The rainfall-runoff process (RRP) is an important part of hydrologic process. There is an effective measure to study RRP through artificial rainfall simulation. This paper describes a study on three growing stages (jointing stage, tasseling stage, and mature stage) of spring maize in which simulated rainfall events were used to study the effects of various factors (rainfall intensity and slope gradient) on the RRP. The RRP was tested with three different rainfall intensities (0.67, 1.00, and 1.67 mm/min) and subjected to three different slopes (5°, 15°, and 20°) so as to study RRP characteristics in semiarid regions. Regression analysis was used to study the results of this test. The following key results were obtained:(1) With the increase in rainfall intensity and slope, the increasing relationship with rainfall OPEN ACCESSWater 2015, 7 2991 duration, overland flow, and cumulative runoff, respectively, complied with logarithmic and quadratic functions before reaching stable runoff in each growing stage of spring maize; (2) The runoff coefficient increased with the increase in rainfall intensity and slope in each growing stages of spring maize. The relationship between runoff coefficient, slope, rainfall intensity, rainfall duration, antecedent soil moisture, and vegetation coverage was multivariate and nonlinear; (3) The runoff lag time decreased with the increase in rainfall intensity and slope within the same growing stage. In addition, the relationship between runoff lag time, slope, rainfall intensity, antecedent soil moisture, and vegetation coverage could also be expressed by a multivariate nonlinear equation; (4) The descent rate of soil infiltration rate curve increased with the increased rainfall intensity and slope in the same growing stage. Furthermore, by comparing the Kostiakov, Horton, and Philip models, it was found that the Horton infiltration model was the best for estimating soil infiltration rate and cumulative infiltration under the condition of test.
Abstract:The characteristics of rainfall-runoff are important aspects of hydrological processes. In this study, rainfall-runoff processes and soil moisture dynamics at different soil depths and slope positions of grassland with two different row spacings (5 cm and 10 cm, respectively, referred to as R5 and R10) were analyzed, by means of a solution of rainfall simulation experiments. Bare land was also considered as a comparison. The results showed that the mechanism of runoff generation was mainly excess infiltration overland flow. The surface runoff amount of R5 plot was greater than that of R10, while the interflow amount of R10 was larger than that of R5 plot, although the differences of the subsurface runoff processes between plots R5 and R10 were little. The effects of rainfall intensity on the surface runoff were significant, but not obvious on the interflow and recession curve, which can be described as a simple exponential equation, with a fitting degree of up to 0.854-0.996. The response of soil moisture to rainfall and evapotranspiration was mainly in the 0-20 cm layer, and the response at the 40 cm layer to rainfall was slower and generally occurred after the rainfall stopped. The upper slope generally responded fastest to rainfall, OPEN ACCESSWater 2014, 6 2672 and the foot of the slope was the slowest. The results presented here could provide insights into understanding the surface and subsurface runoff processes and soil moisture dynamics for grasslands in semi-arid regions.
Drought & flood events, especially the drought & flood combination events (DFCEs) on the North China Plain (NCP), known as an important grain production region in China, constitute a serious threat to China's food security. Studies on DFCEs in this region are of great significance for the rational allocation of water resources and the formulation of integrated response strategy for droughts and floods. In this study, L-moments theory and bivariate copula method were used to evaluate the probability characteristics of seasonal DFCEs (continuous drought, continuous flood, and alternation between drought and flood) on the NCP, based on the daily precipitation data at 19 meteorological stations. Results indicate the following: (1) On the NCP, the precipitation in summer accounts for 56.45%-72.02% of mean annual precipitation, and the precipitation in autumn and spring come second. The winter precipitation is the smallest (less than 4%); (2) The best-fit OPEN ACCESSAtmosphere 2014, 5 848 distribution for precipitation anomaly percentages in spring, summer and autumn are Generalized Normal (GNO), Generalized Logistic (GLO) and Pearson III (P-III) in sub-region I, respectively. While in sub-region II, they are respectively the P-III, P-III and Generalized Extreme-Value (GEV); (3) Compared with the Gumbel copula and Clayton copula, Frank copula is more suitable for spring-summer and summer-autumn precipitation anomaly percentage sequences on the NCP; (4) On the time scale, continuous drought respectively dominate in spring-summer DFCEs and in summer-autumn DFCEs on the NCP. Summer-autumn DFCEs prevail in sub-region I with the average probability value 0.34, while spring-summer DFCEs dominate in sub-region II, of which average probability value is 0.42; (5) On the spatial scale, most areas where the probability of continuous drought in spring-summer and spring drought & summer flood is relatively high are located in the northwest, northeast, and coastal parts of sub-region II; all the events with high probability of continuous drought in summer-autumn and summer flood & autumn drought occurred at the central part in the northwest of sub-region II.
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