Water allocation for multiple uses based on probabilistic reservoir inflow forecasts
Identifieur interne : 00AF87 ( Main/Exploration ); précédent : 00AF86; suivant : 00AF88Water allocation for multiple uses based on probabilistic reservoir inflow forecasts
Auteurs : Sankar Arumugam [États-Unis] ; Ashish Sharma [Australie] ; Upmanu Lall [États-Unis]Source :
- IAHS-AISH publication [ 0144-7815 ] ; 2003.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Statistique, Climat, Simulation.
English descriptors
- KwdEn :
Abstract
Allocating water to downstream users is traditionally a conservative exercise. The amount of water to be allocated for each use is usually decided based on stringent assumptions about the sequence of likely reservoir inflows and a requirement that the reliability of the allocated amount also has to be specified. But, the inflows that actually occur are often predictable based on catchment storage and longer scale climatic fluctuations. This paper presents a framework towards water allocation for multiple uses by developing: (a) 18 months-ahead ensemble forecasts of reservoir inflows based on larger scale climatic indices; (b) the specification of the annual water contract terms; (c) a water allocation model that maximizes the release given the reliability and the contract terms. The approach is demonstrated through an application to the Oros Reservoir in the state of Ceara, Brazil by maximizing annual reservoir yields using ensemble forecasts of inflows conditioned on the climate information developed for the period 1913-1995. Results from this study show the usefulness of this water allocation framework to issue annual water contracts using reservoir inflow forecasts and develop adequate strategies towards better water system management in regions where the link to low-frequency climate variability is strong.
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aut.</sZ></inist:fA14><country>Australie</country><placeName><settlement type="city">Sydney</settlement><region type="état">Nouvelle-Galles du Sud</region></placeName></affiliation></author><author><name sortKey="Lall, Upmanu" sort="Lall, Upmanu" uniqKey="Lall U" first="Upmanu" last="Lall">Upmanu Lall</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>International Research Institute for Climate Prediction</s1><s2>Palisades, New York 10964</s2><s3>USA</s3><sZ>1 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>États-Unis</country><wicri:noRegion>International Research Institute for Climate Prediction</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">03-0493462</idno><date when="2003">2003</date><idno type="stanalyst">PASCAL 03-0493462 INIST</idno><idno type="RBID">Pascal:03-0493462</idno><idno type="wicri:Area/PascalFrancis/Corpus">005143</idno><idno 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aut.</sZ></inist:fA14><country>États-Unis</country><wicri:noRegion>International Research Institute for Climate Prediction</wicri:noRegion></affiliation></author><author><name sortKey="Sharma, Ashish" sort="Sharma, Ashish" uniqKey="Sharma A" first="Ashish" last="Sharma">Ashish Sharma</name><affiliation wicri:level="3"><inist:fA14 i1="02"><s1>School of Civil and Environmental Engineering, The University of New South Wales</s1><s2>Sydney</s2><s3>AUS</s3><sZ>2 aut.</sZ></inist:fA14><country>Australie</country><placeName><settlement type="city">Sydney</settlement><region type="état">Nouvelle-Galles du Sud</region></placeName></affiliation></author><author><name sortKey="Lall, Upmanu" sort="Lall, Upmanu" uniqKey="Lall U" first="Upmanu" last="Lall">Upmanu Lall</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>International Research Institute for Climate Prediction</s1><s2>Palisades, New York 10964</s2><s3>USA</s3><sZ>1 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>États-Unis</country><wicri:noRegion>International Research Institute for Climate Prediction</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">IAHS-AISH publication</title><idno type="ISSN">0144-7815</idno><imprint><date when="2003">2003</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">IAHS-AISH publication</title><idno type="ISSN">0144-7815</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Ceara Brazil</term><term>climate</term><term>discharge</term><term>drainage basins</term><term>fluctuations</term><term>models</term><term>prediction</term><term>probability</term><term>reliability</term><term>reservoirs</term><term>simulation</term><term>statistics</term><term>strategy</term><term>water resource management</term><term>water storage</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Ceara</term><term>Réservoir</term><term>Statistique</term><term>Prévision</term><term>Probabilité</term><term>Fiabilité</term><term>Bassin versant</term><term>Stockage eau</term><term>Fluctuation</term><term>Modèle</term><term>Climat</term><term>Stratégie</term><term>Gestion ressource eau</term><term>Simulation</term><term>Débit</term><term>Affectation</term><term>Variabilité climat</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Statistique</term><term>Climat</term><term>Simulation</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Allocating water to downstream users is traditionally a conservative exercise. The amount of water to be allocated for each use is usually decided based on stringent assumptions about the sequence of likely reservoir inflows and a requirement that the reliability of the allocated amount also has to be specified. But, the inflows that actually occur are often predictable based on catchment storage and longer scale climatic fluctuations. This paper presents a framework towards water allocation for multiple uses by developing: (a) 18 months-ahead ensemble forecasts of reservoir inflows based on larger scale climatic indices; (b) the specification of the annual water contract terms; (c) a water allocation model that maximizes the release given the reliability and the contract terms. The approach is demonstrated through an application to the Oros Reservoir in the state of Ceara, Brazil by maximizing annual reservoir yields using ensemble forecasts of inflows conditioned on the climate information developed for the period 1913-1995. Results from this study show the usefulness of this water allocation framework to issue annual water contracts using reservoir inflow forecasts and develop adequate strategies towards better water system management in regions where the link to low-frequency climate variability is strong.</div></front></TEI><affiliations><list><country><li>Australie</li><li>États-Unis</li></country><region><li>Nouvelle-Galles du Sud</li></region><settlement><li>Sydney</li></settlement></list><tree><country name="États-Unis"><noRegion><name sortKey="Arumugam, Sankar" sort="Arumugam, Sankar" uniqKey="Arumugam S" first="Sankar" last="Arumugam">Sankar Arumugam</name></noRegion><name sortKey="Lall, Upmanu" sort="Lall, Upmanu" uniqKey="Lall U" first="Upmanu" last="Lall">Upmanu Lall</name></country><country name="Australie"><region name="Nouvelle-Galles du Sud"><name sortKey="Sharma, Ashish" sort="Sharma, Ashish" uniqKey="Sharma A" first="Ashish" last="Sharma">Ashish Sharma</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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