85th AMS Annual Meeting

Tuesday, 11 January 2005: 3:30 PM
Topographic and Ecosystem Controls on Soil Moisture Distribution in the SMEX04-NAME Transect Study, Northern Sonora, Mexico
Enrique R. Vivoni, New Mexico Institute of Mining and Technology, Socorro, NM; and H. A. Gutierrez, B. Brooks, C. A. Aragon, A. Rinehart, R. Wyckoff, C. J. Watts, J. C. Rodriguez, and T. J. Jackson
It is widely known that topographic and ecosystem variability exert a strong signature on the surface soil moisture distribution over regional scales, yet there is little observational evidence available to quantify this relationship, in particular over arid and semiarid areas. To properly determine the topographic and vegetation effects on soil moisture, and potentially use terrain and land-cover data to downscale remote sensing data, a spatially-extensive field sampling of soil moisture in regions of topographic variability is required. The SMEX04-NAME field study in northern Sonora, Mexico provides a unique opportunity for understanding the linkages between topographic position and the statistical properties of soil moisture during the North American Monsoon season in a sparsely observed region. In this study, we present a preliminary analysis of the data collected from both an in-situ network of soil moisture sensors and a two-week field campaign over a west-to-east transect in mountainous northern Sonora. The time evolution of topographic profiles of observed hydrometeorological quantities (rainfall, relative humidity, air temperature, pressure) and surface hydrologic properties (soil moisture, soil temperature) will be presented. We utilize available spatial data sets on the regional topography, soil types and vegetation distributions to quantify the linkage between monsoonal soil moisture, topography and ecosystem pattern. A preliminary comparison will also be made between hydrometeorological data and terrain attributes (elevation, slope, aspect, curvature) within a watershed encompassing the study transect. The topographic and vegetation data sets will then be used to interpolate field data and create soil moisture maps that can be aggregated to the aircraft and satellite footprint resolutions for conducting areal average comparisons.

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