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Pouya Hosseinzadeh, Ayman Nassar, Soukaina Filali Boubrahimi and Shah Muhammad Hamdi
Streamflow prediction plays a vital role in water resources planning in order to understand the dramatic change of climatic and hydrologic variables over different time scales. In this study, we used machine learning (ML)-based prediction models, includi...
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Yizhi Wang, Jia Liu, Lin Xu, Fuliang Yu and Shanjun Zhang
Streamflow modelling is one of the most important elements for the management of water resources and flood control in the context of future climate change. With the advancement of numerical weather prediction and modern detection technologies, more and m...
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Rodrigo Valdés-Pineda, Juan B. Valdés, Sungwook Wi, Aleix Serrat-Capdevila and Tirthankar Roy
The combination of Hydrological Models and high-resolution Satellite Precipitation Products (SPPs) or regional Climatological Models (RCMs), has provided the means to establish baselines for the quantification, propagation, and reduction in hydrological ...
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Shanhu Jiang, Shuya Liu, Liliang Ren, Bin Yong, Linqi Zhang, Menghao Wang, Yujie Lu and Yingqing He
Satellite precipitation products (SPPs) are critical data sources for hydrological prediction and extreme event monitoring, especially for ungauged basins. This study conducted a comprehensive hydrological evaluation of six mainstream SPPs (i.e., TMPA 3B...
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Mou Leong Tan, Philip W. Gassman and Arthur P. Cracknell
Gridded climate products (GCPs) provide a potential source for representing weather in remote, poor quality or short-term observation regions. The accuracy of three long-term GCPs (Asian Precipitation?Highly-Resolved Observational Data Integration toward...
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Marc Vis, Rodney Knight, Sandra Pool, William Wolfe and Jan Seibert
Quantification of streamflow characteristics in ungauged catchments remains a challenge. Hydrological modeling is often used to derive flow time series and to calculate streamflow characteristics for subsequent applications that may differ from those env...
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