Soil conservation service curve number determination for forest cover using rainfall and runoff data in experimental forests

Abstract

Using the Soil Conservation Service (SCS) curve number (CN) procedure for estimating runoff volume on an ungauged forest watershed remains controversial because little guidance has been provided for defining appropriate CN values. In this study, alternative methods for assigning CN values (CNs) were assessed to determine whether these methods provide acceptable estimates of runoff on forested watersheds. The estimated CNs varied between the methods employed, showing the highest CN values when derived from a probabilistic method and lowest when derived from a graphical method. The tabulated CN values in Section 4 of the National Engineering Handbook (NEH-4) had relatively higher bias compared to those derived from measured rainfall-runoff data. The storm runoff volume was predicted using the assigned CNs and compared with the observations. The coefficients of determination and RMSE values between the measured and estimated runoff volumes varied with the methods employed. The highest watershed average RMSE value was obtained by the use of the tabulated CN values in NEH-4 (51.19 mm), while arithmetic mean approach provided the lowest average RMSE value of 24.38 mm, even though this method requires intensive data collection. Among the alternatives, probabilistic method was found to be the most reliable in determining CNs for forest cover with limited data. The estimated runoff largely agreed with the observations. Therefore, the revised CNs can be used for estimating storm runoff from ungauged, mountainous forests.

Impacts of different slash disposals on soil and water erosion of high-intensity management Eucalyptus grandis × urophylla plantation

“…Therefore, replacing them is a significant factor for soil and water conservation. No factors are found to be correlated with factor T in this paper, which contradicts the existing conclusions regarding the correlation between soil properties, slashes [ 58 ], and T. The intensity of rainfall is identified as the most critical factor affecting T [ 59 ]. This may be attributed to the excessive intensity of rainfall we considered, which could overshadow the influence of other factors on T. WP has a negative correlation with WL in SE, but WP and WL have no correlation in BF and MA.…”

Performance of LSTM over SWAT in Rainfall-Runoff Modeling in a Small, Forested Watershed: A Case Study of Cork Brook, RI

“…The SWAT model has a strong conceptual and physical understanding of watershed processes and the explainability of parameters. Numerous studies have been conducted using the application of SWAT in forested watersheds [41][42][43]. In this study, the SWAT model is calibrated using the Uncertainty in Sequential Uncertainty Fitting (SUFI) in SWATCUP, a Calibration Uncertainty Procedure program, which has the ability for sensitivity analysis, calibration, validation, and uncertainty analysis of the SWAT model [44].…”

Dominant Role of Stochastic Processes in Soil Fungal Communities in Pioneer Forests at a Regional Scale

“…Precipitation can directly affect the growth of soil fungi by changing soil moisture (15, 16, 17). At the same time, runoff caused by precipitation causes the distribution of nutrients and changes in root biomass (18, 19, 20), indirectly affecting soil fungal communities’ occurrence and spread (21, 22, 23, 24, 25). Similarly, temperature changes can also affect the input of organic matter by changing plant communities and productivity (26), thereby indirectly affecting the occurrence of soil fungal communities (27, 28).…”