scholarly journals An Improved SCS-CN Method Incorporating Slope, Soil Moisture, and Storm Duration Factors for Runoff Prediction

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1335 ◽  
Author(s):  
Wenhai Shi ◽  
Ni Wang
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Prediction Method ◽  
Slope Gradient ◽  
The Loess Plateau ◽  
Calibration And Validation ◽  
Runoff Prediction ◽  
Storm Duration ◽  
Scs Cn ◽  
Runoff Plots

Soil Conservation Service Curve Number (SCS-CN) is a popular surface runoff prediction method because it is simple in principle, convenient in application, and easy to accept. However, the method still has several limitations, such as lack of a land slope factor, discounting the storm duration, and the absence of guidance on antecedent moisture conditions. In this study, an equation was developed to improve the SCS-CN method by combining the CN value with the tabulated CN2 value and three introduced factors (slope gradient, soil moisture, and storm duration). The proposed method was tested for calibration and validation with a dataset from three runoff plots in a watershed of the Loess Plateau. The results showed the model efficiencies of the proposed method were improved to 80.58% and 80.44% during the calibration and validation period, respectively, which was better than the standard SCS-CN and the other two modified SCS-CN methods where only a single factor of soil moisture or slope gradient was considered, respectively. Using the parameters calibrated and validated by dataset of the initial three runoff plots, the proposed method was then applied to runoff estimation of the remaining three runoff plots in another watershed. The proposed method reduced the root-mean-square error between the observed and estimated runoff values from 5.53 to 2.01 mm. Furthermore, the parameters of soil moisture (b1 and b2) is the most sensitive, followed by parameters in storm duration (c) and slope equations (a1 and a2), and the least sensitive parameter is the initial abstraction ratio λ on the basis of the proposed method sensitivity analysis. Conclusions can be drawn from the above results that the proposed method incorporating the three factors in the SCS method may estimate runoff more accurately in the Loess Plateau of China.

scholarly journals Improved SMA-based SCS-CN method incorporating storm duration for runoff prediction on the Loess Plateau, China

2020 ◽  
Vol 51 (3) ◽  
pp. 443-455
Author(s):  
Wenhai Shi ◽  
Ni Wang
Keyword(s):  
Loess Plateau ◽  
Curve Number ◽  
The Loess Plateau ◽  
Moisture Condition ◽  
Soil Moisture Accounting ◽  
Antecedent Moisture ◽  
Storm Duration ◽  
Service Curve ◽  
Scs Cn ◽  
Runoff Events

Abstract In the Soil Conservation Service Curve Number (SCS-CN) method for estimating runoff, three antecedent moisture condition (AMC) levels produce a discrete relation between the curve number (CN) and soil water content, which results in corresponding sudden jumps in estimated runoff. An improved soil moisture accounting (SMA)-based SCS-CN method that incorporates a continuous function for the AMC was developed to obviate sudden jumps in estimated runoff. However, this method ignores the effect of storm duration on surface runoff, yet this is an important component of rainfall-runoff processes. In this study, the SMA-based method for runoff estimation was modified by incorporating storm duration and a revised SMA procedure. Then, the performance of the proposed method was compared to both the original SCS-CN and SMA-based methods by applying them in three experimental watersheds located on the Loess Plateau, China. The results indicate that the SCS-CN method underestimates large runoff events and overestimates small runoff events, yielding an efficiency of 0.626 in calibration and 0.051 in validation; the SMA-based method has improved runoff estimation in both calibration (efficiency = 0.702) and validation (efficiency = 0.481). However, the proposed method performed significantly better than both, yielding model efficiencies of 0.810 and 0.779 in calibration and validation, respectively.

Soil moisture variations in response to precipitation properties and plant communities on steep gully slope on the Loess Plateau

2021 ◽  
Vol 256 ◽  
pp. 107086
Author(s):  
Pingzong Zhu ◽  
Guanghui Zhang ◽  
Hongxiao Wang ◽  
Baojun Zhang ◽  
Yingna Liu
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Plant Communities ◽  
The Loess Plateau

Stochastic soil moisture dynamic modelling: a case study in the Loess Plateau, China

2018 ◽  
Vol 109 (3-4) ◽  
pp. 437-444
Author(s):  
Cong WANG ◽  
Shuai WANG ◽  
Bojie FU ◽  
Lu ZHANG ◽  
Nan LU ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Loess Plateau ◽  
Hydrological Cycle ◽  
Dynamic Modelling ◽  
Vegetation Restoration ◽  
Balance Model ◽  
Rainfall Regime ◽  
The Loess Plateau ◽  
Dry Period

ABSTRACTSoil moisture is a key factor in the ecohydrological cycle in water-limited ecosystems, and it integrates the effects of climate, soil, and vegetation. The water balance and the hydrological cycle are significantly important for vegetation restoration in water-limited regions, and these dynamics are still poorly understood. In this study, the soil moisture and water balance were modelled with the stochastic soil water balance model in the Loess Plateau, China. This model was verified by monitoring soil moisture data of black locust plantations in the Yangjuangou catchment in the Loess Plateau. The influences of a rainfall regime change on soil moisture and water balance were also explored. Three meteorological stations were selected (Yulin, Yan'an, and Luochuan) along the precipitation gradient to detect the effects of rainfall spatial variability on the soil moisture and water balance. The results showed that soil moisture tended to be more frequent at low levels with decreasing precipitation, and the ratio of evapotranspiration under stress in response to rainfall also changed from 74.0% in Yulin to 52.3% in Luochuan. In addition, the effects of a temporal change in rainfall regime on soil moisture and water balance were explored at Yan'an. The soil moisture probability density function moved to high soil moisture in the wet period compared to the dry period of Yan'an, and the evapotranspiration under stress increased from 59.5% to 72% from the wet period to the dry period. The results of this study prove the applicability of the stochastic model in the Loess Plateau and reveal its potential for guiding the vegetation restoration in the next stage.

scholarly journals Soil Moisture-Boundary Layer Feedbacks on the Loess Plateau in China Using Radiosonde Data with 1-D Atmospheric Boundary Layer Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1619
Author(s):  
Yingsai Ma ◽  
Xianhong Meng ◽  
Yinhuan Ao ◽  
Ye Yu ◽  
Guangwei Li ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Atmospheric Boundary Layer ◽  
Loess Plateau ◽  
Atmospheric Stability ◽  
Heat Fluxes ◽  
Radiosonde Data ◽  
Atmospheric Conditions ◽  
The Loess Plateau ◽  
The Impact

The Loess Plateau is one land-atmosphere coupling hotspot. Soil moisture has an influence on atmospheric boundary layer development under specific early-morning atmospheric thermodynamic structures. This paper investigates the sensitivity of atmospheric convection to soil moisture conditions over the Loess Plateau in China by using the convective triggering potential (CTP)—humidity index (HIlow) framework. The CTP indicates atmospheric stability and the HIlow indicates atmospheric humidity in the low-level atmosphere. By comparing the model outcomes with the observations, the one-dimensional model achieves realistic daily behavior of the radiation and surface heat fluxes and the mixed layer properties with appropriate modifications. New CTP-HIlow thresholds for soil moisture-atmosphere feedbacks are found in the Loess Plateau area. By applying the new thresholds with long-time scales sounding data, we conclude that negative feedback is dominant in the north and west portion of the Loess Plateau; positive feedback is predominant in the south and east portion. In general, this framework has predictive significance for the impact of soil moisture on precipitation. By using this new CTP-HIlow framework, we can determine under what atmospheric conditions soil moisture can affect the triggering of precipitation and under what atmospheric conditions soil moisture has no influence on the triggering of precipitation.

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