 WINDOW based. Operating Language- C++ and Fortran Numerical Solution – Finite Difference Modules -water flow, solute transport, soil Chemistry (CHEM), Drainage, cat ion exchange model(XCHANG), Subsurface drainage, irrigation, lime and Gypsum etc. Cost - 1D = Freeware Developer - J. Simunic (1996) Dimension - 1D , 2D Operating System - DOS and WINDOW95, NT Operating Language- C++ and Fortran Numerical Solution – Finite Difference Modules -water flow, solute transport, soil Chemistry, Drainage, Water table monitoring, Subsurface drainage, irrigation etc. Cost - 1D and 2D = Freeware Developer - J. Simunic (1998-2008) Dimension - 1D , 2D and 3D Operating System - DOS and WINDOW Operating Language- C++ and Fortran Numerical Solution – Finite Difference Modules -water flow, solute transport, soil Chemistry,Co2, Heat, Crop Yield Atmosphere plant and soil Interaction, Vertical Drainage, Water table monitoring, Subsurface drainage, irrigation etc. Cost - 1D = Freeware and 2D/3D= $1200 only Developer - Kroes Dam(2003) Dimension - 1D Operating System - DOS and WINDOW95, NT Operating Language- C++ and Fortran Numerical Solution – Finite
26
J. Indian Water Resour. Soc., Vol. 33, No 4, October, 2013
Modules -water flow, solute transport, soil heterogeneity, soil surface- water interaction, Drainage, Water table monitoring, , crop growth, atmosphere-plant and soil Interaction etc. Cost - 1D = Freeware 7
SALTMOD
Developer - Updated year 2000 to 2012 by M. Jurriens, D. Zerihun, J. Boonstra and R. A. L. Kselik. Dimension - 1D , 2D Operating System - DOS and WINDOW95, NT Operating Language- C++ and Fortran Numerical Solution – Finite Difference Modules -water flow, solute transport; soil Chemistry, Drainage, Water table monitoring, Subsurface drainage, irrigation etc. Cost - 1D = Freeware Table 3:Application of Simulation models
Sr. No. 1.
Resource
Major Conclusion
Simulation Model
Yao et al., (2007)
The results show that the RMAE values for the 90 day’s soil water dynamics at soil layers of 20cm, 60cm, 80cm, 100cm below drip tube are 14.2%, 13.0%, 1.1%, 1.0% respectively; the RMAE values for simulation section of before , after irrigation are 5.1%, 4.3% respectively. Indicating the model perform well in simulating soil water dynamic during the growing reason. HYDRUS-2D under predicted drain discharge compared to the empirical and Kirkham-Hooghoudt equations for water table elevations above 70 cm. However, HYDRUS-2D predictions were very close to those using empirical and Kirkham-Hooghoudt equations for water table elevations below 70 cm. The study results indicated LEACHC model could simulate soil moisture movement and solute transport above shallow water tables satisfyingly and be used as a decision making tool for evaluating scenario to manage soil salinity problems due to saline in shallow water tables. On the basis of this study, it is thought that the LEACHM-C model would be a useful tool to predict crop root zone salinity on land irrigated with saline water as well as for planning reclamation activities. To compute the effect of land drainage (12 combination of drain depth (ranging from 1.0 to 2.5 m) and drain spacing (ranging from 125 m to 500m) on soil moisture conditions in the root zone, soil salinization and their effect on crop yield of wheat A water management strategy for sustainable crop production was suggested in which controlling the irrigation supply resulted in a sustainable good crop yield in critical water table areas having up 3 dS/m ground water quality. The average soil salinity of the effective flow region reduced from 20dS/m to 15, 18 and 19 dS/ m for 25, 50 and 75 m drain spacing respectively under steady state groundwater conditions. The study results show that the current practice yields cotton satisfyingly. Changes in the amount of irrigation application with the current water quality level do not significantly affect crop yields for cotton. With the same annual irrigation application, however, improvement in the water quality levels can increase crop yields for cotton. A water management strategy for sustainable crop production was suggested in which controlling the irrigation supply resulted in a sustainable good crop yield in critical water table areas having up 3 dS/m ground water quality.
HYDRUS-2D
2.
Ztekun T.(2001)
3.
Ali et al. (2000a, 2000b)
4.
Bishow (2000)
5.
Asad Sarwar et al., (2000)
6.
Singh al.,(2000)
7.
Lal et al., (2000)
8.
Droogers et al., (2001b)
9.
Minhas (2003)
et
al.
et
et
al.
HYDRUS-2D
LEACHC
LEACHC
SWAP
SWAP
SWAP UNSATCHEM
SWAP
27
J. Indian Water Resour. Soc., Vol. 33, No 4, October, 2013 10.
Kenellers et al., (2000)
11.
Verma (2010)
12.
Samipour et al (2010)
13.
LV et al. (2002)
14.
Gupta (1993)
et
al.
15.
Breve (1998)
et
al.
16
Hamdy et al., (2005)
17.
Kale (2011)
18.
Jin and Sands (2011)
19
Kale S. (2012)
20
Hay et al.,(2013) Rudra al.(2004)
et
al.,
Sema
et
The study results an increase in the leaching fraction from 0.2-0.4 will reduce the time to reach equilibrium drainage water salinity levels by about 50%. The model results established that notwithstanding the seasonal buildup of salt due to saline water use, there would be no long term build up of salts as leaching during the monsoon season would render the root zone soil profile free of salts at the time of sowing of Rabi crops. DRAINMOD under-estimated the drainage water but SWAP overestimated it. A relative yield of 80 % was achieved when drain spacing and depth were set to 25 m and 1.60 m, respectively using SWAP. For DRAINMOD, these values were 15 m and 1.15 m, respectively. The results point out that root production of the high fibrous root type was stimulated more at low and medium salinity than that of the low-fibrous root type. Based on our investigations, it appears that DRAINMOD can be used to design or evaluate subsurface drainage systems under the semi-arid climatic conditions. However, further evaluations are warranted before any concrete conclusions could be drawn. Maximum profits for both soils were predicted for a 1.25 m drain depth and unimproved surface drainage_2.5 cm depressional storage.. The optimum spacings were 40 and 20 m for the Portsmouth and Tomotley soils, respectively. These systems however would not be optimum from the water quality perspective. If the water quality objective is of equal importance to the productivity objective, the drainage systems need to be designed and managed to reduce NO –N losses while still providing an acceptable profit from the crop. The results obtained from DRAINMOD for optimal drainage design show good agreement with those exist in the Dujailah project. This emphasis the capability of DRAINMOD to obtain the best drainage design under Iraqi conditions. The results of the model simulations were analyzed to identify optimum subsurface drainage designs for maximum crop production. He concluded that 1.2 m deep drains at 160 m drain spacing is optimum for the multiple cropping –system. It was reported that 74% of infiltrated water was removed by subsurface drainage during the drainage (March to June) season, while the annual drainage was approximately 40% of annual precipitation on a 2 year return period basis. Decreased drain spacing was found to significantly affect infiltration and drainage over the 85–year simulation period. On the drained soils, the relative yield of the winter wheat was higher by 11.4%, on the average, whereas that of bean was higher by 24.7%. Overall, the net impact of yield enhancement due to drainage was about 36%. This shows the positive impact of drainage system on crop yields in this area. They have been investigated the impact of subsurface drainage on evapotranspiration and water. They have found not much effect on evapotarnspiration of the that particular place. Two different models (ANN and DRAINMOD) were applied for subsurface water quality management at the Greenbelt research farm of Agricultural Canada. The two ANN approaches evaluated in this study shows that the RBF artificial neural networks are better in predicting daily tile drainage water quality as compare to the FBP artificial neural networks, however, FBP artificial neural networks can be used for prediction of monthly tile drainage water quality and No3- concentration .
SWAP SWAP
SWAP, DRAINMOD
SOWACH DRAINMOD
DRAINMOD
DRAINMOD
DRAINMOD
DRAINMOD
DRAINMOD
DRAINMOD ANN DRAINMOD
and
28
J. Indian Water Resour. Soc., Vol. 33, No 4, October, 2013 21.
Shrivastava al. (2002)
22.
Srinivasulu et al. (2004)
23.
Bahçeci (2006)
24
25
It predicted that at 45 m drain spacing, the depth of drains should be at least 1.2 m below ground level, for maintaining the salinity level at around 2.5 dS/m using an irrigation water 9 dS/m. the model also showed that salinity level of 2.5 dS/m could be maintained if irrigation water supplies, remain at least 20 % lower than the present supply level. In this study soil salinity reduced up to desire level for irrigation application
SALTMOD
The soil salinity was not high in the test area, but there were commonly high water table and high salinity in the plain. The average soil salinity in the root zone decreased from 2.90 to 2.3 dS m−1 at the end of 4 year period. Bahçeci et al the results of the simulation indicate: (i) no significant changes in (2008) the root zone salinity should be expected if the drainage control factor applied is lower than 0.75; (ii) a significant increase in root zone soil salinity will occur if the drainage control factor increases above 0.75; (iii) high salinity due to an increased drainage control factor will damage most crops grown in the study area, except for crops with high salt tolerance, such as cotton and barley; (iv) a more significant increase in root zone salinity should be expected if both the drainage control factor and water salinity are increased. Moroizumi and The tillage effect on subsurface drainage land and its changes soil properties because it performs after first irrigation or first rainfall. Horino (2004) Generally its changes occurs in the form of subsurface drainage discharge and pressure head values. In this study HYDRUS version 6.0 use for produce predicting values of subsurface discharge and pressure head and after that it has been checked by three different statistical approaches namely as Root Mean Square Error, Correlation coefficient and Mean Bias Error
SALTMOD
et
et
al
main motive of this review paper is to conclude water and salt transport models in soils and also focused on software package updated features of salinity management, its mainly concern for field-scale models. In the following paragraph software capabilities and their limitation for different application as per the development.
Computer Software Packages for Salinity Management and its Applications: There are seven computer software model /tool discussed in detail in following table and those names as follow are HYDRUS model, DRAINMOD model UNSATCHEM model, LEACHC model, SWAP model, SALTMOD model, and SOWACH model. Their Comparison of different softare package latest updated features is discussed in Table 2.
A comparative study on some of the simulation models for water and soil salinity management has been reviewed in this paper. The simulation capability, limitations and all specific features of these models are presented in a tabular form. These models are generally based on Richards’ equation and convection-dispersion equation for describing the numerical concepts of water flow and solute transport processes. However, these software packages were continuously improved and most of software have user-friendly interface
SALTMOD
HYDRUS
and can be operated on window operating system. This paper can be helped in selecting a particular simulation model under drained condition & results for disposal of drainage effluent and it can give idea about expected quantity of drainage effluent and quality of effluent.
REFERENCE 1.
Abrol, I.P., J.S.P. Yadav and F.I. Massoud, 1998. “Salt-Affected Soils and their Management”. FAO soilsbulletin., pp: 39.
2.
Addiscott, T.M. and R.J. Wagenet, 1985. “Concept of solute leaching in soil: A review of modelingapproaches”. J. Soil Sci., 36(3) :411-424
3.
Ali, R., R.L. Elliott, J.E. Ayars, and E.W. Stevens, 2000a. “Soil salinity modeling over shallow water tables I: Validation of LEACHC”. Journal of Irrigation and Drainage Engineering, 126(4): 223233.
4.
Ali, R., R.L. Elliott, J.E. Ayars and E.W. Stevens, 2000b. “Soil salinity modeling over shallow water tables. II: Application of LEACHC”. Journal of Irrigation and Drainage Engineering, 126(4): 234242.
5.
Aslam, M., 1993. “Large area salinity management modeling,” dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Agricultural and Irrigation Engineering, Utah State University, Logan, Utah.
So many simulation models has been developed and discussed their application in Table 3 for solve soil salinity and water logging problems.
CONCLUSION
SALTMOD
29
J. Indian Water Resour. Soc., Vol. 33, No 4, October, 2013 6.
Bastiaanssen W. G. M., Allen R. G., Droogers P.Urso G.D., and Steduto P., 2007. Twanty – five years modeling and drained soils: State of the art. “J. Agricultural water Management”, 92(3):111-125.
7.
Breve, M.A., R.W.Skaggs., J.E. Passons and J. W.Gulliam, 1998. Using the DRAINMOD-N model to study effects of drainage system design and management on crop productivity, profitability and NO3-N losses in drainage water. “Journal of Agricultural Water Management”. 35:227-243.
8.
Bahcec; I., Cakir; A, Nacar, P and Bahcec; P., 2008. Estimating the Effect of Controlled Drainage on Soil Salinity and Irrigation Efficiency in the Harran Plain using SaltMod. Turk J Agric For 32 ,pp 101-109
9.
Campbell, G.S., 1991. Simulation of water uptake by plant roots. Modeling plant and soil systems. Amer. Soc. Agron Monograph., 31: 273-285.
10.
Droogers, P., H.R. Salemi and A.R. Mamanpoush, 2001a. Exploring Basin-Scale Salinity Problems Using a Simplified Water Accounting Model: The Example of Zayandeh Rud Basin, Iran. Irrig and Drain., 50: 335348.
11.
Droogers, P., M. Torabi, M. Akbari and E. Pazira, 2001b. Field-Scale Modeling to Explore Salinity Problems in Irrigated Agriculture. “Irrigation and Drainage Engg.”, 50: 77-90.
12.
Dudley, L.M. and R.J. Hanks, 1991. Manual for the SOWACH model. Dept. of Plant, Soil and Biometeorology., Utah State University, Logan, Utah.
13.
FAO/AGL, 2000. Extent and Causes of Salt-affected Soils in Participating Countries.
14.
Ghassemi, F., A.J. Jakeman and H.A. Nix, 1995. Salinisation of land and Water Resources: Human causes, extent management and case studies. 1st ed. Centre for Resource and Environmental Studies, The Australian Nation University, Canberra, Australia.
15.
16.
17.
Gupta, G. P., S. O. Prasher, S. T. Chieng and I.N. Mathur, 1993. Application of DRAINMOD under semi-arid conditions. “Agriculture Water Management”, 24: 63-80. Hamdi M.R. , Aldabagh A.S. and E.M.Ghazal (2006) Optimal Drainage Design Under Iraqi Conditions Using DRAINMOD. “Al-Rafidain Engineering”. Vol.14(2) pp88-99. Hank, R.J. and J.K. Cui, 1991. SOWATSAL: Soilwater-plant-atmosphere-irrigation-salinity model. Plant, Soils, and Biometeorology Dept., Utah State University, Logan, Utah.
18.
Hay, Christopher; Kjaersgaard, Jeppe H; Trooien, Todd P., 2013. Subsurface Drainage Impacts on Evapotranspiration and Water. Project ID: 2012SD212B
19.
Hutson, J.L., 2003. LEACHM: Leaching estimation and chemistry model (moel description and user’s
guide). School of Chemistry, Physics and Earth Sciences, the Flinders University of South Australia, Adelaide, Australia. 20.
Jin; X. and Sands; G. R., 2011. The long-term fieldscale hydrology of subsurface drainage systems in a cold climate. Transactions of the ASABE. Vol.46(4): 1011–1021.
21.
Kamra, S.K., Singh, S.R., Rao, K.V.G.K., and van Genuchten, M. Th., 1991. A semi- discrete model for water and solute movement in tile- drained soils: a. Governing equations and solution, “Water Resources Research”, 27(9): 2439-2447.
22.
Kale; S., 2011. Estimating effects of drainage design parameters on crop yields under irrigated lands using Scientific Research and Essays. “Academic Journals” Vol. 6(14), pp. 2955-2963.
23.
Kelleners, T.J., Kamra, S.K., Jhorar, R.K., 2000. Modeling of drainage water salinity of pipe drains “J.Hydrology”, 234: 249- 263.
24.
Kroes, J.G. and J.C. van Dam, 2003. Reference Manual SWAP version 3.0.3. Alterra-report 773, Wageningen, Alterra, Green World Research.
25.
Kuper, M., 1997. Irrigation management strategies for improved salinity and sodicity control. Ph.D. thesis, Wageningen Agricultiural University, The Netherlands.
26.
Kohler; A., Abbaspour, C. Karim, Martin Fritsch and Schulin Rainer, 2001. Functional relationship to describe drain with entrance resistance. “J. Irrigation and Drainage Engg”.127 (6): 355-362.
27.
LV, V., M. JW, S. SE and D. LM, 2002. Root growth and yield of differing alfalfa rooting populations under increasing salinity and zero leaching. “J.Crop Science”. 42(6): 2064-2071.
28.
Madramootool, G.A. and R.S. Broughtonl, 1987. Computer Simulation Model of Surface and Subsurface Flows From Agricultural Areas. “Canadian Water Resources Journal” .12(1):30-43.
29.
Nimah, M.N. and R.J. Hanks, 1973a. Model for estimating soil water, plant, and atmospheric interlations: I. Description and sensitivity. “Sol Sci. Soc. Amer. Proc”., 37(4): 522-527.
30.
Nimah, M.N. and R.J. Hanks, 1973b. Model for estimating soil water, plant, and atmospheric interlations: II. Filed Test of Model. “Sol Sci. Soc. Amer. Proc”., 37(4): 528-532.
31.
Or, D., J.M. Wraith and M. Tuller, 2004. Agricultural and Environmental Soil Physics.
32.
Parlange, J.Y., 1971a. Theory of water movement in soils: 1. One-dimensional absorption. “J.Soil Sci.”, 111(2): 134-137.
33.
Parlange, J.Y., 1971b. Theory of water movement in soils: 2. One-dimensional infiltration. “J.Soil Sci.”, 111(3): 170-174.
30
J. Indian Water Resour. Soc., Vol. 33, No 4, October, 2013 34.
Passioura J. B., 1996. Simulation models, science, snake oil, education or engineering. “Agronomy Journa”l, 88: 690-694.
35.
Philip J.R., 1957. Theory of infiltration: The infiltration equation and its solution. “J.Soil Sci.”, 83(1): 345- 357.
36.
Rhoades J.D., Kandiah A. and A.M. Mashali, 1992. The Use of Saline Waters for Crop Production. FAO Irrigation and Drainage. pp: 48.
37.
Robbins, C.W., J.J. Jurinak and R J. Wagenet, 1980a.Calculating cation exchange in a salt transport model. “Soil Sci. Soc. Am. J.” 44: 1195-1198.
38.
Robbins, C.W., R.J. Wagenet and J.J. Jurinak, 1980b. A combined salt transport-chemical equilibrium model for calcareous and gypsiferous soils. “Soil Sci. Soc. Am. J.” 44: 1191-1194.
39.
Ramesh P.R., S.C. Negi and N. Gupta, 2005. Modelling Approaches for Subsurface Drainage Water Quality Management. “Water Qual. Res. J. Canada.” 40(1): 71–81
40.
41.
42.
43.
44.
45.
Samipour F., M. R., Kourosh Mohammadi, M. H. Mahdian, A. Ali Naseri, 2010. Evaluation of Two Drainage Models in South-West Iran 9th International Drainage Symposium held jointly with CIGR and CSBE/SCGAB Proceedings, 13-16. Simůnek, J., K Huang, and M. Th. van Genuchten, 1998. HYDRUS code for simulating the onedimensional movement of water, heat, and multiple solutes in variably-saturated media. Version 6.0, Research Report No.144, U.S. Salinity Laboratory, USDA, ARS, Riverside, California, pp.-164-175. Sarwar, A. and R.A. Feddes, 2000. Evaluation drainage design parameters for the fourth drainage project ,Pakistan by using SWAP model : Part iimodeling result “Irrigation and Drainage System”.14:281-299. Simunek, J. and D.L. Suarez, 1993. UNSATCHEM-2D Code for Simulating Two-Dimensional Variably Saturated Water Flow, Heat Transport, Carbon Dioxide Production and Transport, and Multicomponent Solute Transport with Major Ion Equilibrium and Kinetic Chemistry, Version 1.1 Research Report No.128, USDAARS U.S. Salinity Laboratory, Riverside, California. Simunek, J., D.L. Suarez and M. Sejna, 1996. The UNSATCHEM Software Package for Simulating OneDimensional Variably Saturated Water Flow, Heat Transport, Carbon Dioxide Production and Transport, and Solute Transport with Major Ion Equilibrium and Kinetic Chemistry, Version 2.0. Research Report No. 141, USDA-ARS U. S. Salinity Laboratory, Riverside, California. Simunek, J., M. Sejna and M. Th. Van Genuchten, 1998. The HYDRUS-1D Software Package for Simulating One-Dimensional Movement of Water,
Heat, and Multiple Solute in Variably-Saturated Media. 46.
Šimůnek, J., M. Th. van Genuchten, and M. Šejna, 2006. The HYDRUS Software Package for Simulating Two- and Three-Dimensional Movement of Water, Heat, and Multiple Solutes in Variably-Saturated Media, Technical Manual, Version 1.0, PC Progress, Prague, Czech Republic, pp. 241.
47.
Shrinivasulu; A., Ch. Sujani Rao, G.V. Lakshami. T.V. Satayanrayan and J. Boonstria, 2004. Model studies on salt and water balance at Konanki pilot area, Andhra Pradesh. “ Irrigation and drainage System”. Vol. 18 No.-1 , pp 1-17.
48.
Simunek, J., M. Sejna and M. Th. Van Genuchten, 2008. The HYDRUS-2D Software Package for Simulating Two-Dimensional Movement of Water, Heat, and Multiple Solute in Variably-Saturated Media, Version 4.0. USDA-ARS U. S. Salinity Laboratory, Riverside, California.
49.
Singh G., Bundela D.S., Sethi, M., Lal, K. and Kamra S.K.,2010. Remote sensing and Geographical Information System for Appraisal of Salt Affected Soils in India. J. Environmental Quality, 39 (1): 5- 15
50.
Toksoz ; S., and D. Krikham ,1971. Steady drainage of layered soils, I, Theory, “J. Irrigation & Drainage (ASCE)”, 97 (IRI), 1-18.
51.
Umali; K.P., 1993. Application of subsurface drainage in semi-arid region using DRAINMOD. “J. of Irrigation and Drainage” Vol.-66, pp124-144.
52.
Verma; A.K., Gupta; S.K. and Isaac; R.K., 2010. Long –term use of Saline Drainge Water for Irrigation Subsurface Drained Lands: Simulation Modeling with SWAP. “Journal of Agricultural Engineering”. Vol.47, No.3
53.
Tanji, K.K., 1977. A conceptual hydrosalinity model for predicting salt load in irrigation return flow, Managing saline water for irrigation. Texus Tech University, Lubbock, Texas.
54.
Tedeschi, A., A. Beltran and R. Aragues, 2001. Irrigation management and hydrosalinity balance in a semiarid area of the middle Ebro river basin (Spain). “Agricultural Water Management”,49(1): 31-50.
55.
Tedeschi, A. and M. Menenti, 2002.Simulation studies of long-term saline water use: model validation and evaluation of schedules. “Agricultural Water Management”, 54: 123-157.
56.
Torabi, M., H.R. Salemi, P. Droogers M. Noshadi, 2004. Integrated basin-scale and field-scale modeling as a tool to assess improved water and salinity management. “Australian Journal of Soil Research,” 42(4): 355- 368.
57.
Van Dam, J.C., J. Huygen, J.G. Wesseling, R.A. Feddes, P. Kabat, P.E.V. van Walsum, P. Groenendijk and C.A. van Diepen, 1997. SWAP version 2.0, Theory. Simulation of water flow, solute transport and plant
31
J. Indian Water Resour. Soc., Vol. 33, No 4, October, 2013 growth in the Soil-Water-Air-Plant environment. Technical Document 45, DLO Winand Staring Centre. 58.
Wageningen. Report 71, Department Water Resources, Wageningen Agricultural University.
59.
Wagenet, R.J. and J.L. Hutson, 1987. LEACHM: Leaching estimation and chemistry model (user’s manual). Center for Environment Research, Cornell University, Ithaca, New York.
60.
Walker, W.R., (1970) “Hydro-salinity model of the Grand Valley,” thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Agricultural and Irrigation Engineering, Colorado State University, Fort Collins, Colorado.
61.
Whisler, F.D. and A. Klute, 1965. The numerical analysis of infiltration, considering hysteresis, into a vertical soil column at equilibrium under gravity. “Soil Sci. Soc. Amer. Proc.”, 29(5): 489-494
62.
Yao; p. , Xinguang; D., and A. Hu, 2007. Using HYDRUS-2D Simulate Soil Water Dynamic in Jujube Root Zone Under Drip Irrigation. This study is sponsored by Chinese Project Supported by National Technology.
32
