Articles | Volume 23, issue 8
https://doi.org/10.5194/hess-23-3405-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-3405-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improving hydrological projection performance under contrasting climatic conditions using spatial coherence through a hierarchical Bayesian regression framework
Zhengke Pan
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City
Construction, Wuhan University, Wuhan, Hubei, China
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City
Construction, Wuhan University, Wuhan, Hubei, China
Shida Gao
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City
Construction, Wuhan University, Wuhan, Hubei, China
Jun Xia
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City
Construction, Wuhan University, Wuhan, Hubei, China
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Jie Chen
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City
Construction, Wuhan University, Wuhan, Hubei, China
Lei Cheng
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City
Construction, Wuhan University, Wuhan, Hubei, China
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Cited
18 citations as recorded by crossref.
- Combined Effects of Land Use/Cover Change and Climate Change on Runoff in the Jinghe River Basin, China Y. Liu et al. 10.3390/atmos14081237
- Analysis of Characteristics and Driving Factors of Land-Use Changes in the Tarim River Basin from 1990 to 2018 Y. Wang et al. 10.3390/su131810263
- Optimization of Spatial Pattern of Land Use: Progress, Frontiers, and Prospects C. Liu et al. 10.3390/ijerph19105805
- Runoff Prediction of Tunxi Basin under Projected Climate Changes Based on Lumped Hydrological Models with Various Model Parameter Optimization Strategies B. Yan et al. 10.3390/su16166897
- Investigating Impacts of Climate Change on Runoff from the Qinhuai River by Using the SWAT Model and CMIP6 Scenarios J. Sun et al. 10.3390/w14111778
- Synergistic impact of climate and land use land cover change dynamics on the hydrological regime of Loktak Lake catchment under CMIP6 scenarios V. Anand et al. 10.1016/j.ejrh.2024.101851
- Combining Downscaled Global Climate Model Data with SWAT to Assess Regional Climate Change Properties and Hydrological Responses T. Yang et al. 10.1007/s12205-023-2211-5
- Identification of Time-Varying Conceptual Hydrological Model Parameters with Differentiable Parameter Learning X. Lian et al. 10.3390/w16060896
- Temporal variation scale of the catchment water storage capacity of 91 MOPEX catchments J. Tian et al. 10.1016/j.ejrh.2022.101236
- Diagnosing structural deficiencies of a hydrological model by time-varying parameters L. Zhou et al. 10.1016/j.jhydrol.2021.127305
- A Differentiable Hydrology Approach for Modeling With Time‐Varying Parameters C. Krapu & M. Borsuk 10.1029/2021WR031377
- Response of active catchment water storage capacity to a prolonged meteorological drought and asymptotic climate variation J. Tian et al. 10.5194/hess-26-4853-2022
- Characteristics and Matching Analysis of Water and Soil Resources Development and Utilization in Hotan Area, Xinjiang 永. 徐 10.12677/JWRR.2023.121004
- Improving Efficiency of Hydrological Prediction Based on Meteorological Classification: A Case Study of GR4J Model X. Wei et al. 10.3390/w13182546
- RCCC-WBM Model for Calculating the Impact of Abrupt Temperature Change and Warming Hiatus on Surface Runoff in China X. Huang et al. 10.3390/w15142522
- Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework L. Zhou et al. 10.1016/j.jhydrol.2022.128843
- A multi‐objective approach to select hydrological models and constrain structural uncertainties for climate impact assessments D. Saavedra et al. 10.1002/hyp.14446
- The influence of a prolonged meteorological drought on catchment water storage capacity: a hydrological-model perspective Z. Pan et al. 10.5194/hess-24-4369-2020
18 citations as recorded by crossref.
- Combined Effects of Land Use/Cover Change and Climate Change on Runoff in the Jinghe River Basin, China Y. Liu et al. 10.3390/atmos14081237
- Analysis of Characteristics and Driving Factors of Land-Use Changes in the Tarim River Basin from 1990 to 2018 Y. Wang et al. 10.3390/su131810263
- Optimization of Spatial Pattern of Land Use: Progress, Frontiers, and Prospects C. Liu et al. 10.3390/ijerph19105805
- Runoff Prediction of Tunxi Basin under Projected Climate Changes Based on Lumped Hydrological Models with Various Model Parameter Optimization Strategies B. Yan et al. 10.3390/su16166897
- Investigating Impacts of Climate Change on Runoff from the Qinhuai River by Using the SWAT Model and CMIP6 Scenarios J. Sun et al. 10.3390/w14111778
- Synergistic impact of climate and land use land cover change dynamics on the hydrological regime of Loktak Lake catchment under CMIP6 scenarios V. Anand et al. 10.1016/j.ejrh.2024.101851
- Combining Downscaled Global Climate Model Data with SWAT to Assess Regional Climate Change Properties and Hydrological Responses T. Yang et al. 10.1007/s12205-023-2211-5
- Identification of Time-Varying Conceptual Hydrological Model Parameters with Differentiable Parameter Learning X. Lian et al. 10.3390/w16060896
- Temporal variation scale of the catchment water storage capacity of 91 MOPEX catchments J. Tian et al. 10.1016/j.ejrh.2022.101236
- Diagnosing structural deficiencies of a hydrological model by time-varying parameters L. Zhou et al. 10.1016/j.jhydrol.2021.127305
- A Differentiable Hydrology Approach for Modeling With Time‐Varying Parameters C. Krapu & M. Borsuk 10.1029/2021WR031377
- Response of active catchment water storage capacity to a prolonged meteorological drought and asymptotic climate variation J. Tian et al. 10.5194/hess-26-4853-2022
- Characteristics and Matching Analysis of Water and Soil Resources Development and Utilization in Hotan Area, Xinjiang 永. 徐 10.12677/JWRR.2023.121004
- Improving Efficiency of Hydrological Prediction Based on Meteorological Classification: A Case Study of GR4J Model X. Wei et al. 10.3390/w13182546
- RCCC-WBM Model for Calculating the Impact of Abrupt Temperature Change and Warming Hiatus on Surface Runoff in China X. Huang et al. 10.3390/w15142522
- Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework L. Zhou et al. 10.1016/j.jhydrol.2022.128843
- A multi‐objective approach to select hydrological models and constrain structural uncertainties for climate impact assessments D. Saavedra et al. 10.1002/hyp.14446
- The influence of a prolonged meteorological drought on catchment water storage capacity: a hydrological-model perspective Z. Pan et al. 10.5194/hess-24-4369-2020
Latest update: 22 Nov 2024
Short summary
Understanding the projection performance of hydrological models under contrasting climatic conditions supports robust decision making, which highlights the need to adopt time-varying parameters in hydrological modeling to reduce performance degradation. This study improves our understanding of the spatial coherence of time-varying parameters, which will help improve the projection performance under differing climatic conditions.
Understanding the projection performance of hydrological models under contrasting climatic...