Answers are grounded in this paper and cite their sources.
Assesses water shortage risk in agricultural watersheds, indicating vital insights for sustainable management.
Water shortage is a critical problem that affects the sustainability of the agricultural sector in Northeastern Thailand, especially areas located far from major rivers. This study developed an integrated QSWAT–WEAP modeling system combined with GIS-based spatial analysis for water shortage risk assessment at the sub-district level in Maha Sarakham Province, covering 5292 sq.km and 133 sub-districts. The system bridges the institutional gap between hydrological sub-watershed boundaries and administrative jurisdictions, enabling model outputs that directly support local governance decision-making. The QSWAT model simulated sub-watershed streamflow while the WEAP model evaluated water balance against water demand from five sectors. QSWAT validation (2017–2023) achieved R2 = 0.72, NSE = 0.70, and RSR = 0.54, while WEAP verification yielded R2 of 0.66–0.80 and NSE of 0.65–0.71. In the spatial analysis, 106 of 133 sub-districts (79.7%) experienced low water availability. Agriculture was the dominant sector in terms of water demand, which has increased at an average rate of 1.7% annually and accounted for 88.7% of total demand in the study period. According to the temporal analysis, the dry season was the most critical period, with peak water shortage of 99.2% in March. Overall, 105 of 133 sub-districts (78.9%) were classified as having water shortages of moderate to very high severity. These findings provide a quantitative basis for sustainable water resource management planning and drought mitigation, thus helping to enhance agricultural sustainability in Maha Sarakham Province.
No takes yet. Share an insight, caveat, or question.
Supakosol et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: