Impact of climate change on the hydrological regime in a small watershed of the tropical Andean Plateau

Sustainable Water Resources Management, Год журнала: 2025, Номер 11(2)

Опубликована: Фев. 19, 2025

Язык: Английский

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Multi-gauge calibration comparison for simulating streamflow across the Major River Basins in Madagascar: SWAT + Toolbox, R-SWAT, and SWAT + Editor Hard calibration

Hydrology Research, Год журнала: 2024, Номер 55(3), С. 412 - 430

Опубликована: Фев. 27, 2024

Abstract This paper aims to improve the Soil and Water Assessment Tool (SWAT) model performance across Major River Basins in Madagascar (MRBM), specifically for SWAT simulation Manambolo, Onilahy, Mananara, Mandrare basins. A multi-gauge calibration was carried out compare of SWAT+ Toolbox, R-SWAT, Editor Hard on a monthly time step periods 1982–1999. We found that generated greater surface runoff, while resulted higher groundwater flow both CSFR CHIRPS datasets. It has been demonstrated Toolbox had more potential calibrating runoff MRBM compared R-SWAT. Calibration methods led reduction percolation, water yield, curve number but increased lateral flow, evapotranspiration (ET), flow. The results showed calibrations did not significantly enhance single-site calibration. within R-SWAT unsatisfactory most basins (NSE < 0) except Betsiboka, Mahavavy, Tsiribihina, Mangoro, Mangoky = 0.40–0.70; R2 0.45–0.80, PBIAS≤ ±25), whether considering or Further study is still required address this issue.

Язык: Английский

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Assessment of land use/ land cover change derived catchment hydrologic response: An integrated parsimonious hydrological modeling and alteration analysis based approach

Journal of Environmental Management, Год журнала: 2024, Номер 356, С. 120637 - 120637

Опубликована: Март 22, 2024

Язык: Английский

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Retrieval of sea ice thickness from FY-3E data using Random Forest method

Advances in Space Research, Год журнала: 2024, Номер 74(1), С. 130 - 144

Опубликована: Март 28, 2024

Язык: Английский

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Quality control of hourly rain gauge data based on radar and satellite multi-source data

Journal of Hydroinformatics, Год журнала: 2024, Номер 26(5), С. 1042 - 1058

Опубликована: Апрель 18, 2024

ABSTRACT Rain gauge networks provide direct precipitation measurements and have been widely used in hydrology, synoptic-scale meteorology, climatology. However, rain observations are subject to a variety of error sources, quality control (QC) is required ensure the reasonable use. In order enhance automatic detection ability anomalies data, novel multi-source data (NMQC) method proposed for hourly data. It employs phased strategy reduce misjudgment risk caused by uncertainty from radar satellite remote-sensing measurements. NMQC applied QC more than 24,000 hydro-meteorological stations Yangtze River basin 2020. The results show that its ratio anomalous 1.73‰, only 1.73% which suspicious needing be confirmed experts. Moreover, distribution characteristics anomaly consistent with climatic study region as well measurement maintenance modes gauges. Overall, has strong label automatically, while identifying lower proportion can greatly manual intervention shorten impact time operational work.

Язык: 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, Год журнала: 2024, Номер 72(6), С. 4575 - 4595

Опубликована: Май 15, 2024

Язык: Английский

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Enhancing streamflow drought prediction: integrating wavelet decomposition with deep learning and quantile regression neural network models

Earth Science Informatics, Год журнала: 2025, Номер 18(2)

Опубликована: Фев. 1, 2025

Язык: Английский

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Neural Networks and Fuzzy Logic-Based Approaches for Precipitation Estimation: A Systematic Review

Ingeniería e Investigación, Год журнала: 2025, Номер 44(3), С. e108609 - e108609

Опубликована: Янв. 31, 2025

Precipitation estimation at the river basin level is essential for watershed management, analysis of extreme events and weather climate dynamics, hydrologic modeling. In recent years, new approaches tools such as artificial intelligence techniques have been used precipitation estimation, offering advantages over traditional methods. Two major paradigms are neural networks fuzzy logic systems, which can be in a wide variety configurations, including hybrid modular models. This work presents literature review on metaheuristic models based signal processes, focusing applications these estimation. The selection comparison criteria were model type, input output variables, performance metrics, fields application. An increase number this type studies was identified, mainly involving network models, tend to get more sophisticated according availability quality training data. On other hand, hybridize with There still challenges related prediction spatial temporal resolution micro-basin levels, but, overall, very promising analysis.

Язык: Английский

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ANALYSIS OF SWAT+ MODEL PERFORMANCE: A COMPARATIVE STUDY USING DIFFERENT SOFTWARE AND ALGORITHMS

Environmental Modelling & Software, Год журнала: 2025, Номер unknown, С. 106425 - 106425

Опубликована: Март 1, 2025

Язык: Английский

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Enhancing daily runoff prediction: A hybrid model combining GR6J-CemaNeige with wavelet-based gradient boosting technique

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 133114 - 133114

Опубликована: Март 1, 2025

Язык: Английский

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