Simulation and Prediction of Snowmelt Runoff in the Tangwang River Basin Based on the NEX-GDDP-CMIP6 Climate Model

In this study, the future snowmelt runoff in the chilly northeast region’s Tangwang River Basin was simulated and predicted using the SWAT model, which was built and used based on the NEX-GDDP-CMIP6 climate model. This study conducted a detailed analysis of the spatial and temporal distribution char...

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Veröffentlicht in:Water (Basel) 2024-08, Vol.16 (15), p.2082
Hauptverfasser: Zhang, Yi-Xin, Liu, Geng-Wei, Dai, Chang-Lei, Zou, Zhen-Wei, Li, Qiang
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container_start_page 2082
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creator Zhang, Yi-Xin
Liu, Geng-Wei
Dai, Chang-Lei
Zou, Zhen-Wei
Li, Qiang
description In this study, the future snowmelt runoff in the chilly northeast region’s Tangwang River Basin was simulated and predicted using the SWAT model, which was built and used based on the NEX-GDDP-CMIP6 climate model. This study conducted a detailed analysis of the spatial and temporal distribution characteristics of snowmelt runoff using high-resolution DEM, land use, and soil data, along with data from historical and future climatic scenarios. Using box plots and the Bflow digital filtering approach, this study first determined the snowmelt runoff period before precisely defining the snowmelt periods. Sensitivity analysis and parameter rate determination ensured the simulation accuracy of the SWAT model, and the correlation coefficients of the total runoff validation period and rate period were 0.75 and 0.76, with Nashiness coefficients of 0.75 for both. The correlation coefficients of the snowmelt runoff were 0.73 and 0.74, with Nashiness coefficients of 0.7 and 0.68 for both, and the model was in good agreement with the measured data. It was discovered that while temperatures indicate an increasing tendency across all future climate scenarios, precipitation is predicted to increase under the SSP2-4.5 scenario. The SSP2-4.5 scenario predicted a decreasing trend regarding runoff, while the SSP1-2.6 and SSP5-8.5 scenarios showed an increasing trend with little overall change and the SSP5-8.5 scenario even showed a decrease of 6.35%. These differences were evident in the monthly runoff simulation projections. Overall, the findings point to the possibility that, despite future climate change having a negligible effect on the hydrological cycle of the Tangwang River Basin, it may intensify and increase the frequency of extreme weather events, creating difficulties for the management of water resources and the issuing of flood warnings. For the purpose of planning water resources and studying hydrological change in this basin and other basins in cold regions, this study offers a crucial scientific foundation. An in-depth study of snowmelt runoff is of great practical significance for optimizing water resource management, rational planning of water use, spring flood prevention, and disaster mitigation and prevention, and provides valuable data support for future research on snowmelt runoff.
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This study conducted a detailed analysis of the spatial and temporal distribution characteristics of snowmelt runoff using high-resolution DEM, land use, and soil data, along with data from historical and future climatic scenarios. Using box plots and the Bflow digital filtering approach, this study first determined the snowmelt runoff period before precisely defining the snowmelt periods. Sensitivity analysis and parameter rate determination ensured the simulation accuracy of the SWAT model, and the correlation coefficients of the total runoff validation period and rate period were 0.75 and 0.76, with Nashiness coefficients of 0.75 for both. The correlation coefficients of the snowmelt runoff were 0.73 and 0.74, with Nashiness coefficients of 0.7 and 0.68 for both, and the model was in good agreement with the measured data. It was discovered that while temperatures indicate an increasing tendency across all future climate scenarios, precipitation is predicted to increase under the SSP2-4.5 scenario. The SSP2-4.5 scenario predicted a decreasing trend regarding runoff, while the SSP1-2.6 and SSP5-8.5 scenarios showed an increasing trend with little overall change and the SSP5-8.5 scenario even showed a decrease of 6.35%. These differences were evident in the monthly runoff simulation projections. Overall, the findings point to the possibility that, despite future climate change having a negligible effect on the hydrological cycle of the Tangwang River Basin, it may intensify and increase the frequency of extreme weather events, creating difficulties for the management of water resources and the issuing of flood warnings. For the purpose of planning water resources and studying hydrological change in this basin and other basins in cold regions, this study offers a crucial scientific foundation. 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Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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It was discovered that while temperatures indicate an increasing tendency across all future climate scenarios, precipitation is predicted to increase under the SSP2-4.5 scenario. The SSP2-4.5 scenario predicted a decreasing trend regarding runoff, while the SSP1-2.6 and SSP5-8.5 scenarios showed an increasing trend with little overall change and the SSP5-8.5 scenario even showed a decrease of 6.35%. These differences were evident in the monthly runoff simulation projections. Overall, the findings point to the possibility that, despite future climate change having a negligible effect on the hydrological cycle of the Tangwang River Basin, it may intensify and increase the frequency of extreme weather events, creating difficulties for the management of water resources and the issuing of flood warnings. For the purpose of planning water resources and studying hydrological change in this basin and other basins in cold regions, this study offers a crucial scientific foundation. 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Liu, Geng-Wei ; Dai, Chang-Lei ; Zou, Zhen-Wei ; Li, Qiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c254t-894f1f63d0d8e10158fc44aa646cdb8530e671395ca42bc7c6662f028f0ad4d23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accuracy</topic><topic>Analysis</topic><topic>Aquatic resources</topic><topic>basins</topic><topic>China</topic><topic>climate</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Climatic changes</topic><topic>cold</topic><topic>Datasets</topic><topic>Economic development</topic><topic>Extreme weather</topic><topic>flood control</topic><topic>Floods</topic><topic>General circulation models</topic><topic>Geospatial data</topic><topic>hydrologic cycle</topic><topic>Hydrology</topic><topic>Land use</topic><topic>Management</topic><topic>Precipitation</topic><topic>Precipitation (Meteorology)</topic><topic>prediction</topic><topic>Radiation</topic><topic>Remote sensing</topic><topic>Runoff</topic><topic>Simulation</topic><topic>snowmelt</topic><topic>soil</topic><topic>Soil and Water Assessment Tool model</topic><topic>spring</topic><topic>Temperature</topic><topic>Water</topic><topic>Water resources management</topic><topic>Water shortages</topic><topic>Water use</topic><topic>watersheds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yi-Xin</creatorcontrib><creatorcontrib>Liu, Geng-Wei</creatorcontrib><creatorcontrib>Dai, Chang-Lei</creatorcontrib><creatorcontrib>Zou, Zhen-Wei</creatorcontrib><creatorcontrib>Li, Qiang</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yi-Xin</au><au>Liu, Geng-Wei</au><au>Dai, Chang-Lei</au><au>Zou, Zhen-Wei</au><au>Li, Qiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulation and Prediction of Snowmelt Runoff in the Tangwang River Basin Based on the NEX-GDDP-CMIP6 Climate Model</atitle><jtitle>Water (Basel)</jtitle><date>2024-08-01</date><risdate>2024</risdate><volume>16</volume><issue>15</issue><spage>2082</spage><pages>2082-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>In this study, the future snowmelt runoff in the chilly northeast region’s Tangwang River Basin was simulated and predicted using the SWAT model, which was built and used based on the NEX-GDDP-CMIP6 climate model. This study conducted a detailed analysis of the spatial and temporal distribution characteristics of snowmelt runoff using high-resolution DEM, land use, and soil data, along with data from historical and future climatic scenarios. Using box plots and the Bflow digital filtering approach, this study first determined the snowmelt runoff period before precisely defining the snowmelt periods. Sensitivity analysis and parameter rate determination ensured the simulation accuracy of the SWAT model, and the correlation coefficients of the total runoff validation period and rate period were 0.75 and 0.76, with Nashiness coefficients of 0.75 for both. The correlation coefficients of the snowmelt runoff were 0.73 and 0.74, with Nashiness coefficients of 0.7 and 0.68 for both, and the model was in good agreement with the measured data. It was discovered that while temperatures indicate an increasing tendency across all future climate scenarios, precipitation is predicted to increase under the SSP2-4.5 scenario. The SSP2-4.5 scenario predicted a decreasing trend regarding runoff, while the SSP1-2.6 and SSP5-8.5 scenarios showed an increasing trend with little overall change and the SSP5-8.5 scenario even showed a decrease of 6.35%. These differences were evident in the monthly runoff simulation projections. Overall, the findings point to the possibility that, despite future climate change having a negligible effect on the hydrological cycle of the Tangwang River Basin, it may intensify and increase the frequency of extreme weather events, creating difficulties for the management of water resources and the issuing of flood warnings. For the purpose of planning water resources and studying hydrological change in this basin and other basins in cold regions, this study offers a crucial scientific foundation. An in-depth study of snowmelt runoff is of great practical significance for optimizing water resource management, rational planning of water use, spring flood prevention, and disaster mitigation and prevention, and provides valuable data support for future research on snowmelt runoff.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w16152082</doi><oa>free_for_read</oa></addata></record>
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subjects Accuracy
Analysis
Aquatic resources
basins
China
climate
Climate change
Climate models
Climatic changes
cold
Datasets
Economic development
Extreme weather
flood control
Floods
General circulation models
Geospatial data
hydrologic cycle
Hydrology
Land use
Management
Precipitation
Precipitation (Meteorology)
prediction
Radiation
Remote sensing
Runoff
Simulation
snowmelt
soil
Soil and Water Assessment Tool model
spring
Temperature
Water
Water resources management
Water shortages
Water use
watersheds
title Simulation and Prediction of Snowmelt Runoff in the Tangwang River Basin Based on the NEX-GDDP-CMIP6 Climate Model
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