M Mirzaee, S Ruy, Gh Ghazavi, C Bogner,
Volume 12, Issue 46 (1-2009)
Abstract
At present, soil surface characteristics (SSC) are recognised as key parameters controlling infiltration rates, runoff generation and erosion. Microtopography of surface among SSC is the main one. The work presented in this paper is based on a set of digital elevation models (DEMs) supplied by two different methods: Laser roughness-meter and photogrammetry method. We used two maquettes. The used maquettes correspond to varying roughness (rough and soft roughness). These methods were compared using different statistical parameters of SSC such as heights and slopes histograms. In addition, we studied estimation of Random Roughness (RR) coefficient and Maximum Depression Storage (MDS). RR is considered as an indicator of microtopography and it is one of the main parameters influencing erosion and runoff-infiltration processes. The obtained RR by photogrammetry method showed, on average, 10 percent difference from laser method for soft maquette and 5 percent for the rough maquette. The range of this difference for the MDS varies from 2 to 34 percent, i.e., maximum 0.17 millimetres. In this study, photogrammetric method gives the DEMs with a lower slope for the rough maquette (on average 40.5 versus 46 for the laser method) and higher slope for the soft maquette (about 23.5 versus 20.7 for the laser method). The results showed the DEMs provided by photogrammetric method is able to perform accurate estimation for RR and provides good estimation for the MDS. Therefore, it can be useful in erosion and hydraulic studies.
M. R. Mirzaei, S. Ruy,
Volume 22, Issue 4 (Winter 2019)
Abstract
Preferential flow is of great importance in the environment and the human health. So, rapid water transportation and consequently, pollutants and pesticides leak out and get into the groundwater, making it very difficult to measure and quantify. To quantify and describe the preferential flow, two gravity-driven models were used: 1) kinematic wave model (KW) introduced by Germann in 1985), and 2) kinematic dispersive wave (KDW) model developed by applying a second-order correction to the Germann’s model by Di Pietro et al. in 2003. So, the experimental data was obtained using the laboratory mini-rainfall-simulator over cylindrical soil samples at the laboratory. Their parameters were obtained using Solver add-ins in the Excel software. Then, the results were compared using the root-mean-square error (RMSE). The results showed that the KDW model could better predict the preferential flow (with lower RMSE). Also, the regression results showed 1) there was no significant relation between the preferential flow and the total porosity, and 2) there is a significant relation between the preferential flow and the macrospores.
