Effect analysis of WRF-Hydro model combined with different precipitation products to simulate runoff in the Qingjiang River Basin
Taking two large runoff events and three small runoff events in the Qingjiang River Basin from 2016 to 2017 as the research objects, we analyze the spatial and temporal distributions of precipitation from the three products of CMORPH satellite-gauge-radar merged precipitation product (CMPAS), China...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Torrential Rain and Disasters
2023-08-01
|
| Series: | 暴雨灾害 |
| Subjects: | |
| Online Access: | http://www.byzh.org.cn/cn/article/doi/10.12406/byzh.2022-205 |
| _version_ | 1827822380800540672 |
|---|---|
| author | Tong NIE Yufang GAO Tao PENG Yazhen WU |
| author_facet | Tong NIE Yufang GAO Tao PENG Yazhen WU |
| author_sort | Tong NIE |
| collection | DOAJ |
| description | Taking two large runoff events and three small runoff events in the Qingjiang River Basin from 2016 to 2017 as the research objects, we analyze the spatial and temporal distributions of precipitation from the three products of CMORPH satellite-gauge-radar merged precipitation product (CMPAS), China global atmospheric reanalysis product (CRA), and rain gauge precipitation (Gauge). Then, based on the characteristics of runoff events and different precipitation products, the two experiments are designed, and the runoff simulations of WRF-Hydro model driven by the precipitation data from the three precipitation products are analyzed. Finally, combined with the spatiotemporal variations of precipitation, we explore the effectiveness of the three precipitation products in the runoff simulations. The main results are as follow. (1) The rainfall centers and the rainband locations and orientations detected with the three precipitation products are similar for the five runoff events, and the temporal trends of rainfall averaged over the Qingjiang River Basin are consistent. (2) All three precipitation products can produce the runoff events in both experiments. For large runoff events, CMPAS performs best, with correlation coefficients above 0.76 and Nash efficiency coefficients above 0.63. For small runoff events, Gauge performs best, with correlation coefficients above 0.75 and Nash efficiency coefficients above 0.48. CRA has a relatively poor performance for both large and small runoff events, but its simulations are significantly improved after calibrating parameters. (3) After calibrating the parameters in the second experiment, the simulation results of runoff are improved to different extents for the peaking, rising, and falling periods of each event. For the small runoff events, compared with the rising and falling periods, the simulations driven by each precipitation product for the peaking period is significantly improved, while, for the large runoff events, the simulation results driven by the three precipitation products for each period is not significantly improved. |
| first_indexed | 2024-03-12T01:57:12Z |
| format | Article |
| id | doaj.art-6cbf1b2841a943e0a1ed8e8057756e7a |
| institution | Directory Open Access Journal |
| issn | 2097-2164 |
| language | zho |
| last_indexed | 2024-03-12T01:57:12Z |
| publishDate | 2023-08-01 |
| publisher | Editorial Office of Torrential Rain and Disasters |
| record_format | Article |
| series | 暴雨灾害 |
| spelling | doaj.art-6cbf1b2841a943e0a1ed8e8057756e7a2023-09-08T01:09:29ZzhoEditorial Office of Torrential Rain and Disasters暴雨灾害2097-21642023-08-0142439540510.12406/byzh.2022-205byzh-42-4-395Effect analysis of WRF-Hydro model combined with different precipitation products to simulate runoff in the Qingjiang River BasinTong NIE0Yufang GAO1Tao PENG2Yazhen WU3School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044China Meteorological Administration Basin Heavy Rainfall Key Laboratory/Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions, CMA, Yinchuan 750002Taking two large runoff events and three small runoff events in the Qingjiang River Basin from 2016 to 2017 as the research objects, we analyze the spatial and temporal distributions of precipitation from the three products of CMORPH satellite-gauge-radar merged precipitation product (CMPAS), China global atmospheric reanalysis product (CRA), and rain gauge precipitation (Gauge). Then, based on the characteristics of runoff events and different precipitation products, the two experiments are designed, and the runoff simulations of WRF-Hydro model driven by the precipitation data from the three precipitation products are analyzed. Finally, combined with the spatiotemporal variations of precipitation, we explore the effectiveness of the three precipitation products in the runoff simulations. The main results are as follow. (1) The rainfall centers and the rainband locations and orientations detected with the three precipitation products are similar for the five runoff events, and the temporal trends of rainfall averaged over the Qingjiang River Basin are consistent. (2) All three precipitation products can produce the runoff events in both experiments. For large runoff events, CMPAS performs best, with correlation coefficients above 0.76 and Nash efficiency coefficients above 0.63. For small runoff events, Gauge performs best, with correlation coefficients above 0.75 and Nash efficiency coefficients above 0.48. CRA has a relatively poor performance for both large and small runoff events, but its simulations are significantly improved after calibrating parameters. (3) After calibrating the parameters in the second experiment, the simulation results of runoff are improved to different extents for the peaking, rising, and falling periods of each event. For the small runoff events, compared with the rising and falling periods, the simulations driven by each precipitation product for the peaking period is significantly improved, while, for the large runoff events, the simulation results driven by the three precipitation products for each period is not significantly improved.http://www.byzh.org.cn/cn/article/doi/10.12406/byzh.2022-205satellite-gauge-radar merged precipitation productreanalysis datagauge precipitationwrf-hydro modelrunoff simulation |
| spellingShingle | Tong NIE Yufang GAO Tao PENG Yazhen WU Effect analysis of WRF-Hydro model combined with different precipitation products to simulate runoff in the Qingjiang River Basin 暴雨灾害 satellite-gauge-radar merged precipitation product reanalysis data gauge precipitation wrf-hydro model runoff simulation |
| title | Effect analysis of WRF-Hydro model combined with different precipitation products to simulate runoff in the Qingjiang River Basin |
| title_full | Effect analysis of WRF-Hydro model combined with different precipitation products to simulate runoff in the Qingjiang River Basin |
| title_fullStr | Effect analysis of WRF-Hydro model combined with different precipitation products to simulate runoff in the Qingjiang River Basin |
| title_full_unstemmed | Effect analysis of WRF-Hydro model combined with different precipitation products to simulate runoff in the Qingjiang River Basin |
| title_short | Effect analysis of WRF-Hydro model combined with different precipitation products to simulate runoff in the Qingjiang River Basin |
| title_sort | effect analysis of wrf hydro model combined with different precipitation products to simulate runoff in the qingjiang river basin |
| topic | satellite-gauge-radar merged precipitation product reanalysis data gauge precipitation wrf-hydro model runoff simulation |
| url | http://www.byzh.org.cn/cn/article/doi/10.12406/byzh.2022-205 |
| work_keys_str_mv | AT tongnie effectanalysisofwrfhydromodelcombinedwithdifferentprecipitationproductstosimulaterunoffintheqingjiangriverbasin AT yufanggao effectanalysisofwrfhydromodelcombinedwithdifferentprecipitationproductstosimulaterunoffintheqingjiangriverbasin AT taopeng effectanalysisofwrfhydromodelcombinedwithdifferentprecipitationproductstosimulaterunoffintheqingjiangriverbasin AT yazhenwu effectanalysisofwrfhydromodelcombinedwithdifferentprecipitationproductstosimulaterunoffintheqingjiangriverbasin |