Using sediment fingerprinting to identify erosion hotspots in a sub-catchment of Lake Kivu, Rwanda

Akayezu, Providence; Musinguzi, Laban; Natugonza, Vianny; Ogutu‐Ohwayo, R.; Mwathe, Ken; Dutton, Christopher L.; Manyifika, Marc

doi:10.1007/s10661-020-08774-5

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…In a case study from the Lake Kivu area of Rwanda, Akayezu et al (2020) showed the utility of erosion hotspot mapping for spatial targeting of soil and water conservation measures. The results of the study presented here can be used in a similar manner to identify hotspots within the study area where erosion is occurring (Fig.…”

Section: Discussionmentioning

confidence: 99%

Assessing soil and land health across two landscapes in eastern Rwanda to inform restoration activities

Winowiecki

Bargués‐Tobella

Mukuralinda

et al. 2021

SOIL

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Abstract. Land degradation negatively impacts water, food, and nutrition security and is leading to increased competition for resources. While landscape restoration has the potential to restore ecosystem function, understanding the drivers of degradation is critical for prioritizing and tracking interventions. We sampled 300–1000 m2 plots using the Land Degradation Surveillance Framework across Nyagatare and Kayonza districts in Rwanda to assess key soil and land health indicators, including soil organic carbon (SOC), erosion prevalence, vegetation structure and infiltration capacity, and their interactions. SOC content decreased with increasing sand content across both sites and sampling depths and was lowest in croplands and grasslands compared to shrublands and woodlands. Stable carbon isotope values (δ13C) ranged from −15.35 ‰ to −21.34 ‰, indicating a wide range of historic and current plant communities with both C3 and C4 photosynthetic pathways. Field-saturated hydraulic conductivity (Kfs) was modeled, with a median of 76 mm h−1 in Kayonza and 62 mm h−1 in Nyagatare, respectively. Topsoil OC had a positive effect on Kfs, whereas pH, sand, and erosion had negative effects. Soil erosion was highest in plots classified as woodland and shrubland. Maps of soil erosion and SOC at 30 m resolution were produced with high accuracy and showed strong variability across the study landscapes. These data demonstrate the importance of assessing multiple biophysical properties in order to assess land degradation, including the spatial patterns of soil and land health indicators across the landscape. By understanding the dynamics of land degradation and interactions between biophysical indicators, we can better prioritize interventions that result in multiple benefits as well as assess the impacts of restoration options.

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Section: Discussionmentioning

confidence: 99%

Assessing soil and land health across two landscapes in eastern Rwanda to inform restoration activities

Winowiecki

Bargués‐Tobella

Mukuralinda

et al. 2021

SOIL

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“…In this context, the inclusion and legalization of electricity transmission lines in the EIA process in future studies are very important in terms of the sustainability of the natural and cultural landscapes in the study area. Besides, Aslan and Soguksulu (2017), Yaman and Hasil, (2018), Akayezu et al (2020), Manolaki et al (2020), andZhao et al (2020) emphasized the necessity of ensuring the compliance of the landscaping studies, within the scope of the EIA reports, with ELC. Thus, within the scope of ELC, landscapes that have changed under pressure must be restored and ecological integrity must be ensured.…”

Section: Discussionmentioning

confidence: 99%

“…The study aims to determine the ecologically sensitive areas in terms of erosion risk. With the MAPA/ ICONA erosion modeling method used in this context, erosion risk status was evaluated with four main variables which are the land use/cover, vegetation, slope, and geological structure of the area (Akayezu et al, 2020;Lu et al, 2019;Safaei et al, 2019). Using the land use and slope data of the area, soil protection level was created (1), and using the slope and geological structure data, the erodibility status was determined (2).…”

Section: Erosion Risk Of the Landscapementioning

confidence: 99%

“…In areas under the threat of erosion, natural and structural solutions such as using vegetation or improving existing vegetation are used to stop erosion (Akayezu, et al, 2020;Lu et al, 2019). Accordingly, areas that have erosion risk were evaluated.…”

Section: Erosion Controlmentioning

confidence: 99%

“…With the restoration works, it is necessary to make water, soil, erosion, biodiversity, visibility, and habitat analyses, and determine the landscape sensitivity values they have in the area where the project will take place, and according to these values, the environmental damage that occurs during the construction and operation phases should be restored, managed, and monitored (LUC, 2017;MEUT, 2020). In this context, Rahman et al (2014), Sahin et al (2014), Akayezu et al (2020), andChazdon et al (2021) used landscape restoration techniques such as soil management-improvement, area to be preserved, erosion control, vegetation screening, and coastal arrangement within the scope of the landscape restoration process.…”

Section: Introductionmentioning

confidence: 99%

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An ecological restoration assessment integrating multi-criteria decision analysis with landscape sensitivity analysis for a hydroelectric power plant project: the Tokat-Niksar case

Demir

Demirel

Okatan

2021

Environ Monit Assess

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the results, the water function was found to have the highest, and the visibility the lowest priority in the ranking. Consequently, 1st, 2nd, 3rd, and 4th-degree sensitive areas with very high, high, and moderate landscape sensitivity were determined by weighted sum function by considering the priority of each landscape function, and accordingly, a five-stage landscape restoration model was developed including soil protection, areas to be protected, erosion control, vegetation screening, and creek reclamation. This study presents a framework for sustainable landscape restoration solutions in the town by combining landscape sensitivity analysis via MCDA.

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Differences in sediment provenance from rainfall and snowmelt erosion in the Mollisol region of Northeast China

Su,

Huang,

Zhou

2024

Earth Surf Processes Landf

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Differences in erosion patterns inevitably lead to different soil loss processes. However, the differences in sediment sources between rainfall and snowmelt erosion are not well studied. To address this gap, a study was conducted in a small agricultural catchment (3.5 km2) using the fingerprinting technique to quantify the various sources contributing to sediment, as well as determine the magnitude of sediment total nitrogen (TN), total phosphorus (TP), total potassium (TK) and soil organic matter (SOM) loads from three sources (cultivated land, unpaved roads and gullies) during the rainy season and spring thawing period. Sediment sources from 17 rainfall erosion and seven snowmelt erosion events of varying magnitudes were compared. The Collins and Bayesian mixing models, coupled with geochemical tracers (Cs, V, Cd, Pb and Ag), were applied to assess the contribution proportion of individual sediment sources to suspended sediment. According to the results obtained from the Bayesian mixing model with higher accuracy, cultivated land, unpaved roads and gullies contributed 60.3% (load‐weighted mean contribution [LMC] = 82.8%), 11.0% (LMC = 6.5%) and 28.7% (LMC = 10.7%) of the sediment in the rainy season, respectively. Cultivated land was the dominant sediment source for rainfall erosion, with high rainfall erosivity and sediment concentration. However, for snowmelt erosion, gullies were the primary sediment source (LMC = 66.2%), followed by cultivated land (LMC = 19.8%) and unpaved roads (load‐weighted = 14.0%). Meanwhile, in the spring thawing period, the contributions of unpaved roads to sediment were higher than in the rainy season. During the rainy season, the greatest contributions of TN, TP, TK and SOM were observed from cultivated land, with respective LMC values of 94.2%, 89.4%, 81.1% and 94.8%. With the increase of sediment contribution from gullies in the spring thawing period, its LMC of TN, TP, TK and SOM increased to 42.6%, 58.3%, 65.0% and 38.0%, respectively. The results of the study could be useful for understanding the processes of soil erosion, clarifying the driving mechanism of compound erosion, developing the compound erosion prediction model and optimizing the spatial configuration of erosion control measures.

show abstract

Using sediment fingerprinting to identify erosion hotspots in a sub-catchment of Lake Kivu, Rwanda

Cited by 7 publications

References 25 publications

Assessing soil and land health across two landscapes in eastern Rwanda to inform restoration activities

Assessing soil and land health across two landscapes in eastern Rwanda to inform restoration activities

An ecological restoration assessment integrating multi-criteria decision analysis with landscape sensitivity analysis for a hydroelectric power plant project: the Tokat-Niksar case

Differences in sediment provenance from rainfall and snowmelt erosion in the Mollisol region of Northeast China

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