ESTIMASI CURVE NUMBER DAERAH ALIRAN SUNGAI KONAWEHA MENGGUNAKAN CITRA SATELIT DAN DATA TANAH GLOBAL

The Curve Number (CN) method is widely used to estimate surface runoff in watershed hydrology. This study aims to estimate the CN value of the Konaweha Watershed using remote sensing and spatial analysis approaches. Sentinel-2 satellite imagery was utilized to derive land cover information, while soil type data from the Food and Agriculture Organization (FAO) were employed to determine the Hydrologic Soil Group (HSG). The analysis was carried out on the Google Earth Engine (GEE) platform by integrating the land cover map derived from Sentinel-2 classification with the HSG map obtained from FAO soil data. CN values were assigned based on the Soil Conservation Service (SCS) method by linking land cover classes and soil groups. The results indicate that the Konaweha Watershed is dominated by forest and agricultural land cover, with a heterogeneous distribution of HSG. The integration of both datasets produced a spatially distributed CN map with an average value of 52.6, reflecting the hydrological condition of the watershed with relatively good infiltration capacity and moderate surface runoff potential. The findings provide valuable input for hydrological modeling and water resources management planning. This study demonstrates that the integration of Sentinel-2 satellite imagery and FAO soil data through GEE offers a fast, efficient, and reliable approach for CN estimation at the watershed scale.

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Journal
SINERGI Jurnal Riset Ilmiah
Published
2025-08-27
DOI
https://doi.org/10.62335/sinergi.v2i8.1748
Primary Topic
Water and Land Management
Type
article
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article

ESTIMASI CURVE NUMBER DAERAH ALIRAN SUNGAI KONAWEHA MENGGUNAKAN CITRA SATELIT DAN DATA TANAH GLOBAL

Muhammad Fathur Aditya
SINERGI Jurnal Riset Ilmiah
Water and Land Management
article

ESTIMASI CURVE NUMBER DAERAH ALIRAN SUNGAI KONAWEHA MENGGUNAKAN CITRA SATELIT DAN DATA TANAH GLOBAL

Muhammad Fathur Aditya
article en

Abstract

The Curve Number (CN) method is widely used to estimate surface runoff in watershed hydrology. This study aims to estimate the CN value of the Konaweha Watershed using remote sensing and spatial analysis approaches. Sentinel-2 satellite imagery was utilized to derive land cover information, while soil type data from the Food and Agriculture Organization (FAO) were employed to determine the Hydrologic Soil Group (HSG). The analysis was carried out on the Google Earth Engine (GEE) platform by integrating the land cover map derived from Sentinel-2 classification with the HSG map obtained from FAO soil data. CN values were assigned based on the Soil Conservation Service (SCS) method by linking land cover classes and soil groups. The results indicate that the Konaweha Watershed is dominated by forest and agricultural land cover, with a heterogeneous distribution of HSG. The integration of both datasets produced a spatially distributed CN map with an average value of 52.6, reflecting the hydrological condition of the watershed with relatively good infiltration capacity and moderate surface runoff potential. The findings provide valuable input for hydrological modeling and water resources management planning. This study demonstrates that the integration of Sentinel-2 satellite imagery and FAO soil data through GEE offers a fast, efficient, and reliable approach for CN estimation at the watershed scale.

SINERGI Jurnal Riset IlmiahVol. 2(8)
Universitas Sulawesi Tenggara (ID)
Openalex Percentile: Top 69%
Water and Land Management
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