Evaluation of RUSLE and spatial assessment of agricultural soil erosion in Finland

Räsänen, Timo A.; Tähtikarhu, Mika; Uusi-Kämppä, Jaana; Piirainen, Sirpa; Туртола, Эйла

doi:10.1016/j.geodrs.2023.e00610

Cited by 17 publications

(4 citation statements)

References 53 publications

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“…Soil texture sampling was performed in the years 1979–1981 (Jokinen, 1983). Texture is a static soil property and considering the young landscape (Mokma et al, 2000) and the low erosion rates in the study area (Panagos et al, 2015; Puustinen et al, 2007; Räsänen et al, 2023), these values can also be assumed to be valid for recent conditions. The maximum spatial distance between the sampling points that was ~40 m and sampling depth 0–25 cm (2‐l samples).…”

Section: Methodsmentioning

confidence: 99%

Spatial pattern consistency and repeatability of proximal soil sensor data for digital soil mapping

Ahrends,

Simojoki,

Lajunen

2023

European J Soil Science

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Data from proximal soil sensors can facilitate digital soil mapping at high spatial resolutions. However, their use for predicting static soil properties, such as texture, is affected by spatio‐temporal changes in environmental and measurement conditions. In this research study, seasonal changes in spatial patterns and repeatability of data provided by a platform that simultaneously measures the red (Red) and near infrared (NIR) reflectance, apparent soil electrical conductivity (ECa), temperature and volumetric moisture content of topsoil (at 3‐6 cm depth) were assessed. Test fields are located in Southern Finland with textures dominated by clay and fine sandy till. During single scans, mean relative differences between the data from duplicated measurement points ranged from ~4 to 6 % and were the highest for temperature and Red values. The consistency of spatial patterns across seasons (spring and autumn 2021 and 2022) was the highest for ECa values, and the lowest for NIR. ECa and moisture were significant for predicting the clay contents at a cereal grain crop site, whereas temperature was significant at grass ley sites. Errors were generally lower when using spring data compared with autumn data (RMSE ranging from 4.8 to 11.1 % for the data from different fields and measurement dates). For the fields, where static soil properties change at small spatial scales, spatially detailed moisture and temperature data support the understanding of seasonal changes in the spatial patterns derived from multi‐sensor data, and the corresponding changes in the performance of calibration models.This article is protected by copyright. All rights reserved.

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Section: Methodsmentioning

confidence: 99%

Spatial pattern consistency and repeatability of proximal soil sensor data for digital soil mapping

Ahrends,

Simojoki,

Lajunen

2023

European J Soil Science

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“…Wischmeier et al [7] ont proposé l'équation universelle des pertes en sol (Universal Soil Loss Equation, USLE). Ce modèle empirique, largement appliqué par les chercheurs, se base sur le pouvoir érosif des précipitations, les propriétés physiques du sol, le couvert végétal, les pratiques de gestion de l'érosion et la topographie (Räsänen et al [16], Achu et al [17], Joshi et al [18]).…”

Section: Evolution Des Terrasses Agricolesunclassified

L’impact du Terrassement des Versants sur L’érosion Dans le Pourtour Occidental du Plateau du Jord Tannourine-Aaqoura (Liban)

El Hage Hassan,

Charbel,

Blond

2023

ridg

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Le pourtour occidental du plateau du Jord Tannourine-Aaqoura (Liban) est une région montagnarde méditerranéenne qui réunit les conditions de l’érosion hydrique : pluie abondante, pente raide, couvert végétal naturel ravagé et sol sensible à la dégradation. Cependant les terrasses agricoles aménagées depuis des décennies demeurent une pratique robuste pour limiter le ruissellement et élargir la surface agricole utile. Afin d’évaluer l’érosion aréolaire et le rôle des pratiques antiérosives, la méthodologie adoptée repose sur l’équation universelle de l’USLE révisée (RUSLE). La combinaison de paramètres du modèle, dans un SIG, a permis de définir que l’érosion hydrique peut dépasser les 51 t/ha/an essentiellement dans les secteurs marqués par l’absence des terrasses agricoles, et dépourvus d’un couvert végétal dense. Alors que les versants modelés en terrasses ne subissent que des pertes inférieures à 16 t/ha/an. La validation est faite par l’implantation d’un réseau de tiges métalliques. Face à ce risque de dégradation, il semble indispensable de conseiller des techniques agricoles protectrices.

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“…In recent decades, the USLE has undergone major changes, resulting in improved versions, such as the Revised USLE (RUSLE) [7,28], enabling the application of the equation at the watershed level and the development of maps that identify areas susceptible to water erosion. This model provides a clear perspective for understanding the interaction between erosion and its causal factors, is a computer-based model, and has benefited greatly from advances in Geographic Information System (GIS) and remote sensing technologies [1,13,14,[24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

“…This model provides a clear perspective for understanding the interaction between erosion and its causal factors, is a computer-based model, and has benefited greatly from advances in Geographic Information System (GIS) and remote sensing technologies [1,13,14,[24][25][26][27]. Rasanen et al (2023) [28] used the RUSLE in Finland to estimate the soil erosion on different spatial scales. Kumar et al (2022) [29] carried out a global-scale application of the RUSLE and outlined the suitability of the model under varying conditions.…”

Section: Introductionmentioning

confidence: 99%

Soil Erosion Modeling Using the Revised Universal Soil Loss Equation and a Geographic Information System in a Watershed in the Northeastern Brazilian Cerrado

Barbosa,

Guerra,

Valladares

2024

Geosciences

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Soils have an important task in maintaining vegetation cover and natural resources on Earth and are indispensable to societies. However, the accelerated soil erosion has become an environmental problem related to land settlement for agricultural practices and forestry and is linked to population growth. This study aimed to evaluate soil erosion in a watershed downstream of Parnaíba river, northwest of Piauí state, in the Brazilian Cerrado using geotechnology products and tools in order to understand the soil loss and map the potential erosion and actual erosion through qualitative and quantitative results to support the management and planning of the watershed in an effective and efficient way. As a modeling tool, this research used the Revised Universal Soil Loss Equation (RUSLE). The potential erosion ranged from very low to very high. The soil loss obtained by the integration of natural physical factors with land use (anthropic action) resulted in soil loss corresponding to the category slight (0–0.01 t.ha−1.year−1) to extremely high (>100 t.ha−1.year−1). The areas with the greatest soil loss were identified in land uses linked to pasture, exposed soil, and cultivated land. It was also possible to identify erosion features in the field, indicating the need to implement soil conservation practices.

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Evaluation of RUSLE and spatial assessment of agricultural soil erosion in Finland

Cited by 17 publications

References 53 publications

Spatial pattern consistency and repeatability of proximal soil sensor data for digital soil mapping

Spatial pattern consistency and repeatability of proximal soil sensor data for digital soil mapping

L’impact du Terrassement des Versants sur L’érosion Dans le Pourtour Occidental du Plateau du Jord Tannourine-Aaqoura (Liban)

Soil Erosion Modeling Using the Revised Universal Soil Loss Equation and a Geographic Information System in a Watershed in the Northeastern Brazilian Cerrado

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