Quantification and simulation of soil water on grazed fescue watersheds

Abstract

A 2-year study was conducted at the Agriculture and Agri-Food Canada Stavely Range Substation, Alberta. The objective was to quantify and simulate the soil water status of small grassland watersheds under 3 grazing intensities and 4 topographic positions. The grazing treatments were ungrazed (or control), heavy (2.4 AUM ha-1) and very heavy (4.8 AUM ha-1) grazing and the topographic positions were upperslope, midslope, lowerslope and 5 m away from the collector drain. Moisture readings were taken every 2 weeks between spring and fall using a CPN 503 moisture neutron probe. Readings were taken at the soil surface and at 15-, 25-, 35-, 45- and 55-cm depths. Total annual precipitation in 1998 and 1999 was 648 and 399 mm, respectively. In both years grazing treatments did not affect total soil water in the 0-50 cm (TSW50) depth interval for the upper, middle and lower slope positions, but TSW50 close to the collector drain was significantly (P ≤ 0.05) greater for the heavy grazed compared to the very heavy grazed treatment. Within each grazing treatment, TSW50 differences among slope positions occurred mainly under the heavy grazed treatment. Simulation of soil water at each soil depth and watershed was conducted using the Versatile Soil Moisture Budget Model (VB2000). Statistical and graphical evaluations of the model results were conducted using the volumetric soil water data collected for 1998 and 1999. The statistics determined included average error (AE), root mean square (RMS), coefficient of residual mass (CRM), modeling efficiency (EF) and coefficient of determination (CD). All statistics varied with each soil depth and watershed, indicating the transient nature of the data. This is reflected in the mostly negative CRM values, which ranged between -1.0 and 0.16. Overall model fitting to the whole data for all depths, watersheds and years gave values of CRM = -0.08 and EF = 0.19, indicating a slight over-prediction by the model. Spatial variation due to presence of rocks or cracks and averaging across slopes may have partly contributed to the discrepancies between model results and observed data.