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Abstract and Figures

The spatial (polygonal) Agricultural-Hydrological-Soil-Salinity model SahysMod (including a routine for the flow of groundwater from polygon to polygon) has been used frequently in irrigated lands in (semi)arid regions as can be seen in the list of references. Azar Inam, Jan Adamowsky et al. (2017) have applied the model in the Rechna Doab area of Pakistan. The purpose of this article is to use their data for demonstration of the large number of mapping options of SahysMod.
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Mapping facilities of the spatial agro-hydro-soil-salinity model SahysMod
R.J. Oosterbaan, 25-08-2019. On www.waterlog.info public domain
Abstract
The spatial (polygonal) Agricultural-Hydrological-Soil-Salinity model SahysMod (including a
routine for the flow of groundwater from polygon to polygon) has been used frequently in
irrigated lands in (semi)arid regions as can be seen in the list of references. Azar Inam, Jan
Adamowsky et al. (2017) have applied the model in the Rechna Doab area of Pakistan. The
purpose of this article is to use their data for demonstration of the large number of mapping
options of SahysMod.
Contents
1. Introduction
2. Mapping examples
3. Conclusions
4. References
5. Appendix. SahysMod nodal networks overlaid on Google Earth
1. Introduction
The SahysMod model [Ref. 1] uses polygons to simulate agricultural, hydrological and soil
conditions in larger areas. It simulates the conditions over as many years as desired by the
user.
The polygonal system makes it possible to present the results not only in tables or graphs, but
also in maps.
The mapping options are summarized in figure 1.
Figure 1. Output categories of Sahysmod and output selection procedure.
Azar Inam and Jan Adamowski et. Al [Ref. 2, Ref. 3, Ref. 4] have applied SahysMod to the
Rechna Doab region in Pakistan. Their data will be used to illustrate the mapping options of
SahysMod.
2. Mapping examples
As the study in Reachna Doab concerned amongst other the salinization of the irrigated land,
the first mapping example is shown for this aspect.
The first example shows a map of the weighted average soil salinity per polygon (figure 2)
Figure 2. Average soil salinity per polygon in year 2, season 1. Especially in the
North-Eastern part of the area the salinity is high, hampering crop
production.
Figure 2 demonstrates that the salinity problems occur more strongly in the North-Eastern part
of the Rechna Doab region, though elsewhere also instances of severe salinity happen, for
example in polygon 142, 158 and 122.
Figure 3 maps the same salinity of figure 1, with the difference that the classification scales
are increased and the color pattern is changed.
Figure 3. Average soil salinity per polygon in year 2, season . As in figure 1, but
using another classification scale and color pattern
Figure 3 is like figure 2, but it has a different classification and another color pattern. These
are optional characteristics.
SahysMod distinguishes three types of crops and up to 4 seasons per year. The crops of group
A have the following areal distribution in season 1 (figure 4).
Figure 4. Fraction of land under irrigated A type crops in season 1.
The majority of the land is densely cultivated.
The soil salinity in the areas under A type crops is depicted as follows (figure 5).
Figure 5. Soil salinity of the land under A type crops in season 1.
The crops can also be rotated over the seasons. The rotations may include fallow land. The
salinity development in the areas of crop rotation outside the areas of the permanent A type
crops can be seen in the next figure 6.
Figure 6. Soil salinity in land with seasonal crop rotations.
The salinity is not only calculated in the root zone, but also in the transition zone between root
zone and aquifer (figure 7). This is of importance for the root zone when capillary rise occurs.
Figure 7. Salinity of the transition zone between root zone and aquifer.
The permanently fallow land runs a severe risk of salinization because there is no application
of irrigation water that helps to leach the salts down away from the root zone. Figure 8 shows
the actual evaporation from the fallow land, which is less than the potential evaporation, but
which may be an indicator of the capillary rise.
Figure 8. Evaporation from dry land
The fraction of non-irrigated land (see figure 9) is relatively large owing to a shortage of
irrigation water as also discussed in figure 12.
Figure 9. Fractions of fallow land
The groundwater balance in the aquifer is determined by the inflow from neighboring
polygons (figure 10), the outflow to other neighboring polygons (figure 11), the downward
percolation of irrigation water that is not evaporated and/or the capillary rise.
Figure 10. Groundwater inflow through the aquifer per polygon.
Figure 11. Groundwater outflow through the aquifer per polygon. The inflow
(figure 10) reduced by the outflow (this picture) determines the depth of the
water table, together with other water balance factors like downward
percolation and upward capillary rise.
The following picture gives an overview of the irrigation sufficiency (figure 12) indicating the
fraction of the potential evapo-transpiration of the crops that is covered by the amount of net
irrigation and rain water, i.e. after subtraction of the losses to the under ground.owing to a less
than 100% irrigation efficiency.
Figure 12. This makes it clear that the irrigation sufficiency is low and that scarcity
of irrigation water plays an important role in the region
Although there are many more mapping options, this series of examples is terminated with a
map of depths of the water table (figure 13).
Figure 13. The water table is fairly deep except in the dark blue polygons bordering
the river. Especially the central part of the region has deep water tables.
This may be partly due to the scarcity of irrigation water as discussed
before so that the recharge to the water table is limited.
3. Conclusions
The SahysMod model integrates many soil and water management aspects of irrigated lands
and offers the possibility to study a large number of phenomena over a large project area.
4. References
1 – SahysMod, free software for polygonal agro-hydro-soil-salinity modeling including aquifer
conditions and groundwater flow. Download from https://www.waterlog,info/sahysmod.htm
2 - Azhar Inam et al. , 2017. '' Coupling of a distributed stakeholder-built system dynamics socio-
economic model with SAHYSMOD for sustainable soil salinity management – Part 1: Model
development''. In Journal of Hydrology, http://dx.doi.org/10.1016/j.jhydrol.2017.03.039
3 - Azhar Inam et al. , 2017. '' Coupling of a distributed stakeholder-built system dynamics socio-
economic model with SAHYSMOD for sustainable soil salinity management – Part 2: Model
coupling and application''. In Journal of Hydrology,
https://www.sciencedirect.com/science/article/pii/S0022169417301865?via%3Dihub
4 - Jan Adamowski et al., 2017. ''Parameter estimation and uncertainty analysis of the Spatial Agro Hydro
Salinity Model (SAHYSMOD) in the semi-arid climate of Rechna Doab, Pakistan''. Journal of
Environmmental Modelling & Software 94 (2017) 186-211.
http://dx.doi.org/10.1016/j.envsoft.2017.04.002
List of other publications in which SahysMod is used, chronologically
1 - Sina Akram, Heydar Kashkouli, Ebrahim Pazira, 2008. ''Sensitive variables controlling salinity
and water table in a bio-drainage system using SahysMod''. Irrigation and Drainage Systems
Volume 22, Numbers 3-4, December, 2008 pp. 271-285. Online:
http://www.springerlink.com/content/r102ju4952710421/
2 - Hosein Liaghat, M Mashal, 2008. ''Sustainability of Biodrainage Systems Considering Declining of
Evapotranspiration Rate of Trees Due to Soil Salinization.'' Published by the American Society of
Agricultural and Biological Engineers (http://www.asabe.org), St. Joseph, Michigan . Citation: 9th
International Drainage Symposium held jointly with CIGR and CSBE/SCGAB Proceedings, 13–16 June
2010 IDS-CSBE-100129. Online: http://elibrary.asabe.org/abstract.asp?aid=32127
3 - Tsegay F. Desta, 2009. ''Spatial modeling and timely prediction of salinization processes using
SahysMod in GIS environment''. Thesis International Institute for Geo-information Science and
Earth Observation (ITC), Enschede, The Netherlands. On line :
http://www.itc.nl/library/papers_2009/msc/aes/desta.pdf
4 - Sina Akram and Hossein Liaghat. (2010) ''Performance of biodrainage systems in arid and
semiarid areas with salt accumulation in soils''. 9th International Drainage Symposium held jointly
with CIGR and CSBE/SCGAB Proceedings, 13–16 June 2010.
http://www.csbe-scgab.ca/docs/meetings/2010/CSBE100116.pdf
5 - Ajay Singh, Sudhindra Nath Panda. (2012) ''Integrated Salt and Water Balance Modeling for
the Management of Waterlogging and Salinization. I: Validation of SAHYSMOD''. Journal of
Irrigation and Drainage Engineering 138:11, 955-963
http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29IR.1943-4774.0000510
6 - Singh, A. and Panda, S. (2012).''Integrated Salt and Water Balance Modeling for the
Management of Waterlogging and Salinization. II: Application of SAHYSMOD'' J. Irrig. Drain Eng.,
138(11), 964–971. http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29IR.1943-4774.0000510
7 - Yao, R.J, Yang, J.S., Wu, D., Xie, W. 2017. Calibration and Sensitivity Analysis of Sahysmod for
Modeling Field Soil and Groundwater Salinity Dynamics in Coastal Rainfed Farmland. Irrig Drain.
66(3):411-427. https://doi.org/10.1002/ird.2106.
8- Yao, R.J., Yang, J.S., Wu, D., Xie, W., Wang, X,P. 2017. Scenario Simulation of Field Soil Water and
Salt Balances Using SahysMod for Salinity Management in a Coastal Rainfed Farmland. Irrig Drain. 66.
https://doi.org/10.1002/ird.2159.
9 - Agro-hydro-soil-salinity characteristics of the irrigated Garmsar alluvial fan, Iran, described with
the SahysMod model. On line:
https://www.researchgate.net/publication/336680433_Agro-hydro-soil-
salinity_characteristics_of_the_irrigated_Garmsar_alluvial_fan_Iran_described_with_the_SahysMod
_model
or:
https://www.waterlog.info/pdf/Garmsar.pdf
10 - Irrigation, groundwater, wells, drainage and soil salinity control in the alluvial fan of Garmsar,
Iran – assessments with the Sahysmod model. On line:
https://www.researchgate.net/publication/341607069_Irrigation_groundwater_wells_drainage_and
_soil_salinity_control_in_the_alluvial_fan_of_Garmsar_Iran_-
assessments_with_the_Sahysmod_model
or:
https://www.waterlog.info/pdf/Garmsar irrigation.pdf
11 - The groundwater hydraulics of the Garmsar alluvial fan, Iran, assessed with the SahysMod
model. On line:
https://www.researchgate.net/publication/336232156_The_groundwater_hydraulics_of_the_Garms
ar_alluvial_fan_Iran_assessed_with_the_SahysMod_model
or:
https://www.waterlog.info/pdf/Garmsar groundwater.pdf
5. Appendix. SahysMod nodal networks overlaid on Google Earth
The Garmsar alluvial fan (Google Earth) overlain by the SahysMod nodal network (blue
lines) with internal/external polygon numbers using https://overlay.imageonline.co/
The Garmsar alluvial fan (Google Earth) overlain by the SahysMod nodal network (blue
lines) and the surface level contour lines (black) made with the QuikGrid program, see
https://www.waterlog.info/pdf/QuikgridHelp.pdf .
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
Manual calibration of distributed models with many unknown parameters can result in problems of equifinality and high uncertainty. In this study, the Generalized Likelihood Uncertainty Estimation (GLUE) technique was used to address these issues through uncertainty and sensitivity analysis of a distributed watershed scale model (SAHYSMOD) for predicting changes in the groundwater levels of the Rechna Doab basin, Pakistan. The study proposes and then describes a stepwise methodology for SAHYSMOD uncertainty analysis that has not been explored in any study before. One thousand input data files created through Monte Carlo simulations were classified as behavior and non-behavior sets using threshold likelihood values. The model was calibrated (1983–1988) and validated (1998–2003) through satisfactory agreement between simulated and observed data. Acceptable values were observed in the statistical performance indices. Approximately 70% of the observed groundwater level values fell within uncertainty bounds. Groundwater pumping (Gw) and hydraulic conductivity (Kaq) were found to be highly sensitive parameters affecting groundwater recharge.
Article
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Bio-drainage can be considered as an important part of sustainable irrigation water management. Bio-drainage has potential for managing shallow water conditions in arid and semiarid areas especially when traditional subsurface drains are not available. Bio-drainage theory does not go back too far. The relationship between soil characteristics, water management regimes, and climatic conditions is not yet well defined. This study attempted to use a mathematical model (SAHYSMOD) to evaluate factors affecting design and operation of a bio-drainage system and study its sensitivity to different variables. The study showed that the major constraint of bio-drainage is salt accumulation in tree plantation strips in arid and semiarid regions. Maximum soil water salinity which can be controlled by bio-drainage is around 3dS m−1 in rather medium run and sustainability may only be achieved where a salt removal mechanism is considered. The study also showed that the effectiveness of the system is higher where the neighboring strips are narrower. It also showed that bio-drainage is very sensitive to the amount of applied water. While the barrier depth does not have an important effect on water table draw down, it does have a great influence on lowering the salinization rate of tree plantation strips. The application of bio-drainage could be economically controversial since in humid areas water is sufficient for agricultural crops, allocating parts of the expensive land to mostly non-fruit trees may not be feasible, while in arid and semiarid regions there is usually enough cheap land to grow trees.
Article
Understanding the long-term soil water and salt balances in coastal salt-affected farming area is important for developing appropriate management practices, controlling salinization and maximizing crop production. An integrated spatial agro-hydro-salinity model (SahysMod) was employed to analyze water and salt balances of rainfed salt-affected farmland. The model was calibrated using the observed soil and groundwater data, and the potential influence of various field management practices on the rootzone salinity and groundwater properties was simulated using the calibrated model. Results revealed that rootzone soil salinity (ECe) generally decreased at an annual average rate of 2.2 dS/m under the existing conditions, and the decreasing rate of rootzone salinity ranged from 1.9 dS/m to 2.7 dS/m per year under the other scenarios. Practices including subsurface drainage system and plastic film mulching were suggested for managing soil salinity and stabilizing the groundwater table. Irrigation with brackish water in the dry season was not recommended since it increased soil and groundwater salinity in comparison with the existing conditions. It was concluded that subsurface drainage was the most high-efficient approach for salt leaching, whereas plastic film mulching was more economic and effective to control soil and groundwater salinization when considering the additional cost and environmental influence.
Article
Understanding water and salt balances in salt-affected farming areas is becoming increasingly important because of the growing public interest in controlling salinization. An integrated spatial-agro-hydro-salinity model (SahysMod) was used to model field soil and groundwater salinity dynamics in coastal rainfed farmland, and calibration, error analysis, and sensitivity analysis were performed for the SahysMod model. Results indicated that a leaching efficiency ranging between 0.4 and 0.7 in the root zone, hydraulic conductivity of 0.2 m day⁻¹ and leaching efficiency of 1.2 in the aquifer produced model results best matching the measured data. The predicted root zone soil salinity, average groundwater salinity and level data showed agreement with the observed values when using the determined parameters. Leaching efficiency of the root zone, hydraulic conductivity and leaching efficiency of the aquifer were the most sensitive parameters for soil salinity, groundwater table and groundwater salinity, respectively. Soil and groundwater salinity were moderately sensitive to effective porosity of the root zone and hydraulic conductivity of the aquifer, whereas groundwater level was not sensitive to the leaching efficiency of soil and aquifer. It could be concluded that the SahysMod model can be used as a successful tool to model field water and salt balances in soil and aquifers in a coastal rainfed agroecosystem.
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Irrigated agriculture faces serious threats of waterlogging and soil salinization in the arid and semiarid regions of the world. In this paper, an integrated spatial-agro-hydro-salinity model (SAHYSMOD) was used to analyze water and salt balances of an irrigated semiarid area located in the Haryana State of India where the groundwater level is rising continuously. The calibration, validation, error analysis, and sensitivity analysis of the model parameters were performed. The sensitivity analysis revealed that hydraulic conductivity is the most sensitive model parameter for both groundwater levels and salinities, followed by effective porosity of the aquifer. The leaching efficiency of the soil is sensitive only to the groundwater salinities. The results show a good agreement between the simulated and observed groundwater levels and salinities for almost all the nodes during the calibration and validation periods. The results are also substantiated by the high R-squared values and low mean error (ME) and root mean square error (RMSE) values. On the basis of the results, it could be concluded that the SAHYSMOD performed very well in predicting groundwater levels and salinities during the calibration and validation periods. DOI: 10.1061/(ASCE)IR.1943-4774.0000511. (C) 2012 American Society of Civil Engineers.
Conference Paper
Biodrainage is the use of vegetation to manage water fluxes through evapotranspiration. It is an alternative technique that has recently attracted interest in drainage and environmental management. Sometimes "drainage" has become a "dirty word" and its implementation has been restricted. Biodrainage is one of the alternative options. The absence of effluent makes the system attractive. However, biodrainage systems must be sustainable in the long-term. Biodrainage theory does not go back too far. The relationship between soil, climate, irrigation management and salinity is not yet well defined. In this research the SAHYSMOD mathematical model was used with two different approaches. 1) Evapotranspiration rate of plantation strips does not change because of increased salinity with the passage of time (S. Akram et al., 2009); and 2) Evapotranspiration rate decreases due to salt accumulation in the soil. While the first approach showed that in most cases the system can perform for about 15 to 20 years, the second approach showed that the life time of the system may not exceed 10 years. In the second system water table draws down during the first 3 to 4 years; however, it rises afterwards due to lower evapotranspiration rate caused by salt accumulation in the soil of plantation strips. This, however, shows that the system may not be considered sustainable in arid and semi arid areas especially where the irrigation water is saline. The result agrees with Heuperman et al. (2002) who says that it is doubtful that biodrainage can maintain soil salinity to an extent that crops could be grown economically. The result, however, does not agree with Kapoor and Denecke (2001) who indicates that biodrainage could be used in various regions ranging from humid to semi arid areas, except when the ground water EC is greater than 12 dS m-1. Hybrid system that combines bio-drainage and conventional drainage technology and/or salt removal and extra land for tree plantation may lengthen the life of the system.
Sustainability of Biodrainage Systems Considering Declining of Evapotranspiration Rate of Trees Due to Soil Salinization
  • Hosein Liaghat
-Hosein Liaghat, M Mashal, 2008. ''Sustainability of Biodrainage Systems Considering Declining of Evapotranspiration Rate of Trees Due to Soil Salinization.'' Published by the American Society of Agricultural and Biological Engineers (http://www.asabe.org), St. Joseph, Michigan. Citation: 9th International Drainage Symposium held jointly with CIGR and CSBE/SCGAB Proceedings, 13-16 June 2010 IDS-CSBE-100129. Online: http://elibrary.asabe.org/abstract.asp?aid=32127
Spatial modeling and timely prediction of salinization processes using SahysMod in GIS environment
  • F Tsegay
  • Desta
Tsegay F. Desta, 2009. ''Spatial modeling and timely prediction of salinization processes using SahysMod in GIS environment''. Thesis International Institute for Geo-information Science and Earth Observation (ITC), Enschede, The Netherlands. On line : http://www.itc.nl/library/papers_2009/msc/aes/desta.pdf
Integrated Salt and Water Balance Modeling for the Management of Waterlogging and Salinization. II: Application of SAHYSMOD
  • A Singh
  • S Panda
Singh, A. and Panda, S. (2012).''Integrated Salt and Water Balance Modeling for the Management of Waterlogging and Salinization. II: Application of SAHYSMOD'' J. Irrig. Drain Eng., 138(11), 964-971. http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29IR.1943-4774.0000510