Hydrometeorological Insights into the Forecasting Performance of Multi-Source Weather over a Typical Hill-Karst Basin, Southwest China

Author:

Mo Chongxun1234,Wan Xiaoyu1234,Lei Xingbi1234ORCID,Chen Xinru5,Ma Rongyong1234,Huang Yi6,Sun Guikai1234

Affiliation:

1. Key Laboratory of Disaster Prevention and Structural Safety of the Ministry of Education, Nanning 530004, China

2. College of Architecture and Civil Engineering, Guangxi University, Nanning 530004, China

3. Guangxi Provincial Engineering Research Center of Water Security and Intelligent Control for Karst Region, Guangxi University, Nanning 530004, China

4. Guangxi Key Laboratory of Disaster Prevention and Engineering Safety, Guangxi University, Nanning 530004, China

5. Shanghai Nuclear Engineering Research & Design Institute Co., Ltd., Shanghai 310000, China

6. Guangxi Water & Power Design Institute Co., Ltd., Nanning 530023, China

Abstract

Reliable precipitation forecasts are essential for weather-related disaster prevention and water resource management. Multi-source weather (MSWX), a recently released ensemble meteorological dataset, has provided new opportunities with open access, fine horizontal resolution (0.1°), and a lead time of up to seven months. However, few studies have comprehensively evaluated the performance of MSWX in terms of precipitation forecasting and hydrological modeling, particularly in hill-karst basins. The key concerns and challenges are how precipitation prediction performance relates to elevation and how to evaluate the hydrologic performance of MSWX in hill-karst regions with complex geographic heterogeneity. To address these concerns and challenges, this study presents a comprehensive evaluation of MSWX at the Chengbi River Basin (Southwest China) based on multiple statistical metrics, the Soil and Water Assessment Tool (SWAT), and a multi-site calibration strategy. The results show that all ensemble members of MSWX overestimated the number of precipitation events and tended to have lower accuracies at higher altitudes. Meanwhile, the error did not significantly increase with the increased lead time. The “00” member exhibited the best performance among the MSWX members. In addition, the multi-site calibration-enhanced SWAT had reliable performance (Average Nash–Sutcliffe value = 0.73) and hence can be used for hydrological evaluation of MSWX. Furthermore, MSWX achieved satisfactory performance (Nash–Sutcliffe value > 0) in 22% of runoff event predictions, but the error increased with longer lead times. This study gives some new hydrometeorological insights into the performance of MSWX, which can provide feedback on its development and applications.

Funder

National Natural Science Foundation of China

Guangxi Water Resource Technology Promotion Foundation

Publisher

MDPI AG

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