Home About us Contact
|
Home About us Contact | ||
|
|
||
Saturation Excess (saturation + excess)
Selected AbstractsModelling variable source area dynamics in a CEAP watershedECOHYDROLOGY, Issue 3 2009Helen E. Dahlke Abstract In the Northeast US, saturation excess is the most dominant runoff process and locations of runoff source areas, typically called variable source areas (VSAs), are determined by the available soil water storage and the landscape topographic position. To predict runoff generated from VSAs some water quality models use the Soil Conservation Service Curve Number equation (SCS-CN), which assumes a constant initial abstraction of rainfall is retained by the watershed prior to the beginning of runoff. We apply a VSA interpretation of the SCS-CN runoff equation that allows the initial abstraction to vary with antecedent moisture conditions. We couple this modified SCS-CN approach with a semi-distributed water balance model to predict runoff, and distribute predictions using a soil topographic index for the Town Brook watershed in the Catskill Mountains of New York State. The accuracy of predicted VSA extents using both the original and the modified SCS-CN equation were evaluated for 14 rainfall-runoff events through a comparison with average water table depths measured at 33 locations in Town Brook from March,September 2004. The modified SCS-CN equation captured VSA dynamics more accurately than the original equation. However, during events with high antecedent rainfall VSA dynamics were still under-predicted suggesting that VSA runoff is not captured solely by knowledge of the soil water deficit. Considering the importance of correctly predicting runoff generation and pollutant source areas in the landscape, the results of this study demonstrate the feasibility of integrating VSA hydrology into water quality models to reduce non-point source pollution. Copyright © 2009 John Wiley & Sons, Ltd. [source] Delineating runoff processes and critical runoff source areas in a pasture hillslope of the Ozark HighlandsHYDROLOGICAL PROCESSES, Issue 21 2008M. D. Leh Abstract The identification of runoff contributing areas would provide the ideal focal points for water quality monitoring and Best Management Practice (BMP) implementation. The objective of this study was to use a field-scale approach to delineate critical runoff source areas and to determine the runoff mechanisms in a pasture hillslope of the Ozark Highlands in the USA. Three adjacent hillslope plots located at the Savoy Experimental Watershed, north-west Arkansas, were bermed to isolate runoff. Each plot was equipped with paired subsurface saturation and surface runoff sensors, shallow groundwater wells, H-flumes and rain gauges to quantify runoff mechanisms and rainfall characteristics at continuous 5-minute intervals. The spatial extent of runoff source areas was determined by incorporating sensor data into a geographic information-based system and performing geostatistical computations (inverse distance weighting method). Results indicate that both infiltration excess runoff and saturation excess runoff mechanisms occur to varying extents (0,58% for infiltration excess and 0,26% for saturation excess) across the plots. Rainfall events that occurred 1,5 January 2005 are used to illustrate the spatial and temporal dynamics of the critical runoff source areas. The methodology presented can serve as a framework upon which critical runoff source areas can be identified and managed for water quality protection in other watersheds. Copyright © 2008 John Wiley & Sons, Ltd. [source] Effects of land-cover changes on the hydrological response of interior Columbia River basin forested catchmentsHYDROLOGICAL PROCESSES, Issue 13 2002James R. VanShaar Abstract The topographically explicit distributed hydrology,soil,vegetation model (DHSVM) is used to simulate hydrological effects of changes in land cover for four catchments, ranging from 27 to 1033 km2, within the Columbia River basin. Surface fluxes (stream flow and evapotranspiration) and state variables (soil moisture and snow water equivalent) corresponding to historical (1900) and current (1990) vegetation are compared. In addition a sensitivity analysis, where the catchments are covered entirely by conifers at different maturity stages, was conducted. In general, lower leaf-area index (LAI) resulted in higher snow water equivalent, more stream flow and less evapotranspiration. Comparisons with the macroscale variable infiltration capacity (VIC) model, which parameterizes, rather than explicitly represents, topographic effects, show that runoff predicted by DHSVM is more sensitive to land-cover changes than is runoff predicted by VIC. This is explained by model differences in soil parameters and evapotranspiration calculations, and by the more explicit representation of saturation excess in DHSVM and its higher sensitivity to LAI changes in the calculation of evapotranspiration. Copyright © 2002 John Wiley & Sons, Ltd. [source] GIS-Based Predictive Models of Hillslope Runoff Generation Processes,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 4 2009Mansour D. Leh Abstract:, Successful nonpoint source pollution control using best management practice placement is a complex process that requires in-depth knowledge of the locations of runoff source areas in a watershed. Currently, very few simulation tools are capable of identifying critical runoff source areas on hillslopes and those available are not directly applicable under all runoff conditions. In this paper, a comparison of two geographic information system (GIS)-based approaches: a topographic index model and a likelihood indicator model is presented, in predicting likely locations of saturation excess and infiltration excess runoff source areas in a hillslope of the Savoy Experimental Watershed located in northwest Arkansas. Based on intensive data collected from a two-year field study, the spatial distributions of hydrologic variables were processed using GIS software to develop the models. The likelihood indicator model was used to produce probability surfaces that indicated the likelihood of location of both saturation and infiltration excess runoff mechanisms on the hillslope. Overall accuracies of the likelihood indicator model predictions varied between 81 and 87% for the infiltration excess and saturation excess runoff locations respectively. On the basis of accuracy of prediction, the likelihood indicator models were found to be superior (accuracy 81-87%) to the predications made by the topographic index model (accuracy 69.5%). By combining statistics with GIS, runoff source areas on a hillslope can be identified by incorporating easily determined hydrologic measurements (such as bulk density, porosity, slope, depth to bed rock, depth to water table) and could serve as a watershed management tool for identifying critical runoff source areas in locations where the topographic index or other similar methods do not provide reliable results. [source] | ||||||||||