Modeling of terracette‐hillslope soil moisture as a function of aspect, slope and vegetation in a semi‐arid environment

Abstract

In the semi‐arid western United States, water availability plays a defining role in land use. Soil moisture, vegetation, and microtopography are key variables in the hydrologic function of these ecosystems. Previous research has not addressed the influence of site‐specific aspect, vegetation, or slope gradient on terracette soil moisture patterns in semi‐arid rangelands. Therefore, the objectives of this study were to: (1) assess the influence of terracette site aspect, vegetation cover, and slope on soil moisture; (2) conceptualize conditions at the hillslope scale given terracette morphology; and (3) estimate the extent of terracettes at a regional scale. The Simultaneous Heat and Water (SHAW) model was used to simulate soil water dynamics of terracettes given variations in site conditions. These results were coupled with time‐of‐flight laser scans to quantify terracette bench and riser percent‐area, and statewide assessments of terracette extent using digital orthoimagery and a geographical information system (GIS). Modeling results indicated site aspect had minimal influence (±0.005 m3 m−3) on terracette soil moisture. Vegetation, represented as leaf area index (LAI), had the single‐most influential effect on terracette volumetric water content (θv) demonstrated by an inverse relationship of LAI to mean terracette hillslope θv; and slope increases of ≥15% on northern azimuths increased mean θv which contrasted with southern azimuths for similar slope increases. Laser scanning results indicated bench width and riser length could be estimated from mean site slope (R2 = 0.82 risers and R2 = 0.93 benches). Aerial orthoimagery/GIS assessments estimated >159 000 ha of terracettes throughout the State of Idaho, with >41 000 ha (~26%) occurring on lands managed as grazing allotments. These findings provide an increased understanding of rangeland hydrologic processes as influenced by cattle density, vegetation, and terracettes which can aide land managers in their selection and application of best management practices on these lands. Copyright © 2017 John Wiley & Sons, Ltd.

Detection of terracettes in semi‐arid rangelands using Fourier‐based image analysis of very‐high‐resolution satellite imagery

“…The study areas used here covered a total of 117 km 2 , of which 66.6% was used for analysis under the explicit assumption that terracettes are limited to on slopes >5°and <60°and within grassland and shrub NLCD classifications. For aspect, our final classification results were consistent with Buckhouse and Krueger (1981) and Corrao et al (2017), with north as the dominant aspect where terracettes are found. While the current spatial coverage of this study does not allow for extrapolation from these values to larger scales, the methodology used here, combined with random, kilometric-scale plot sampling across watershed or greater scales, enables future research.…”

Understanding plot‐scale hydrology of Lesser Himalayan watershed—A field study and HYDRUS‐2D modelling approach

“…Further, Anache et al () have performed plot‐scale studies in 52 plots under different land use conditions and indicated the less runoff generating potential of forest land in comparison with grass and pasture land and fallow land. The soil moisture was observed higher in AF plot in comparison with DE plot, which simultaneously verified the concept that the north aspect of catchment carries more moisture than the south aspect (Corrao et al, ; Geroy et al, ). Greater silt content in AF plot in comparison with the DE plot results in high moisture holding capacity of former one (Geroy et al, ).…”

“…In the present study, the sand content of AF plot was 42.34%, which was higher than the DE plot (37.6%). The higher sand content reduced the runoff coefficient of the AF plot by 25% in comparison with the DE plot (Vaezi, Bahrami, Sadeghi, & Mahdian, 2010 (Corrao et al, 2017;Geroy et al, 2011). Greater silt content in AF plot in comparison with the DE plot results in high moisture holding capacity of former one (Geroy et al, 2011).…”

“…The saturation-excess overland flow is generated when an entire soil profile becomes saturated due to the rise in groundwater table or complete infiltration of precipitation (Dunne & Black, 1970). In a plot scale, microtopography and soil moisture vary dynamically, influencing soil infiltration rate and runoff (Corrao, Link, Heinse, & Eitel, 2017). The overland flow mechanisms mainly depend on rainfall characteristics, surface conditions, and soil infiltrability.…”

Flash-Flood Susceptibility Assessment Using Multi-Criteria Decision Making and Machine Learning Supported by Remote Sensing and GIS Techniques

“…Finally, the MFI values were derived by using the precipitation amount in raster format and Equation (1). These values were reclassified into five classes using natural breaks ( [48,[51][52][53][54][55][56], slope degree has the highest impact on the generation of surface runoff. This morphometric flash-flood predictor was derived from the DEM (Figure 3a).…”