Monitoring and forecasting water erosion in response to climate change effects using the integration of the global RUSLE/SDR model and predictive models

Applied Soil Ecology, Год журнала: 2025, Номер 206, С. 105910 - 105910

Опубликована: Янв. 28, 2025

Язык: Английский

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Spatio-temporal distribution and prediction of agricultural and meteorological drought in a Mediterranean coastal watershed via GIS and machine learning

Physics and Chemistry of the Earth Parts A/B/C, Год журнала: 2023, Номер 131, С. 103425 - 103425

Опубликована: Июнь 1, 2023

Язык: Английский

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Projected climate change impacts on streamflow in the Upper Oum Er Rbia Basin, Upstream of the Ahmed El Hansali Dam, Morocco

Environmental Challenges, Год журнала: 2025, Номер 18, С. 101101 - 101101

Опубликована: Фев. 3, 2025

Язык: Английский

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Predicting precipitation and NDVI utilization of the multi-level linear mixed-effects model and the CA-markov simulation model

Climate Services, Год журнала: 2025, Номер 38, С. 100554 - 100554

Опубликована: Март 10, 2025

Язык: Английский

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Evaluation of soil texture classification from orthodox interpolation and machine learning techniques

Environmental Research, Год журнала: 2023, Номер 246, С. 118075 - 118075

Опубликована: Дек. 28, 2023

The current investigation examines the effectiveness of various approaches in predicting soil texture class (clay, silt, and sand contents) Rawalpindi district, Punjab province, Pakistan. employed techniques included artificial neural networks (ANNs), kriging, co-kriging, inverse distance weighting (IDW). A total 44 specimens from depths 10-15 cm were gathered, then hydrometer method was adopted to measure their texture. map grain sets formulated ArcGIS environment, utilizing distinct interpolation approaches. MATLAB software used evaluate gradient fraction, latitude longitude, elevation, fragments points proposed an ANN. Several statistical values, such as correlation coefficient (R), geometric mean error ratios (GMER), root square (RMSE), utilized precision intended techniques. In assessing size spatial dissemination clay, sand, ANN superior compared weighting. Still, less than a 50% observed using this examination, IDW had inferior other results demonstrated that practices produced acceptable can be for future research. Soil is among most central variables manipulate agriculture plans. prepared maps exhibiting groups are imperative crop yield pastoral scheduling.

Язык: Английский

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Comparing the ability of different remotely sensed evapotranspiration products in enhancing hydrological model performance and reducing prediction uncertainty

Ecological Informatics, Год журнала: 2023, Номер 78, С. 102352 - 102352

Опубликована: Ноя. 2, 2023

The mitigation of uncertainties in the identification natural systems is a fundamental aspect development hydrological models, and represents major challenge for improvement modelling techniques. In particular, calibration models based on streamflow measurements at outlet catchment exposed to significant sources uncertainty, such as impact landscape features runoff generation. Remote sensing-based actual evapotranspiration (AET) data can be incorporated with improve model accuracy reduce uncertainty modelling, resulting enhancement performance. selection right AET dataset crucial task, front availability multi-source datasets that differ methods, parameters, spatiotemporal resolution. Despite existence few studies proposing usage remote data, there lack systematic comparisons between different products, terms performance modelling. This paper aims compare efficacy products improving simulation responses, both single multi-variable scenarios. this investigation, Soil Water Assessment Tool (SWAT) was calibrated observed by experimenting eight datasets. findings our study suggest incorporation process significantly enhance reliability predictions. Thus, proposed approach contribute effectiveness quantitative tool management water resources. Another finding solely yields reasonable results streamflow, which an advantageous promising feature ungauged basins.

Язык: Английский

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Assessing climate change-driven social flood exposures and flood damage to residential areas in the Solo River basin of Indonesia

Modeling Earth Systems and Environment, Год журнала: 2025, Номер 11(2)

Опубликована: Фев. 24, 2025

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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The Impact of soil data on SWAT modeling: Effects, requirements, and future directions

Scientific African, Год журнала: 2025, Номер unknown, С. 2694 - 2694

Опубликована: Апрель 1, 2025

Язык: Английский

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Sensitivity of Swat Model Parameters for Modeling Streamflow at Bajulmati Watershed, Situbondo—East Java, Indonesia

Lecture notes in civil engineering, Год журнала: 2025, Номер unknown, С. 553 - 561

Опубликована: Янв. 1, 2025

Язык: Английский

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