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The evaluation of drought indices: Standard Precipitation Index, Standard Precipitation Evapotranspiration Index, and Palmer Drought Severity Index in Cilacap-Central Java
Balbo F.a, Wulandari R.A.a, Nugraha M.R.R.a, Dwiandani A.a, Syahputra M.R.a, Suwarman R.a
a Atmospheric Science Research Group, Bandung Institute of Technology, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 IOP Publishing Ltd. All rights reserved.The Cilacap Regency-Central Java, is the largest agricultural area with a high level of drought vulnerability. This study aims to evaluate three indices in quantifying a drought condition in Cilacap Regency and its application in forecasting. The indices that were used in this study are Standard Precipitation Index (SPI), Standard Precipitation Evapotranspiration Index (SPEI), and Palmer Drought Severity Index (PDSI). The comparison between SPI and SPEI shows that there is no significant difference in terms of determining the drought severity. SPEI should be used when there is a temperature difference more than 2°C in 30 years. PDSI may provide more frequency of drought event and a good result in indicating the effects of drought on agricultural productivity. We used Climate Forecast System Version 2 (CFSv2) to predict drought severity by SPI. The result of model prediction shows that there is no significant improvement in accuracy before and after statistical bias correction. The prediction can be done on three months (lead3) before initial planting.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Agricultural productivity,CFSv2,Drought conditions,Palmer drought severity indices,PDSI,SPEI,Standard precipitation indices,Temperature differences[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]CFSv2,drought,PDSI,SPEI[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]This research is partly funded by Research, Community Service and Innovation Program (P3MI LPPM) Bandung Institute of Technology. The authors would like to thanks to Indonesian Meteorological Climatological and Geophysical Agency (BMKG), Plantation and Forestry Service of Cilacap Regency, and Center of Statistic Agency of Cilacap (BPS-Cilacap) for providing data.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1755-1315/303/1/012012[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]