Machine learning models for gully erosion susceptibility assessment in the Tensift catchment, Haouz Plain, Morocco for sustainable development

Journal of African Earth Sciences, Journal Year: 2024, Volume and Issue: 213, P. 105229 - 105229

Published: March 11, 2024

Gully erosion is a widespread environmental danger, threatening global socio-economic stability and sustainable development. This study comprehensively applied seven machine learning (ML) models including SVM, KNN, RF, XGBoost, ANN, DT, LR, evaluated gully susceptibility in the Tensift catchment predict it within Haouz plain, Morocco. To ensure reliability of findings, employed robust combination inventory, sentinel images, Digital Surface Model. Eighteen predictors, encompassing topographical, geomorphological, environmental, hydrological factors, were selected after multicollinearity analyses. The revealed that approximately 28.18% at very high risk erosion. Furthermore, 15.13% 31.28% are categorized as low respectively. These findings extend to where 7.84% surface area highly risking erosion, while 18.25% 55.18% characterized areas. gauge performance ML models, an array metrics specificity, precision, sensitivity, accuracy employed. highlights XGBoost KNN most promising achieving AUC ROC values 0.96 0.93 test phase. remaining namely RF (AUC = 0.89), LR 0.80), SVM 0.81), DT 0.86), ANN 0.78), also displayed commendable performance. novelty this research its innovative approach combat through cutting edge offering practical solutions for watershed conservation, management, prevention land degradation. insights invaluable addressing challenges posed by region, beyond geographical boundaries can be used defining appropriate mitigation strategies local national scale.

Language: Английский

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Comparative analysis of GIS and RS based models for delineation of groundwater potential zone mapping

Geomatics Natural Hazards and Risk, Journal Year: 2023, Volume and Issue: 14(1)

Published: June 1, 2023

Groundwater is a crucial natural resource that varies in quality and quantity across Khyber Pakhtunkhwa (KPK), Pakistan. Increased population urbanization place enormous demands on groundwater supplies, reducing both their quantity. This research aimed to delineate the potential zone Kohat region, Pakistan by integrating twelve thematic layers. In current research, Potential Zone (GWPZ) were created implementing Weight of Evidence (WOE), Frequency Ratio (FR), Information Value (IV) models region. this study, we used Sentinel-2 satellite data utilized generate an inventory map using machine learning algorithms Google Earth Engine (GEE). Furthermore, validation was done with field survey ground data. The divided into training (80%) testing (20%) datasets. WOE, FR, IV are applied assess relationship between factors GWPZ Finally, results Area Under Curve (AUC) technique for 88%, 91%, 89%. final can aid better future planning exploration, management, supply water

Language: Английский

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Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone

International Journal of Digital Earth, Journal Year: 2023, Volume and Issue: 16(1), P. 3105 - 3124

Published: Aug. 10, 2023

In this research, we used the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) to predict annual rate of soil loss in District Chakwal Pakistan. The parameters RUSLE model were estimated using remote sensing data, erosion probability zones determined GIS. length slope (LS), crop management (C), rainfall erosivity (R), erodibility (K), support practice (P) range from 0–68,227, 0–66.61%, 0–0.58, 495.99–648.68 MJ/mm.t.ha−1.year−1, 0.15–0.25 1 respectively. results indicate that total potential approximately 4,67,064.25 t.ha−1.year−1 is comparable with measured sediment 11,631 during water year 2020. predicted due an increase agricultural area 164,249.31 t.ha−1.year−1. study, also Landsat imagery rapidly achieve actual land use classification. Meanwhile, 38.13% region was threatened by very high erosion, where quantity ranged 365487.35 Integrating GIS helped researchers their final objectives. Land-use planners decision-makers result's spatial distribution for conservation planning.

Language: Английский

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Improved soil carbon stock spatial prediction in a Mediterranean soil erosion site through robust machine learning techniques

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(2)

Published: Jan. 10, 2024

Language: Английский

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Dredged materials in Morocco: Current practices, policies, and roadmap for sustainable management

Case Studies in Construction Materials, Journal Year: 2024, Volume and Issue: 20, P. e03045 - e03045

Published: March 13, 2024

Dredging is essential for maintaining navigable waters in ports, rivers, and dams, but it faces environmental scrutiny as the push industrial circularity intensifies. The management of dredged materials (DMs) presents a unique challenge opportunity, especially Morocco, where there notable gap research application. This paper conducts two-pronged exploration: critically assesses Morocco's legislative environment concerning DMs, highlighting its strengths shortcomings, evaluates potential DMs civil engineering projects, illustrating their alignment with 11 17 UN Sustainable Development Goals. Central to this stakeholder survey that sheds light on perceived benefits, obstacles, socio-political hindrances DM adoption construction sector. In exploration DMs' advantageous applications, identified key challenges utilization management. Market entry DM-derived products impeded by absence standardized safety regulations. Additionally, transportation costs represent substantial practical hurdle leverage beneficially. Nonetheless, exists discernible willingness among end users adopt containing within operations, despite prevalent lack awareness regarding intrinsic benefits properties DMs. Collectively, study not only vivid snapshot Morocco also charts pathway researchers, policymakers, industry stakeholders collaboratively champion sustainable circular economy practices dredging

Language: Английский

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Modeling Current and Future Run-off and Soil Erosion Dynamics in Eastern Mediterranean Ecosystems Using the WEPP Model

Energy Nexus, Journal Year: 2025, Volume and Issue: unknown, P. 100375 - 100375

Published: Feb. 1, 2025

Language: Английский

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Projections of rainfall erosivity in climate change scenarios for mainland China

CATENA, Journal Year: 2023, Volume and Issue: 232, P. 107391 - 107391

Published: July 27, 2023

Language: Английский

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Advances in sheet erosion and rainfall simulator performance: A comprehensive review

CATENA, Journal Year: 2024, Volume and Issue: 248, P. 108601 - 108601

Published: Nov. 26, 2024

Language: Английский

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Robustness of Optimized Decision Tree-Based Machine Learning Models to Map Gully Erosion Vulnerability

Soil Systems, Journal Year: 2023, Volume and Issue: 7(2), P. 50 - 50

Published: May 16, 2023

Gully erosion is a worldwide threat with numerous environmental, social, and economic impacts. The purpose of this research to evaluate the performance robustness six machine learning ensemble models based on decision tree principle: Random Forest (RF), C5.0, XGBoost, treebag, Gradient Boosting Machines (GBMs) Adaboost, in order map predict gully erosion-prone areas semi-arid mountain context. first step was prepare inventory data, which consisted 217 points. This database then randomly subdivided into five percentages Train/Test (50/50, 60/40, 70/30, 80/20, 90/10) assess stability models. Furthermore, 17 geo-environmental variables were used as potential controlling factors, several metrics examined results revealed that all performed well terms predicting vulnerability erosion. C5.0 RF had best prediction (AUC = 90.8 AUC 90.1, respectively). However, according random subdivisions database, these exhibit small but noticeable instability, high for 80/20% 70/30% subdivisions. demonstrates significance refining need test various splitting data ensure efficient reliable output results.

Language: Английский

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Rapid magnetic susceptibility measurement as a tracer to assess the erosion–deposition process using tillage homogenization and simple proportional models: A case study in northern of Morocco

International Journal of Sediment Research, Journal Year: 2023, Volume and Issue: 38(5), P. 739 - 753

Published: June 8, 2023

Language: Английский

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