Search Results - "Journal of hydrology (Amsterdam)"

Short-term runoff prediction with GRU and LSTM networks without requiring time step optimization during sample generation by Gao, Shuai, Huang, Yuefei, Zhang, Shuo, Han, Jingcheng, Wang, Guangqian, Zhang, Meixin, Lin, Qingsheng

“…•LSTM and GRU networks are used for short term runoff predictions.•These models process rainfall and runoff sequence data better than ANN models.•No time step…”
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A survey on river water quality modelling using artificial intelligence models: 2000–2020 by Tiyasha, Tung, Tran Minh, Yaseen, Zaher Mundher

“…•Artificial intelligent (AI) model’s development for river water quality is reviewed.•The review is comprised multiple soft computing and water quality…”
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Evaluation of the ERA5 reanalysis precipitation dataset over Chinese Mainland by Jiang, Qin, Li, Weiyue, Fan, Zedong, He, Xiaogang, Sun, Weiwei, Chen, Sheng, Wen, Jiahong, Gao, Jun, Wang, Jun

“…•5th-generation reanalysis ERA5 precipitation dataset evaluated over Chinese Mainland.•Performance varies significantly spatio-temporally across four mainland…”
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Cotransport of heavy metals and SiO2 particles at different temperatures by seepage by Bai, Bing, Nie, Qingke, Zhang, Yike, Wang, Xiaolong, Hu, Wei

“…•Cotransport of HMs and SPs is investigated at different temperatures by seepage.•A model considering the particle size and dielectric property is…”
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Machine learning methods for better water quality prediction by Najah Ahmed, Ali, Binti Othman, Faridah, Abdulmohsin Afan, Haitham, Khaleel Ibrahim, Rusul, Ming Fai, Chow, Shabbir Hossain, Md, Ehteram, Mohammad, Elshafie, Ahmed

“…[Display omitted] •The water quality parameters (i.e. pH, AN, and SS) of Johor River was predicted.•Three models were implemented using enhanced Wavelet…”
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Research on particle swarm optimization in LSTM neural networks for rainfall-runoff simulation by Xu, Yuanhao, Hu, Caihong, Wu, Qiang, Jian, Shengqi, Li, Zhichao, Chen, Youqian, Zhang, Guodong, Zhang, Zhaoxi, Wang, Shuli

“…•Provides a protocol to optimize hyperparameters of LSTM.•Proposes a PSO-LSTM model for flood simulation and forecast.•Study the effect of hyperparameter…”
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Spatial prediction of groundwater potential mapping based on convolutional neural network (CNN) and support vector regression (SVR) by Panahi, Mahdi, Sadhasivam, Nitheshnirmal, Pourghasemi, Hamid Reza, Rezaie, Fatemeh, Lee, Saro

“…•Novel hybrid models proposed for groundwater potential mapping.•Compared predictive capability of two different models (CNN, SVR).•Highest reliability of…”
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Flood susceptibility mapping with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory by Gudiyangada Nachappa, Thimmaiah, Tavakkoli Piralilou, Sepideh, Gholamnia, Khalil, Ghorbanzadeh, Omid, Rahmati, Omid, Blaschke, Thomas

“…[Display omitted] •Application of knowledge-based spatial decision support system for flood susceptibility mapping.•Performance of data-base machine learning…”
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A deep convolutional neural network model for rapid prediction of fluvial flood inundation by Kabir, Syed, Patidar, Sandhya, Xia, Xilin, Liang, Qiuhua, Neal, Jeffrey, Pender, Gareth

“…•A CNN model is proposed to estimate flood water depths.•The model can predict water depths for over half of a million cells instantly.•The CNN can potentially…”
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XGBoost-based method for flash flood risk assessment by Ma, Meihong, Zhao, Gang, He, Bingshun, Li, Qing, Dong, Haoyue, Wang, Shenggang, Wang, Zhongliang

“…•An XGBoost-based method is proposed for flash flood risk assessment.•This approach was demonstrated based on two flood  inventories and the comparative SVM…”
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A review of remote sensing applications for water security: Quantity, quality, and extremes by Chawla, Ila, Karthikeyan, L., Mishra, Ashok K.

“…•Review role of satellite remote sensing to assess water security.•Water quality, quantity, and extremes are the three aspects considered.•Water quality:…”
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Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs by Adnan, Rana Muhammad, Liang, Zhongmin, Heddam, Salim, Zounemat-Kermani, Mohammad, Kisi, Ozgur, Li, Binquan

“…•This study compares the accuracy of new heuristic methods, optimally pruned extreme learning machine (OP-ELM), least square support vector machine (LSSVM),…”
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Hydropower dams of the Mekong River basin: A review of their hydrological impacts by Hecht, Jory S., Lacombe, Guillaume, Arias, Mauricio E., Dang, Thanh Duc, Piman, Thanapon

“…•Hydropower reservoirs and diversions are severely altering Mekong basin streamflow.•Dam-induced flow alteration on both mainstream and tributaries are…”
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A nonlinear attachment-detachment model with adsorption hysteresis for suspension-colloidal transport in porous media by Bai, Bing, Rao, Dengyu, Chang, Tao, Guo, Zhiguang

“…•A nonlinear attachment-detachment model with hysteresis is proposed.•Introducing scanning desorption isotherms to model the deposition effect.•Static…”
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Deep learning of subsurface flow via theory-guided neural network by Wang, Nanzhe, Zhang, Dongxiao, Chang, Haibin, Li, Heng

“…•TgNN model trained with data while being guided by theory of the underlying problem.•TgNN achieves better predictability, reliability, and generalizability…”
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Monthly runoff time series prediction by variational mode decomposition and support vector machine based on quantum-behaved particle swarm optimization by Feng, Zhong-kai, Niu, Wen-jing, Tang, Zheng-yang, Jiang, Zhi-qiang, Xu, Yang, Liu, Yi, Zhang, Hai-rong

“…•Monthly runoff is divided into several subseries by variational mode decomposition.•Support vector machine models the input-output relationships of all the…”
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Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles by Chen, Wei, Hong, Haoyuan, Li, Shaojun, Shahabi, Himan, Wang, Yi, Wang, Xiaojing, Ahmad, Baharin Bin

“…[Display omitted] •Novel hybrid Bag-REPTree and RS-REPTree ensemble frameworks for flood susceptibility.•Optimization of input factors using ReliefF…”
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Urban flood resilience – A multi-criteria index to integrate flood resilience into urban planning by Bertilsson, Louise, Wiklund, Karin, de Moura Tebaldi, Isadora, Rezende, Osvaldo Moura, Veról, Aline Pires, Miguez, Marcelo Gomes

“…•A multucriteria index is proposed to map urban flood resilience (S-FRESI).•This index provides a quantitative value to flood resilience assessment.•S-FRESI:…”
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Urban flooding risk assessment based on an integrated k-means cluster algorithm and improved entropy weight method in the region of Haikou, China by Xu, Hongshi, Ma, Chao, Lian, Jijian, Xu, Kui, Chaima, Evance

“…[Display omitted] •An improved entropy-cluster algorithm approach was used to develop the flood risk map.•The index weights were calculated by integrating…”
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Global data assessment and analysis of drought characteristics based on CMIP6 by Wang, Tian, Tu, Xinjun, Singh, Vijay P., Chen, Xiaohong, Lin, Kairong

“…•CMIP6 has a high simulation accuracy at mid latitudes.•Trends in future droughts will be global and exceptional droughts will increase.•Evapotranspiration…”
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