Digital soil erodibility mapping by soilscape trending and kriging

Avalos, Fabio Arnaldo Pomar; Silva, Marx Leandro Naves; Batista, Pedro Velloso Gomes; Pontes, Lucas Machado; Oliveira, Marcelo Silva de

doi:10.1002/ldr.3057

Cited by 16 publications

(10 citation statements)

References 33 publications

(47 reference statements)

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“…However, varying the values of the USLE parameters had little impact on estimated sediment load, as showed by the OAT sensitivity analysis. Importantly, we used a wide range of possible USLE_K values, which were selected considering the specificities of the erodibility of tropical soils (Salvador Sanchis et al, 2009;Borselli et al, 2012;Avalos et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Assessing sediment yield and streamflow with SWAT model in a small sub-basin of the Cantareira System

Pontes¹,

Batista²,

Silva³

et al. 2021

Revista Brasileira De Ciência Do Solo

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Hydro-sedimentological models might be useful tools for investigating the effectiveness of soil and water conservation practices. However, evaluating the usefulness of such models requires that predictions are tested against observational data and that uncertainty from model parameterization is addressed. Here we aimed to evaluate the capacity of the SWAT model to simulate monthly streamflow and sediment load in the Posses creek catchment (12 km 2 ), Southeast Brazil. The SUFI-2 algorithm from SWAT-CUP was applied for calibration, testing, uncertainty, and sensitivity analysis. The model was calibrated and initially tested using discharge and sediment load data, which were measured at the catchment outlet. Additionally, we used soil loss measurements from erosion plots within the catchment as independent data for model evaluation. Average monthly streamflow simulations obtained satisfactory results, with Nash-Sutcliffe coefficient (NSE) values of 0.75 and 0.51 for the calibration and testing periods, respectively. Sediment load simulations also displayed satisfactory results for calibration (NSE = 0.65) and testing (NSE = 0.52). However, the comparison with independent plot data revealed that SWAT severely overestimated hillslope erosion rates and compensated it with high sediment channel deposition. Moreover, the model was not sensitive to the parameters used for calculating hillslope sediment yields. Therefore, it should be used with caution for evaluating the interactions between land use, soil erosion, and sediment delivery. We found that the commonly used outlet-based approach for model calibration and testing can lead to internal misrepresentations, and models can reproduce the right answer for the wrong reasons.

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Section: Discussionmentioning

confidence: 99%

Assessing sediment yield and streamflow with SWAT model in a small sub-basin of the Cantareira System

Pontes¹,

Batista²,

Silva³

et al. 2021

Revista Brasileira De Ciência Do Solo

Self Cite

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“…It causes serious off-site pollution in channels and reservoirs, thereby reducing their storage volume, lifetime, and ecological benefits [4,5]. The analysis and quantification of soil erosion and its linked processes are essential for the conservation of natural resources [6]. Soil erodibility reflects the inherent susceptibility of soil to exogenic erosive forces, and it is one of the key parameters for estimating soil loss [7,8].…”

Section: Introductionmentioning

confidence: 99%

Use of Visible and Near-Infrared Reflectance Spectroscopy Models to Determine Soil Erodibility Factor (K) in an Ecologically Restored Watershed

Jiang

Chen

et al. 2020

Remote Sensing

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This study aimed to assess the ability of using visible and near-infrared reflectance (Vis–NIR) spectroscopy to quantify soil erodibility factor (K) rapidly in an ecologically restored watershed. To achieve this goal, we explored the performance and transferability of the developed spectral models in multiple land-use types: woodland, shrubland, terrace, and slope farmland (the first two types are natural land and the latter two are cultivated land). Subsequently, we developed an improved approach by combining spectral data with related topographic variables (i.e., elevation, watershed location, slope height, and normalized height) to estimate K. The results indicate that the calibrated spectral model using total samples could estimate K factor effectively (R2CV = 0.71, RMSECV = 0.0030 Mg h Mj−1 mm−1, and RPDCV = 1.84). When predicting K in the new samples, models performed well in natural land soils (R2P = 0.74, RPDP = 1.93) but failed in cultivated land soils (R2P = 0.24, RPDP = 0.99). Furthermore, the developed models showed low transferability between the natural and cultivated land datasets. The results also indicate that the combination of spectral data with topographic variables could slightly increase the accuracies of K estimation in total and natural land datasets but did not work for cultivated land samples. This study demonstrated that the Vis–NIR spectroscopy could be used as an effective method in predicting K. However, the predictability and transferability of the calibrated models were land-use type dependent. Our study also revealed that the coupling of spectrum and environmental variable is an effective improvement of K estimation in natural landscape region.

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“…The uncertainties associated with USLE-SDR family models are barely discussed in the literature and validating the soil erosion rates produced by these models is challenging due to the lack of observational records, especially in data-scarce environments [58]. However, some efforts have been made to compute K-factor flaws [53,[59][60][61][62][63], which tend to present a higher uncertainty when compared to the other USLE factors [37]. In contrast to the K-factor, the SDR uncertainties were found to be around 5% [37].…”

Section: Sdr-usle Model Evaluationmentioning

confidence: 99%

USLE K-Factor Method Selection for a Tropical Catchment

et al. 2019

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The use of the Universal Soil Loss Equation (USLE) and the Sediment Delivery Ratio (SDR) facilitates sediment yield (SY) estimates in watersheds. However, the soil loss predictions are frequently unrealistic because of the methods used to estimate the USLE’s factors. Here, we evaluated the performance of methods to estimate the soil erodibility (K-factor) and the influence of its estimation in the SY predictions. K-factor values were obtained from three widely used equations and using a portable rainfall simulator. These values were used to compute annual average soil loss and SY in a tropical watershed. We compared SY estimates with a 15-month observed sediment discharge dataset sampled in the catchment outlet. The most reliable method for the K-factor estimating was the USLE nomograph. Furthermore, our results indicate that the use of a portable rainfall simulator to estimate the K-factor tends to underestimate soil loss and sediment delivery.

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Digital soil erodibility mapping by soilscape trending and kriging

Cited by 16 publications

References 33 publications

Assessing sediment yield and streamflow with SWAT model in a small sub-basin of the Cantareira System

Assessing sediment yield and streamflow with SWAT model in a small sub-basin of the Cantareira System

Use of Visible and Near-Infrared Reflectance Spectroscopy Models to Determine Soil Erodibility Factor (K) in an Ecologically Restored Watershed

USLE K-Factor Method Selection for a Tropical Catchment

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