USING REMOTELY SENSED IMAGERY AND GIS FOR URBAN EVAPOTRANSPIRATION STUDIES

Daily and annual evapotranspiration (ET) estimates were computed for three separate cities along the Front Range of the Colorado Rocky Mountains. Estimates were derived using two different methods: 1) a traditional crop coefficient method, and 2) a reflectance-based vegetation coefficient index in order to simulate both present and future urban water requirements. For the first method, an urban area land use and land cover classification was derived using a combination of video rasterized National Aerial Photography Program (NAPP) data and Landsat Thematic Mapper (TM) data sets. NAPP color infrared transparencies were video rasterized at 7.125-m ground resolution as RGB separates (visible green, red, and near infrared) and then combined with multi-date TM satellite imagery into a single data set. This multi-temporal and high spatial resolution data set was used as input to an unsupervised classification algorithm. The resulting classification map was converted into a geographic information system (GIS) in order to model 1993 annual evapotranspiration (ET) for the community of Greeley, Colorado. The second method used a linear correlation between the Normalized Difference Vegetation Index (NDVI) and crop coefficients to relate a reflectance-based vegetation coefficient (Vc) to NDVI. Landsat-5 Thematic Mapper imagery was transformed into three spatially distributed ET maps using the Vc and reference ET in a GIS environment. Irrigated areas subject to water conservation management were extracted from the ET maps using a GIS masking technique. As a result of this research, an urban land use crop coefficient curve was developed that may be useful for predicting seasonal and annual consumptive water requirements for a typical city in the semi-arid western United States. ET predictions were comparable using the vegetation coefficients and the crop use coefficient curve adds additional tools for predicting urban water consumption during drought conditions.