GSA Annual Meeting in Denver, Colorado, USA - 2016

Paper No. 59-30
Presentation Time: 9:00 AM-5:30 PM

CHARACTERIZATIONS OF RIVER BASINS IN THE SAN JUAN MOUNTAINS, COLORADO: AN ADVANCED GEOSPATIAL MAPPING TECHNIQUE


ZHAO, Panshu, 1700 Southwest PKWY, 94 apt, College Station, TX 77840, GIARDINO, John R., High Alpine and Arctic Research Program, Department of Geology and Geophysics and Water Management and Hydrological Sciences Program, Texas A&M University, College Station, TX 77843-3115 and KELKAR, Kaytan, High Alpine and Arctic Research Program, Department of Geology and Geophysics, Texas A&M University, College Station, TX 77843, kaytank@tamu.edu

Alpine streams are not only a vital source of water for human settlements in mountain terrain, but also potential hazards associated with spring melt and summer convective storms. Thus, the identification and characterization of alpine river basins is crucial for the optimization of potable water resources, as well as minimizing floods. Second- and third-order drainage basins are an integral part of the geomorphology of the San Juan Mountains. However, with an increase in year-round residents and greater influx of tourists to the region, there is a need to improve the management of water resources and to minimize flood hazards in the San Juan Mountains (SJM).

In the SJM, streams represent regional topography and local surface roughness. Our study area encompasses the Ironton, Ophir, Ouray, Silverton, and Telluride USGS Quadrangles in Southwestern Colorado, covering an areas of 805 Km2.

We have developed an innovative geospatial approach implementing novel geomorphometric indices to efficiently delineate river basins in mountain terrains. To accomplish this we employed Fast Fourier Transformation (FFT) analysis to confirm that there is no scale dependence for the regional topography. And, to supplement the FFT, we created a new topographical-classification approach that addresses surface roughness. To better understand hydrological controls in the study area, lithology was coupled with the topographical-classification map. We further developed divergence and convergence indices based on water flow to improve the existing river-channel extraction algorithm. This new method will be cost-effective and expedite the process of delineating river basins in mountain terrains to better manage water resources and prepare hazard mitigation plans.