Accelerating the Identification of Soil Drought Index in Wair Koja Village Using Web-Based Thornthwaite-Mather Water Balance Calculations

Wairkoja Village is one of the villages in the Kewapante Sub-district, Sikka Regency, where drought issues have been identified in several areas of agricultural land. A survey conducted on-site revealed extremely dry soil conditions, and the main crop, maize, had dried up or failed to yield. This research is highly urgent to address the drought problem in the study area. Through this research, it is possible to evaluate drought events, including the drought index, the impact of drought on the economic growth of residents, recommendations for addressing drought issues, and educational information regarding the drought index through web-based digital media. The purpose of this study is to provide information about the drought index at the study location using the Thornthwaite-Mather water balance method and to offer recommendations to farmers regarding the impacts of drought problems (crop failure) based on the levels of the drought index. Additionally, it aims to develop a drought index calculation website using the Thornthwaite-Mather water balance method to deliver information about drought issues in specific areas. This research employs ArcGIS software to analyze data, including soil type maps, land use maps, and topographic maps of the study area. The outputs of this research will provide information on the drought index in the study location using the web-based Thornthwaite-Mather water balance method. This study is classified as basic research with Technology Readiness Level (TRL) 2: formulation of concepts and/or technological applications.

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Publication Details

Journal
Brilliance Research of Artificial Intelligence
Published
2024-12-26
DOI
https://doi.org/10.47709/brilliance.v4i2.5164
Primary Topic
Soil and Land Suitability Analysis
Type
article
Field-Weighted Citation Impact
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article

Accelerating the Identification of Soil Drought Index in Wair Koja Village Using Web-Based Thornthwaite-Mather Water Balance Calculations

Maria Kurniaty Lete, Margaretha Yuneta, Maria Wihelmina Lodan
Brilliance Research of Artificial Intelligence
Soil and Land Suitability Analysis
article

Accelerating the Identification of Soil Drought Index in Wair Koja Village Using Web-Based Thornthwaite-Mather Water Balance Calculations

Maria Kurniaty Lete, Margaretha Yuneta, Maria Wihelmina Lodan
article en

Abstract

Wairkoja Village is one of the villages in the Kewapante Sub-district, Sikka Regency, where drought issues have been identified in several areas of agricultural land. A survey conducted on-site revealed extremely dry soil conditions, and the main crop, maize, had dried up or failed to yield. This research is highly urgent to address the drought problem in the study area. Through this research, it is possible to evaluate drought events, including the drought index, the impact of drought on the economic growth of residents, recommendations for addressing drought issues, and educational information regarding the drought index through web-based digital media. The purpose of this study is to provide information about the drought index at the study location using the Thornthwaite-Mather water balance method and to offer recommendations to farmers regarding the impacts of drought problems (crop failure) based on the levels of the drought index. Additionally, it aims to develop a drought index calculation website using the Thornthwaite-Mather water balance method to deliver information about drought issues in specific areas. This research employs ArcGIS software to analyze data, including soil type maps, land use maps, and topographic maps of the study area. The outputs of this research will provide information on the drought index in the study location using the web-based Thornthwaite-Mather water balance method. This study is classified as basic research with Technology Readiness Level (TRL) 2: formulation of concepts and/or technological applications.

Brilliance Research of Artificial IntelligenceVol. 4(2)
Universitas Nusa Nipa Maumere (ID)
Openalex Percentile: Top 56%
Soil and Land Suitability Analysis
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