Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT model

Authors: TAN, LILI - China Agricultural University; QI, JUNYU - University Of Maryland; Marek, Gary; ZHANG, XUELIANG - China Agricultural University; GE, JIANING - China Agricultural University; SUN, DANFENG - China Agricultural University; LI, BAOGUI - China Agricultural University; FENG, PUYU - China Agricultural University; LIU, DE LI - Wagga Wagga Agricultural Institute; LI, BAOGUO - China Agricultural University; SRINIVASAN, RAGHAVAN - Texas A&M University; CHEN, YONG - China Agricultural University

Submitted to: Journal of Hydrology: Regional Studies
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/7/2025
Publication Date: 2/17/2025
Citation: Tan, L., Qi, J., Marek, G.W., Zhang, X., Ge, J., Sun, D., Li, B., Feng, P., Liu, D., Li, B., Srinivasan, R., Chen, Y. 2025. Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT model. Journal of Hydrology: Regional Studies. 58. Article 102235. https://doi.org/10.1016/j.ejrh.2025.102235.
DOI: https://doi.org/10.1016/j.ejrh.2025.102235

Interpretive Summary: Climate change caused by global warming has been attributed to more frequent occurrences of extreme precipitation events around the world. While increased rainfall can be beneficial, large intensity events often lead to excessive runoff and flooding. Knowledge of anticipated magnitude and frequency of future rainfall may help in resource management and disaster planning for regional landscapes. Computer simulation modeling of surface and groundwater hydrology may provide insight for the development of alternate land management strategies that reduce runoff and promote groundwater conservation. Researchers from USDA-ARS Bushland and university partners from the U.S., Australia, and China used a modified Soil and Water Assessment Tool (SWAT) model along with extreme precipitation indices (EPI) to simulate temporal and spatial variations in hydrological process for the Haihe Basin (HB) in China. Simulations results included increased precipitation, evapotranspiration, and percolation overall as compared to historical conditions. However, EPI for heavy rainfall events between 20-50 mm contributed most to increases in precipitation and percolation. These findings provide reference for understanding the changes in hydrological processes in the HB under extreme precipitation conditions and for the formulation of water resource management, disaster prevention, and mitigation policies.

Technical Abstract: The climate change caused by global warming has led to more frequent occurrences of extreme precipitation events around the world. Studying the impact of extreme precipitation on watershed hydrological processes plays a crucial role in water resource management, climate adaptation, and disaster resilience. An improved SWAT model was utilized to assess the impact of extreme precipitation indices (EPIs) on temporal and spatial variations in hydrological processes in the Haihe Basin (HB), China. Five EPIs were identified in this study, including R10 (moderate rain), R20 (heavy rain), R50 (torrential rain), R95p (95th percentile of precipitation), and R99p (99th percentile of precipitation). The results showed an increase in precipitation, actual evapotranspiration (ETa), water yield, and percolation under EPIs compared with average conditions during the historical period (1989-2018) in the HB. The EPIs with the greatest contribution rates to precipitation, water yield, and percolation in the historical period were R20 (32.1 percent), R50 (14.3 percent), and R20 (29.0 percent), respectively, for the entire basin. During the historical period, there were more occurrences of extreme precipitation events in the plain area of the HB compared to the mountainous area. In the plain area, rainfall was beneficial for replenishing groundwater when daily precipitation exceeded 50 mm. Over the entire future period (2041-2100), R50 contributed the greatest water yield (18.4 percent) and percolation (36.3 percent) in the HB. It also forecasted an increase in rainfall intensity under R95p and R99p conditions in the future period compared to the historical period. Furthermore, the number of days with rainfall between 20 mm per day and 50 mm per day and those exceeding 50 mm per day increased in the future period relative to the historical period. The results of this study provide reference for understanding the changes in hydrological processes in the HB under extreme precipitation conditions and for the formulation of water resource management, disaster prevention, and mitigation policies.