Estimation of surface depression storage capacity from surface roughness

Abstract. Depression storage 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 microcatchments in arid regions with only one fitting parameter. Laboratory impermeable surfaces of 30 × 30 cm² were constructed with four sizes of gravel and mortar resulting in random roughness values ranged 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 were estimated by mass balance approach. Analysis of experimental results indicated that the developed linear model between DSC and the square root of the ration of random roughness (RR) to slope was significant at probability value of 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.