Institute: New Mexico
Year Established: 2017 Start Date: 2017-03-01 End Date: 2018-02-28
Total Federal Funds: $15,000 Total Non-Federal Funds: $30,000
Principal Investigators: Colby Brungard
Abstract: Water in arid soils is highly temporally and spatially variable, complicating mechanistic models which quantify the hydrological budget of arid watersheds. Accounting for fine-resolution soil spatial variability improves predictions of surface soil moisture, evapotranspiration, and runoff (Mez-Barroso et al., 2016; Tavares Wahren et al., 2016). We propose to utilize digital soil mapping techniques to map soil properties (depth + texture) necessary for parameterizing water balance, evapotranspiration, and ecohydrologic models. Digital soil mapping (DSM) is the creation of spatially explicit soil information from quantitative relationships between easily measured environmental covariates and more difficult to measure soil properties (McBrantney et al., 2003). Environmental covariates are spatially explicit biogeophysical properties derived from remote sensing, digital elevation models, and other geospatial information (e.g., geology maps). Soil observations are measurements obtained by field sampling and/or laboratory analysis (Lagacherie and McBratney, 2006).