Rainfall-runoff erosivity factors for single storm events in northern Iraq were derived from the basic theory of soil detachment and transport. The factors derived are a single parameter which includes runoff depth only and a factor which combines runoff depth and peak rate. These two erosivity ...
An accurate assessment of run-off through aerial rainfall is a basic concept in most of the rainfall-runoff models, particularly conceptual models which em... DG Durbude,BK Purandara,A Sharma - 《Journal of the Indian Society of Remote Sensing》 被引量: 26发表: 2001年 Integrated approach fo...
The use of cloud tracking techniques and storm identification procedures is proposed in this paper with the aim of predicting the evolution of cloud entities associated with the highest rainfall probability within a given meteorological scenario. Suitable algorithms for this kind of analysis are based ...
Numerical models and machine learning methods are implemented and compared to simulate and predict erosional dam-break flows and bed morphodynamics. The nonlinear shallow water equations, including sediment transport and bedload terms, are solved using a well-balanced finite volume method. Empirical erosi...
Rainfall (SHV = 1.6), surface water discharge (SHV = 2.4), mean wind speed (SHV = 10.1), and erosive winds frequency (SHV = 1.6) had the highest contribution in predicting the target variable in winter, spring, summer, and autumn, respectively. These findings demonstrate...
Tani, M., Fujimoto, M., Katsuyama, M., Kojima, N., Hosoda, I., Kosugi, K., Kosugi, Y., and Nakamura, S.: Predicting the dependencies of rainfall-runoff responses on human forest disturbances with soil loss based on the runoff mechanisms in granitic and sedimentary-rock mountains, ...
The model used chemical oxygen demand parameters from a highway runoff site in west Los Angeles for eight storm events. FF indices such as the mass first flush ratio (MFF n) and the partial event mean concentration to event mean concentration ratio (PEMC t/EMC) were calculated from ...
2006. Predicting storm runoff from different land-use classes using a geographical information system-based distributed model. Hydrological Processes 20: 533-548.Liu, Y. B., Gebremeskel, S., De Smedt, F., Hoffmann, L. and Pfister, L. (2006), Predicting storm runoff from...
Predicting storm runoff from different land-use classes using a geographical information system-based distributed model. Hydrological Processes 20: 533-548.Liu, Y.B., Gebremeskel, S., de Smedt, F., Hoffman, L., Pfister, L., 2006. Predicting storm runoff from different land-use classes ...
Predicting storm runoff from different land-use classes using a geographical information system-based distributed model. Hydrological Processes 20: 533-548.Liu YB, Gebremeske S, Smedt FD, Hoffmann L, Pfister L. 2006. Predicting storm runoff from different land-use classes using a geographical ...