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

Study region: Haihe Basin (HB), North China. Study focus: Studying the impact of extreme precipitation on watershed hydrological factors plays a crucial role in water resource management, climate adaptation, and disaster resilience. An improved Soil and Water Assessment Tool (SWAT) was employed to a...

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Main Authors: Lili Tan, Junyu Qi, Gary W. Marek, Xueliang Zhang, Jianing Ge, Danfeng Sun, Baogui Li, Puyu Feng, De Li Liu, Baoguo Li, Raghavan Srinivasan, Yong Chen
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Journal of Hydrology: Regional Studies
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Online Access:http://www.sciencedirect.com/science/article/pii/S221458182500059X
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author Lili Tan
Junyu Qi
Gary W. Marek
Xueliang Zhang
Jianing Ge
Danfeng Sun
Baogui Li
Puyu Feng
De Li Liu
Baoguo Li
Raghavan Srinivasan
Yong Chen
author_facet Lili Tan
Junyu Qi
Gary W. Marek
Xueliang Zhang
Jianing Ge
Danfeng Sun
Baogui Li
Puyu Feng
De Li Liu
Baoguo Li
Raghavan Srinivasan
Yong Chen
author_sort Lili Tan
collection DOAJ
description Study region: Haihe Basin (HB), North China. Study focus: Studying the impact of extreme precipitation on watershed hydrological factors plays a crucial role in water resource management, climate adaptation, and disaster resilience. An improved Soil and Water Assessment Tool (SWAT) was employed to assess the impact of extreme precipitation indices (EPIs) on temporal and spatial variations in hydrological factors in the 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). New hydrological insights for the region: The EPIs with the greatest contribution rates to precipitation, water yield, and percolation in the historical period were R20 (32.1 %), R50 (14.3 %), and R20 (29.0 %), respectively, for the entire basin. During the historical period, there were more occurrences of extreme precipitation events in the plain area 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 %) and percolation (36.3 %) in the HB. Furthermore, the number of days with rainfall from 20 to 50 mm d−1 and those exceeding 50 mm d−1 increased in the future period relative to the historical period. The results of this study provide a reference for understanding the spatiotemporal distribution pattern of extreme precipitation in the HB and for relevant departments to formulate response strategies.
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spelling doaj-art-4dc357a76a2342c4a35dab49ab3ecec12025-08-20T02:57:44ZengElsevierJournal of Hydrology: Regional Studies2214-58182025-04-015810223510.1016/j.ejrh.2025.102235Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT modelLili Tan0Junyu Qi1Gary W. Marek2Xueliang Zhang3Jianing Ge4Danfeng Sun5Baogui Li6Puyu Feng7De Li Liu8Baoguo Li9Raghavan Srinivasan10Yong Chen11College of Hydraulic and Civil Engineering, Ludong University, Yantai 264025, ChinaEarth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USAUSDA-ARS Conservation and Production Research Laboratory, Bushland, TX 79012, USACollege of Land Science and Technology, China Agricultural University, Beijing 100193, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Arable Land Conservation in North China, Ministry of Agriculture and Rural Affairs, Beijing 100193, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Arable Land Conservation in North China, Ministry of Agriculture and Rural Affairs, Beijing 100193, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Arable Land Conservation in North China, Ministry of Agriculture and Rural Affairs, Beijing 100193, ChinaNSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia; Climate Change Research Centre, University of New South Wales, Sydney 2052, AustraliaCollege of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Arable Land Conservation in North China, Ministry of Agriculture and Rural Affairs, Beijing 100193, ChinaDepartment of Ecosystem Science and Management, Texas A&M University, TX 77843, USACollege of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Arable Land Conservation in North China, Ministry of Agriculture and Rural Affairs, Beijing 100193, China; Corresponding author at: College of Land Science and Technology, China Agricultural University, Beijing 100193, China.Study region: Haihe Basin (HB), North China. Study focus: Studying the impact of extreme precipitation on watershed hydrological factors plays a crucial role in water resource management, climate adaptation, and disaster resilience. An improved Soil and Water Assessment Tool (SWAT) was employed to assess the impact of extreme precipitation indices (EPIs) on temporal and spatial variations in hydrological factors in the 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). New hydrological insights for the region: The EPIs with the greatest contribution rates to precipitation, water yield, and percolation in the historical period were R20 (32.1 %), R50 (14.3 %), and R20 (29.0 %), respectively, for the entire basin. During the historical period, there were more occurrences of extreme precipitation events in the plain area 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 %) and percolation (36.3 %) in the HB. Furthermore, the number of days with rainfall from 20 to 50 mm d−1 and those exceeding 50 mm d−1 increased in the future period relative to the historical period. The results of this study provide a reference for understanding the spatiotemporal distribution pattern of extreme precipitation in the HB and for relevant departments to formulate response strategies.http://www.sciencedirect.com/science/article/pii/S221458182500059XExtreme precipitation indicesContribution rateBasin scaleHydrological factorsSWATGCMs
spellingShingle Lili Tan
Junyu Qi
Gary W. Marek
Xueliang Zhang
Jianing Ge
Danfeng Sun
Baogui Li
Puyu Feng
De Li Liu
Baoguo Li
Raghavan Srinivasan
Yong Chen
Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT model
Journal of Hydrology: Regional Studies
Extreme precipitation indices
Contribution rate
Basin scale
Hydrological factors
SWAT
GCMs
title Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT model
title_full Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT model
title_fullStr Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT model
title_full_unstemmed Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT model
title_short Assessing the impacts of extreme precipitation projections on Haihe Basin hydrology using an enhanced SWAT model
title_sort assessing the impacts of extreme precipitation projections on haihe basin hydrology using an enhanced swat model
topic Extreme precipitation indices
Contribution rate
Basin scale
Hydrological factors
SWAT
GCMs
url http://www.sciencedirect.com/science/article/pii/S221458182500059X
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