Document Type

Thesis

Degree

Master of Science (MS)

Department

Environmental Studies

First Advisor's Name

Michael McClain

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Robert Black

Third Advisor's Name

Dean Whitman

Date of Defense

4-2-2004

Abstract

The purpose of this research was to investigate the influence of elevation and other terrain characteristics over the spatial and temporal distribution of rainfall. A comparative analysis was conducted between several methods of spatial interpolations using mean monthly precipitation values in order to select the best. Following those previous results it was possible to fit an Artificial Neural Network model for interpolation of monthly precipitation values for a period of 20 years, with input values such as longitude, latitude, elevation, four geomorphologic characteristics and anchored by seven weather stations, it reached a high correlation coefficient (r=0.85). This research demonstrated a strong influence of elevation and other geomorphologic variables over the spatial distribution of precipitation and the agreement that there are nonlinear relationships. This model will be used to fill gaps in time-series of monthly precipitation, and to generate maps of spatial distribution of monthly precipitation at a resolution of 1km2.

Identifier

FI14032379

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