|
|
|
|
|
Yik Kang Ang, Amin Talei, Izni Zahidi and Ali Rashidi
Neuro-fuzzy systems (NFS), as part of artificial intelligence (AI) techniques, have become popular in modeling and forecasting applications in many fields in the past few decades. NFS are powerful tools for mapping complex associations between inputs and...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sergei Borsch, Yuri Simonov, Andrei Khristoforov, Natalia Semenova, Valeria Koliy, Ekaterina Ryseva, Vladimir Krovotyntsev and Victoria Derugina
This paper presents a method of hydrograph extrapolation, intended for simple and efficient streamflow forecasting with up to 10 days lead time. The forecast of discharges or water levels is expressed by a linear formula depending on their values on the ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Aifeng Zhai, Guohua Fan, Xiaowen Ding and Guohe Huang
The development of an efficient and accurate hydrological forecasting model is essential for water management and flood control. In this study, the ensemble model was applied to predict the daily discharge; it not only could enhance the algorithm and imp...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lili Liang, Yufeng Hu, Zhiwu Liu, Yuntao Ye, Kuang Li, Kexin Liu, Haiqing Xu and Xiquan Liu
The lumped hydrological model and empirical model have the problems of low accuracy and short forecasting period in real-time flood forecasting of small- and medium-sized rivers in a mountainous watershed. The sharing of underlying surface data such as h...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tiziana De Filippis, Leandro Rocchi, Giovanni Massazza, Alessandro Pezzoli, Maurizio Rosso, Mohamed Housseini Ibrahim and Vieri Tarchiani
Emerging hydrological services provide stakeholders and political authorities with useful and reliable information to support the decision-making process and develop flood risk management strategies. Most of these services adopt the paradigm of open data...
ver más
|
|
|
|
|
|
|
|
|
|
|
Vsevolod Moreido, Boris Gartsman, Dimitri P. Solomatine and Zoya Suchilina
With more machine learning methods being involved in social and environmental research activities, we are addressing the role of available information for model training in model performance. We tested the abilities of several machine learning models for...
ver más
|
|
|
|
|
|
|
|
|
|
|
Paul Muñoz, Johanna Orellana-Alvear, Jörg Bendix, Jan Feyen and Rolando Célleri
Worldwide, machine learning (ML) is increasingly being used for developing flood early warning systems (FEWSs). However, previous studies have not focused on establishing a methodology for determining the most efficient ML technique. We assessed FEWSs wi...
ver más
|
|
|
|
|
|
|
|
|
|
|
|
Larissa Zaira Rafael Rolim and Francisco de Assis de Souza Filho
Improved water resource management relies on accurate analyses of the past dynamics of hydrological variables. The presence of low-frequency structures in hydrologic time series is an important feature. It can modify the probability of extreme events occ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ye Tian, Yue-Ping Xu, Zongliang Yang, Guoqing Wang and Qian Zhu
This study applied a GR4J model in the Xiangjiang and Qujiang River basins for rainfall-runoff simulation. Four recurrent neural networks (RNNs)?the Elman recurrent neural network (ERNN), echo state network (ESN), nonlinear autoregressive exogenous input...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kuang Li, Guangyuan Kan, Liuqian Ding, Qianjin Dong, Kexin Liu and Lili Liang
The influence of initial state variables on flood forecasting accuracy by using conceptual hydrological models is analyzed in this paper and a novel flood forecasting method based on correction of initial state variables is proposed. The new method is ab...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andrei Bugaets, Boris Gartsman, Alexander Gelfan, Yury Motovilov, Oleg Sokolov, Leonid Gonchukov, Andrei Kalugin, Vsevolod Moreido, Zoya Suchilina and Evgeniya Fingert
This paper considers the main principles and technologies used in developing the operational modeling system for the Ussuri River Basin of 24,400 km2 based on the automated system of hydrological monitoring and data management (ASHM), the physical-mathem...
ver más
|
|
|
|
|
|
|
|
|
|
|
Oreste Terranova, Stefano Luigi Gariano, Pasquale Iaquinta, Valeria Lupiano, Valeria Rago and Giulio Iovine
GASAKe is an empirical-hydrological model aimed at forecasting the time of occurrence of landslides. Activations can be predicted of either single landslides or sets of slope movements of the same type in a homogeneous environment. The model requires a r...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andrei Bugaets, Boris Gartsman, Alexander Gelfan, Yury Motovilov, Oleg Sokolov, Leonid Gonchukov, Andrei Kalugin, Vsevolod Moreido, Zoya Suchilina and Evgeniya Fingert
This paper considers the main principles and technologies used in developing the operational modeling system for the Ussuri River Basin of 24,400 km2 based on the automated system of hydrological monitoring and data management (ASHM), the physical-mathem...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jianjin Wang, Peng Shi, Peng Jiang, Jianwei Hu, Simin Qu, Xingyu Chen, Yingbing Chen, Yunqiu Dai and Ziwei Xiao
Flooding contributes to tremendous hazards every year; more accurate forecasting may significantly mitigate the damages and loss caused by flood disasters. Current hydrological models are either purely knowledge-based or data-driven. A combination of dat...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yong Liu, Yan-Fang Sang, Xinxin Li, Jian Hu and Kang Liang
Long-term streamflow forecasting is crucial to reservoir scheduling and water resources management. However, due to the complexity of internally physical mechanisms in streamflow process and the influence of many random factors, long-term streamflow fore...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yong Liu, Yan-Fang Sang, Xinxin Li, Jian Hu, Kang Liang
Pág. 1 - 11
Long-term streamflow forecasting is crucial to reservoir scheduling and water resources management. However, due to the complexity of internally physical mechanisms in streamflow process and the influence of many random factors, long-term streamflow fore...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jianjin Wang, Peng Shi, Peng Jiang, Jianwei Hu, Simin Qu, Xingyu Chen, Yingbing Chen, Yunqiu Dai, Ziwei Xiao
Pág. 1 - 16
Flooding contributes to tremendous hazards every year; more accurate forecasting may significantly mitigate the damages and loss caused by flood disasters. Current hydrological models are either purely knowledge-based or data-driven. A combination of dat...
ver más
|
|
|
|
|
|
|
|
|
|
|
Moyuan Yang, Yan-Fang Sang, Changming Liu and Zhonggen Wang
The combination of wavelet analysis methods with data-driven models is a prevalent approach to conducting hydrological time series forecasting, but the results are affected by the accuracy of the wavelet decomposition of the series. The choice of decompo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Moyuan Yang, Yan-Fang Sang, Changming Liu, Zhonggen Wang
Pág. 1 - 11
The combination of wavelet analysis methods with data-driven models is a prevalent approach to conducting hydrological time series forecasting, but the results are affected by the accuracy of the wavelet decomposition of the series. The choice of decompo...
ver más
|
|
|
|
|
|