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Accueil du site → Doctorat → Inde → 2011 → Regional Frequency Analysis Of Hydrometeorological Events - An Approach Based On Climate Information

Indian Institute of Science (2011)

Regional Frequency Analysis Of Hydrometeorological Events - An Approach Based On Climate Information

Satyanarayana, P

Titre : Regional Frequency Analysis Of Hydrometeorological Events - An Approach Based On Climate Information

Auteur : Satyanarayana, P

Etablissement de soutenance : Indian Institute of Science

Grade : Doctor of Philosophy (PhD) 2011

Résumé
The thesis is concerned with development of efficient regional frequency analysis (RFA) approaches to estimate quantiles of hydrometeorological events. The estimates are necessary for various applications in water resources engineering. The classical approach to estimate quantiles involves fitting frequency distribution to at-site data. However, this approach cannot be used when data at target site are inadequate or unavailable to compute parameters of the frequency distribution. This impediment can be overcome through RFA, in which sites having similar attributes are identified to form a region, and information is pooled from all the sites in the region to estimate the quantiles at target site. The thesis proposes new approaches to RFA of precipitation, meteorological droughts and floods, and demonstrates their effectiveness. The approach proposed for RFA of precipitation overcomes shortcomings of conventional approaches with regard to delineation and validation of homogeneous precipitation regions, and estimation of precipitation quantiles in ungauged and data sparse areas. For the first time in literature, distinction is made between attributes/variables useful to form homogeneous rainfall regions and to validate the regions. Another important issue is that some of the attributes considered for regionalization vary dynamically with time. In conventional approaches, there is no provision to consider dynamic aspects of time varying attributes. This may lead to delineation of ineffective regions. To address this issue, a dynamic fuzzy clustering model (DFCM) is developed. The results obtained from application to Indian summer monsoon and annual rainfall indicated that RFA based on DFCM is more effective than that based on hard and fuzzy clustering models in arriving at rainfall quantile estimates. Errors in quantile estimates for the hard, fuzzy and dynamic fuzzy models based on the proposed approach are shown to be significantly less than those computed for Indian summer monsoon rainfall regions delineated in three previous studies. Overall, RFA based on DFCM and large scale atmospheric variables appeared promising. The performance of DFCM is followed by that of fuzzy and hard clustering models. Next, a new approach is proposed for RFA of meteorological droughts. It is suggested that homogeneous precipitation regions have to be delineated before proceeding to develop drought severity - areal extent - frequency (SAF) curves. Drought SAF curves are constructed at annual and summer monsoon time scales for each of the homogeneous rainfall regions that are newly delineated in India based on the proposed approach.

Présentation (etd@IISc)

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