Estimation of surface depression storage capacity from random roughness and slope

Abstract

Depression storage capacity (DSC) models found in the literature were developed using statistical regression for relatively large soil surface  roughness and slope values resulting in several fitting parameters. In this research, we developed and tested a conceptual model to estimate  surface depression storage having small roughness values usually encountered in rainwater harvesting micro-catchments and bare soil in arid  regions with only one fitting parameter. Laboratory impermeable surfaces of 30 x 30 cm2 were constructed with 4 sizes of gravel and mortar resulting in random roughness values ranging from 0.9 to 6.3 mm. A series of laboratory experiments were conducted under 9 slope values using simulated rain. Depression storage for each combination of relative roughness and slope was estimated by the mass balance approach. Analysis of
experimental results indicated that the developed linear model between DSC and the square root of the ratio of random roughness (RR) to slope was significant at p < 0.001 and coefficient of determination R2 = 0.90. The developed model predicted depression storage of small relief at higher accuracy compared to other models found in the literature. However, the model is based on small-scale laboratory plots and further testing in the
field will provide more insight for practical applications.

Keywords: modelling depression storage surface roughness arid regions runoff