CMADS and CFSR Data-Driven SWAT Modeling for Impacts of Climate and Land-Use Change on Runoff

Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soi...

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Published inWater (Basel) Vol. 15; no. 18; p. 3240
Main Authors Du, Bailin, Wu, Lei, Ruan, Bingnan, Xu, Liujia, Liu, Shuai
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2023
Subjects
agricultural land
Aquatic resources
Arid regions
China
climate
Climate change
data collection
Datasets
forest land
Geospatial data
Global temperature changes
Hydrology
Land use
land use change
Management
Precipitation
Precipitation (Meteorology)
Runoff
Software
Soil and Water Assessment Tool model
Soil erosion
temperature
Water
Water conservation
Watersheds
China
Loess Plateau
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Abstract Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soil and Water Assessment Tool (SWAT) model in conjunction with spatial interpolation techniques to evaluate the accuracy of Climate Forecast System Reanalysis (CFSR), China Meteorological Assimilation Driven Dataset (CMADS), and observation (OBS) in runoff simulations, and configured various scenarios using the Patch-generating Land-use Simulation (PLUS) model to analyze effects of climate and land-use changes on runoff in the Jing River Basin from 1999 to 2018. Results demonstrated the superior performance of the CMADS+SWAT model compared to than CFSR+SWAT model, as the latter underestimated peak runoff. Changes in precipitation had a stronger impact on runoff than temperature, with increased flow from farmland and strong interception effects from forestland. Integrated climate and land-use changes led to an average annual runoff reduction of 1.24 m3/s (I2), primarily attributed to climate change (1.12 m3/s, I3), with a small contribution from land-use change (0.12 m3/s, I4). CMADS exhibited robust applicability under diverse scenarios, effectively enhancing runoff simulation accuracy. The findings provide invaluable guidance for water resources management in semi-arid regions.
AbstractList Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soil and Water Assessment Tool (SWAT) model in conjunction with spatial interpolation techniques to evaluate the accuracy of Climate Forecast System Reanalysis (CFSR), China Meteorological Assimilation Driven Dataset (CMADS), and observation (OBS) in runoff simulations, and configured various scenarios using the Patch-generating Land-use Simulation (PLUS) model to analyze effects of climate and land-use changes on runoff in the Jing River Basin from 1999 to 2018. Results demonstrated the superior performance of the CMADS+SWAT model compared to than CFSR+SWAT model, as the latter underestimated peak runoff. Changes in precipitation had a stronger impact on runoff than temperature, with increased flow from farmland and strong interception effects from forestland. Integrated climate and land-use changes led to an average annual runoff reduction of 1.24 m3/s (I2), primarily attributed to climate change (1.12 m3/s, I3), with a small contribution from land-use change (0.12 m3/s, I4). CMADS exhibited robust applicability under diverse scenarios, effectively enhancing runoff simulation accuracy. The findings provide invaluable guidance for water resources management in semi-arid regions.
Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soil and Water Assessment Tool (SWAT) model in conjunction with spatial interpolation techniques to evaluate the accuracy of Climate Forecast System Reanalysis (CFSR), China Meteorological Assimilation Driven Dataset (CMADS), and observation (OBS) in runoff simulations, and configured various scenarios using the Patch-generating Land-use Simulation (PLUS) model to analyze effects of climate and land-use changes on runoff in the Jing River Basin from 1999 to 2018. Results demonstrated the superior performance of the CMADS+SWAT model compared to than CFSR+SWAT model, as the latter underestimated peak runoff. Changes in precipitation had a stronger impact on runoff than temperature, with increased flow from farmland and strong interception effects from forestland. Integrated climate and land-use changes led to an average annual runoff reduction of 1.24 m[sup.3]/s (I[sub.2]), primarily attributed to climate change (1.12 m[sup.3]/s, I[sub.3]), with a small contribution from land-use change (0.12 m[sup.3]/s, I[sub.4]). CMADS exhibited robust applicability under diverse scenarios, effectively enhancing runoff simulation accuracy. The findings provide invaluable guidance for water resources management in semi-arid regions.
Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soil and Water Assessment Tool (SWAT) model in conjunction with spatial interpolation techniques to evaluate the accuracy of Climate Forecast System Reanalysis (CFSR), China Meteorological Assimilation Driven Dataset (CMADS), and observation (OBS) in runoff simulations, and configured various scenarios using the Patch-generating Land-use Simulation (PLUS) model to analyze effects of climate and land-use changes on runoff in the Jing River Basin from 1999 to 2018. Results demonstrated the superior performance of the CMADS+SWAT model compared to than CFSR+SWAT model, as the latter underestimated peak runoff. Changes in precipitation had a stronger impact on runoff than temperature, with increased flow from farmland and strong interception effects from forestland. Integrated climate and land-use changes led to an average annual runoff reduction of 1.24 m³/s (I₂), primarily attributed to climate change (1.12 m³/s, I₃), with a small contribution from land-use change (0.12 m³/s, I₄). CMADS exhibited robust applicability under diverse scenarios, effectively enhancing runoff simulation accuracy. The findings provide invaluable guidance for water resources management in semi-arid regions.
Audience Academic
Author Du, Bailin
Ruan, Bingnan
Xu, Liujia
Liu, Shuai
Wu, Lei
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Snippet Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and...
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SubjectTerms agricultural land
Aquatic resources
Arid regions
China
climate
Climate change
data collection
Datasets
forest land
Geospatial data
Global temperature changes
Hydrology
Land use
land use change
Management
Precipitation
Precipitation (Meteorology)
Runoff
Software
Soil and Water Assessment Tool model
Soil erosion
temperature
Water
Water conservation
Watersheds
Title CMADS and CFSR Data-Driven SWAT Modeling for Impacts of Climate and Land-Use Change on Runoff
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Volume 15
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