A. Vaezi, M. Abbasi,
Volume 16, Issue 61 (10-2012)
Abstract
The Soil Conservation Service Curve Number (SCS-CN) method is widely used for predicting direct runoff from rainfall events. The ratio of initial abstraction (λ=Ia/S) to maximum potential retention (S) was assumed in its original development to be equal to 0.2 (λ=Ia/S=0.2) in SCS-CN method. Application of the initial abstraction ratio equal to 0.2 out of the area where it has been developed may lead to a non logical estimation of runoff. Thus, the study was conducted to determine the initial abstraction ratio (λ=Ia/S) by analyzing measured rainfall-runoff events. The dataset consisted of 58 rainfall-runoff events during 15 years (1987-2001) of rainfall and runoff measurements from Taham-Chay watershed, northwest of Zanjan, Iran. Based on the results, the estimated runoff value on the basis of Ia= 0.2S was 26.7 times higher than the measured value, on average. There was a very low relationship between the measured and estimated runoff values (R2=0.09) and mean model error was 0.13. The Ia/S values varied from 0.004 to 0.008 with an average of 0.006. When Ia/S value was modified to 0.08, ratio of the measured to estimate runoff value was 1.4 and the determination coefficient (R2) of the relationship between the two was 0.41. When seven rainfall events that had the low rainfall intensity values (lower than 0.14 mm/h) and two events that had the high rainfall depth (bigger than 10.47 mm) during the past five days were removed from the data analysis process, ratio of the measured to estimated runoff value decreased to 1.3 and the determination coefficient (R2) of the relationship between the two enhanced to 0.90. The mean model error for the modified Ia/S value also decreased to 0.007. It also improved model efficiency coefficient (EF) to -0.089 compared with 0.91 for traditional Ia/S value (0.2).
A. R. Vaezi, M. Ahmadi,
Volume 21, Issue 3 (11-2017)
Abstract
Modified Universal Soil Loss Equation (MUSLE) is one of soil loss estimation models which has been developed based on the runoff characteristics in the event scale. However, it needs to be evaluated in the plot scale for the semi-arid rainfall events. With this aim, a field study was designed using twenty one plots. Runoff and soil loss were measured using 5-min samples under seven rainfall intensities consisted of 10, 20, 30, 40, 50 60, and 70 mm h-1 for 60 min. Soil loss was estimated using the MUSLE based on the runoff volume (Q) and runoff peak discharge (qp) and the values were compared with the observed values. The estimated soil loss was about 3.89 times bigger than the observed value on average. In order to improve model estimations, the power of rainfall erosivity index was modified from 0.56 to 0.62, (Q qp)0.62. The modification of the MUSLE model improved model efficiency (ME) from -5.5 to 0.47 and decreased the root mean square error from 0.000137 to 0.000031. This study revealed that the MUSLE overestimates soil loss from the small plots in the semi -arid regions. Therefore it is essential to calibrate runoff erosivity index using the data observed in the area. The modified MUSLE can be reliably used to predict soil loss in the small plot scale in semi-arid regions.
