Assessment of Actual Evapotranspiration (ALARM) under SSP Scenarios and Its Impact on Soil Salinity Case Study: Ahar Chay Watershed

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Asadi Mehdi

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Journal Paper

Paper Information

Journal: HYDROGEOMORPHOLOGY Year:2025 | Volume:12 | Issue:43 Page(s): 141-125

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Title

Assessment of Actual Evapotranspiration (ALARM) under SSP Scenarios and Its Impact on Soil Salinity Case Study: Ahar Chay Watershed

Author(s)

Asadi Mehdi | Issue Writer Certificate

Keywords

evapotranspiration

ALARM

remote sensing

Watershed

Ahar Chai

Abstract

In this study, the ALARM method (Analytical Land Atmosphere Radiometer Model) and UKESM1-0-LL, INM-CM5-0, CanESM5, BCC-ESM1, and ACCESS-CM2 models from the CMIP6 report and SSP scenarios (SSP1.2.6, SSP3.7.0, and SSP5.8.5 scenarios) were used to predict the amount of evapotranspiration in the Ahar Chay watershed. The results of the ALARM method were also compared with the FAO Penman-Monteith and Torrent-White methods. For this purpose, 72 Landsat 8 OLI sensor images related to row 168 and pass 33 were used. The results showed that the ALARM method had the highest correlation (R^20.915) and the lowest error (RMSE 1.493 and MSE 1.232 mm) with the Penman-Monteith method. The RMSE and MSE values for evapotranspiration in all the models studied were below 2.867, and the lowest RMSE and MSE values were for the ACCESS-CM2 model with numerical values of 0.198 and 0.165, respectively, in the SSP1.2.6 scenario. It is also worth noting that the models studied did not perform very well in evaluating the evapotranspiration parameter in the SSP5.8.5 scenario, and the RMSE and MSE values in all models were above 1. This value in SSP5.8.5 in the UKESM1-0-LL model has the highest evapotranspiration rates with numerical values of 2.867 and 2.735, respectively. Also, the amount of very high soil salinity, based on the NDSI and S indices, has increased by about 6,613.81 and 6,296.81 hectares, respectively, from 2013 to 2024, which has a correlation of 0.987 with the increasing trend of evaporation and transpiration in climate scenarios.

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