Assessing the Impact of Climate Change on Water Scarcity in the Tormes &#8206;Catchment, Spain: A Human-Water System Modeling Approach
Authors: Hassan Osama Gasimelseed Bakhit , Pérez-Blanco C. Dionisio , González-López Héctor 
Published: March 2024

Climate change presents a pressing challenge to global water availability resulting in &#8206;increased variability in precipitation and increased temperatures, imposing more stress &#8206;on existing water resources and the economic activities that depend on them. The &#8206;Tormes catchment, located in a semi-arid region, is facing increasingly severe water &#8206;shortages, which may be further aggravated under climate change. This catchment is &#8206;extensively employed for agricultural purposes, and a potential reduction in the &#8206;availability of water for irrigation emerges as a significant concern.&#8206;This study evaluates the impact of climate change on water availability, and the &#8206;responses implemented by irrigators to adapt to growing scarcity, in the Tormes &#8206;catchment. To this end, we develop a human-water system model that couples the Soil &#8206;and Water Assessment Tool (SWAT) model and a Positive Multi-Attribute Utility &#8206;Programming (PMAUP) model using a dynamic and modular approach. The coupled &#8206;model runs the water (SWAT) and human (PMAUP) system models iteratively and &#8206;over time using inputs from six different bias-corrected Global Climate &#8206;Models(GCMs) under CMIP6 scenarios, as follows: i) CMIP6 climate change scenario &#8206;simulations are fed to the SWAT model to estimate relevant hydrological data &#8206;including water availability in March (beginning of the irrigation campaign); ii) &#8206;information on water availability is fed to the PMAUP model to simulate the adaptive &#8206;responses of irrigators in terms of water and land allocation; iii) land and water use &#8206;choices by irrigators are fed into the SWAT model, which reproduces the &#8206;consequences of human decisions on the water system; iv) when the hydrological year &#8206;is over, a new iteration starts where CMIP6 climate change scenario simulations for &#8206;the following year are fed into the SWAT model and the process is repeated again. The &#8206;non-linearity and modular approach in both the hydrological and economic models &#8206;imply complex and interconnected interactions within these systems, with behaviors &#8206;that may or may not follow linear patterns.&#8206;Six bias-corrected GCMs under CMIP6 scenarios were employed for the climate &#8206;change scenario simulations. The dataset covered precipitation, maximum and &#8206;minimum temperatures for the historical period (1981&#8211;2010) and projections for &#8206;SSP245 and SSP585. Future data was analyzed for three periods: 2020&#8211;2039, 2040&#8211;&#8206;&#8206;2059, and 2060&#8211;2100. A multi-model ensemble approach was applied, averaging &#8206;outputs from the six models. Precipitation and temperature data were integrated into &#8206;the SWAT model.&#8206;The hydrological analysis revealed a downward trend in projected precipitation, with &#8206;reductions of 0.7% (2020s), 0.3% (2040s), and up to 5.3% (2060s) under SSP245. &#8206;SSP585 showed declines of 6.4% (2020s), 6.6% (2040s), and 16.1% (2060s). &#8206;Maximum and minimum temperatures exhibited an upward trend under both &#8206;scenarios. Simulated mean annual runoff under SSP245 experienced a drastic &#8206;reduction of 48.1% in the 2020s, followed by 43.8% (2040s) and 53% (2060s). &#8206;Similarly, under SSP585, mean annual runoff decreased by 47.2% over the entire &#8206;projection period. While the hydrological analysis reveals concerning trends in &#8206;precipitation, temperature, and mean annual runoff under different scenarios, the &#8206;economic results, reflecting the effects of these hydrological changes on human &#8206;activities, are still being investigated and are not yet finalized.&#8206;