The continuous ecological management of the Loess Plateau is known throughout the world for two strategies: the integrated soil conservation project that began in the 1970s, and the “Grain for Green” project that began in the 1990s. Six sub-catchments nested in the Beiluo River basin were selected to investigate streamflow regime variations during the two project periods. The annual streamflow ...

[1] In the past few years sequential data assimilation (SDA) methods have emerged as the best possible method at hand to properly treat all sources of error in hydrological modeling. However, very few studies have actually implemented SDA methods using realistic input error models for precipitation. In this study we use particle filtering as a SDA method to propagate input errors through a conc...

Most current quantitative precipitation nowcasting (QPN) methodologies are deterministic in nature and convey little realistic information regarding the uncertainty in the forecast. For flood and streamflow forecasting applications it is important to understand and accurately represent this uncertainty (Smith and Austin, 2000). This will allow a greater deal of confidence in the use of precipit...

[1] There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently ...

High-precision streamflow forecasting has important implications for the water resources efficient planning and rational allocation. Recently, data-driven models represented by deep learning have become a research hotspot. However, existing study less on application of attention mechanism in prediction. This proposes novel model based gated recurrent units mechanism, GRU-AT. The automatically e...

Precise streamflow prediction is crucial in the optimization of distribution water resources. This study develops machine learning models by integrating recurrent gate unit (GRU) with bacterial foraging (BFO), gray wolf optimizer (GWO), and human group (HGO) to forecast Tra Khuc River, Vietnam. For this purpose, time series daily rainfall river flow at Son Giang station from 2000 2020 were empl...

Quantifying the isolated and integrated impacts of land use (LU) and climate change on streamflow is challenging as well as crucial to optimally manage water resources in river basins. This paper presents a simple hydrologic modeling-based approach to segregate the impacts of land use and climate change on the streamflow of a river basin. The upper Ganga basin (UGB) in India is selected as the ...