Open AccessDYNAMICS PATTERNS OF INFLOW IN THE RESERVOIR THAT OPERATED FOR TWO DECADES
Author(s) -
Heriantono Waluyadi,
Pitojo Tri Juwono,
Widandi Soetopo,
Rispiningtati,
Lily Montarcih Limantara,
Djoko Legono
Publication year - 2021
Publication title -
xi'nan jiaotong daxue xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 21
ISSN - 0258-2724
DOI - 10.35741/issn.0258-2724.56.4.10
Subject(s) - climatology , environmental science , sea surface temperature , anomaly (physics) , watershed , el niño southern oscillation , inflow , water year , hydrology (agriculture) , oceanography , geography , geology , drainage basin , physics , cartography , geotechnical engineering , machine learning , computer science , condensed matter physics
Climate change in the past 20 years brings significant alteration in the earth surface. It affects extremely anomaly temperature, such as the ENSO, IOD, and SOI phenomena. The Pacific Ocean Region, the Indian Ocean Region, and the Darwin – Tahiti Region undergo an increase and a decrease in the sea surface temperatures (SST); thus, it can lead to seasonal change in Indonesia. Due to ENSO, IOD, and SOI, climate change also highly affects the operation pattern of reservoirs, food production, and other commodities. This research used SST data (Nino 1.2, Nino 3, Nino 3.4, Nino 4, IOD West, IOD East, and SOI) from National Oceanic and Atmospheric Administration (NOAA) and rainfall data from 1998 to 2018 of nine stations at Wonogiri Reservoir watershed. Trend analysis of the SST index indicated an increase in trend SST index. Trend analysis of monthly rainfall average at Wonogiri Watershed area indicated a decrease in January, March, April, May, June, July, August, and October, while it increased in February, September, November, and December. Multiple linear regression analysis with the stepwise regression method indicated that during the rainy season, the rainfall at Wonogiri Watershed and Inflow at Wonogiri reservoir were influenced by the SST index (Nino 1.2, Nino 3, Nino 3.4, Nino 4). Meanwhile, during the dry season, the rainfall at Wonogiri Watershed and the Inflow at Wonogiri reservoir were influenced by the SST index (IOD West, IOD East, and SOI). With monthly correlations between SST and rainfall data that have a dynamic characteristic, it can be used to calculate the inflow probability distribution in optimizing reservoir operation patterns.