- SahysMod
SahysMod is a computer program for the prediction of the salinity of soil moisture, groundwater and drainage water, the depth of the water table, and the drain discharge in irrigated agricultural lands, using different hydrogeologic (aquifer) conditions, varying water management options, including the use of ground water for irrigation, and several crop rotation schedules, whereby the spatial variations are accounted for through a network of polygons. [cite book |first=R.J. |last=Oosterbaan |year=1995 |title=SahysMod: Spatial Agro-Hydro-Salinity Model. Description of Principles, User Manual, and Case Studies |publisher=International Institute for Land Reclamation and Improvement, Wageningen, Netherlands |url=http://waterlog.info/pdf/sahysmod.pdf ] [ [http://www.hydrogeologie.uni-bonn.de/de/pdf/DiplArbBreuer.pdf Bonn University] , Germany (in German)]
Rationale
There is a need for a
computer program that is easier to operate and that requires a simplerdata structure then most currently available models. Therefore, the SahysMod program was designed keeping in mind a relative simplicity of operation to facilitate the use by field technicians, engineers and project planners instead of specialized geo-hydrologists.
It aims at usinginput data that are generally available, or that can be estimated with reasonableaccuracy , or that can be measured with relative ease. Although thecalculations are donenumerical ly and have to be repeated many times, the final results can be checked by hand using the formulas in this manual.SahysMod's objective is to
predict thelong-term hydro-salinity in terms of generaltrend s, not to arrive at exact predictions of how, for example, the situation would be on the first of April in ten years from now.
Further, SahysMod gives the option of the re-use ofdrainage andwell water (e.g. forirrigation ) and it can account forfarmer s'response s towaterlogging ,soil salinity , waterscarcity and over-pumping from theaquifer . Also it offers the possibility to introducesubsurface drainage systems at varying depths and with varying capacities so that they can be optimized.Other features of SahysMod are found in the next section.Methods
Calculation of aquifer conditions in polygons
The model calculates the ground water levels and the incoming and outgoing ground water flows between the
polygon s by a numerical solution of the well-known Boussinesq equation. The levels and flows influence each other mutually.The ground water situation is further determined by the vertical
groundwater recharge that is calculated from the agronomicwater balance s. These depend again on the levels of theground water .When semi-confined
aquifer s 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 ashydraulic head s in the external nodes in combination with thehydraulic 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 ageological 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.The depth of the
water table , therainfall and salt concentrations of the deeper layers are assumed to be the same over the whole polygon. Other parameters can very within the polygons according to type of crops and cropping rotation schedule.Seasonal approach
The model is based on
season alinput data and returns seasonaloutput s. 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 orfallow seasons. Reasons of not using smaller input/output periods are:
#short-term (e.g., daily) inputs would require much information ,which, in large areas, may not be readily available;
#short-term outputs would lead to immense output files ,which would be difficult to manage and interpret;
#this model is especially developed topredict 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;
#though theprecision 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 majorconstraint to the design of appropriatesalinity control measures when a certain salinity level, predicted by SahysMod to occur after 20 years, will in reality occur after 15 or 25 years.Computational time steps
Many
water balance factors depend on the level of thewater table , which again depends on some of the water-balance factors. Due to these mutual influences there can be non-linear changes throughout the season. Therefore, thecomputer program performs dailycalculation s. For this purpose, the seasonal water-balance factors given with theinput are reduced automatically to daily values. The calculated seasonal water-balance factors, as given in theoutput , are obtained by summations of the daily calculated values.Groundwater levels andsoil salinity (thestate variable s) at the end of the season are found by accumulating the 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 for better
accuracy . The necessary adjustments are made automatically.Data requirements
Polygonal network
The model permits a maximum of 240 internal and 120 external
polygon s with a minimum of 3 and a maximum of 6 sides each. The subdivision of the area into polygons, based on nodal points with knowncoordinates , should be governed by the characteristics of the distribution of thecrop ping,irrigation ,drainage andgroundwater characteristics over the study area.The nodes must be numbered, which can be done at will. With an index one indicates whether the node is internal or external. Nodes can be added and removed at will or changed from internal to external or vice versa. Through another index one indicates whether the internal nodes have an unconfined or semi-confined aquifer. This can also be changed at will.
Nodal network relations are to be given indicating the neighboring polygon numbers of each node. The program then calculates the surface area of each polygon, the distance between the nodes and the length of the sides between them using the Thiessen principle.
The
hydraulic conductivity can vary for each side of the polygons.The depth of the
water table , therainfall andsalt concentrations of the deeper layers are assumed to be the same over the whole polygon. Otherparameters can very within the polygons according to type of crops and cropping rotation schedule.Hydrological data
The method uses seasonal water balance components as
input data. These are related to the surfacehydrology (likerainfall ,potential evaporation ,irrigation , use ofdrain and well water forirrigation ,runoff ), and the aquifer hydrology (e.g., pumping from wells). The otherwater balance components (like actualevaporation , downwardpercolation , upwardcapillary rise ,subsurface drainage ,groundwater flow ) are given asoutput .The quantity of drainage water, as output, is determined by two drainage intensity factors for drainage above and below drain level respectively (to be given with the input data) and the height of the water table above the given drain level. This height results from the computed water balance Further, a drainage reduction factor can be applied to simulate a limited operation of the drainage system. Variation of the drainage intensity factors and the drainage reduction factor gives the opportunity to simulate the impact of different drainage options.
To obtain accuracy in the computations of the ground water flow (sect. 2.8), the actual evaporation and the capillary rise, the computer calculations are done on a daily basis. For this purpose, the seasonal hydrological data are divided by the number of days per season to obtain daily values. The daily values are added to yield seasonal values.
Cropping patterns/rotations
The
input data onirrigation ,evaporation , and surfacerunoff are to be specified per season for three kinds of agricultural practices, which can be chosen at the discretion of the user::A: irrigated land with crops of group A:B: irrigated land with crops of group B:U: non-irrigated land with rain-fed crops or fallow land
The groups, expressed in fractions of the total area, may consist of combinations of crops or just of a single kind of crop. For example, as the A-type crops one may specify the lightly irrigated cultures, and as the B type the more heavily irrigated ones, such as sugar cane and rice. But one can also take A as rice and B as sugar cane, or perhaps trees and orchards. A, B and/or U crops can be taken differently in different seasons, e.g. A=wheat plus barley in winter and A=maize in summer while B=vegetables in winter and B=cotton in summer. Non-irrigated land can be specified in two ways: (1) as and (2) as A and/or B with zero irrigation. A combination can also be made.
Further, a specification must be given of the seasonal rotation of the different land uses over the total area, e.g. full rotation, no rotation at all, or incomplete rotation. This occurs with a rotation index. The rotations are taken over the seasons within the year. To obtain rotations over the years it is advisable to introduce annual input changes as explained
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 indexes, 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.Soil strata, type of aquifer
SahysMod accepts four different reservoirs of which three are in the soil profile:
:s: a surface reservoir,:r: an upper (shallow) soil reservoir or root zone,:x: an intermediate soil reservoir or transition zone,:q: a deep reservoir or main
aquifer .The upper soil reservoir is defined by the soil depth, from which water can evaporate or be taken up by plant roots. It can be taken equal to the root zone. It can be saturated, unsaturated, or partly saturated, depending on the water balance. All water movements in this zone are vertical, either upward or downward, depending on the water balance. (In a future version of Sahysmod, the upper soil reservoir may be divided into two equal parts to detect the trend in the vertical salinity distribution.)
The transition zone can also be
saturated ,unsaturated or partly saturated. All flows in this zone are horizontal, except the flow to subsurface drains, which is radial.If a horizontal subsurfacedrainage system is present, this must be placed in the transition zone, which is then divided into two parts: an upper transition zone (above drain level) and a lower transition zone (below drain level).If one wishes to distinguish an upper and lower part of the transition zone in the absence of a subsurface drainage system, one may specify in the input data a drainage system with zero intensity.
The aquifer has mainly horizontal flow. Pumped
wells , if present, receive their water from theaquifer only. The flow in the aquifer is determined in dependence of spatially varying depths of the aquifer, levels of the water table, andhydraulic conductivity .SahysMod permits the introduction of "phreatic" (unconfined) and "semi-confined" aquifers. The latter may develop a hydraulic over or under pressure below the slowly permeable top-layer (
aquitard ).Agricultural water balances
The agricultural
water balance s are calculated for each soil reservoir separately. The excess water leaving one reservoir is converted into incoming water for the next reservoir. The three soil reservoirs can be assigned different thickness and storage coefficients, to be given as input data. When, in a particular situation the transition zone or the aquifer is not present, they must be given a minimum thickness of 0.1 m.The depth of the
water table at the end of the previous time step, calculated from thewater balance s, is assumed to be the same within eachpolygon . If this assumption is not acceptable, the area must be divided into a larger number of polygons.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 ofaccuracy .Drains, wells, and re-use
The sub-surface
drainage can be accomplished through drains or pumped wells.The subsurface drains, if any, are characterized 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 characterized by the welldischarge .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.Salt balances
The
salt balance s are calculated for each soil reservoir separately. They are based on theirwater balance s, using the salt concentrations of the incoming and outgoing water. Some concentrations must be given asinput data, like the initial salt concentrations of the water in the different soil reservoirs, of theirrigation water and of the incominggroundwater in the aquifer. The concentrations are expressed in terms ofelectric conductivity (EC in dS/m). When the concentrations are known in terms of g salt/l water, the rule of thumb: 1 g/l -> 1.7 dS/m can be used. Usually, salt concentrations of the soil are expressed in ECe, the electric conductivity of an extract of a saturated soil paste. In Sahysmod, the salt concentration is expressed as the EC of the soil moisture when saturated under field conditions. As a rule, one can use the conversion rate EC : ECe = 2 : 1.Salt concentrations of outgoing water (either from one reservoir into the other or by subsurface drainage) are computed on the basis of salt balances, using different leaching or salt mixing efficiencies to be given with the input data. The effects of different
leaching efficiencies can be simulated varying theirinput value.If drain or well water is used for irrigation, the method computes the salt concentration of the mixed irrigation water in the course of the time and the subsequent impact on the soil and ground water salinity, which again influences the salt concentration of the drain and well water. By varying the fraction of used drain or well water (through the input), the long term impact of different fractions can be simulated.
The dissolution of solid soil minerals or the chemical
precipitation of poorly soluble salts is not included in the computation method. However, but to some extent, it can be accounted for through the input data, e.g. increasing or decreasing the salt concentration of the irrigation water or of the incoming water in theaquifer . In a future version, the precipitation of gypsum may be introduced.Farmers' responses
If required, farmers' responses to
waterlogging andsoil salinity can be automatically accounted for. The method can gradually decrease:# The amount of
irrigation water applied when the water table becomes shallower depending on the kind of crop (paddy rice and non-rice)
# The fraction of irrigated land when the availableirrigation water is scarce;
# The fraction of irrigated land when thesoil salinity increases; for this purpose, the salinity is given astochastic interpretation;
# Thegroundwater abstraction by pumping fromwells 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.
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 onlong-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 systemgeometry , the thickness of the soil layers, and the totalporosity , 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.Output data
The
output is given for eachseason of anyyear during any number of years, as specified with theinput 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 certainpolygon over time, or for a certain season over the polygons. Also, the program has the facility to store the selected data in aspreadsheet 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 judgment of the user.
References
External links & download location
* Free download location of software : [http://www.waterlog.info/software.htm] .
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