Brief Introduction to PhD Thesis

Title of the Thesis:

Impact of large-scale coupled Atmospheric-Oceanic circulation on hydrologic variability and uncertainty through hydroclimatic teleconnection

Brief Summary

There is an established evidence of hydroclimatic teleconnection between large-scale atmospheric circulations and large-scale (both spatially and temporally) rainfall pattern around the globe. However, for Indian subcontinent research towards this direction is not fully explored. Moreover, the impact of such ‘large-scale’ atmospheric circulation on comparatively smaller ‘basin-scale’ hydrologic variables, such as, rainfall, surface runoff, streamflow etc., is yet to be explored for smaller temporal resolutions, which is all the more essential in hydrology and water resources development and management. The proposed research aims to address this issue, with the following specific considerations:

  1. Investigation of hydroclimatic teleconnection pattern for Indian subcontinent.

  2. Establishment of the link between ‘large-scale’ atmospheric/oceanic variable and ‘basin-scale’ hydrologic variables. identification and development of suitable methodology to predict the ‘basin-scale’ hydrologic variables using the ‘large-scale’ circulation information.

  3. The basin-scale hydrologic time series, being significantly influenced by the large-scale atmospheric circulation phenomena, is likely to be nonstationary in nature. While stationarity is a common assumption in most hydrologic modeling approaches, it is necessary to model nonstationary temporal structure of hydrologic time series expected under climate change scenario.

  4. Dynamic nature of cause-effect relationship creates difficulties in robust and consistent prediction of hydrologic variables. Thus, the dynamic relationship between hydrologic time series and large-scale circulation is to be captured.

  5. Probabilistic prediction of hydrologic variables, using the information of large-scale circulation, is another important issue to be addressed. It will provide the information about the uncertainty associated with the predicted values.

  6. Being most essential for Hydrology and Water Resources, responses of ‘basin-scale’ hydrologic variables to ‘large-scale’ atmospheric circulation will be investigated

  7. nurUse of such relationship with a goal to improve the prediction performance of hydrologic time series.

Abstract

In the recent scenario of climate changes, the natural variability and uncertainty associated with the hydrologic variables is of great concern to the community. Hydroclimatic teleconnection between hydrologic variables and large-scale atmospheric circulation phenomena is being studied worldwide and gaining more and more interest in recent years due to its potential use for analyzing variability and uncertainty of hydrologic variables. Research in this direction, for Indian subcontinent, is still in its nascent stage even at large spatio-temporal scale. Assessment of hydroclimatic teleconnection for Indian subcontinent and its use in basin-scale hydrologic time series analysis and forecasting is the broad goal of this PhD thesis.

This thesis opens up a new area of 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.

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 link between ISMR and ENSO is established long back but the same between EQUINOO and ISMR is recognized recently. 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 over different homogeneous monsoon regions of India 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 between basin-scale hydrologic variables and the large-scale atmospheric circulation phenomena helps to improve the predictability of the hydrologic variables using prior information of the large-scale atmospheric circulation. 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. It is also observed that conditional probabilities of low and high inflows, conditioned on the composite index (CI), are much higher than their unconditional probabilities. A linear regression analysis shows that the natural variability of inflow data, at least in part, can be captured successfully. 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 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.

Last updated: May, 2007

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