How to model the effect of mechanical erosion control practices at a catchment scale?

Didoné, Elizeu Jonas; Minella, Jean Paolo Gomes; Allasia, Daniel

doi:10.1016/j.iswcr.2021.01.007

Cited by 10 publications

(6 citation statements)

References 32 publications

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Section: Best Management Practicesmentioning

confidence: 99%

“…Soil type is an important factor to consider when selecting erosion control practices [69]. Different types of soil have different levels of erodibility [69], which can affect the effectiveness of certain practices. For example, practices such as terracing and contour farming may be more effective on steep, sloping soils, while filter strips are more effective on flat, loamy soils.…”

Section: Best Management Practicesmentioning

confidence: 99%

“…National policy requirements are also important to consider when selecting erosion control practices [69,73]. Different countries may have different policies and regulations regarding land use and erosion control.…”

Section: Best Management Practicesmentioning

confidence: 99%

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Evaluation of Spatial-Temporal Variation of Soil Loss and Best Conservation Measures in an East Africa Catchment

2023

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Soil conservation (SC) is essential to maintain the reservoir service life and increase the yield since soil erosion is a major global concern that adversely affects not only the storage capacity but also the land fertility. This study evaluates the spatio-temporal variation of soil erosion using the popular SWAT model and identifies the best SC practice for Tekeze watershed located in the Northern part of Ethiopia. To accomplish this, four soil conservation management scenarios involving baseline, terracing, contouring, and grassed waterway scenarios are selected for soil loss evaluation. The SWAT model was calibrated and validated with R2 values of 0.7 and 0.9 and NSE values of 0.8 and 0.7, respectively, indicating satisfactory model performance. Five sub-basins of the catchment were found to be more susceptible to erosion with an average annual soil loss of 25.15 tons/ha/yr. Employment of the proposed SC measures in the sub-watershed erosion was reduced by 35.18%, 27.11%, and 18.76%, respectively, which is significant when compared with the baseline scenario. Since the investment cost of execution of an SC measure in a large watershed is very high, priority areas are also identified for cost savings as well as improved work efficiency.

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Section: Best Management Practicesmentioning

confidence: 99%

Section: Best Management Practicesmentioning

confidence: 99%

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Evaluation of Spatial-Temporal Variation of Soil Loss and Best Conservation Measures in an East Africa Catchment

2023

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“…Nevertheless, this complexity has to be considered especially for steep slopes during an evaluation. The alternative is to use the individual contour lines within the land parcel to compare the main cultivation direction with the local aspect [70].…”

Section: Dem Analysismentioning

confidence: 99%

Deriving the Main Cultivation Direction from Open Remote Sensing Data to Determine the Support Practice Measure Contouring

Scholand

Schmalz

2021

Land

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The P-factor for support practice of the Universal Soil Loss Equation (USLE) accounts for soil conservation measures and leads to a significant reduction in the modelled soil loss. However, in the practical application, the P-factor is the most neglected factor overall due to high effort for determining or lack of input data. This study provides a new method for automatic derivation of the main cultivation direction from seed rows and tramlines on agricultural land parcels using the Fast Line Detector (FLD) of the Open Computer Vision (OpenCV) package and open remote sensing data from Google Earth™. Comparison of the cultivation direction with the mean aspect for each land parcel allows the determination of a site-specific P-factor for the soil conservation measure contouring. After calibration of the FLD parameters, the success rate in a first application in the low mountain range Fischbach catchment, Germany, was 77.7% for 278 agricultural land parcels. The main reasons for unsuccessful detection were problems with headland detection, existing soil erosion, and widely varying albedo within the plots as well as individual outliers. The use of a corrected mask and enhanced parameterization offers promising improvements for a higher success rate of the FLD.

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“…The model of Woldemariam et al (2018) provides a quantitative estimate of the rates of water-induced soil loss and the spatial distribution of erosion risk. In this context, many studies in Brazil have obtained satisfactory results in verifying different soil losses as a function of precipitation data using the universal soil loss equation (USLE) method (Mello et al, 2015;Didoné et al, 2021;Godoi et al, 2021;Silva et al, 2021). The USLE has been used in several studies (Bezak et al, 2021) and requires a relatively small amount of information when compared to more complex models.…”

Section: Introductionmentioning

confidence: 99%

Estimating soil loss by laminar erosion using precision agriculture computational tools

Krug

Gomes

Souza

et al. 2022

Rev. bras. eng. agríc. ambient.

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The study aimed to identify and evaluate the spatial variability in laminar erosion in areas using precision agriculture tools. Soil data from three properties in the western region of Paraná state, Brazil, were used: one in the municipality of Céu Azul (area A) and two in Serranópolis do Iguaçu (areas B and C). To identify discrepant data (outliers), analysis of the dispersion of quartiles was performed using a box-plot graph. Data normality was verified using the Kolmogorov-Smirnov test. A spatial analysis was performed using AgDataBox-Map software. The parameters of the universal soil loss equation were estimated and used with map algebra to produce a model to identify areas susceptible to erosion. Area A (soil loss estimate = 0-200 t ha-1 per year) presented greater susceptibility to erosion than areas B and C (soil loss estimate = 0-150 t ha-1 per year); however, all areas had a low susceptibility to erosion.

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How to model the effect of mechanical erosion control practices at a catchment scale?

Cited by 10 publications

References 32 publications

Evaluation of Spatial-Temporal Variation of Soil Loss and Best Conservation Measures in an East Africa Catchment

Evaluation of Spatial-Temporal Variation of Soil Loss and Best Conservation Measures in an East Africa Catchment

Deriving the Main Cultivation Direction from Open Remote Sensing Data to Determine the Support Practice Measure Contouring

Estimating soil loss by laminar erosion using precision agriculture computational tools

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