Probabilistic seasonal streamflow forecasts of the Citarum River, Indonesia, based on general circulation models
In this study we discuss probabilistic forecasts of Citarum River streamflow, which supplies 80 % of the water demands in Jakarta, Indonesia, based on general circulation model (GCM) output, for the September–November (SON) season. Retrospective forecasts of precipitation made over the period 1982–2...
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| Veröffentlicht in: | Stochastic environmental research and risk assessment 2017-09, Vol.31 (7), p.1747-1758 |
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| container_title | Stochastic environmental research and risk assessment |
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| creator | Sahu, Netrananda Robertson, Andrew W. Boer, Rizaldi Behera, Swadhin DeWitt, David G. Takara, Kaoru Kumar, Manish Singh, R. B. |
| description | In this study we discuss probabilistic forecasts of Citarum River streamflow, which supplies 80 % of the water demands in Jakarta, Indonesia, based on general circulation model (GCM) output, for the September–November (SON) season. Retrospective forecasts of precipitation made over the period 1982–2010 with two coupled-ocean atmosphere GCMs, initialized in August, are used in conjunction historical streamflow records, with a cross-validated regression model. Pearson’s product moment correlation skill values of 0.58–0.67 are obtained, with relative operating characteristic scores of 0.67–0.84 and 0.74–0.92 for the lower and upper tercile categories of flows respectively. Both GCMs thus demonstrate promising ability to forecast below/above normal streamflow for the Citarum River flow during the SON season. |
| doi_str_mv | 10.1007/s00477-016-1297-4 |
| format | Article |
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B.</creator><creatorcontrib>Sahu, Netrananda ; Robertson, Andrew W. ; Boer, Rizaldi ; Behera, Swadhin ; DeWitt, David G. ; Takara, Kaoru ; Kumar, Manish ; Singh, R. B.</creatorcontrib><description>In this study we discuss probabilistic forecasts of Citarum River streamflow, which supplies 80 % of the water demands in Jakarta, Indonesia, based on general circulation model (GCM) output, for the September–November (SON) season. Retrospective forecasts of precipitation made over the period 1982–2010 with two coupled-ocean atmosphere GCMs, initialized in August, are used in conjunction historical streamflow records, with a cross-validated regression model. Pearson’s product moment correlation skill values of 0.58–0.67 are obtained, with relative operating characteristic scores of 0.67–0.84 and 0.74–0.92 for the lower and upper tercile categories of flows respectively. Both GCMs thus demonstrate promising ability to forecast below/above normal streamflow for the Citarum River flow during the SON season.</description><identifier>ISSN: 1436-3240</identifier><identifier>EISSN: 1436-3259</identifier><identifier>DOI: 10.1007/s00477-016-1297-4</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aquatic Pollution ; Atmospheric models ; Chemistry and Earth Sciences ; Computational Intelligence ; Computer Science ; Earth and Environmental Science ; Earth Sciences ; Environment ; General circulation models ; Math. 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B.</creatorcontrib><title>Probabilistic seasonal streamflow forecasts of the Citarum River, Indonesia, based on general circulation models</title><title>Stochastic environmental research and risk assessment</title><addtitle>Stoch Environ Res Risk Assess</addtitle><description>In this study we discuss probabilistic forecasts of Citarum River streamflow, which supplies 80 % of the water demands in Jakarta, Indonesia, based on general circulation model (GCM) output, for the September–November (SON) season. Retrospective forecasts of precipitation made over the period 1982–2010 with two coupled-ocean atmosphere GCMs, initialized in August, are used in conjunction historical streamflow records, with a cross-validated regression model. Pearson’s product moment correlation skill values of 0.58–0.67 are obtained, with relative operating characteristic scores of 0.67–0.84 and 0.74–0.92 for the lower and upper tercile categories of flows respectively. Both GCMs thus demonstrate promising ability to forecast below/above normal streamflow for the Citarum River flow during the SON season.</description><subject>Aquatic Pollution</subject><subject>Atmospheric models</subject><subject>Chemistry and Earth Sciences</subject><subject>Computational Intelligence</subject><subject>Computer Science</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environment</subject><subject>General circulation models</subject><subject>Math. Appl. in Environmental Science</subject><subject>Original Paper</subject><subject>Physics</subject><subject>Precipitation</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Regression models</subject><subject>River flow</subject><subject>Rivers</subject><subject>Statistical analysis</subject><subject>Statistics for Engineering</subject><subject>Stream discharge</subject><subject>Stream flow</subject><subject>Streamflow forecasting</subject><subject>Waste Water Technology</subject><subject>Water circulation</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><issn>1436-3240</issn><issn>1436-3259</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kF1LwzAUhosoOOZ-gHcBb1dN0nw0lzL8GAwU2X1I2mRG2mbmdIr_3oyKeONVDuF9Xs55iuKS4GuCsbwBjJmUJSaiJFTJkp0UM8IqUVaUq9PfmeHzYgEQbGZ4pRTBs2L_nKI1NnQBxtAgcAbiYDoEY3Km9138RD4m1xgYAUWPxleHVmE06dCjl_Dh0hKthzYODoJZImvAtSgOaOcGl3JNE1Jz6MwY8l8fW9fBRXHmTQdu8fPOi-393Xb1WG6eHtar203ZVDUdSy-aSnLuLW-lUzQv74S1mHnOMVXKMEkpq4mQ3pK24kJwLBWzlLaqZcxX8-Jqqt2n-H5wMOq3eEj5MtBEsRpzoWqRU2RKNSkCJOf1PoXepC9NsD6q1ZNandXqo1rNMkMnBnJ22Ln0p_lf6BsJjHwo</recordid><startdate>20170901</startdate><enddate>20170901</enddate><creator>Sahu, Netrananda</creator><creator>Robertson, Andrew W.</creator><creator>Boer, Rizaldi</creator><creator>Behera, Swadhin</creator><creator>DeWitt, David G.</creator><creator>Takara, Kaoru</creator><creator>Kumar, Manish</creator><creator>Singh, R. 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B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Probabilistic seasonal streamflow forecasts of the Citarum River, Indonesia, based on general circulation models</atitle><jtitle>Stochastic environmental research and risk assessment</jtitle><stitle>Stoch Environ Res Risk Assess</stitle><date>2017-09-01</date><risdate>2017</risdate><volume>31</volume><issue>7</issue><spage>1747</spage><epage>1758</epage><pages>1747-1758</pages><issn>1436-3240</issn><eissn>1436-3259</eissn><abstract>In this study we discuss probabilistic forecasts of Citarum River streamflow, which supplies 80 % of the water demands in Jakarta, Indonesia, based on general circulation model (GCM) output, for the September–November (SON) season. Retrospective forecasts of precipitation made over the period 1982–2010 with two coupled-ocean atmosphere GCMs, initialized in August, are used in conjunction historical streamflow records, with a cross-validated regression model. 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| subjects | Aquatic Pollution Atmospheric models Chemistry and Earth Sciences Computational Intelligence Computer Science Earth and Environmental Science Earth Sciences Environment General circulation models Math. Appl. in Environmental Science Original Paper Physics Precipitation Probability Theory and Stochastic Processes Regression models River flow Rivers Statistical analysis Statistics for Engineering Stream discharge Stream flow Streamflow forecasting Waste Water Technology Water circulation Water Management Water Pollution Control |
| title | Probabilistic seasonal streamflow forecasts of the Citarum River, Indonesia, based on general circulation models |
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