Application of VIC-WUR model for assessing the spatiotemporal distribution of water availability in anthropogenically-impacted basins

Abstract

Climate change, rapid increase in population, and urbanization have given rise to over-exploitation and shortage of freshwater resources. Acquiring accurate representations of fresh water availability is therefore crucial to sustainable development. Based on the underlying hydrological processes and storage types, fresh water can be divided into blue and green water components. Hence, quantification of the spatio-temporal distribution of blue and green water requires estimating the components of terrestrial water cycle. In this study, a framework is proposed to evaluate the water scarcity using the blue and green water concept. In this framework, the Wageningen Institute and Research (WUR) version of the Variable Infiltration Capacity Model (VIC) is employed to simulate terrestrial water cycle. Compared to VIC model, VIC-WUR model employs additional modules to account for sectoral water demands, return flows, and groundwater withdrawals, however, very limited number of its applications have been reported so far. The Divandareh-Bijar (DBJ) basin in west of Iran is selected because it has experienced severe anthropogenic alterations in the past three decades. To address precipitation and parameter uncertainty, the VIC-WUR model is separately calibrated for three precipitation datasets. As a part of this framework, the calibrated model is used to simulate blue and green water components and their corresponding scarcity metrics for the first time. According to the results, blue and green water resources in the DBJ are relatively scarce. The results also highlight the importance of considering anthropogenic impacts on the spatiotemporal dynamics of green and blue water resources. Additionally, quantification of the uncertainty in blue and green water components can help produce more reliable estimations for intelligent management of water resources. The ANalysis Of VAriance (ANOVA) method is therefore used to quantify the contribution of three major factors, including precipitation inputs, model parameters, and the interaction of these two, on the uncertainty of calculated water scarcity metrics. Structural uncertainty is implicitly addressed through the use of the modified version of the VIC model. The results indicate seasonality of these contributions for the two metrics under investigation and the differences in relative contribution of different sources to the overall uncertainty. The proposed framework could be employed to identify water stress in various spatiotemporal scales across the globe.