Online ISSN: 2382-9931
Journal of Water and Irrigation Management
Homepage: https://jwim.ut.ac.ir/
University of Tehran Press
Spatial Gradient Modeling of Water Yield Service Using Invest in Northern Sub-Basins of Kerman Province
Malihe Erfani1 | Sharif Joorabian Shooshtari2 | Tahereh Ardakani3 | Fatemeh Jahanishakib4
1. Corresponding Author, Department of Environmental Sciences, Faculty of Natural Resources, University of Zabol,
Zabol, Iran. E-mail: [email protected]
2. Department of Nature Engineering, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran. E-mail: [email protected]
3. Department of Environmental Sciences & Engineering, Faculty of Agriculture and Natural Resources, Ardakan University, P.O. Box 184, Ardakan, Iran. E-mail: [email protected]
4. Department of Environmental Sciences, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran. E-mail: [email protected]
Article Info ABSTRACT
Article type:
Research Article
Article history:
Received: October 11, 2022 Received in revised form:
November 28, 2022 Accepted: April 3, 2023 Published online: April 14, 2023
Keywords:
Arid and semi-arid regions, Economic valuation, Ecosystem service, modeling.
The ecosystem service of water yield is affected by damaging human activities, and the estimation of its quantity through modeling is the first step to sustainable management of this service. This research applied the InVEST hydrological model to quantify the ecosystem service of water yield and its valuation in the northern arid and semi-arid sub-basins of Kerman province. First, for modelling the water yield were entered the maps such as annual average precipitation, depth of root limiting layers, plant accessible water capacity, land use/land cover (LULC), and the boundaries of the basin and sub-basins, and the approximate amount of actual evapotranspiration (AET) in each pixel. Then maps of estimated water yield in each pixel was obtained. The model calculated 5112.43 million cubic meters of water with a value of more than 418500 billion Rails are produced annually, the highest amount of water yield is in sub-basin one (Abargho-Sirjan) with 2103 million cubic meters per year and the lowest amount of water yield in sub-region three (north Kavir-e lut) with the amount of 741.84 million cubic meters. The results showed that the value of supply the water yield service is strongly influenced by the spatial changes of LULC. Dense range lands produce 27630.7 MCM of water per hectare, and each hectare of dense forest can produce 1104.6 MCM of water. Therefore the role of vegetation shows the influence of water infiltration and feeding of aquifers in high areas.
The results of this study can be used in spatial planning to reduce the destructive effects of floods and droughts, prevent land degradation and develop vegetation, feed aquifers, and also estimate damages in green accounting.
Cite this article: Erfani, M., Joorabian Shooshtari, Sh., Ardakani, T., & Jahanishakib, F. (2023). Spatial Gradient Modeling of Water Yield Service Using Invest in Northern Sub-Basins of Kerman Province. Journal of Water and Irrigation Management, 13 (1), 63-81. DOI: https://doi.org/10.22059/jwim.2023.349742.1024
© The Author(s). Publisher: University of Tehran Press.
DOI: https://doi.org/ 10.22059/jwim.2023.349742.1024
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Table 1. Biophysical table used in Kerman province to implement the water production model
Area (ha) Root depth
Kc Land use/land cover
8944.65 0
1 Playa
160112.34 1200
0.5 Sparse forest
217604 1200
0.5 Dense forest
269466.75 800
0.7 Agriculture
101122.74 0
0.6 Residential
3244385 5
0.1 Bare
3375481 1000
0.5 Sparse range
4750376.13 1000
0.5 Dense range
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evapotranspiration, c: soil depth, d: plant accessible water capacity and e) land use/land cover
3 . 2 .
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Table 2. Amount of produced water (M3/ha) in different land use/covers in Kerman province
SD Max
Min Mean
Sum LULC
0 0
0 0
0 Playa
260.6 1703.4
69.2 659.7
1663704961.6 Sparse forest
197.3 1461.5
38.7 620.9
1104558789.7 Dense forest
275.2 1481.1
71.01 735.8
2201157216.7 Agriculture
0 0
0 0
0 Residential
187.1 1679.9
0 84.9
3058259198 Bare
187 1681.9
60.6 561.8
21049121921.5 Sparse range
268.1 1766.5
11.9 524
27630736571.7 Dense range
Table 3. Actual evapotranspiration, precipitation and produced water in each sub-basin in Kerman province
Area (ha) Actual evapotranspiration
(mm) Precipitation
(mm) Water yield
(MCM/ year) Water yield
(M3/ha/year) Sub-Basin
3120030 125.2
192.6 21030.0
673.9 1
3385030 97.4
130.2 1110.3
328.03 2
1975200 85.2
122.7 741.8
375.6 3
3647700 103.4
135.1 1157.1
317.2 4
Figure 4. Estimated actual evapotranspiration per pixel (mm)
&S#T . 7 ' HW 1 4 " 6) &+W ' KL ;#M e P MY 4
( F/ M 9 M . 7LULC
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Table 4. The economic value of water yield service under sub-basins in 2021
Sub-basin Total value of water yield (Rail)
Pixel statistics of each sub-basin
Mean Min Max SD
1 172000348873000 497364320 0 130374750 253838460
2 90966110720000 242082320 0 582307940 167960430
3 60730816888200 277230070 0 531001880 170368950
4 94807107194500 234146630 0 587294560 1915627290
Table 5. The economic value of water yield service by land use class in 2021
LULC Total value of water yield (Rail)
Playa 0
Sparse forest 136423806851200
Dense forest 90573820755400
Agriculture 180494891769400
Residential 0
Bare 250777254236000
Sparse range 1726027997563000
Dense range 2265720398879400
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