☆ 4.5 Article

Physical and artificial intelligence-based hybrid models for rainfall-runoff-sediment process modelling

HYDROLOGICAL SCIENCES JOURNAL (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Environmental Sciences

Basin Runoff Responses to Climate Change Using a Rainfall-Runoff Hydrological Model in Southeast Australia

Newton Muhury et al.

Summary: The Murrumbidgee River basin in southeastern Australia, an important agricultural region, is experiencing the effects of climate change. The predicted decrease in rainfall in the upper catchments of the basin is causing a significant impact on the volumes of runoff, while the lower catchments are experiencing an increasing potential for runoff, suggesting the need for irrigation dams.

ATMOSPHERE (2023)

添加到收藏夹

Article Engineering, Civil

Simulating glacier mass balance and its contribution to runoff in Northern Sweden

Babak Mohammadi et al.

Summary: This study applied the FLEXG model to understand the glacier melting process and the effect of topography on GMB in the Torne River basin. The model simulated glacier and snow accumulation, ablation, and runoff from the basin. Results showed that the FLEXG model performed well in reproducing streamflow and peak runoff, and a downward trend in GMB was observed due to climate change.

JOURNAL OF HYDROLOGY (2023)

添加到收藏夹

Article Geosciences, Multidisciplinary

A comparison of performance of SWAT and machine learning models for predicting sediment load in a forested Basin, Northern Spain

Patricia Jimeno-Saez et al.

Summary: This study explores the use of the M5P and random forest (RF) machine learning models as alternatives to the Soil and Water Assessment Tool (SWAT) model for estimating suspended sediment load (SSL). The ML models were found to be more accurate than the SWAT model at the daily scale, with the M5P model demonstrating superior performance. However, the SWAT model remains a useful tool in basins with limited streamflow data.

CATENA (2022)

添加到收藏夹

Article Engineering, Environmental

Evaluate River Water Salinity in a Semi-Arid Agricultural Watershed by Coupling Ensemble Machine Learning Technique with SWAT Model

Chunggil Jung et al.

Summary: This study established a new approach to estimate river salinity in a semi-arid agricultural watershed using hydrologic modeling and machine learning. By analyzing soil physical characteristics, it was found that soil salinity levels are directly affected by soil permeability and irrigation water, showing higher TDS levels in silt loam sites and lower TDS levels in very cobbly soil sites.

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION (2022)

添加到收藏夹

Article Water Resources

Performance assessment of SWAT and HEC-HMS model for runoff simulation of Toba watershed, Ethiopia

Sewmehon Sisay Fanta et al.

Summary: This study evaluates the performance of SWAT and HEC-HMS models in daily runoff simulation in the Toba watershed in Abbay River Basin, Ethiopia using the same input data and methods. The results show that both models perform well in simulating runoff. Overestimation of peak discharge and average runoff for cultivated land provides insight into the characteristics of land use/land cover in the watershed. This study can serve as a baseline scenario for future assessments of land use/land cover and runoff potential.

SUSTAINABLE WATER RESOURCES MANAGEMENT (2022)

添加到收藏夹

Article Multidisciplinary Sciences

IHACRES, GR4J and MISD-based multi conceptual-machine learning approach for rainfall-runoff modeling

Babak Mohammadi et al.

Summary: This study combines conceptual and machine learning approaches to establish a robust and reliable rainfall-runoff model. By incorporating the outcomes of conceptual models and hydro-meteorological variables into machine learning models, the accuracy of the models in runoff simulation is improved. The recommended methodology may be applied in alternative hydrological problems.

SCIENTIFIC REPORTS (2022)

添加到收藏夹

Article Water Resources

Comparison of machine learning and process-based SWAT model in simulating streamflow in the Upper Indus Basin

Khalil Ur Rahman et al.

Summary: This study compared the performance of process-based hydrological SWAT model with a machine learning-based multi-layer perceptron (MLP) model for simulating streamflow in the Upper Indus Basin. The results showed that the SWAT model had relatively poor performance compared to the MLP model. Based on the robust performance of the MLP model, the study recommends developing and assessing machine learning models and merging them with the SWAT model.

APPLIED WATER SCIENCE (2022)

添加到收藏夹

Article Water Resources

Evaluating the performance of HBV, HEC-HMS and ANN models in simulating streamflow for a data scarce high-humid tropical catchment in Tanzania

Nickson Tibangayuka et al.

Summary: This study evaluates the performance of HEC-HMS, HBV model, and ANN model in a data-scarce high-humidity tropical catchment. The results show that HEC-HMS performs the best, followed by the HBV model and ANN model. These findings provide insight into the effectiveness of hydrological models and are important for effective water resources management in the region.

HYDROLOGICAL SCIENCES JOURNAL (2022)

添加到收藏夹

Article Environmental Sciences

Model identification and accuracy for estimation of suspended sediment load

Khabat Khosravi et al.

Summary: This study applied three widely used modeling approaches to predict suspended sediment load at the Talar watershed in Iran and evaluated their performance. The random forest model showed the best prediction power in the training phase, while the dagging-RF hybrid algorithm outperformed all other models in the validation phase.

GEOCARTO INTERNATIONAL (2022)

添加到收藏夹

Article Physics, Fluids & Plasmas

Comparison of Two Hydrological Models, HEC-HMS and SWAT in Runoff Estimation: Application to Huai Bang Sai Tropical Watershed, Thailand

Imiya M. Chathuranika et al.

Summary: This study compared the streamflow simulation capacities of the Soil and Water Assessment Tool (SWAT) and the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) for the Huai Bang Sai watershed in Thailand. The results showed that the SWAT model performed well in capturing high flows, while the HEC-HMS model performed better for medium flows. Both models accurately simulated low flows. Additionally, the SWAT model reasonably simulated dry and wet seasonal flows, while the HEC-HMS model under-predicted these flows compared to observations.

FLUIDS (2022)

添加到收藏夹

Article Water Resources

Evaluation of soft computing and regression-based techniques for the estimation of evaporation

Aparajita Singh et al.

Summary: In this study, artificial neural network (ANN) and multiple linear regression (MLR) models were developed to estimate pan evaporation using rainfall, relative humidity, and temperature parameters. The ANN model outperformed the MLR model in terms of correlation coefficient, root-mean-square error, and Nash-Sutcliffe efficiency values. Sensitivity analysis revealed that relative humidity was the most effective parameter for estimating evaporation.

JOURNAL OF WATER AND CLIMATE CHANGE (2021)

添加到收藏夹

Article Mathematics, Interdisciplinary Applications

Estimation of Suspended Sediment Load Using Artificial Intelligence-Based Ensemble Model

Vahid Nourani et al.

Summary: The study developed artificial intelligence-based ensemble methods for modeling suspended sediment load (SSL) in Katar catchment, Ethiopia. Different single AI-based models and ensemble methods were used, with the ANFIS model showing higher efficiency and the ANFIS ensemble model as the most accurate method among all developed models. Overall, the proposed ensemble models in general and the AI-based ensemble in particular provide excellent performance in SSL estimation.

COMPLEXITY (2021)

添加到收藏夹

Article Mathematics, Interdisciplinary Applications

Estimation of Daily Suspended Sediment Load Using a Novel Hybrid Support Vector Regression Model Incorporated with Observer-Teacher-Learner-Based Optimization Method

Siyamak Doroudi et al.

Summary: In water resource management, predicting suspended sediment load is crucial. This study introduces a novel hybrid predictive model combining SVR with OTLBO, outperforming other models by achieving the highest prediction performance.

COMPLEXITY (2021)

添加到收藏夹

Article Environmental Sciences

A novel multi-model data-driven ensemble approach for the prediction of particulate matter concentration

Ibrahim Khalil Umar et al.

Summary: A novel neuro fuzzy ensemble (NF-E) model was proposed for predicting hourly PM2.5 and PM10 concentration in the atmosphere, demonstrating higher generalization ability and accuracy compared to other models.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2021)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Ensemble data-driven rainfall-runoff modeling using multi-source satellite and gauge rainfall data input fusion

Vahid Nourani et al.

Summary: Different modeling techniques, including FFNN, ANFIS, and SVR, were applied in the study for rainfall-runoff modeling of the Gilgel Abay catchment in the Blue Nile basin, Ethiopia. Ensemble modeling using input fusion from multiple source satellite rainfall products showed significant improvement in validation, indicating it as a promising option for accurate modeling of the rainfall-runoff process in ungagged or sparsely gauged catchments.

EARTH SCIENCE INFORMATICS (2021)

添加到收藏夹

Review Water Resources

A review on the applications of machine learning for runoff modeling

Babak Mohammadi

Summary: This study critically reviews the characteristics of machine learning models in runoff simulation, including the advantages and disadvantages of three widely used machine learning models. Topics covered in this review study include surface hydrology, streamflow, rainfall-runoff, and flood modeling via ML approaches in recent years.

SUSTAINABLE WATER RESOURCES MANAGEMENT (2021)

添加到收藏夹

Article Water Resources

Improving the performance of rainfall-runoff models using the gene expression programming approach

Hassan Esmaeili-Gisavandani et al.

Summary: The study compared the performance of five hydrological models in simulating the flow of the Hablehroud River in Iran, with the SWAT model showing the best results. Peak flows were generally underestimated by the models, and a hybrid model developed using gene expression programming demonstrated the best performance in both calibration and validation stages, showcasing the effectiveness of combining outputs from less accurate individual models.

JOURNAL OF WATER AND CLIMATE CHANGE (2021)

添加到收藏夹

Article Water Resources

Performance of HEC-HMS and SWAT to simulate streamflow in the sub-humid tropical Hemavathi catchment

N. C. Sanjay Shekar et al.

Summary: The study examined the accuracy and applicability of hydrological models SWAT and HEC-HMS in simulating streamflows, finding that SWAT model performed better than HEC-HMS model. Through calibration and optimization, the models showed good results in the humid tropical Hemavathi catchment.

JOURNAL OF WATER AND CLIMATE CHANGE (2021)

添加到收藏夹

Article Water Resources

Rainfall-Runoff Modeling Using the HEC-HMS Model for the Al-Adhaim River Catchment, Northern Iraq

Ahmed Naseh Ahmed Hamdan et al.

Summary: This study developed a hydrological model named HEC-HMS and successfully identified the discharge of the Al-Adhaim River catchment and embankment dam in Iraq through simulating rainfall-runoff processes. The model's performance was evaluated to be good based on calibration and verification results, indicating its suitability for hydrological simulations in the Al-Adhaim river catchment.

HYDROLOGY (2021)

添加到收藏夹

Article Environmental Sciences

Artificial intelligence based ensemble model for prediction of vehicular traffic noise

Vahid Nourani et al.

ENVIRONMENTAL RESEARCH (2020)

添加到收藏夹

Article Engineering, Civil

Multi-step ahead modeling of reference evapotranspiration using a multi-model approach

Vahid Nourani et al.

JOURNAL OF HYDROLOGY (2020)

添加到收藏夹

Article Engineering, Civil

Suitability of the SWAT Model for Simulating Water Discharge and Sediment Load in a Karst Watershed of the Semiarid Mediterranean Basin

Alberto Martinez-Salvador et al.

WATER RESOURCES MANAGEMENT (2020)

添加到收藏夹

Article Water Resources

Predicting of Runoff Using an Optimized SWAT-ANN: A Case Study

Zhihua LV et al.

JOURNAL OF HYDROLOGY-REGIONAL STUDIES (2020)

添加到收藏夹

Article Geosciences, Multidisciplinary

A novel study of SWAT and ANN models for runoff simulation with application on dataset of metrological stations

Hamidreza Zakizadeh et al.

PHYSICS AND CHEMISTRY OF THE EARTH (2020)

添加到收藏夹

Article Environmental Sciences

Sensitivity and Interdependency Analysis of the HBV Conceptual Model Parameters in a Semi-Arid Mountainous Watershed

Hamza Ouatiki et al.

WATER (2020)

添加到收藏夹

Article Engineering, Civil

A physical process and machine learning combined hydrological model for daily streamflow simulations of large watersheds with limited observation data

Shuyu Yang et al.

JOURNAL OF HYDROLOGY (2020)

添加到收藏夹

Article Engineering, Civil

Water quality prediction using SWAT-ANN coupled approach

Navideh Noori et al.

JOURNAL OF HYDROLOGY (2020)

添加到收藏夹

Article Computer Science, Information Systems

Hybrid Machine Learning Ensemble Techniques for Modeling Dissolved Oxygen Concentration

Sani Isah Abba et al.

IEEE ACCESS (2020)

添加到收藏夹

Article Environmental Studies

Land-use and land-cover change in Lake Ziway watershed of the Ethiopian Central Rift Valley Region and its environmental impacts

Hayal Desta et al.

LAND USE POLICY (2020)

添加到收藏夹

Article Agricultural Engineering

Coupling machine-learning techniques with SWAT model for instantaneous peak flow prediction

Javier Senent-Aparicio et al.

BIOSYSTEMS ENGINEERING (2019)

添加到收藏夹

Article Geosciences, Multidisciplinary

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)

添加到收藏夹

Article Meteorology & Atmospheric Sciences

Estimation of monthly pan evaporation using support vector machine in Three Gorges Reservoir Area, China

Ji-Long Chen et al.

THEORETICAL AND APPLIED CLIMATOLOGY (2019)

添加到收藏夹

Article Engineering, Civil

Lake Water-Level fluctuations forecasting using Minimax Probability Machine Regression, Relevance Vector Machine, Gaussian Process Regression, and Extreme Learning Machine

Hossein Bonakdari et al.

WATER RESOURCES MANAGEMENT (2019)

添加到收藏夹

Article Engineering, Civil

Multi-station artificial intelligence based ensemble modeling of reference evapotranspiration using pan evaporation measurements

Vahid Nourani et al.

JOURNAL OF HYDROLOGY (2019)

添加到收藏夹

Article Engineering, Civil

Multi-step ahead modelling of river water quality parameters using ensemble artificial intelligence-based approach

Gozen Elkiran et al.

JOURNAL OF HYDROLOGY (2019)

添加到收藏夹

Article Engineering, Civil

Daily streamflow prediction using optimally pruned extreme learning machine

Rana Muhammad Adnan et al.

JOURNAL OF HYDROLOGY (2019)

添加到收藏夹

Article Meteorology & Atmospheric Sciences

A comparison between the application of empirical and ANN methods for estimation of daily global solar radiation in Iran

Babak Jahani et al.

THEORETICAL AND APPLIED CLIMATOLOGY (2019)

添加到收藏夹

Article Engineering, Civil

Evaluating Different Machine Learning Models for Runoff and Suspended Sediment Simulation

Ashish Kumar et al.

WATER RESOURCES MANAGEMENT (2019)

添加到收藏夹

Article Water Resources

Estimating the Sediment Flux and Budget for a Data Limited Rift Valley Lake in Ethiopia

Alemu O. Aga et al.

HYDROLOGY (2019)

添加到收藏夹

Article Water Resources

Application of HEC-HMS Model for Flow Simulation in the Lake Tana Basin: The Case of Gilgel Abay Catchment, Upper Blue Nile Basin, Ethiopia

Bilew G. Tassew et al.

HYDROLOGY (2019)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Predicting compressive strength of lightweight foamed concrete using extreme learning machine model

Zaher Mundher Yaseen et al.

ADVANCES IN ENGINEERING SOFTWARE (2018)

添加到收藏夹

Article Water Resources

Evaluation of four hydrological models for operational flood forecasting in a Canadian Prairie watershed

Fisaha Unduche et al.

HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES (2018)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Earthfill dam seepage analysis using ensemble artificial intelligence based modeling

Elnaz Sharghi et al.

JOURNAL OF HYDROINFORMATICS (2018)

添加到收藏夹

Article Engineering, Civil

A probabilistic appraisal of rainfall-runoff modeling approaches within SWAT in mixed land use watersheds

Ali Tasdighi et al.

JOURNAL OF HYDROLOGY (2018)

添加到收藏夹

Article Engineering, Environmental

Improving monthly streamflow prediction in alpine regions: integrating HBV model with Bayesian neural network

Wei Wei Ren et al.

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2018)

添加到收藏夹

Article Engineering, Civil

Forecasting Daily Streamflow for Basins with Different Physical Characteristics through Data-Driven Methods

Sinan Jasim Hadi et al.

WATER RESOURCES MANAGEMENT (2018)

添加到收藏夹

Article Environmental Sciences

Applicability of a Spatially Semi-Distributed Hydrological Model for Watershed Scale Runoff Estimation in Northwest Ethiopia

Demlie G. Zelelew et al.

WATER (2018)

添加到收藏夹

Article Environmental Sciences

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)

添加到收藏夹

Article Environmental Sciences

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

Mohammad Isazadeh et al.

ENVIRONMENTAL EARTH SCIENCES (2017)

添加到收藏夹

Article Engineering, Civil

An Estimation of the Suspended Sediment Load Using Adaptive Network Based Fuzzy Inference System, Support Vector Machine and Artificial Neural Network Models

Meral Buyukyildiz et al.

WATER RESOURCES MANAGEMENT (2017)

添加到收藏夹

Article Computer Science, Artificial Intelligence

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)

添加到收藏夹

Article

Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria

Transactions of the ASABE (2016)

添加到收藏夹

Article Multidisciplinary Sciences

Rainfall-Runoff Modeling Using Support Vector Machine in Snow-Affected Watershed

Fatemeh Sedighi et al.

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2016)

添加到收藏夹

Article Engineering, Civil

Coupling SWAT and ANN models for enhanced daily streamflow prediction

Navideh Noori et al.

JOURNAL OF HYDROLOGY (2016)

添加到收藏夹

Article Environmental Sciences

A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States

Ehsan Olyaie et al.

ENVIRONMENTAL MONITORING AND ASSESSMENT (2015)

添加到收藏夹

Article Environmental Sciences

Improving forecasting accuracy of medium and long-term runoff using artificial neural network based on EEMD decomposition

Wen-chuan Wang et al.

ENVIRONMENTAL RESEARCH (2015)

添加到收藏夹

Article Water Resources

The influence of parametric uncertainty on the relationships between HBV model parameters and climatic characteristics

Marzena Osuch et al.

HYDROLOGICAL SCIENCES JOURNAL (2015)

添加到收藏夹

Article Engineering, Civil

Assessing the capability of the SWAT model to simulate snow, snow melt and streamflow dynamics over an alpine watershed

Youen Grusson et al.

JOURNAL OF HYDROLOGY (2015)

添加到收藏夹

Article Engineering, Multidisciplinary

Prediction models for performance and emissions of a dual fuel CI engine using ANFIS

A. Adarsh Rai et al.

SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES (2015)

添加到收藏夹

Article Engineering, Civil

ANN Based Sediment Prediction Model Utilizing Different Input Scenarios

Haitham Abdulmohsin Afan et al.

WATER RESOURCES MANAGEMENT (2015)

添加到收藏夹

Article Engineering, Civil

Smart low flow signature metrics for an improved overall performance evaluation of hydrological models

Matthias Pfannerstill et al.

JOURNAL OF HYDROLOGY (2014)

添加到收藏夹

Article Transportation Science & Technology

Vehicular traffic noise modeling using artificial neural network approach

Paras Kumar et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2014)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Modeling rainfall-runoff process using soft computing techniques

Ozgur Kisi et al.

COMPUTERS & GEOSCIENCES (2013)

添加到收藏夹

Article Environmental Sciences

Assessment of a conceptual hydrological model and artificial neural networks for daily outflows forecasting

M. Rezaeianzadeh et al.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY (2013)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Improved annual rainfall-runoff forecasting using PSO-SVM model based on EEMD

Wen-chuan Wang et al.

JOURNAL OF HYDROINFORMATICS (2013)

添加到收藏夹

Article Engineering, Civil

A geomorphology-based ANFIS model for multi-station modeling of rainfall-runoff process

Vahid Nourani et al.

JOURNAL OF HYDROLOGY (2013)

添加到收藏夹

Article Engineering, Civil

Suspended sediment modeling using genetic programming and soft computing techniques

Ozgur Kisi et al.

JOURNAL OF HYDROLOGY (2012)

添加到收藏夹

Article Engineering, Civil

Modeling discharge-suspended sediment relationship using least square support vector machine

Ozgur Kisi

JOURNAL OF HYDROLOGY (2012)

添加到收藏夹

Article Engineering, Civil

Two hybrid Artificial Intelligence approaches for modeling rainfall-runoff process

Vahid Nourani et al.

JOURNAL OF HYDROLOGY (2011)

添加到收藏夹

Article Engineering, Civil

Simulation of Runoff and Suspended Sediment Transport Rate in a Basin with Multiple Watersheds

Ching-Nuo Chen et al.

WATER RESOURCES MANAGEMENT (2011)

添加到收藏夹

Article Engineering, Civil

Sensitivity and uncertainty analysis of the conceptual HBV rainfall-runoff model: Implications for parameter estimation

Nibret A. Abebe et al.

JOURNAL OF HYDROLOGY (2010)

添加到收藏夹

Article Automation & Control Systems

A combined neural-wavelet model for prediction of Ligvanchai watershed precipitation

Vahid Nourani et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2009)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM

Ulas Caydas et al.

EXPERT SYSTEMS WITH APPLICATIONS (2009)

添加到收藏夹

Article Engineering, Civil

Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data

M. Cobaner et al.

JOURNAL OF HYDROLOGY (2009)

添加到收藏夹

Article Computer Science, Software Engineering

Software reliability prediction by soft computing techniques

N. Raj Kiran et al.

JOURNAL OF SYSTEMS AND SOFTWARE (2008)

添加到收藏夹

Article Agricultural Engineering

Model evaluation guidelines for systematic quantification of accuracy in watershed simulations

D. N. Moriasi et al.

TRANSACTIONS OF THE ASABE (2007)

添加到收藏夹

Article Meteorology & Atmospheric Sciences

Summarizing multiple aspects of model performance in a single diagram.

KE Taylor

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES (2001)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.