مدلسازی و مدیریت آب و خاک (Nov 2022)
The effect of climate change on the Fariman Dam watershed health using VOR model
Abstract
Introduction Ecosystem health is the ability of ecosystems to maintain structure and function in the face of external pressures over time. The knowledge of watershed health with a systemic approach seeks to conserve the natural ecosystem by protecting healthy watersheds and preventing changes in them. Assessing watershed health and prioritizing sub-watersheds is essential for effective watershed management and will help in proper management and optimal allocation of resources. Considering that watersheds are dynamic systems, the hydrological function and health of watersheds are constantly changing under the influence of land use changes, climate change, and human interventions. The emission of greenhouse gases in recent decades has caused global warming, followed by changes in the hydrological regime and function of watersheds, which can threaten the health of the watersheds. In order to evaluate the health status of the ecosystem, various methods such as pressure-state-response (PSR), vigor-organization-resilience (VOR), reliability-resilience-vulnerability (RRV), and watershed health index (WHI) have been presented which determine the watershed health using several indicators. The aim of this research is to evaluate the health of the Fariman dam watershed in Khorasan Razavi province under current and future climate using the VOR model and hydrological simulation. Materials and Methods In order to achieve the research objectives, the hydrology of the watershed was simulated using the SWAT model. For this purpose, parameters sensitivity analysis, calibration, and validation of the model were performed using the SUFI-2 algorithm in SWAT-CUP software using daily discharge and suspended sediment yield data for the period of 2008-2014 and 2016-2019. Then, using the VOR model, the health of the watershed was calculated for the historical period of 1985-2014. In the VOR model, the indicators of landscape, soil erosion, and water loss were used to determine the components of the vigor, organization, and resilience of the watershed. The landscape indicators were determined using the watershed land use map in FRAGSTATS 4.2.1 software and indicators related to watershed hydrology (sediment yield and runoff) achieved from the output of the SWAT model. To assess the effect of climate change on watershed hydrology, precipitation and temperature data from CMCC-ESM2, GFDL-ESM4, and MRI-ESM2-0 climate models of IPCC sixth assessment report for three SSP1-2.6, SSP2-4.5 and SSP5-8.5 emission scenarios for two future time period (2030-2059 and 2070-2099), were downloaded. Then, CMhyd software was used for bias correction and downscaling of climate data. In the end, the SWAT model was run and the health index was calculated for future periods and compared with the historical period. Results and Discussion Calibration results of the SWAT model showed that Nash-Sutcliffe criterion for discharge and monthly sediment in the calibration period was 0.66 and 0.65, respectively. Nash-Sutcliffe criteria values for the validation period were 0.57 and 0.56 respectively for discharge and sediment. The results of watershed health by VOR model in the historical period showed that the average health index of the sub-watersheds for MRI-ESM2-0, GFDL-ESM4, and CMCC-ESM2 models is 0.545, 0.533, and 0.665, respectively. The average index of all three models is 0.581 which means the watershed health status is "Moderate". The presented results show that in the SSP1-2.6 scenario in the period of 2030-2059, the health index in three sub-watersheds 2, 8 and 9 has decreased by 16.1, 3.6, and 0.6% (average 7.6%) compared to the historical period (1985-2014). The health index has decreased in 4 sub-watersheds in the SSP2-4.5 scenario and in 6 sub-watersheds in the SSP5-8.5 scenario. The average reduction in the SSP2-4.5 scenario is 9.3 percent and in the SSP5-8.5 scenario, it is 10.6%. The health index of sub-watersheds 2 and 9 has decreased in all emission scenarios and the health index of sub-watersheds 5 has decreased only in the SSP5-8.5 by 10.7 %. As a result, watershed health in the future and under climate change indicated that in the period of 2030- 2059 with the increase of greenhouse gas emissions, the number of sub-watersheds with a decrease in watershed health index will increase from three sub-watersheds in the SSP1-2.6 to 4 and 6 sub-watersheds in the SSP2 -4.5 and SSP5-8.5. In other words, the watershed health index has decreased in 34.6 % of the watershed area in the SSP1-2.6, while in the SSP2-4.5, 51 % and in the SSP5-8.5, 5.65 % of the watershed area will experience a decrease in health. Also, The results for the period 2070-2099 show that in the SSP1-2.6, the health index has decreased in sub-watersheds 2, 3, 5, 6, and 9 with an average of 11.2%, in the SSP2-4.5 scenario, sub-watersheds 2, 5, 7, 8, and 9 with an average of 5.1% and in the SSP5-8.5 scenario, sub-watersheds 2, 4, 5, 6, 8 and 9 with an average of 7.5% had a more decreasing trend. Sub-watersheds 2, 5, and 9 had a decreasing trend in all three scenarios, and sub-watersheds 3, 4, and 7 only had a decrease only in SSP1-2.6, SSP5-8.5, and SSP2-4.5 scenarios. The results in the period of 2070-2099 indicate that the watershed health index in the SSP1-2.6 has decreased in 50.1% of the watershed area, while in the SSP2-4.5, it was 56.3%, and in the SSP5-8.5, 65.5% of the watershed area. Conclusion The results showed that the overall watershed health index in the study area based on the VOR model is “moderate”, but with the increase in the amount of greenhouse gas emissions and the increase in temperature, the watershed health index decreases in a larger number of sub-watersheds, as in the SSP1 -2.6, the watershed health index has decreased in 34.6 % of the watershed, while in the SSP2-4.5, 51 % and in the SSP5-8.5 scenario, 65.5 % of the watershed area has been associated with a decrease in health. Overall, the results of the research showed that climate change can affect the watershed health index, and these effects are different in various sub-watersheds.
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