| dc.description.abstract | The aim of this thesis is to understand linkages between hydrologic processes and patterns from the perspective of a complex system. In hydrologic systems, there exist interactions of hydrologic components among themselves and with the surrounding environment at a wide range of space and time scales. These interactions impart distinct properties to the spatial and temporal behaviour of variables in the catchment. One of the important aspects of a catchment system is complexity, which describes the inherent structural dynamics of a variable that arises due to multiscale interactions and co-evolution between catchment and environment. The two important aspects of complexity considered in this thesis are hydrologic persistence and the uniformity in rainfall distribution. Both hydrologic as well hydro-meteorologic systems are considered as complex systems and the investigation is performed at catchment and regional scales respectively.
Hydrologic persistence plays an important role in natural mechanisms governing hydrologic processes and their interdependence. The space-time evolution of persistence in rainfall and streamflow and their joint behaviour is examined here through the estimation of Hurst Coefficient using Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA). The MOPEX (Model Parameter Estimation Project) watersheds in USA and the Cauvery River Basin in India are used as case studies. The analyses show that the temporal dynamics of persistence of rainfall and streamflow and their joint behaviour are non-uniform across different time scales. It is found that the contribution of catchment processes influencing the persistence of the streamflow is a function of the catchment area. The state of persistence of joint behaviour is neither dependent on the rainfall amount nor affected by the changing patterns of dry and wet spells while the persistence of rainfall alone is affected by the latter.
The dynamics of streamflow is a manifestation of interactions between components of landscape as well as hydroclimatic regimes. The nature of these interactions imparts distinct patterns to the temporal behaviour of streamflow in a structured way to support functioning of the hydrologic and ecosystem services. In this study, information theoretic measures based on Shannon Entropy are conceptualized to quantify such patterns as emergence, self-organization and complexity of temporal streamflow characteristics. Complexity of a process measures the balance of change and stability in the temporal dynamics of streamflow arising from multiscale interactions with constituent components of the hydrologic system. The temporal clustering of low and high flows, responsible for occurrence of droughts and floods, can be attributed to long-term persistence (LTP) in streamflow. It is observed that the state of complexity of streamflow depends on the interactions between soil, vegetation, hydroclimatic regimes and streamflow generation mechanism. It is also found that LTP is an emergent property and can be interpreted as the complexity of streamflow dynamics. Detection of causal interactions among catchment components and climate variables governing streamflow generation is essential to characterize the complexity of streamflow. Conventional causal detection methods of Granger Causality, Transfer Entropy and Causal Decomposition are used to identify the source and target variables in a synthetic system and a real system comprising of precipitation-runoff transformation. It is observed that the presence of LTP and the inherent assumptions in these methods constrain the inference on the causal dynamics.
Understanding the response of temporal distribution, timing, frequency and amount of high and low intensity rainfall to warming is important in water resources management. In this thesis, Relative Entropy is used to investigate the spatial variability and change in uniformity of rainfall distribution over India. Temporal trends in atmospheric temperature can alter the frequency and amount of high and low intensity rainfall events, which influence the uniformity of rainfall distribution. The study is divided into two time periods, 1951–1980 and 1981–2010 based on time trend in annual mean temperature. The sensitivity of rainfall uniformity and high and low intensity rainfall events to annual mean temperature and the degree of coherence between them are investigated. The uniformity of rainfall distribution shows a significant spatial variability. Significant changes are observed in both the amount and timing of rainfall across India. A significant association between rainfall uniformity and low intensity of rainfall is observed in the recent past over a larger aerial extent compared to the distant past. It is concluded that rise in temperature modifies both high and low intensity rainfall events, thus altering the uniformity in rainfall distribution. A regionally varied strength of coherence between rainfall uniformity and high and low intensity rainfall is observed which may be due to regionally dependent soil moisture-precipitation feedbacks. | en_US |
