Performance of Wanggu Watershed Management Based on Land Indicators DOI Creative Commons

Kahirun,

Nurnaningsih Hamzah,

Arwan A. Rahman

et al.

Indonesian Journal of Environmental Management and Sustainability, Journal Year: 2023, Volume and Issue: 7(3), P. 116 - 127

Published: Sept. 14, 2023

Based on the study, it was found that land in Wanggu Watershed is highly dynamic due to community activities such as agriculture, plantations, forestry, and settlement development. This can affect performance carrying capacity of watershed. The purpose study evaluate watershed management analyze land-carrying based indicators land. parameters analyzed were percentage critical area, vegetation cover, erosion index. To obtain data needed for both primary secondary used. Primary obtained through overlay base map a land, making cover maps, calculating prediction analysis Watershed. Secondary from related agencies form data, literature, policy documents, reports are relevant performance. results showed somewhat area 16.07 percent, which means this value still qualifies high category recovery. especially forest 27.10 bad condition. average index 2.00, high. these three condition Watershed, has poor with 50. Overall, highlights need better conservation improve its capacity.

Language: Английский

Assessing soil erosion risk in Meghalaya, India: integrating geospatial data with RUSLE model DOI
Naveen Badavath, Smrutirekha Sahoo, Rasmiranjan Samal

et al.

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: April 12, 2024

Language: Английский

Citations

4
Identificación de áreas erosionadas y en riesgo de erosión utilizando imágenes Landsat 8 OLI y Sentinel-2, procesamiento digital y SIG DOI Creative Commons
Cristopher Camargo Roa, C. Pacheco, Tatiana Gómez-Orgulloso

et al.

Revista de Ciencias, Journal Year: 2025, Volume and Issue: 27(2)

Published: March 5, 2025

El objetivo de esta investigación fue identificar y comparar Áreas Erosionadas en Riesgo De Erosión (EAER, por sus siglas inglés) como indicadores degradación suelos erosión hídrica una cuenca hidrográfica empleando imágenes Landsat 8 OLI Sentinel-2. Para ello, se emplearon técnicas procesamiento digital Sistemas Información Geográfica (SIG), enfocándose los datos espectrales reflectancia satelitales. estudio implicó estimaciones del Potencial Hídrica (RPEH), generación cartografías EAER a partir cálculo distancia espectral euclidiana desnudos técnica percepción remota seleccionada mediante regresión lineal. Se determinaron curvas ROC (Características Operativas Receptor) para definir umbrales clasificación, cuales fueron validados clasificaciones supervisadas asociados valores RPEH. Los resultados indican que EAER1 identificaron más áreas erosionadas EAER2. igual modo, evidenció derivados Sentinel-2 tuvieron mayores aciertos 8. análisis RPEH, además las desarrolladas otros criterios, podrían ayudar considerar medidas necesarias conservación suelos.

Citations

0
Advancing Soil Erosion Assessment: Application of Remote Sensing and Geospatial Techniques in Bulango Ulu Reservoir Basin DOI Creative Commons
Muhammad Ramdhan Olii,

Bambang Agus Kironoto,

Aleks Olii

et al.

E3S Web of Conferences, Journal Year: 2024, Volume and Issue: 476, P. 01041 - 01041

Published: Jan. 1, 2024

Soil erosion is an important concern due to the steepness of terrain and significant elevation differential between upstream downstream regions basin. Revised Universal Loss Equation (RUSLE) was integrated with Remote Sensing (RS) Geographic Information System (GIS) in current work establish annual soil map Bulango Ulu Reservoir The RUSLE model incorporated zonation features such as rainfall erosivity, erodibility, topographic, vegetation cover, conservation support practices. results show that 0 110.31 t year −1 are minimum maximum erosion, average rate 17.30 present study area. risk were divided into five categories: very slight, moderate, severe extremely areal extent area percentages 229.17 km 2 (94.48%), 7.83 km2 (3.23%), 4.25 (1.75%), 1.20 (0.50%), 0.12 (0.05%), respectively. Area Under Curve indicated had good performance (75.1%). This demonstrates utility GIS remote sensing for predicting allowing information be extracted implementing programs reservoir

Language: Английский

Citations

2
Soil redistribution rates along the forested and cultivated steep hillslope in the mid‐Himalayas using fallout—137Cs and RUSLE model DOI
Anu David Raj, Suresh Kumar, K. R. Sooryamol

et al.

Land Degradation and Development, Journal Year: 2024, Volume and Issue: 35(16), P. 4795 - 4813

Published: Aug. 20, 2024

Abstract Soil erosion emerged as a significant land degradation concern, causing serious threat to soil ecosystem services in the Himalayan region. The complex topography of region poses limitations measurement redistribution (erosion, transport, and deposition) rate, necessitated for effective conservation planning. study investigated processes over typical hillslope mid‐Himalayan using fallout radionuclide (FRN)— 137 Cs method Revised Universal Loss Equation (RUSLE) model. It involved comparison measured RUSLE model estimates, aiming assess its correspondence hillslope. Analysis measurements revealed highest net (−13.2 t ha −1 year ) at upper with convex shape, while sediment deposition occurred lower (36.9 valley (32.5 positions concave shape. also estimated on (−12.3 but lowest (−0.88 (−0.32 hillslopes, that differed method. provided rate (either or deposition), whereas only showed gross rate. Thus, estimate from corresponds straight shapes. distribution has clearly influence slope shape steepness governing shapes, respectively. In addition, terraces effectively trap sediments upslope areas. Investigation along helped validate positions. will help suggest suitable measures various

Language: Английский

Citations

2
Utilizing Machine Learning and DSAS to Analyze Historical Trends and Forecast Future Shoreline Changes Along the River Niger, Niger Delta DOI Creative Commons

Desmond Rowland Eteh,

Moses Paaru,

Francis E. Egobueze

et al.

Water Conservation Science and Engineering, Journal Year: 2024, Volume and Issue: 9(2)

Published: Dec. 1, 2024

Language: Английский

Citations

2
Flood Susceptibility Mapping for Kedah State, Malaysia: Geographics Information System-Based Machine Learning Approach DOI Creative Commons
Tahmina Afrose, Sreeramanan Subramanıam,

S B Siventhiran

et al.

Medical Journal of Dr D Y Patil Vidyapeeth, Journal Year: 2024, Volume and Issue: 17(5), P. 990 - 1003

Published: June 24, 2024

A BSTRACT Background: The world economy is significantly impacted by floods. Identifying flood risk essential to mitigation techniques. Aim: primary goal of this study create a geographic information system (GIS)-based susceptibility map for the area. Methods: Ten flood-influencing factors from geospatial database were taken into account when mapping flood-prone areas. Every element demonstrated robust relationship with probability flooding. Results: highest contributing elements disaster in region drainage density, distance, and curvature. Flood models’ performance was validated using standard statistical measures AUC. ROC curves that all ensemble models had good on validation data sets (AUC = >0.97) high accuracy scores 0.80. Based maps, most northwest regions area are more likely because low land areas, areas lower gradient slope, linear concave shape curvature, density rainfall, “water bodies,” “crops land,” “built areas,” abundance sea surface water, Quaternary types soil feature so on. very class accounts 18.2% area, according RF-embedding model, whereas high, moderate, low, classes found at about 20.0%, 24.6%, 24.3%, 12.9%, respectively. Conclusion: In comparison other commonly used applied approaches, research presents novel modeling approach integrates machine learning data. It has been be stronger efficient, highly accurate, prediction performance, less biased. Overall, our learning-based solutions points positive path technologically can serve as reference manual future applications academic specialists decision-makers.

Language: Английский

Citations

1
Identification of Eroded and Erosion Risk Areas Using Remote Sensing and GIS in the Quebrada Seca watershed DOI Creative Commons
Cristopher Camargo Roa, C. Pacheco, Sergio Alberto Monjardín-Armenta

et al.

Ingeniería e Investigación, Journal Year: 2023, Volume and Issue: 43(3), P. e105003 - e105003

Published: Aug. 4, 2023

The aim of this research was to identify eroded areas and at risk erosion (EAER) as indicators soil degradation by water in a semiarid watershed the Venezuelan Andes 2017. To effect, remote sensing techniques geographic information systems (GIS) were used, focusing on spectral reflectance data from satellite image, given absence continuous pluviographic properties developing countries. This methodology involved estimating potential (PWER) mapping based calculating Euclidean distance bare soils technique, which selected via linear regression. Receiver operating characteristics (ROC) curves determined define classification thresholds, validated means supervised associated PWER values. main results indicate that EAER1 identified more with (229,77 ha) opposed EAER2 (195,57 ha). Similarly, it evident first alternative successful second (sum three principal components). analysis, addition developed other criteria, such mini-mum area size interest, could help consider necessary conservation measures.

Language: Английский

Citations

2
Perceived effect of soil erosion on maize production in Imo State, Nigeria DOI Open Access

Juochi P. Okoroh,

Daniella C. Irebuisi

Journal of Agriculture and Food Sciences, Journal Year: 2024, Volume and Issue: 22(1), P. 99 - 117

Published: Aug. 6, 2024

This study analyzed the perceived effects of soil erosion on maize production in Imo State, Nigeria. Specifically, ascertained causes as by farmers; farmers’ production; identified control measure used farmers coping with their and constraints to use measures. A multistage sampling procedure was selection 180 farmers. Data were collected using structured questionnaire descriptive statistical tools Ordinary Least Square (OLS) regression analysis. Results showed that include: excessive/heavy rainfall flooding (x̄ = 3.107), overgrazing ((x̄ 2.96), deforestation/ destruction vegetation ( x̄ 2.80), blocked or poor drainage system 2.77 among others. Farmers decline yield when erodes 3.46); food insecurity poverty 3.22); reduction land for agricultural activities 3.32) Maize filling affected area farm residue (86.67%), raising ridges prevent water from running through (76.11%), building structures should not obstruct ways (68.33%), implementing cover crops, mulching, crop (61.67%). constrained such inadequate funding (78.89%), high cost some measures (73.33%), lack incentive governments (70.00%), difficulty acquiring forest establishment (68.89%). The result shows age, marital status, level education, household size, monthly income extension contact influenced production, these significant at 1% probability level. concludes there prevalence experiencing constrains reducing production. recommends others judiciously cooperative association sharing relevant information minimizing land.

Language: Английский

Citations

0
Performance of Wanggu Watershed Management Based on Land Indicators DOI Creative Commons

Kahirun,

Nurnaningsih Hamzah,

Arwan A. Rahman

et al.

Indonesian Journal of Environmental Management and Sustainability, Journal Year: 2023, Volume and Issue: 7(3), P. 116 - 127

Published: Sept. 14, 2023

Based on the study, it was found that land in Wanggu Watershed is highly dynamic due to community activities such as agriculture, plantations, forestry, and settlement development. This can affect performance carrying capacity of watershed. The purpose study evaluate watershed management analyze land-carrying based indicators land. parameters analyzed were percentage critical area, vegetation cover, erosion index. To obtain data needed for both primary secondary used. Primary obtained through overlay base map a land, making cover maps, calculating prediction analysis Watershed. Secondary from related agencies form data, literature, policy documents, reports are relevant performance. results showed somewhat area 16.07 percent, which means this value still qualifies high category recovery. especially forest 27.10 bad condition. average index 2.00, high. these three condition Watershed, has poor with 50. Overall, highlights need better conservation improve its capacity.

Language: Английский

Citations

0