Selected soil properties as indicators of soil water regime in the Cathedral Peak VI catchment of KwaZulu-Natal, South Africa

Kuenene, B.T.; Huyssteen, CW van; Roux, Pal le

doi:10.1080/02571862.2013.767387

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…In the recent past, hydropedological studies done on landscape scale in South Africa have focussed on the interpretation of soil morphological properties, and their spatial distribution, in order to derive the hydrological behaviour of hillslopes and catchments (e.g. Van Tol et al 2010;Kuenene et al 2013). These qualitative descriptions of the dominant hydrological behaviour were then used to construct conceptual flowpath models that were used in hydrological modelling (Van Zijl et al 2016) to determine the migration paths of pollutants (Mamera & Van Tol 2018), wetland rehabilitation (Riddell, Lorentz & Kotze 2012) and the impact of land-use changes (e.g.…”

Section: Introductionmentioning

confidence: 99%

Identification of hydropedological flowpaths in Stevenson–Hamilton catena from soil morphological, chemical and hydraulic properties

Bouwer

Roux

Tol

2020

KOEDOE - African Protected Area Conservation and Science

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Section: Introductionmentioning

confidence: 99%

Identification of hydropedological flowpaths in Stevenson–Hamilton catena from soil morphological, chemical and hydraulic properties

Bouwer

Roux

Tol

2020

KOEDOE - African Protected Area Conservation and Science

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“…The dense grassland minimizes soil evaporation while keeping the surface temperature lower than surrounding exposed areas. The soils act as an efficient storage of organic carbon due to the dense root networks of the grasses (Kunene et al., 2015). This is the principal research catchment of SAEON owing to the density and comprehensive nature of monitoring.…”

Section: Study Areamentioning

confidence: 99%

Estimation of soil moisture using environmental covariates and machine learning algorithms in Cathedral Peak Catchment, South Africa

Kibirige,

Gokool,

Mkhize

2023

Vadose Zone Journal

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Soil moisture (SM) is a fundamental constituent of the terrestrial environment and the hydrological cycle. Owing to its significant influence on catchment hydrological responses, it can be utilized as an indicator of floods and droughts to aid early warning systems. This study aimed to develop a field‐scale method to estimate SM using parametric and machine learning‐based methods to compare whether advanced artificial intelligence methods can give similar results as traditional methods. Considering this, monthly observed SM data (from the top 10 cm), environmental covariates, and remotely sensed data from March 2019 to July 2021 for the Cathedral Peak Research Catchments VI and IX in South Africa were obtained. From the 241 observations obtained across 12 sites, 160 (∼66%) were used for model training, while the remaining 81 (∼34%) were used for model testing. Employing 10‐fold cross‐validation, the individual machine learning models (viz., support vector machine [SVM], random forest (RF), k‐nearest neighbor, classification and regression trees [Rpart], and generalized linear model) displayed a satisfactory performance (R2 = 0.52–0.79; root mean square error = 3.79–5.80). In the validation phase, the RF model displayed a superior performance, followed by the SVM. Subsequent SM estimation using the hybrid model produced satisfactory results in training (R2 = 0.90) and testing (R2 = 0.45). The results obtained from this study can aid in predicting SM variations in catchments with limited monitoring. Furthermore, this model can be applied in drought monitoring, forecasting, and informing agricultural management practices.

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“…Instead, almost all hillslope seeps are stratigraphic and form where a layer with restricted permeability deflects water that has filtered through the soils of the upper slope via gravity. The layer of restricted permeability may occur either at the soil/bedrock interface or within the soil where there is a change in soil texture associated with reduced hydraulic conductivity (Kuenene et al, 2011(Kuenene et al, , 2013Van Tol et al, 2011).…”

Section: Colluvial Wetlands Hillslope Seep Wetlandsmentioning

confidence: 99%

A Genetic Geomorphic Classification System for Southern African Palustrine Wetlands: Global Implications for the Management of Wetlands in Drylands

Grenfell

Ellery

et al. 2019

Front. Environ. Sci.

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Due to climatic constraints in dryland regions, wetlands usually occur at confluences of flow paths, whether from surface flow, inter-flow or at locations of groundwater discharge. Long-term landscape processes that shape valleys and focus the movement of water and sediment are accountable for providing a suitable template with which hydrology interacts to allow wetland formation. Current hydrogeomorphic classification systems do not address system-scale linkages of sediment and water transport across the landscape, and are therefore unable to contextualise long-term process dynamics. Misunderstanding long-term earth system processes can result in the application of inappropriate restoration strategies that isolate wetlands from longitudinal drivers of their formation. We propose a genetic classification system that focuses on the mode of wetland formation, and is based on the understanding that genetic processes impact on the outcome hydrology, sedimentology, geomorphology, ecosystem service provision, and long-term dynamics of wetlands in drylands. The classification aims to impart understanding of dynamic processes of sediment transport through wetlands, such that restoration plans can be sensitive to long-term landscape processes. The classification system, derived from a combination of international literature and published South African case studies, has four wetland macrotypes based on sediment source (colluvial, alluvial, Aeolian, and geochemical). These are subdivided into eight wetland types; hillslope seep, floodplain, valley-bottom, plain, blocked-valley, alluvial fan, aeolian depression, and geochemical depression. The classification is based on landscape location, shape, and the occurrence of geomorphic characteristics indicative of process.

show abstract

Selected soil properties as indicators of soil water regime in the Cathedral Peak VI catchment of KwaZulu-Natal, South Africa

Cited by 5 publications

References 16 publications

Identification of hydropedological flowpaths in Stevenson–Hamilton catena from soil morphological, chemical and hydraulic properties

Identification of hydropedological flowpaths in Stevenson–Hamilton catena from soil morphological, chemical and hydraulic properties

Estimation of soil moisture using environmental covariates and machine learning algorithms in Cathedral Peak Catchment, South Africa

A Genetic Geomorphic Classification System for Southern African Palustrine Wetlands: Global Implications for the Management of Wetlands in Drylands

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