DESCRIPTION OF PRINCIPLES, USER MANUAL, AND CASE
STUDIES INTRODUCTION Sahysmod is a computer program for the prediction of the salinity of soil moisture, ground and drainage water (groundwater), the depth of the water table, and the drain discharge in irrigated agricultural lands, using different (geo)hydrologic conditions, varying water management options, including the use of ground water for irrigation, and several cropping rotation schedules, whereby the spatial variations are accounted for through a network of polygons. The mathematical simulation model Sahysmod combines the agro-hydro-salinity model Saltmod (Oosterbaan 1998) snd the nodal (polygonal) ground water (groundwater) model SGMP (Boonstra and de Ridder 1981). The combination was made by K.V.G.K.Rao with guidance from J.Boonstra and R.J.Oosterbaan, the user menu by H.Ramnandanlal, R.A.L.Kselik and R.J.Oosterbaan to facilitate the management of input and output data. These five persons formed the Sahysmod working group of ILRI with Oosterbaan as co-ordinator and editor. He also rebuilt the program to reduce the computer memory requirements and to increase the maximum number of polygons. The program was designed keeping in mind a relative simplicity of operation to promote its use by field technicians and project planners. It aims at using input data thatare generally available, or that can be estimated with reasonable accuracy, or that can be measured with relative ease. |
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2. PRINCIPLES 2.1. Model components
2.3. Seasonal approach The model is based on seasonal input data and returns seasonal outputs. The number of seasons per year can be chosen between a minimum of one and a maximum of four. One can distinguish for example dry, wet, cold, hot, irrigation or fallow seasons. Reasons of not using smaller input/output periods are: -a. short-term (e.g. daily) inputs would require much information, which, in large areas may not be readily available; -b. short-term outputs would lead to immense output files, which would be difficult to manage and interpret; -c. this model is especially developed to predict long term trends, and predictions for the future are more reliably made on a seasonal (long term) than on a daily (short term) basis, due to the high variability of short term data; -d. though the precision of the predictions for the future may be limited, a lot is gained when the trend is sufficiently clear. For example, it need not be a major constraint to the design of appropriate salinity control measures when a certain salinity level, predicted by Sahysmod to occur after 20 years, will in reality occur after 15 or 25 years. 2.4. Computational time steps Many water balance factors depend on the level of the water table, which again depends onsome of the water balance factors. Due to these mutual influences there can be non-linearchanges throughout the season. Therefore, the computer program performs daily calculations.For this purpose, the seasonal water-balance factors given with the input are reducedautomatically to daily values. The calculated seasonal water-balance factors, as given inthe output, are obtained by summations of the daily calculated values. Ground-water levelsand soil salinity (the state variables) at the end of the season are found by accumulatingthe daily changes of water and salt storage. In some cases the program may detect that the time step must be taken less than 1 day forbetter accuracy. The necessary adjustments are made automatically. 2.5. Hydrological data
When a fraction A1, B1 and/or U1 differs from the fraction A2, B2 and/or U2 in another season, because the irrigation regime changes in the different seasons, the program will detect that a certain rotation occurs. If one wishes to avoid this, one may specify the same fractions in all seasons (A2=A1, B2=B1, U2=U1) but the crops and irrigation quantities may be different and may need to be proportionally adjusted. One may even specify irrigated land (A or B) with zero irrigation, which is the same as un-irrigated land (U). Cropping rotation schedules vary widely in different parts of the world. Creative combinations of area fractions, rotation indices, irrigation quantities and annual input changes can accommodate many types of agricultural practices. Variation of the area fractions and/or the rotational schedule gives the opportunity to simulate the impact of different agricultural practices on the water and salt balance. 2.7. Soil strata
Under certain conditions, the height of the water table influences the water-balance components. For example a rise of the water table towards the soil surface may lead to an increase of capillary rise, actual evaporation, and subsurface drainage, or a decrease of percolation losses. This, in turn, leads to a change of the water-balance, which again influences the height of the water table, etc. This chain of reactions is one of the reasons why Sahysmod has been developed into a computer program, in which the computations are made day by day to account for the chain of reactions with a sufficient degree of accuracy. 2.9. Ground water flow The model calculates the groundwater levels and the incoming and outgoing ground water flows between the polygons by a numerical solution of the well-known Boussinesq equation. The levels and flows influence each other mutually. The groundwater situation is further determined by the vertical recharge that is calculated from the agronomic water balances. These depend again on the levels of the ground water. When semi-confined aquifers are present, the resistance to vertical flow in the slowly permeable top-layer and the overpressure in the aquifer, if any, are taken into account. Hydraulic boundary conditions are given as hydraulic heads in the external nodes in combination with the hydraulic conductivity between internal and external nodes. If one wishes to impose a zero flow condition at the external nodes, the conductivity can be set at zero. Further, aquifer flow conditions can be given for the internal nodes. These are required when a geological fault line is present at the bottom of the aquifer or when flow occurs between the main aquifer and a deeper aquifer separated by a semi-confining layer. 2.10 Drains, wells, and re-use The sub-surface drainage can be accomplished through drains or pumped wells. The subsurface drains, if any, are characterised by drain depth and drainage capacity. The drains are located in the transition zone. The subsurface drainage facility can be applied to natural or artificial drainage systems. The functioning of an artificial drainage system can be regulated through a drainage control factor. By installing a drainage system with zero capacity one obtains the opportunity to have separate water and salt balances in the transition above and below drain level. The pumped wells, if any, are located in the aquifer. Their functioning is characterised by the well discharge. The drain and well water can be used for irrigation through a (re)use factor. This may have an impact on the water and salt balance and on the irrigation efficiency or sufficiency.
2.12 Farmers' responses If required, farmers' responses to water logging and salinity can be automatically accounted for. The method can gradually decrease: -1. the amount of irrigation water applied when the water table becomes shallower depending on the kind of crop (paddy rice and non-rice) -2. the fraction of irrigated land when the available irrigation water is scarce; -3. the fraction of irrigated land when the soil salinity increases; for this purpose, the salinity is given a stochastic interpretation; -4. the ground-water abstraction by pumping from wells when the water table drops.The farmers' responses influence the water and salt balances, which, in turn, slows down the process of water logging and salinization. Ultimately a new equilibrium situation will arise. The user can also introduce farmers' responses by manually changing the relevant input data. Perhaps it will be useful first to study the automatic farmers' responses and their effect first and thereafter decide what the farmers' responses will be in the view of the user. 2.13 Annual input changes The program runs either with fixed input data for the number of years determined by the user. This option can be used to predict future developments based on long-term average input values, e.g. rainfall, as it will be difficult to assess the future values of the input data year by year. The program also offers the possibility to follow historic records with annually changing input values (e.g. rainfall, irrigation, cropping rotations), the calculations must be made year by year. If this possibility is chosen, the program creates a transfer file by which the final conditions of the previous year (e.g. water table and salinity) are automatically used as the initial conditions for the subsequent period. This facility makes it also possible to use various generated rainfall sequences drawn randomly from a known rainfall probability distribution and to obtain a stochastic prediction of the resulting output parameters. Some input parameters should not be changed, like the nodal network relations, the system geometry, the thickness of the soil layers, and the total porosity, otherwise illogical jumps occur in the water and salt balances. These parameters are also stored in the transfer file, so that any impermissible change is overruled by the transfer data. In some cases of incorrect changes, the program will stop and request the user to adjust the input. 2.14 Output data The output is given for each season of any year during any number of years, as specified with the input data. The output data comprise hydrological and salinity aspects. The data are filed in the form of tables that can be inspected directly, through the user menu, that calls selected groups of data either for a certain polygon over time, or for a certain season over the polygons. Also, the program has the facility to store the selected data in a spreadsheet format for further analysis and for import into a mapping program. A user interface to assist with the production of maps of output parameters is still in development. The program offers only a limited number of standard graphics, as it is not possible to foresee all different uses that may be made. This is the reason why the possibility for further analysis through spreadsheet program was created. The interpretation of the output is left entirely to the judgement of the user.
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