3.9 GIS-Based Soil Erosion Modeling

Mitášová, Helena; Barton, C. Michael; Ullah, Isaac; Hofierka, Jaroslav; Harmon, Russell S.

doi:10.1016/b978-0-12-374739-6.00052-x

Cited by 55 publications

(44 citation statements)

References 65 publications

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“…The change in RR parameter values is dictated more by variation in soil texture with different magnitude of initial surface roughness than the impact of rainfall. In contrast to the relative Ac exponent values of 0.4–0.6 identified by Govers () and Mitasova et al (), the current study predicted lower values. This may be attributed to the difference in experimental conditions and consideration of small size of rills, which need further research under medium rill size conditions.…”

Section: Resultscontrasting

confidence: 99%

“…The current research results confirmed that due to the rougher surfaces in the form of ridges and depressions, a gradual effect on rill initiation occurred when rainfall increased. (1991) and Mitasova et al (2013), the current study predicted lower values. This may be attributed to the difference in experimental conditions and consideration of small size of rills, which need further research under medium rill size conditions.…”

Section: Figurecontrasting

confidence: 54%

“…Earlier studies have developed empirical rill incision indices that are used to find threshold area for rill initiation (Desmet & Govers, ; Mitasova et al, ; Moore, Burch, & Mackenzie, ). These indices describe thresholds when exceeded, it identifies areas prone to rill erosion by overland flow.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, parameters considered in self-organized critical rill network model such as surface reduction by erosion and erodibility are less suitable for simulating both oriented and random roughness and net surface change over time (Hofer et al, 2012). A lack of representing detailed rough surfaces in erosion modelling overestimates actual erosion (Mitasova, Barton, Ullah, Hofierka, & Harmon, 2013;Warren et al, 2005); thus, there is a need for detailed topographic and soil surface roughness information to better predict the initiation and location of erosive rills and deriving realistic rill erosion parameters. Desmet and Govers (1997) and Favis-Mortlock (1998) observed the difficulty to predict initiation of individual rills without the influence of tillage-induced surface irregularities.…”

Section: Introductionmentioning

confidence: 99%

“…Earlier studies have developed empirical rill incision indices that are used to find threshold area for rill initiation (Desmet & Govers, 1997;Mitasova et al, 2013;Moore, Burch, & Mackenzie, 1988).…”

Section: Introductionmentioning

confidence: 99%

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Tillage‐induced surface roughness and topographic conditions for rill initiation in Angereb watershed, Ethiopia

Desta

2018

Hydrological Processes

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Rill erosion makes up one source of sediment detachment and transport on agricultural fields in the Ethiopia highlands. It is so important to understand the conditions for rill initiation and demarcating rill prone areas for management planning. In this paper, we estimated rill incision considering tillage‐induced surface roughness, upslope contributing area, and slope gradient. Field experiments were installed on two fresh‐tilled smallholder agricultural plots of 3.2 m wide and 14.4 m long in the Angereb watershed of the upper Lake Tana subbasin in Ethiopia. The plots mainly represent clay and sandy clay loam soils. Time series digital elevation models generated by digital photogrammetry were used to derive topographic and surface roughness variables corresponding to 46, 116, 174, and 410‐mm cumulative rainfall. A non‐linear regression model was fitted on the slope gradient, upslope contributing area, and surface random roughness of individual rills to predict threshold area for rill initiation. Subsequent rainfall events have resulted in rough surfaces later. The change in random roughness in each rainfall event compared with the first stage amounts to 1.81, 1.62, 1.68, and 1.74 cm on clay soil and −0.05, 0.86, 1.55, and 2.06 cm on sandy clay loam soil. Prediction of the threshold area for rill initiation has improved when considering random roughness and its temporal changes. The average prediction parameter of the unit contributing area was 0.03 ± 0.05 and 0.04 ± 0.04, and of the random roughness was −0.08 ± 0.13 and −0.13 ± 0.05 on clay and sandy clay loam soils, respectively. The prediction resulted in a threshold area between 0.20 and 0.47 (average of 0.36 ± 0.11) on clay soil and 0.28 and 0.39 (average of 0.34 ± 0.05) on sandy clay loam soil. The significant variation of threshold area (p < 0.05) over the subsequent rainfall events ensures the role of incorporating surface roughness in predicting rill initiation. The result demonstrates the need to consider the variable threshold area over rainfall periods for rill incision modelling and indirectly improves the slope–length factor of erosion models.

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Section: Resultscontrasting

confidence: 99%

Section: Figurecontrasting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Tillage‐induced surface roughness and topographic conditions for rill initiation in Angereb watershed, Ethiopia

Desta

2018

Hydrological Processes

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Runoff–sediment dynamics and degradation patterns in an abandoned terraced landscape on the Loess Plateau

Fang,

Peng,

Yan

et al. 2024

Earth Surf Processes Landf

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Terracing is an important measure to conserve water and soil on the Loess Plateau. Previous studies have showed that due to extreme rainstorms and a lack of maintenance, loess terraces have experienced degradation predominantly as collapses and sinkholes. Investigating the hydrological processes associated with terrace degradation is vital to understand terrace degradation mechanisms and maintain terraced landscape sustainability. Using a high‐resolution digital elevation model (DEM) based on unmanned aerial vehicle (UAV)remote sensing, as well as SIMulated Water Erosion (SIMWE) model, we explored the runoff–sediment dynamics on the terraced slopes on the Loess Plateau under rainstorm conditions and the terrace degradation patterns. The results showed that the dominant longitudinal water flow between terrace steps and converging lateral water flow along terrace surfaces indicate terrace ridge collapses and terrace surface sinkholes, respectively. Damaged areas exhibit high sediment flux and erosion potential. The water dynamics and degradation pattern were influenced by the original slope topography and terrace morphology. Specifically, most damages are distributed on concave slopes with concentrated water flow. In narrow terraces, under scattered longitudinal water flow, the dominant damages are ordinary collapses and the overall terraced topography tends to degrade into natural slopes. In wide terraces, concentrated longitudinal and well‐developed transverse water flows form a basic degradation pattern dominated by sinkhole‐induced collapses. This study verified the feasibility of SIMWE‐based hydrological simulation in assessing the degradation pattern of terraces on the Loess Plateau and demonstrated its potential for spatial scales and complex scenarios through compared with the soil moisture content (SMC)‐based method. The study concluded that the dominant runoff paths under the constraints of slope microtopography control the terrace degradation patterns. Our findings can serve as a theoretical basis for predicting hydrological hazards on terraces on the Loess Plateau and conducting a scientific design of terraces.

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Soil and water conservation in terraced and non‐terraced cultivations: an extensive comparison of 50 vineyards

et al. 2022

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Understanding the soil and water conservation (SWC) impact of steep-slope agricultural practices (e.g. terraces) has arguably never been more relevant than today, in the face of widespread intensifying rainfall conditions. In Italy, a diverse mosaic of terraced and non-terraced cultivation systems have historically developed from local traditions and more recently from the introduction of machinery. Previous studies suggested that each type of vineyard configuration is characterised by a specific set of soil degradation patterns. However, an extensive analysis of SWC impacts by different vineyard configurations is missing, while this is crucial for providing robust guidelines for future-proof viticulture. Here, we provide a unique extensive comparison of SWC in 50 vineyards, consisting of 10 sites of 5 distinct practices: slope-wise cultivation (SC), contour cultivation (CC), contour terracing (CT), broad-base terracing (BT) and oblique terracing (OT). A big-data analysis approach of physical erosion modelling based on high-resolution LiDAR data is performed, while four predefined SWC indicators are systematically analysed and statistically quantified. Regular contour terracing (CT) ranked best across all indicators, reflecting a good combination of flow interception and homogeneous distribution of runoff and sediment under intense rainfall conditions. The least SWC-effective practices (SC, CC, and OT) were related to vineyards optimised for trafficability by access roads or uninterrupted inter-row paths, which created high upstream-downstream connectivity and are thus prone to flow accumulation. The novel large-scale approach of this study offers a robust comparison of SWC impacts under intense rainstorms, which is becoming increasingly relevant for the sustainable future management of such landscapes.

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3.9 GIS-Based Soil Erosion Modeling

Cited by 55 publications

References 65 publications

Tillage‐induced surface roughness and topographic conditions for rill initiation in Angereb watershed, Ethiopia

Tillage‐induced surface roughness and topographic conditions for rill initiation in Angereb watershed, Ethiopia

Runoff–sediment dynamics and degradation patterns in an abandoned terraced landscape on the Loess Plateau

Soil and water conservation in terraced and non‐terraced cultivations: an extensive comparison of 50 vineyards

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