Meteorological Water Scarcity Projection for 2021-2035 Based on CMIP6 (Coupled Model Intercomparison Project Phase 6) Scenario in Daerah Istimewa Yogyakarta

Climate change can lead to an imbalance between water demand and supply, resulting in problems such as water scarcity. To avoid this, a projection of the level of water scarcity is needed. Water scarcity is calculated as the percentage of water demand to water supply. This research aims to determine the level of need, availability, and scarcity of meteorological water. This research uses meteorological water supply obtained through Thornthwaite- Mather water balance calculation from CMIP6 rainfall and temperature projection modeling data in SSP2 and SSP5 scenarios. CMIP6 data was corrected using distribution mapping and average ratios methods to improve the distribution and data values. Water demand indicators are reviewed from three sectors, namely domestic water demands, agricultural water demands, and livestock water demands. The water supply calculation results in Daerah Istimewa Yogyakarta (DIY) show a pattern that fluctuates from year to year during the 2021-2035. Meanwhile, water demand continues to increase along with population growth. The level of water scarcity shows that, overall, DIY is classified as not critical to slightly critical in the SSP2 scenario and not critical to critical in the SSP5 scenario. The difference in the level of scarcity is influenced by socio-economic development and climate change mitigation efforts assumed in each scenario. By knowing the projected level of water scarcity, policymakers are expected to pursue appropriate climate change mitigation measures to actualize the best SSP scenario.

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Journal
Jurnal Meteorologi dan Geofisika
Published
2025-03-28
DOI
https://doi.org/10.31172/jmg.v25i1.1063
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Meteorological Water Scarcity Projection for 2021-2035 Based on CMIP6 (Coupled Model Intercomparison Project Phase 6) Scenario in Daerah Istimewa Yogyakarta

Emilya Nurjani, Andung Bayu Sekaranom, A. Prabowo, Malinda Budi Oktaviani et al.
Jurnal Meteorologi dan Geofisika
Data Mining and Machine Learning Applications
article

Meteorological Water Scarcity Projection for 2021-2035 Based on CMIP6 (Coupled Model Intercomparison Project Phase 6) Scenario in Daerah Istimewa Yogyakarta

Emilya Nurjani, Andung Bayu Sekaranom, A. Prabowo, Malinda Budi Oktaviani, Pramuditya Vanesya Putri Febrian Abidin, Asshaffa Naim, Aurelia Zerlinda, Etik Setyaningrum
article en

Abstract

Climate change can lead to an imbalance between water demand and supply, resulting in problems such as water scarcity. To avoid this, a projection of the level of water scarcity is needed. Water scarcity is calculated as the percentage of water demand to water supply. This research aims to determine the level of need, availability, and scarcity of meteorological water. This research uses meteorological water supply obtained through Thornthwaite- Mather water balance calculation from CMIP6 rainfall and temperature projection modeling data in SSP2 and SSP5 scenarios. CMIP6 data was corrected using distribution mapping and average ratios methods to improve the distribution and data values. Water demand indicators are reviewed from three sectors, namely domestic water demands, agricultural water demands, and livestock water demands. The water supply calculation results in Daerah Istimewa Yogyakarta (DIY) show a pattern that fluctuates from year to year during the 2021-2035. Meanwhile, water demand continues to increase along with population growth. The level of water scarcity shows that, overall, DIY is classified as not critical to slightly critical in the SSP2 scenario and not critical to critical in the SSP5 scenario. The difference in the level of scarcity is influenced by socio-economic development and climate change mitigation efforts assumed in each scenario. By knowing the projected level of water scarcity, policymakers are expected to pursue appropriate climate change mitigation measures to actualize the best SSP scenario.

Jurnal Meteorologi dan GeofisikaVol. 25(1)
Universitas Gadjah Mada (ID)
Openalex Percentile: Top 93%
Data Mining and Machine Learning Applications
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Meteorological Water Scarcity Projection for 2021-2035 Based on CMIP6 (Coupled Model Intercomparison Project Phase 6) Scenario in Daerah Istimewa Yogyakarta — Emilya Nurjani, Andung Bayu Sekaranom, et al. · Jurnal Meteorologi dan Geofisika (2025) | TGRS Research Map | TGRS