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p-Index From 2021 - 2026
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All Journal West Science Interdisciplinary Studies West Science Interdisciplinary Studies West Science Social and Humanities Studies
Dicky Artha
State University of Gorontalo
Humanities Economics, Econometrics & Finance Environmental Science Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Prediction of Forest and Land Rehabilitation Impacts on Peak Discharge, Erosion, and Sedimentation Reduction in The Piloliyanga Micro Catchment, Modelomo Watershed Dicky Artha; Iswan Dunggio; Sukirman Rahim
West Science Social and Humanities Studies Vol. 4 No. 05 (2026): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v4i05.2881

Abstract

Watershed degradation contributes to increased peak discharge, erosion, and sedimentation in downstream areas. Forest and Land Rehabilitation (FLR) has become an important approach for restoring hydrological functions through increasing vegetation cover and controlling surface runoff. This study aimed to analyze the predicted impacts of FLR on peak discharge, erosion, and sedimentation in the Piloliyanga micro-catchment, Modelomo Watershed. The study employed a quantitative descriptive approach based on Geographic Information Systems (GIS), hydrological analysis, and land cover change simulation. Erosion analysis was conducted using the Universal Soil Loss Equation (USLE), while sedimentation was estimated using the Sediment Delivery Ratio (SDR) approach. The results showed that FLR has the potential to reduce peak discharge, erosion, and sedimentation through increased infiltration and vegetation interception. The novelty of this study lies in the integration of USLE, SDR, and land cover change simulation within a tropical micro-catchment watershed scale. The findings imply that watershed-based vegetative rehabilitation can improve hydrological stability and support land degradation control in the upstream area of the Modelomo Watershed.
Attributing Climate vs. Land-Cover Effects on Watershed Hydrology and Water Quality: A Systematic Review of Modeling and Statistical Frameworks Dicky Artha; Fitriyane Lihawa; Dewi Wahyuni K Baderan
West Science Interdisciplinary Studies Vol. 3 No. 12 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i12.2515

Abstract

Climate change and land-use/land-cover (LULC) dynamics jointly reshape watershed hydrology and water quality, yet their relative contributions remain difficult to isolate across regions, indicators, and methods. This systematic review synthesizes 28 peer-reviewed studies (2000–2025) that explicitly attribute or partition climate and LULC effects on streamflow, water yield, evapotranspiration, baseflow, and multiple water-quality indicators (e.g., nutrients, sediments, dissolved organic matter, salinity/alkalinity, and contaminant mixtures). Studies were grouped into four synthesis themes: (i) conceptualizations and study designs, (ii) process-based and hybrid modeling frameworks, (iii) statistical and decomposition approaches, and (iv) cross-context patterns and water-quality attribution. Across the evidence base, attribution outcomes are strongly conditioned by methodological choices—especially baseline definition, construction of climate-only and LULC-only counterfactuals, spatial and temporal scale, and the metric used to express contributions (e.g., scenario contrasts, sensitivities, or variance explained). Long-term water-balance responses are often attributed primarily to climate forcing, while water-quality outcomes are more frequently attributed to LULC and direct anthropogenic pressures, with climate acting as a key modulator of transport pathways and exposure. We conclude that robust climate–LULC attribution requires explicit counterfactual design, integrated use of process-based and data-driven frameworks, explicit representation of interactions, and routine uncertainty analysis to support context-sensitive watershed management and climate adaptation.
Attributing Climate vs. Land-Cover Effects on Watershed Hydrology and Water Quality: A Systematic Review of Modeling and Statistical Frameworks Dicky Artha; Fitriyane Lihawa; Dewi Wahyuni K Baderan
West Science Interdisciplinary Studies Vol. 3 No. 12 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i12.2515

Abstract

Climate change and land-use/land-cover (LULC) dynamics jointly reshape watershed hydrology and water quality, yet their relative contributions remain difficult to isolate across regions, indicators, and methods. This systematic review synthesizes 28 peer-reviewed studies (2000–2025) that explicitly attribute or partition climate and LULC effects on streamflow, water yield, evapotranspiration, baseflow, and multiple water-quality indicators (e.g., nutrients, sediments, dissolved organic matter, salinity/alkalinity, and contaminant mixtures). Studies were grouped into four synthesis themes: (i) conceptualizations and study designs, (ii) process-based and hybrid modeling frameworks, (iii) statistical and decomposition approaches, and (iv) cross-context patterns and water-quality attribution. Across the evidence base, attribution outcomes are strongly conditioned by methodological choices—especially baseline definition, construction of climate-only and LULC-only counterfactuals, spatial and temporal scale, and the metric used to express contributions (e.g., scenario contrasts, sensitivities, or variance explained). Long-term water-balance responses are often attributed primarily to climate forcing, while water-quality outcomes are more frequently attributed to LULC and direct anthropogenic pressures, with climate acting as a key modulator of transport pathways and exposure. We conclude that robust climate–LULC attribution requires explicit counterfactual design, integrated use of process-based and data-driven frameworks, explicit representation of interactions, and routine uncertainty analysis to support context-sensitive watershed management and climate adaptation.
Co-Authors Dewi Wahyuni K Baderan Fitriyane Lihawa Iswan Dunggio Sukirman Rahim