Related references
Note: Only part of the references are listed.A two-stage partitioning monthly model and assessment of its performance on runoff modeling
Chao Deng et al.
JOURNAL OF HYDROLOGY (2021)
Simulating runoff under changing climatic conditions: A comparison of the long short-term memory network with two conceptual hydrologic models
Peng Bai et al.
JOURNAL OF HYDROLOGY (2021)
Comparison of different methodologies for rainfall-runoff modeling: machine learning vs conceptual approach
Rana Muhammad Adnan et al.
NATURAL HAZARDS (2021)
Comparative study of very short-term flood forecasting using physics-based numerical model and data-driven prediction model
Fiaz Hussain et al.
NATURAL HAZARDS (2021)
The effect of calibration data length on the performance of a conceptual hydrological model versus LSTM and GRU: A case study for six basins from the CAMELS dataset
Georgy Ayzel et al.
COMPUTERS & GEOSCIENCES (2021)
Global Observations and CMIP6 Simulations of Compound Extremes of Monthly Temperature and Precipitation
Yi Wu et al.
GEOHEALTH (2021)
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
Taereem Kim et al.
JOURNAL OF HYDROLOGY (2021)
Exploring a Long Short-Term Memory based Encoder-Decoder framework for multi-step-ahead flood forecasting
I-Feng Kao et al.
JOURNAL OF HYDROLOGY (2020)
A Rainfall-Runoff Model With LSTM-Based Sequence-to-Sequence Learning
Zhongrun Xiang et al.
WATER RESOURCES RESEARCH (2020)
Machine learning assisted hybrid models can improve streamflow simulation in diverse catchments across the conterminous US
Goutam Konapala et al.
ENVIRONMENTAL RESEARCH LETTERS (2020)
Evaluating the performance of random forest for large-scale flood discharge simulation
Lukas Schoppa et al.
JOURNAL OF HYDROLOGY (2020)
Comparison of the performance of SWAT, IHACRES and artificial neural networks models in rainfall-runoff simulation (case study: Kan watershed, Iran)
Mehdi Ahmadi et al.
PHYSICS AND CHEMISTRY OF THE EARTH (2019)
Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting
Xuan-Hien Le et al.
WATER (2019)
An evaluation of HSPF and SWMM for simulating streamflow regimes in an urban watershed
Mohammad Nayeb Yazdi et al.
ENVIRONMENTAL MODELLING & SOFTWARE (2019)
Evaluation and machine learning improvement of global hydrological model-based flood simulations
Tao Yang et al.
ENVIRONMENTAL RESEARCH LETTERS (2019)
Flood Inundation Generation Mechanisms and Their Changes in 1953-2004 in Global Major River Basins
Yuna Mao et al.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES (2019)
Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning
Frederik Kratzert et al.
WATER RESOURCES RESEARCH (2019)
A multi-objective ensemble approach to hydrological modelling in the UK: an application to historic drought reconstruction
Katie A. Smith et al.
HYDROLOGY AND EARTH SYSTEM SCIENCES (2019)
Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts
Jamal Zaherpour et al.
ENVIRONMENTAL RESEARCH LETTERS (2018)
Reconciling the Attribution of Changes in Streamflow Extremes From a Hydroclimate Perspective
Xing Yuan et al.
WATER RESOURCES RESEARCH (2018)
A Comparison of SWAT and ANN Models for Daily Runoff Simulation in Different Climatic Zones of Peninsular Spain
Patricia Jimeno-Saez et al.
WATER (2018)
A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists
Chaopeng Shen
WATER RESOURCES RESEARCH (2018)
Flood Prediction Using Machine Learning Models: Literature Review
Amir Mosavi et al.
WATER (2018)
Deep Learning with a Long Short-Term Memory Networks Approach for Rainfall-Runoff Simulation
Caihong Hu et al.
WATER (2018)
Rainfall-runoff modelling using Long Short-Term Memory (LSTM) networks
Frederik Kratzert et al.
HYDROLOGY AND EARTH SYSTEM SCIENCES (2018)
Nonstationarity in threshold response of stormflow in southern Appalachian headwater catchments
Charles I. Scaife et al.
WATER RESOURCES RESEARCH (2017)
Global projections of river flood risk in a warmer world
Lorenzo Alfieri et al.
EARTHS FUTURE (2017)
The CAMELS data set: catchment attributes and meteorology for large-sample studies
Nans Addor et al.
HYDROLOGY AND EARTH SYSTEM SCIENCES (2017)
A physically based and machine learning hybrid approach for accurate rainfall-runoff modeling during extreme typhoon events
Chih-Chieh Young et al.
APPLIED SOFT COMPUTING (2017)
Comparison of an artificial neural network and a conceptual rainfall-runoff model in the simulation of ephemeral streamflow
Ioannis N. Daliakopoulos et al.
HYDROLOGICAL SCIENCES JOURNAL (2016)
Establishing a rainfall threshold for flash flood warnings in China's mountainous areas based on a distributed hydrological model
Qinghua Miao et al.
JOURNAL OF HYDROLOGY (2016)
Evaluating Regional and Global Hydrological Models against Streamflow and Evapotranspiration Measurements
Yongqiang Zhang et al.
JOURNAL OF HYDROMETEOROLOGY (2016)
Design of experiments and focused grid search for neural network parameter optimization
F. J. Pontes et al.
NEUROCOMPUTING (2016)
More extreme precipitation in the world's dry and wet regions
Markus G. Donat et al.
NATURE CLIMATE CHANGE (2016)
THE IMPACT OF THE VARIABILITY OF PRECIPITATION AND TEMPERATURES ON THE EFFICIENCY OF A CONCEPTUAL RAINFALL-RUNOFF MODEL
P. Sleziak et al.
SLOVAK JOURNAL OF CIVIL ENGINEERING (2016)
Comparison of performance of twelve monthly water balance models in different climatic catchments of China
Peng Bai et al.
JOURNAL OF HYDROLOGY (2015)
Physically based modeling in catchment hydrology at 50: Survey and outlook
Claudio Paniconi et al.
WATER RESOURCES RESEARCH (2015)
Integrating risks of climate change into water management
P. Doell et al.
HYDROLOGICAL SCIENCES JOURNAL (2015)
Assessing the spatial and temporal variation of the rainwater harvesting potential (1971-2010) on the Chinese Loess Plateau using the VIC model
Baoqing Zhang et al.
HYDROLOGICAL PROCESSES (2014)
Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation
Thomas Vansteenkiste et al.
JOURNAL OF HYDROLOGY (2014)
'As simple as possible but not simpler': What is useful in a temperature-based snow-accounting routine? Part 2 - Sensitivity analysis of the Cemaneige snow accounting routine on 380 catchments
Audrey Valery et al.
JOURNAL OF HYDROLOGY (2014)
Runoff predictions in ungauged catchments in southeast Tibetan Plateau
Fapeng Li et al.
JOURNAL OF HYDROLOGY (2014)
Global flood risk under climate change
Yukiko Hirabayashi et al.
NATURE CLIMATE CHANGE (2013)
Effects of conditional parameterization on performance of rainfall-runoff model regarding hydrologic non-stationarity
Jiangmei Luo et al.
HYDROLOGICAL PROCESSES (2012)
The transferability of hydrological models under nonstationary climatic conditions
C. Z. Li et al.
HYDROLOGY AND EARTH SYSTEM SCIENCES (2012)
A comparative analysis of forest cover and catchment water yield relationships in northern China
Shuai Wang et al.
FOREST ECOLOGY AND MANAGEMENT (2011)
Climate and catchment controls on the performance of regional flood simulations
Thomas Nester et al.
JOURNAL OF HYDROLOGY (2011)
Flood simulation using parallel genetic algorithm integrated wavelet neural networks
Yuhui Wang et al.
NEUROCOMPUTING (2011)
Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water
Eric F. Wood et al.
WATER RESOURCES RESEARCH (2011)
Use of Remotely Sensed Actual Evapotranspiration to Improve Rainfall-Runoff Modeling in Southeast Australia
Yongqiang Zhang et al.
JOURNAL OF HYDROMETEOROLOGY (2009)
Division-based rainfall-runoff simulations with BP neural networks and Xinanjiang model
Qin Ju et al.
NEUROCOMPUTING (2009)
Multistep ahead streamflow forecasting: Role of calibration data in conceptual and neural network modeling
Elena Toth et al.
WATER RESOURCES RESEARCH (2007)