Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS
Authors
Keywords
Daily streamflow simulation, Hydrologic models, Data-driven machine learning model, Process-based hydrological model, Artificial Neural Networks
Journal
JOURNAL OF HYDROLOGY
Volume 598, Issue -, Pages 126423
Publisher
Elsevier BV
Online
2021-05-07
DOI
10.1016/j.jhydrol.2021.126423
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Ensemble‐based Neural Network Modeling for Hydrologic Forecasts: Addressing Uncertainty in the Model Structure and Input Variable Selection
- (2020) Taereem Kim et al. WATER RESOURCES RESEARCH
- The Use of Large-Scale Climate Indices in Monthly Reservoir Inflow Forecasting and Its Application on Time Series and Artificial Intelligence Models
- (2019) Taereem Kim et al. Water
- Deep learning and process understanding for data-driven Earth system science
- (2019) Markus Reichstein et al. NATURE
- Forecasting monthly precipitation using sequential modelling
- (2019) Deepak Kumar et al. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
- Deep learning for multi-year ENSO forecasts
- (2019) Yoo-Geun Ham et al. NATURE
- Evaluation and machine learning improvement of global hydrological model-based flood simulations
- (2019) Tao Yang et al. Environmental Research Letters
- Physics‐Constrained Machine Learning of Evapotranspiration
- (2019) Wen Li Zhao et al. GEOPHYSICAL RESEARCH LETTERS
- Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning
- (2019) Frederik Kratzert et al. WATER RESOURCES RESEARCH
- Temporal and spatial evaluation of satellite rainfall estimates over different regions in Latin-America
- (2018) Oscar Manuel Baez-Villanueva et al. ATMOSPHERIC RESEARCH
- “Grand Challenges” in Big Data and the Earth Sciences
- (2018) S. L. Sellars BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
- Comparison between the TOPMODEL and the Xin’anjiang model and their application to rainfall runoff simulation in semi-humid regions
- (2018) Gairui Hao et al. Environmental Earth Sciences
- The effect of rain gauge density and distribution on runoff simulation using a lumped hydrological modelling approach
- (2018) Qiang Zeng et al. JOURNAL OF HYDROLOGY
- A comparative study of LSTM neural networks in forecasting day-ahead global horizontal irradiance with satellite data
- (2018) Shikhar Srivastava et al. SOLAR ENERGY
- Impact Assessment of Rainfall-Runoff Simulations on the Flow Duration Curve of the Upper Indus River—A Comparison of Data-Driven and Hydrologic Models
- (2018) Ateeq-ur Rauf et al. Water
- Insights into Hydrometeorological Factors Constraining Flood Prediction Skill during the May and October 2015 Texas Hill Country Flood Events
- (2018) Peirong Lin et al. JOURNAL OF HYDROMETEOROLOGY
- Multiple hydrological models comparison and an improved Bayesian model averaging approach for ensemble prediction over semi-humid regions
- (2018) Wenbo Huo et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- A trans-disciplinary review of deep learning research and its relevance for water resources scientists
- (2018) Chaopeng Shen WATER RESOURCES RESEARCH
- A comparison of SAC-SMA and ANFIS for real-time flood forecasting in small urban catchments
- (2018) Babak K. Roodsari et al. Journal of Flood Risk Management
- Evaluating the Temporal Dynamics of Uncertainty Contribution from Satellite Precipitation Input in Rainfall-Runoff Modeling Using the Variance Decomposition Method
- (2018) Qiumei Ma et al. Remote Sensing
- Flood Prediction Using Machine Learning Models: Literature Review
- (2018) Amir Mosavi et al. Water
- Study on the Applicability of the Hargreaves Potential Evapotranspiration Estimation Method in CREST Distributed Hydrological Model (Version 3.0) Applications
- (2018) Zhansheng Li et al. Water
- Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks
- (2018) Ata Akbari Asanjan et al. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
- An enhanced artificial neural network with a shuffled complex evolutionary global optimization with principal component analysis
- (2017) Tiantian Yang et al. INFORMATION SCIENCES
- Refining a Distributed Linear Reservoir Routing Method to Improve Performance of the CREST Model
- (2017) Xinyi Shen et al. JOURNAL OF HYDROLOGIC ENGINEERING
- Full-flow-regime storage-streamflow correlation patterns provide insights into hydrologic functioning over the continental US
- (2017) Kuai Fang et al. WATER RESOURCES RESEARCH
- Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information
- (2017) Tiantian Yang et al. WATER RESOURCES RESEARCH
- An Improved Coupled Routing and Excess Storage (CREST) Distributed Hydrological Model and Its Verification in Ganjiang River Basin, China
- (2017) Guangyuan Kan et al. Water
- Comparative Analysis of ANN and SVM Models Combined with Wavelet Preprocess for Groundwater Depth Prediction
- (2017) Ting Zhou et al. Water
- Application of BP Neural Network Algorithm in Traditional Hydrological Model for Flood Forecasting
- (2017) Jianjin Wang et al. Water
- Lecturer performance system using neural network with Particle Swarm Optimization
- (2016) Tarik A. Rashid et al. COMPUTER APPLICATIONS IN ENGINEERING EDUCATION
- POLARIS: A 30-meter probabilistic soil series map of the contiguous United States
- (2016) Nathaniel W. Chaney et al. GEODERMA
- Comparison of an artificial neural network and a conceptual rainfall–runoff model in the simulation of ephemeral streamflow
- (2016) Ioannis N. Daliakopoulos et al. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
- Estimating a-priori kinematic wave model parameters based on regionalization for flash flood forecasting in the Conterminous United States
- (2016) Humberto Vergara et al. JOURNAL OF HYDROLOGY
- Event-based hydrological modeling for detecting dominant hydrological process and suitable model strategy for semi-arid catchments
- (2016) Pengnian Huang et al. JOURNAL OF HYDROLOGY
- High-resolution ensemble projections of near-term regional climate over the continental United States
- (2016) Moetasim Ashfaq et al. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
- A unified approach for process-based hydrologic modeling: 1. Modeling concept
- (2015) Martyn P. Clark et al. WATER RESOURCES RESEARCH
- An integrated modeling system for estimating glacier and snow melt driven streamflow from remote sensing and earth system data products in the Himalayas
- (2014) M.E. Brown et al. JOURNAL OF HYDROLOGY
- Comment on “High-dimensional posterior exploration of hydrologic models using multiple-try DREAM (ZS) and high-performance computing” by Eric Laloy and Jasper A. Vrugt
- (2014) Wei Chu et al. WATER RESOURCES RESEARCH
- A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model
- (2013) Yanjun Gan et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Assessment of a conceptual hydrological model and artificial neural networks for daily outflows forecasting
- (2013) M. Rezaeianzadeh et al. International Journal of Environmental Science and Technology
- Statistical and hydrological evaluation of TRMM-based Multi-satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the latest satellite precipitation products 3B42V7 ready for use in ungauged basins?
- (2013) Xianwu Xue et al. JOURNAL OF HYDROLOGY
- A benchmarking approach for comparing data splitting methods for modeling water resources parameters using artificial neural networks
- (2013) Wenyan Wu et al. WATER RESOURCES RESEARCH
- Application of artificial neural networks to rainfall forecasting in Queensland, Australia
- (2012) John Abbot et al. ADVANCES IN ATMOSPHERIC SCIENCES
- On the use of cross-validation for time series predictor evaluation
- (2012) Christoph Bergmeir et al. INFORMATION SCIENCES
- Comparison of three global optimization algorithms for calibration of the Xinanjiang model parameters
- (2012) Dong-mei Xu et al. JOURNAL OF HYDROINFORMATICS
- Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios
- (2012) Harald Kling et al. JOURNAL OF HYDROLOGY
- Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir
- (2012) Mohammad Valipour et al. JOURNAL OF HYDROLOGY
- The coupled routing and excess storage (CREST) distributed hydrological model
- (2011) Jiahu Wang et al. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
- A Solution to the Crucial Problem of Population Degeneration in High-Dimensional Evolutionary Optimization
- (2011) Wei Chu et al. IEEE Systems Journal
- A new evolutionary search strategy for global optimization of high-dimensional problems
- (2011) Wei Chu et al. INFORMATION SCIENCES
- Study of the Xinanjiang Model Parameter Calibration
- (2011) Li Zhijia et al. JOURNAL OF HYDROLOGIC ENGINEERING
- Daily streamflow forecasting by machine learning methods with weather and climate inputs
- (2011) Kabir Rasouli et al. JOURNAL OF HYDROLOGY
- Annual precipitation forecast for west, southwest, and south provinces of Iran using artificial neural networks
- (2011) Samira Azadi et al. THEORETICAL AND APPLIED CLIMATOLOGY
- High-dimensional posterior exploration of hydrologic models using multiple-try DREAM(ZS) and high-performance computing
- (2011) Eric Laloy et al. WATER RESOURCES RESEARCH
- Hydrologic evaluation of satellite precipitation products over a mid-size basin
- (2010) Ali Behrangi et al. JOURNAL OF HYDROLOGY
- The Hydrology and Hydrometeorology of Flooding in the Delaware River Basin
- (2010) James A. Smith et al. JOURNAL OF HYDROMETEOROLOGY
- Improving the shuffled complex evolution scheme for optimization of complex nonlinear hydrological systems: Application to the calibration of the Sacramento soil-moisture accounting model
- (2010) Wei Chu et al. WATER RESOURCES RESEARCH
- Low-Flows in Deterministic Modelling: A Brief Review
- (2009) B. Davison et al. Canadian Water Resources Journal
- Application of a Developed Grid-Xinanjiang Model to Chinese Watersheds for Flood Forecasting Purpose
- (2009) Cheng Yao et al. JOURNAL OF HYDROLOGIC ENGINEERING
- A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series
- (2009) Wen-Chuan Wang et al. JOURNAL OF HYDROLOGY
- Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling
- (2009) Hoshin V. Gupta et al. JOURNAL OF HYDROLOGY
- From lumped to distributed via semi-distributed: Calibration strategies for semi-distributed hydrologic models
- (2009) Behnaz Khakbaz et al. JOURNAL OF HYDROLOGY
- Artificial neural network models for forecasting intermittent monthly precipitation in arid regions
- (2009) Ahmad Dahamsheh et al. METEOROLOGICAL APPLICATIONS
- Division-based rainfall-runoff simulations with BP neural networks and Xinanjiang model
- (2009) Qin Ju et al. NEUROCOMPUTING
- An application of artificial intelligence for rainfall-runoff modeling
- (2008) Ali Aytek et al. Journal of Earth System Science
- Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?
- (2008) Jasper A. Vrugt et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- Artificial neural network models for forecasting monthly precipitation in Jordan
- (2008) Hafzullah Aksoy et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- Data-driven modelling: some past experiences and new approaches
- (2007) Dimitri P. Solomatine et al. JOURNAL OF HYDROINFORMATICS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now