Scale effects on runoff generation in meso-scale and large-scale sub-basins in the Luanhe River Basin

Abstract

Abstract. The scale effects on runoff coefficients have been observed by several researchers on plots or small watersheds, however, little research has been done on meso-scale and large-scale catchments. So six meso-scale and large-scale sub-basins of the Luanhe river basin, in northeast of China, were selected for calculating the runoff coefficients of single event during 1956–2002. An obvious reduction in average runoff coefficients from 0.43 (Liuhe basin) to 0.10 (Luanhe basin) was found with increasing basin area. And for the annual runoff coefficients from 1956 to 2002, the same trend was also observed. In addition, runoff coefficients varied wildly from one rainstorm to the other. One of the reasons is that at the beginning of the storm, the rainfall is absorbed in the soil and fills in the macropores of the soil, and after runoff generation rainfall infiltrates during the routing process. And the spatial variability of rainfall, the groundwater discharge ability can also lead to runoff coefficients reduction with the increasing basin area. The study on the scale effects on runoff coefficient is very important to develop a physically-based hydrological model and parameter estimation on different scales.

Spatial scale impact on daily surface water and sediment fluxes in Thukela river, South Africa

“…The same appeared to occur at subcatchment level, where sediment fluxes were even lower. Several studies have also shown lower unit-area runoff and sediment fluxes on stream channels than hillslopes (Constantz, 1998;Feng and Li, 2008;Goransson et al, 2013;Xu, 2014) due to lower slope gradients which promote high infiltration and sediment deposition (Doble et al, 2012;Eder et al, 2014). Results of cumulative runoff (Table 2) showed great annual runoff microcatchment level, which in some years (e.g.…”

Annual water, sediment, nutrient, and organic carbon fluxes in river basins: A global meta‐analysis as a function of scale

“…The erosion variables in this paper are annual data, based on natural precipitation, corresponding to hydrological years (Table ). The age of trials, time periods for which experiments had been running, varied from 1 to 45 years [e.g., Feng and Li , ], with 63% of the studies being 1 year old. In cases where erosion variables were reported for more than 1 year, each year's data were treated as a separate and independent measurement for purposes of this meta‐analysis.…”

Potencial De Escorrentía en Función Del Número De Curva en Una Cuenca Serrana, Napostá Grande (Argentina)

“…Dicha variable se determinó históricamente en función de la precipitación acumulada de los cinco días previos, P 5, la que condiciona el valor que toma CN medio de una cuenca para condiciones antecedentes secas (P5 < 23 mm) o húmedas (P5 > 40 mm) (SCS, 1972). Sin embargo, el NRCS (2004a) advierte que no existe correlación entre P5 y la variabilidad del CN y, en consecuencia, el uso de tablas de P5 ya no es compatible ni aprobado por NRCS (Grabau et al, 2009). Sobre la base de los resultados de Hjelmfelt et al (1982), se postula que el CN constituye una variable aleatoria con tendencia central de tipo II y límites de error I y III, correspondientes al 90 y 10 % de probabilidad de excedencia, respectivamente (Grabau et al, 2009).…”