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Verification of surface runoff volume prediction with statistical downscaling method by using climate forecast system version 2 (CFSv2) output
Ernita C.A.a, Fajary F.R.a, Rahayu R.a
a Department of Meteorology, 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]© 2018 Author(s).Surface runoff is one of the factors causing flood. The surface runoff volume prediction is one of important activities to be conducted for flood mitigation. CFSv2 (Climate Forecast System version 2) is a seasonal prediction system that can be used to predict surface runoff volume. However, CFSv2 outputs are relatively coarse which cannot represent well the climate information at local scale. Thus, downscaling of these outputs is needed before continuing to use them to predict surface runoff. One of the methods is statistical bias correction applied to improve the prediction accuracy and skills, and to reduce the bias. The study areas of this research are located at Balangan and Tabalong sub-watershed in South Kalimantan, Indonesia. The study focuses on wet season (December-February). The predicted result of surface runoff volume from CFSv2 output is verified using Brier Score (BS) and Brier Skill Score (BSS). In this study, two schemes are performed to predict surface runoff volume. The results show slightly different values of BS between corrected and raw CFSv2 in both schemes. Scheme 1 uses water surface runoff variable. The corrected CFSv2 output of scheme 1 has BS values ranging from 0.5 to 0.7, and it has positive and negative BSS values where the negative BSS values indicate a low prediction accuracy in predicting high surface runoff. While scheme 2 uses prate (rainfall) variable. The corrected CFSv2 output of scheme 2 has a fairly good accuracy based on BS values ranging from 0.32 to 0.46, and it has positive BSS values. Thus, scheme 2 can be considered to predict the surface runoff volume for flood mitigation.[/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][/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,runoff volume,statistical bias-correction[/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 financially supported by Research, Community Service and Innovation Program (P3MI LPPM) Bandung Institute of Technology. The authors would also like to thanks the members of Weather and Climate Prediction Laboratory (WCPL-ITB) for their contribution to discussions during this research.[/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/10.1063/1.5047340[/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]