Date of Completion

2-25-2014

Embargo Period

8-10-2014

Keywords

Remote Sensing; Hydrology; Ecology

Major Advisor

Dr. Emmanouil N. Anagnostou

Co-Major Advisor

Dr. Ziad S. Haddad

Associate Advisor

Dr. Glenn Warner

Associate Advisor

Dr. Guiling Wang

Associate Advisor

Dr. Marina Astitha

Field of Study

Environmental Engineering

Degree

Doctor of Philosophy

Open Access

Campus Access

Abstract

Precipitation and soil moisture are two key hydrologic variables in the global water, energy, and carbon cycles that control land-atmosphere interactions. Accurate quantification of both of these parameters at continental scale is of paramount importance in order to better characterize climate patterns and understand climate change. Although there has been significant improvement on the current satellite rainfall retrieval techniques, much can be done to minimize uncertainty, which becomes more apparent over complex terrain and during heavy precipitation events (HPEs). To this end, an evaluation of remote sensing rainfall estimates, derived from different satellite algorithms, is conducted over the high-heterogeneity terrain of Europe and for different seasons. Moreover, a detailed error analysis of different quasi-global high-resolution satellite products for major HPEs of different precipitation types (stratiform versus convective) over mountainous areas provides quantitative information about the error structure of satellite rainfall products during these major precipitation events. Furthermore, obtaining high-sensitivity soil moisture measurements at the regional scale is a very difficult problem that satellite retrievals are aiming to address. In this study, a first step towards the achievement of an improved soil moisture-retrieval algorithm is described, which demonstrates how combining the advantages of active (radar-derived) and passive (radiometer-derived) measurements constitutes a promising way of achieving estimates with unprecedented resolution and sensitivity. Taking into account that climate change is one of the major factors driving biodiversity patterns, it becomes evident that precipitation and soil moisture can be deemed as two fundamental environmental parameters that determine life. The last part of this study bridges the two remote sensing techniques with ecology, contributing to a more effective conservation planning. Specifically, the hydro-geomorphologic drivers of biodiversity patterns over Madagascar are assessed using satellite remote sensing data-based investigations of the different hydrologic properties of the watersheds of the island.

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