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|Title: ||Impact Of Large-Scale Coupled Atmospheric-Oceanic Circulation On Hydrologic Variability And Uncertainty Through Hydroclimatic Teleconnection|
|Authors: ||Maity, Rajib|
|Advisors: ||Kumar, D Nagesh|
|Keywords: ||Hydroclimatic Teleconnection|
Monsoon - India
Rainfall - India
Indian Ocean - Oscillaltion
Large Scale Climate Teleconnections
Indian Summer Monsoon Rainfall (ISMR)
El Niño-Southern Oscillation (ENSO)
Bayesian Dynamic Linear Model (BDLM)
Equatorial Indian Ocean Oscillation (EQUINOO)
|Submitted Date: ||1-Jan-2007|
|Series/Report no.: ||G20938|
|Abstract: ||In the recent scenario of climate change, the natural variability and uncertainty associated with the hydrologic variables is of great concern to the community. This thesis opens up a new area of multi-disciplinary research. It is a promising field of research in hydrology and water resources that uses the information from the field of atmospheric science. A new way to identify and capture the variability and uncertainty associated with the hydrologic variables is established through this thesis. Assessment of hydroclimatic teleconnection for Indian subcontinent and its use in basin-scale hydrologic time series analysis and forecasting is the broad aim of this PhD thesis.
The initial part of the thesis is devoted to investigate and establish the dependence of Indian summer monsoon rainfall (ISMR) on large-scale Oceanic-atmospheric circulation phenomena from tropical Pacific Ocean and Indian Ocean regions. El Niño-Southern Oscillation (ENSO) is the well established coupled Ocean-atmosphere mode of tropical Pacific Ocean whereas Indian Ocean Dipole (IOD) mode is the recently identified coupled Ocean-atmosphere mode of tropical Indian Ocean. Equatorial Indian Ocean Oscillation (EQUINOO) is known as the atmospheric component of IOD mode. The potential of ENSO and EQUINOO for predicting ISMR is investigated by Bayesian dynamic linear model (BDLM). A major advantage of this method is that, it is able to capture the dynamic nature of the cause-effect relationship between large-scale circulation information and hydrologic variables, which is quite expected in the climate change scenario. Another new method, proposed to capture the dependence between the teleconnected hydroclimatic variables is based on the theory of copula, which itself is quite new to the field of hydrology. The dependence of ISMR on ENSO and EQUINOO is captured and investigated for its potential use to predict the monthly variation of ISMR using the proposed method.
The association of monthly variation of ISMR with the combined information of ENSO and EQUINOO, denoted by monthly composite index (MCI), is also investigated and established. The spatial variability of such association is also investigated. It is observed that MCI is significantly associated with monthly rainfall variation all over India, except over North-East (NE) India, where it is poor.
Having established the hydroclimatic teleconnection at a comparatively larger scale, the hydroclimatic teleconnection for basin-scale hydrologic variables is then investigated and established. The association of large-scale atmospheric circulation with inflow during monsoon season into Hirakud reservoir, located in the state of Orissa in India, has been investigated. The strong predictive potential of the composite index of ENSO and EQUINOO is established for extreme inflow conditions. So the methodology of inflow prediction using the information of hydroclimatic teleconnection would be very suitable even for ungauged or poorly gauged watersheds as this approach does not use any information about the rainfall in the catchment.
Recognizing the basin-scale hydroclimatic association with both ENSO and EQUINOO at seasonal scale, the information of hydroclimatic teleconnection is used for streamflow forecasting for the Mahanadi River basin in the state of Orissa, India, both at seasonal and monthly scale. It is established that the basin-scale streamflow is influenced by the large-scale atmospheric circulation phenomena. Information of streamflow from previous month(s) alone, as used in most of the traditional modeling approaches, is shown to be inadequate. It is successfully established that incorporation of large-scale atmospheric circulation information significantly improves the performance of prediction at monthly scale. Again, the prevailing conditions/characteristics of watershed are also important. Thus, consideration of both the information of previous streamflow and large-scale atmospheric circulations are important for basin-scale streamflow prediction at monthly time-scale.
Adopting the developed approach of using the information of hydroclimatic teleconnection, hydrologic variables can be predicted with better accuracy which will be a very useful input for better management of water resources.|
|Appears in Collections:||Civil Engineering (civil)|
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