2025 : 9 : 29
Ali Mahdavi

Ali Mahdavi

Academic rank: Professor
ORCID:
Education: PhD.
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HIndex:
Faculty: Agriculture
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Research

Title
Annual Water Yield Estimation for Different Land uses of Mish-khas Catchment in Ilam City Using a GIS-based InVEST Model
Type
JournalPaper
Keywords
Evapotranspiration, Soil Depth, Plant Available Water, Bio-physical Database
Year
2018
Journal Journal of Rangeland Science
DOI
Researchers AliAkbar Jafarzadeh ، Ali Mahdavi ، Rashid Fallah Shamsi ، Rasoul YousefPour

Abstract

Fresh water supply and its security are facing a high level of fluctuating variability under global climate change. To address these concerns in catchment water management, a good understanding of land use/cover impacts on the hydrological cycle affecting water supply is crucial. The objective of this study is defined as to model the impact of existing land use/cover on water yielding in Mish-khas catchment of Zagros region, Western IRAN. In this research, a water yield model of Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) was employed to estimate annual water yield in the catchments as a basic foundation for policy and decision making. The input data set included land use/cover layers of the region, produced in 2016, average annual precipitation and potential evapotranspiration from 1986–2016, soil depth, plant available water content and land use/cover bio-physical database. Based on the results, the total annual water yield was estimated 30209321 m3 for the whole Mish-khas catchment. Thepercent of annual water yield for rangeland, forest, farmland and orchards landuses were 57%, 31%, 8.6% and 3.4% of the total water yield of the catchment, respectively. In addition, the results showed that the farmland had the highest water yield per hectare (2449 m3/ha) followed by forests (2269 m3/ha), orchards (2254 m3/ha) and rangeland (2196 m3/ha) land uses. In terms of water distribution, the northern regions with a volume of 2315 m3 per hectare had more water yield than the southern regions (2210 m3 per hectare). The results also indicate that a GIS-based InVEST model is helpful instrument to identify more suitable areas for water-table recharge.