Enhancing Streamflow Prediction Physically Consistently Using Process-Based Modeling and Domain Knowledge: A Review

Sustainability, Journal Year: 2024, Volume and Issue: 16(4), P. 1376 - 1376

Published: Feb. 6, 2024

Streamflow prediction (SFP) constitutes a fundamental basis for reliable drought and flood forecasting, optimal reservoir management, equitable water allocation. Despite significant advancements in the field, accurately predicting extreme events continues to be persistent challenge due complex surface subsurface watershed processes. Therefore, addition framework, numerous techniques have been used enhance accuracy physical consistency. This work provides well-organized review of more than two decades efforts SFP physically consistent way using process modeling flow domain knowledge. covers hydrograph analysis, baseflow separation, process-based (PBM) approaches. paper an in-depth analysis each technique discussion their applications. Additionally, existing are categorized, revealing research gaps promising avenues future research. Overall, this offers valuable insights into current state enhanced within consistent, knowledge-informed data-driven framework.

Language: Английский

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Monthly River Discharge Forecasting Using Hybrid Models Based on Extreme Gradient Boosting Coupled with Wavelet Theory and Lévy–Jaya Optimization Algorithm

Water Resources Management, Journal Year: 2023, Volume and Issue: 37(10), P. 3953 - 3972

Published: June 9, 2023

Language: Английский

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Bayesian joint longitudinal models for assessing the exploitation rates of sardine stock in the Mediterranean Sea

Stochastic Environmental Research and Risk Assessment, Journal Year: 2024, Volume and Issue: 38(4), P. 1635 - 1646

Published: Jan. 12, 2024

Abstract The European sardine is a pelagic species of great ecological importance for the conservation Mediterranean Sea as well economic countries. Its fishing has suffered significant decline in recent years due to various economic, cultural and reasons. This paper focuses on evolution catches from 1985 2018 according country type practised, artisanal industrial. We propose three Bayesian longitudinal linear mixed models assess differences temporal industrial fisheries between within Overall results confirm that fishery time series are highly diverse along their dynamics this heterogeneity persistent throughout time. Furthermore, our highlight positive correlation fishing. Finally, study observes consistent decreasing trend quantity fish landings. Although causes feature could be also linked motivations (such reduction demand or reorientation fleets towards more commercially beneficial species), it may indicate potential risk stock Sea.

Language: Английский

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Machine learning modeling of base flow generation potential: A case study of the combined application of BWM and Fallback bargaining algorithm

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 636, P. 131220 - 131220

Published: April 19, 2024

Language: Английский

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A comparative study of daily streamflow forecasting using firefly, artificial bee colony, and genetic algorithm-based artificial neural network

Acta Geophysica, Journal Year: 2024, Volume and Issue: 72(6), P. 4575 - 4595

Published: May 15, 2024

Language: Английский

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Proxy-based Bayesian inversion of strain tensor data measured during well tests

Geomechanics for Energy and the Environment, Journal Year: 2023, Volume and Issue: 36, P. 100506 - 100506

Published: Sept. 22, 2023

Language: Английский

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Assessing the performance of machine learning algorithms for analyzing land use changes in the Hyrcanian forests of Iran

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 30, 2024

Language: Английский

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Sediment yield modelling using SDR and MUSLE with high resolution satellite precipitation dataset in an ungauged basin

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: March 1, 2023

Abstract Erosion has become one of the extreme ecological dangers in up to date. Decrease minerals upper layer soil leads failure sustainable crop practices. Many researchers have developed prediction models Sediment Yield (SY) gauged basins. But modelling for an ungauged basin is very difficult due difficulty validating predicted model. The primary goal study was identify sedimentation area using multiple(SY) methodologies, including Delivery Ratio (SDR) and Modified Universal Soil Loss Equation (MUSLE), with a high-resolution satellite precipitation dataset.. Different attributes such as LULC (land use / land cover), texture, precipitation, topography, etc. incorporated estimate SY Ponnaniyar river basin,. generated map from SDR MUSLE evaluated by receiver operating characteristic curve (ROC). model found be efficient method determining basin, also satisfied criteria AUC value 0.752. severely affected sub-watershed identified help erosion yield spatial map. obtained results will prioritize locating water harvesting structures further studies. This suggests placing gauging station monitor daily observation discharge estimation prevent loss during flash flooding.

Language: Английский

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Radon in Hydrograph Separation and Water Balance Studies

Environmental science and engineering, Journal Year: 2023, Volume and Issue: unknown, P. 109 - 124

Published: Jan. 1, 2023

Language: Английский

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