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Chenkai Cai, Yi?an Hua, Huibin Yang, Jing Wang, Changhuai Wu, Helong Wang and Xinyi Shen
Ecological droughts in rivers, as a new type of drought, have been greatly discussed in the past decade. Although various studies have been conducted to identify and evaluate ecological droughts in rivers from different indices, a forecast model for this...
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Baydaa Abdul Kareem, Salah L. Zubaidi, Hussein Mohammed Ridha, Nadhir Al-Ansari and Nabeel Saleem Saad Al-Bdairi
Accurate streamflow prediction is significant when developing water resource management and planning, forecasting floods, and mitigating flood damage. This research developed a novel methodology that involves data pre-processing and an artificial neural ...
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Durga Sharma, Swagat Patnaik, Basudev Biswal and John T. Reager
Despite the fact that streamflow occurs mainly due to depletion of storage, our knowledge on how a drainage basin stores and releases water is very limited due to measurement limitations. A window of opportunity, however, is provided to us by GRACE (Grav...
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Hua Zhou, Yang Luo, Guang Zhou, Jian Yu, Sher Shah, Shengwang Meng and Qijing Liu
Subtropical forest productivity is significantly affected by both natural disturbances (local and regional climate changes) and anthropogenic activities (harvesting and planting). Monthly measures of forest aboveground productivity from natural forests (...
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Haibo Chu, Jiahua Wei and Jun Qiu
For the inherent characteristics of a raw streamflow times series and the complicated relationship between multi-scale predictors and streamflow, monthly streamflow forecasting is very difficult. In this paper, an method was proposed integrating the ense...
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Jianzhong Zhou, Tian Peng, Chu Zhang and Na Sun
This paper introduces three artificial neural network (ANN) architectures for monthly streamflow forecasting: a radial basis function network, an extreme learning machine, and the Elman network. Three ensemble techniques, a simple average ensemble, a wei...
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Fernando Delgado-Ramos and Carmen Hervás-Gámez
Accurately forecasting streamflow values is essential to achieve an efficient, integrated water resources management strategy and to provide consistent support to water decision-makers. We present a simple, low-cost, and robust approach for forecasting m...
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Lei Zou, Jun Xia, Like Ning, Dunxian She and Chesheng Zhan
Long records (1960?2013) of monthly streamflow observations from 8 hydrological stations in the East Asian monsoon region are modeled using a nonstationarity framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Mod...
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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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Muhammad Tayyab, Ijaz Ahmad, Na Sun, Jianzhong Zhou and Xiaohua Dong
Consistent streamflow forecasts play a fundamental part in flood risk mitigation. Population increase and water cycle intensification are extending not only globally but also among Pakistan’s water resources. The frequency of floods has increased i...
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