Research graph
References from Application of an ANN model integrating station network distribution and water level increment principle in flood season water level prediction of Taihu Lake basin. Local targets link to admitted publications; unresolved targets remain external evidence.
Application of partial least-squares regression in seasonal streamflow forecasting
10.1061/(asce)he.1943-5584.0000216 · 2010 · External reference
Developments and trends in water level forecasting using machine learning models–a review
10.1109/access.2025.3557910 · 2025 · External reference
Explaining Great Lakes water level variability through interpretable ensemble machine learning
10.1016/j.scitotenv.2025.181302 · 2026 · External reference
A review of XAI methods applications in forecasting runoff and water level hydrological tasks
10.3390/math13172830 · 2025 · External reference
Hydrologic uncertainty for Bayesian probabilistic forecasting model based on BP ANN
2007 · External reference
A review of coupled hydrologic-hydraulic models for floodplain assessments in Africa: opportunities and challenges for floodplain wetland management
10.3390/hydrology8010044 · 2021 · External reference
Influence of changes in river system structure on hydrological processes in Taihu Basin, China
10.1080/02626667.2019.1645333 · 2019 · External reference
An evaluation framework for input variable selection algorithms for environmental data-driven models
10.1016/j.envsoft.2014.08.015 · 2014 · External reference
Coupling and comparison of physical mechanism and machine learning models for water level simulation in plain river network area
10.3390/app142412008 · 2024 · External reference
Spatial-temporal analysis of ecosystem services value and research on ecological compensation in Taihu Lake Basin of Jiangsu Province in China from 2005 to 2018
10.1016/j.jclepro.2021.128241 · 2021 · External reference
The proper care and feeding of CAMELS: how limited training data affects streamflow prediction
10.1016/j.envsoft.2020.104926 · 2021 · External reference
Hybrid machine learning models for groundwater level prediction in a snow-dominated region: an evaluation of EEMD, VMD and EWT decomposition techniques
10.1002/hyp.15169 · 2024 · External reference
Precipitation variability and its response to urbanization in the Taihu Lake Basin, China
10.1007/s00704-021-03597-x · 2021 · External reference
Spatiotemporal patterns and atmospheric drivers of anomalous precipitation in the Taihu Basin, Eastern China
10.3390/w17162442 · 2025 · External reference
Study on the proportion and flow path of Yangtze River water diversion into Taihu Lake
10.2166/ws.2021.313 · 2022 · External reference
Improving explainable AI in attributing hydrological responses to climate variabilities in snow-dominated watersheds
10.1016/j.asoc.2025.113682 · 2025 · External reference
Enhancing hydrological time series forecasting with a hybrid Bayesian-ConvLSTM model optimized by particle swarm optimization
10.1007/s11600-025-01570-0 · 2025 · External reference
Rainfall–runoff modelling using long short-term memory (LSTM) networks
10.5194/hess-22-6005-2018 · 2018 · External reference
Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets
10.5194/hess-23-5089-2019 · 2019 · External reference
Assessing the hydrologic impacts of land use change in the Taihu Lake Basin of China from 1985 to 2010
10.3390/w10111512 · 2018 · External reference
The application of water conservancy project in the comprehensive management of water environment in Taihu Lake Basin
10.56028/aetr.2.1.306 · 2022 · External reference
A study on flood susceptibility mapping in the Poyang Lake basin based on machine learning model comparison and SHapley Additive exPlanations interpretation
10.3390/w17202955 · 2025 · External reference
On the development of improved artificial neural network model and its application on hydrological forecasting
2007 · External reference
A unified approach to interpreting model predictions
2017 · External reference
Using Bayesian optimization to automate the calibration of complex hydrological models: framework and application
10.1016/j.envsoft.2021.105235 · 2022 · External reference
Hydrologic and water quality models: performance measures and evaluation criteria
10.13031/trans.58.10715 · 2015 · External reference
Flood prediction using machine learning models: literature review
10.3390/w10111536 · 2018 · External reference
A high resolution coupled hydrologic–hydraulic model (HiResFlood-UCI) for flash flood modeling
10.1016/j.jhydrol.2015.10.047 · 2016 · External reference
Rainfall and runoff time-series trend analysis using LSTM recurrent neural network and wavelet neural network with satellite-based meteorological data: case study of Nzoia hydrologic basin
10.1007/s40747-021-00365-2 · 2022 · External reference
Intelligent decoupling of hydrological effects in Han River cascade dam system: spatial heterogeneity mechanisms via an LSTM-attention-SHAP interpretable framework
10.3390/hydrology12080217 · 2025 · External reference
Prediction and modeling of flood hydrology and hydraulics
2000 · External reference
"Why should I trust you?" Explaining the predictions of any classifier
2016 · External reference
The response of water balance components to land cover change based on hydrologic modeling and partial least squares regression (PLSR) analysis in the Upper Awash Basin
2019 · External reference
Applications of deep learning in hydrology
2021 · External reference
Spatial distribution and stratigraphic characteristics of surface sediments in Taihu Lake, China
10.1007/s11434-010-4214-0 · 2011 · External reference
Hydrologic modeling: progress and future directions
10.1186/s40562-018-0113-z · 2018 · External reference
A comprehensive review of deep learning applications in hydrology and water resources
10.2166/wst.2020.369 · 2020 · External reference
Study on the joint operation scheme of key water conservancy projects in the Taihu Lake Basin: a case study on ensuring flood control safety
10.54254/2977-3903/2025.30940 · 2025 · External reference
Assessment on the evolution of river structure characteristics and hydrological connectivity in Taihu Lake basin based on index of connectivity during the past 35 years
10.1002/hyp.70286 · 2025 · External reference
Research on particle swarm optimization in LSTM neural networks for rainfall-runoff simulation
10.1016/j.jhydrol.2022.127553 · 2022 · External reference
Investigating the spatial variability of water security risk and its driving mechanisms in China using machine learning
10.1016/j.jclepro.2022.132303 · 2022 · External reference
Impacts of land use change on watershed streamflow and sediment yield: an assessment using hydrologic modelling and partial least squares regression
10.1016/j.jhydrol.2013.01.008 · 2013 · External reference
Numerical study of coupled one-dimensional and two-dimensional hydrodynamic and water quality model for complex lake and river network areas
2012 · External reference
Relationship between changes of river-lake networks and water levels in typical regions of Taihu Lake Basin, China
10.1007/s11769-012-0570-9 · 2012 · External reference
Development and performance of a 1D–2D coupled shallow water model for large river and lake networks
10.1080/00221686.2018.1534286 · 2019 · External reference
Model simulations of potential contribution of the proposed Huangpu Gate to flood control in the Lake Taihu basin of China
10.5194/hess-21-5339-2017 · 2017 · External reference
The response of chlorophyll a to nutrient and hydro-meteorological factors in Lake Taihu
10.1007/s10661-025-13775-3 · 2025 · External reference
The hydrological regime of Taihu Lake under the influence of anthropogenic activities
2023 · External reference
Simulation and application of water environment in highly urbanized areas: a case study in Taihu Lake Basin
10.3390/hydrology11020020 · 2024 · External reference
Copula-based joint impact assessment of rainfall and tidal level on flood risk in tidal-influenced plain river network areas, Taihu Lake Basin
10.1016/j.jhydrol.2025.132785 · 2025 · External reference
