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Journal of Arid Land  2020, Vol. 12 Issue (4): 545-560    DOI: 10.1007/s40333-020-0125-3
Research article     
Integrating water use systems and soil and water conservation measures into a hydrological model of an Iranian Wadi system
MAHMOODI Nariman1,*(), KIESEL Jens1,2, D WAGNER Paul1, FOHRER Nicola1
1 Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, Kiel 24118, Germany
2 Department of Ecosystem Research, Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin 12489, Germany
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Water resources are precious in arid and semi-arid areas such as the Wadis of Iran. To sustainably manage these limited water resources, the residents of the Iranian Wadis have been traditionally using several water use systems (WUSs) which affect natural hydrological processes. In this study, WUSs and soil and water conservation measures (SWCMs) were integrated in a hydrological model of the Halilrood Basin in Iran. The Soil and Water Assessment Tool (SWAT) model was used to simulate the hydrological processes between 1993 and 2009 at daily time scale. To assess the importance of WUSs and SWCMs, we compared a model setup without WUSs and SWCMs (Default model) with a model setup with WUSs and SWCMs (WUS-SWCM model). When compared to the observed daily stream flow, the number of acceptable calibration runs as defined by the performance thresholds (Nash-Sutcliffe efficiency (NSE)≥0.68, -25%≤percent bias (PBIAS)≤25% and ratio of standard deviation (RSR)≤0.56) is 177 for the Default model and 1945 for the WUS-SWCM model. Also, the average Kling-Gupta ef?ciency (KGE) of acceptable calibration runs for the WUS-SWCM model is higher in both calibration and validation periods. When WUSs and SWCMs are implemented, surface runoff (between 30% and 99%) and water yield (between 0 and 18%) decreased in all sub-basins. Moreover, SWCMs lead to a higher contribution of groundwater flow to the channel and compensate for the extracted water by WUSs from the shallow aquifer. In summary, implementing WUSs and SWCMs in the SWAT model enhances model plausibility significantly.

Key wordsSWAT model      stream flow      Wadis      multi-metric framework      water use systems      soil and water conservation measures      Halilrood Basin     
Received: 11 September 2019      Published: 10 July 2020
Corresponding Authors:
About author: *Corresponding author: Nariman MAHMOODI (E-mail:
Cite this article:

Nariman MAHMOODI, Jens KIESEL, Paul D WAGNER, Nicola FOHRER. Integrating water use systems and soil and water conservation measures into a hydrological model of an Iranian Wadi system. Journal of Arid Land, 2020, 12(4): 545-560.

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Fig. 1 Location of Halilrood Basin in Kerman Province of Iran (a) and water use systems, and climatic and hydrometric stations in the Halilrood Basin (b)
WUSs Number Number of deactivated SWAT-variables affected Hydrological components affected Implemented scale Total annual extracted water
(×104 m3)
Average daily discharge (L/s) Drilling period
1966-1980 1981-1994 1995-2011
Qanats 347 85 WUSHAL Groundwater, baseflow Sub-basin 16.67 1.52 * * *
Springs 184 14 WUSHAL Groundwater, baseflow Sub-basin 9.99 1.36 * * *
Wells 422 93 WUSHAL Groundwater, baseflow Sub-basin 48.56 * 65 59 268
Table 1 Characteristics of the water use systems (WUSs) in the study area
Parameter Unit Description Baft Rabor
SUB-BASIN - Number of the sub-basin in which the reservoir is located 169 198
IYRES - The operational year 2007 2009
RES_ESA hm2 Reservoir surface area when the reservoir is filled to the emergency spillway 8.0 85.0
RES_EVOL ×104 m3 Volume of water needed to fill the reservoir to the emergency spillway 70 4000
RES_PSA hm2 Reservoir surface area when the reservoir is filled to the principal spillway 7.4 32.0
RES_PVOL ×104 m3 Volume of water needed to fill the reservoir to the principal spillway 65 3500
RES_VOL ×104 m3 Initial reservoir volume 30 2000
Table 2 Hydrological details of the two reservoirs (Baft and Rabor dams)
SWCMs Number of sub-basins SWAT-variables affected Hydrological components and processes affected
Semi-circular bunds 17 Curve number Surface runoff and infiltration
Soil bunds 53 Curve number Surface runoff and infiltration
Table 3 Characteristics of the soil and water conservation measures (SWCMs) in the study area
Parameter Description Unit Calibration range Type
Minimum Maximum
CN2 Initial soil conservation service runoff curve number for moisture condition II - -30 -15 Add
SOL_AWC Available water capacity of soil layer mm H2O/mm soil -0.5 0.5 Add
ESCO Soil evaporation compensation factor - 0.90 0.96 Replace
GW_DELAY Ground water delay time d 4 10 Replace
RCHRG_DP Deep aquifer percolation fraction - 0.5 0.9 Replace
ALPHA_BF Base flow alpha factor Per day 0.08 0.20 Replace
SOL_K Saturated hydraulic conductivity mm/h 30 40 Add
EVRCH Reach evaporation adjustment factor - 0.5 0.8 Replace
Table 4 Selected parameters for calibration in the SWAT model
Fig. 2 Number (n) of acceptable calibration runs for each performance metric (black points) for the Default model in the left column and the WUS-SWCM model in the right column. Default model, a model setup without water use systems and water conservation measures; WUS-SWCM model, a model setup with water use systems and water conservation measures. The gray points represent the range of the KGE (Kling-Gupta ef?ciency) for the complete dataset of the 3000 model runs. The last row of both columns shows the selection of acceptable calibration runs after the application of all thresholds for the different performance metrics. NSE, Nash-Sutcliffe efficiency; PBIAS, percent bias; RSR, ratio of standard deviation.
Fig. 3 Comparison of the 150 best calibration runs for the KGE values of the Default model and the WUS-SWCM model setups in the calibration (solid lines) and validation (dashed lines) periods
Fig. 4 Flow duration curves (FDCs) of the selected 150 best calibration runs for the WUS-SWCM model (light green) and Default model (pink) in the calibration (1995-2003; a-f) and validation (2004-2009; g-l) periods. The common FDCs between the two model setups are shown in dark green. Different segments of the hydrograph are separated by dotted vertical lines.
Model setup Calibration period (1995-2003) Validation period (2004-2009)
Performance metrics Performance metrics
Very high High Middle Low Very low Very high High Middle Low Very low
Default model 0.77 0.22 0.42 0.38 3.10 3.71 0.58 0.32 0.53 0.87 3.44 0.99
WUS-SWCM model 0.82 0.29 0.22 0.70 2.60 3.71 0.61 0.28 1.04 0.81 3.44 0.99
Relative changes + - + - + * + + - + * *
Table 5 Summary of the application of the ratio of standard deviation (RSR) for each flow duration curve (FDC) segment for the average of the 150 best calibration runs of each model setup in calibration (1995-2003) and validation (2004-2009) periods
Model setup Number of model runs Parameters
Default model 292 -24.610 0.005 0.956 8.345 0.527 0.143 32.359 0.655
WUS-SWCM model 2868 -20.917 -0.008 0.954 4.791 0.508 0.191 36.070 0.798
Table 6 Parameter sets that lead to the best model performance for each model setup
Fig. 5 Comparison of observed and simulated stream flow from the Default model (a) and the WUS-SWCM model (b) setups in the calibration (1995-2003) and validation (2004-2009) periods
Fig. 6 Detailed comparison of observed and simulated stream flow from the Default model and the WUS-SWCM model setups for the period of January-June in 2001
Fig. 7 Spatial distribution of sub-basins with or without WUSs and SWCMs (a) and changes of hydrological components when WUSs and SWCMs are implemented (b-d). (b), water yield; (c), groundwater flow; (d), surface runoff. Decreasing change is shown as negative value (red) while increasing change is shown as positive value (blue).
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