Soil erodibility indices affecting the development of gully erosion in highly erodible soils of the Tsitsa Catchment in T35D and T35E, Eastern Cape, South Africa
- Kanuka, Gcobisa https://orcid.org/0000-0003-4736-7136
- Authors: Kanuka, Gcobisa https://orcid.org/0000-0003-4736-7136
- Date: 2022-01
- Subjects: Soil erosion , River sediments
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/22677 , vital:52642
- Description: This study evaluated soil inherent properties for the development of gullies and their erodibility potential using the holistic field and laboratory sample investigation approach. The potential of negative impact of sedimentation on dam and water infrastructure performance has raised the need to evaluate the factors promoting soil erosion leading to land degradation. The study aimed to assess the relationship among the selected properties of soil and variability among various soil groups. A case study design approach was adopted at the T35D and T35E areas of Tsitsa hydrologic Basin, Eastern Cape, South Africa. The task was accomplished through detailed random soil sampling in the field, soil chemical analysis and comparative analysis of soil variables. Based on the scope of the study soil laboratory analysis included the following: particle size distribution, soil textural analysis, physicochemical parameters analysis, macro-and-micronutrient analysis, and micro-porosity analysis. Further spatial and scenario analysis of soil erodibility was done using selected erodibility indices such as Sodium Adsorption Ratio (SAR), Exchangeable Sodium Percentage (ESP), Dispersivity Ratio (DR), Clay Dispersion Ratio (CDR), Clay Flocculation Index (CFI), Water-Stable Aggregate analysis (WSA), and Soil Erodibility factor analysis (KEF). The findings of the study showed that the catchment hosts sixteen distinct soil forms categorized into seven unique soil groups. The results further indicated that the Katspruit soil form of the gleyic soil group has the highest clay-size particles and a considerably high clay dispersion attribute among others soil forms. It was further deduced that gleyic soil type exhibited the highest soil pH (6.36), a considerably low Ca:Mg ratio (1.43), a substantially high sodium ion (0.50 mg/kg), the highest SAR (0.5), lowest WSA (0.018percent) and a substantially high KEF (0.018ab). Similarly, saprolite soils exhibited the nature of the lixisol with a virtually equal amount of clay (43.63percent) and fine sands (41.68percent), the lowest amount of Ca:Mg ratio (1.35), the highest acid saturation (50.59), the highest ESP (8.39), and a considerably high WSA (38.75). Other remarkable problematic soils identified in the study include the lithic soil and the duplex soil. For instance, the Lithic soil is characterized by the highest fine sand-size texture (61.38percent), considerably low organic carbon (2.63percent), low cation exchange capacity (3.55 cmol(+)/kg), much high DR (0.75), very low WSA (0.027percent), and the highest KEF (0.027a). Whereas, the duplex soil is characterized by the highest DR (0.81), critically high CDR (38.19percent), very low WSA (0.019percent), and a considerably high KEF (0.019a). The relatively stable soils within the catchment are the oxidic, and melanic, where the WSA is highest in oxidic (38.19percent) and relatively high for melanic (36.6percent), CFI is highest in melanic (85.02percent), and oxidic (74.32percent), and KEF is relatively low (0.016b) for both. Correlation of the selected soil erodibility indices shows that CFI shares a perfect inverse relationship with CDR while maintaining a strong significant relationship with DR (R = -0.504). Findings also show that the SAR expectedly produced a robust significant relationship with ESP (R = 0.644), while KEF exhibited a solid inverse relationship with WSA (R = 0.913). The correlation across the physical and chemical properties suggests that DR and CDR can be firmly and positively influenced by dispersive clay. At the same time, the two factors maintain a significantly negative relationship with dispersive sand. Also, clay-sized particles depicted a significant relationship with WSA. Physicochemical and chemical parameters influence only the ESP and SAR. A remarkable finding is the influence of iron and its presence on SAR. On the other hand, ESP was distinguished from SAR due to the inverse influence of potassium. The lithic soils identify as members of the collapsible soil of South Africa, while the gleyic soils identify with duplex and saprolite soils in the class of dispersive soils. The vertic soils characterize as expansive soil, while the Duplex soil also exhibits a soft soil attribute. In general, the study suggests that T35D and T35E areas of Tsitsa catchment vary spatially in soil erodibility potential. T35D area is characterized by dominant oxidic soil cover of relatively stable aggregate whose iron oxide enrichment could be attributed to inculcation of dolerite debris. Overall, the soil erodibility indices showed that the development of gully erosion in Tsitsa catchment is driven by high clay dispersivity ratio of the soil (mean = 0.70; 24percent CV), and poor soil structure relative to the low WSA range (18.1 – 34.0). Erodibility due to high sodicity are associated with saprolite (ESP = 8.02) and gleyic soils (ESP = 7.43) while the high soil dispersion was due to the vertic (46percent), duplex (38percent), cumulic (30percent), and lithic (27percent) soil components. The poor soil aggregates (WSA) were mainly controlled by the lithic (10percent), vertic (27percent), duplex (28percent), cumulic (31percent), and gleyic (34percent) soil components. Meanwhile, the T35E area is dominated by the dispersive and collapsible soils dominated by saprolites and lithic soils. Therefore, the environmental stakeholders are advised to adopt the best management practices within the dam area considering the vulnerability of the catchment to the development of gullies and the potential impact of sedimentation on the adequate performance of Tsitsa dam and its water infrastructures. , Thesis (MSc) -- Faculty of Science and Agriculture, 2022
- Full Text:
- Date Issued: 2022-01
- Authors: Kanuka, Gcobisa https://orcid.org/0000-0003-4736-7136
- Date: 2022-01
- Subjects: Soil erosion , River sediments
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/22677 , vital:52642
- Description: This study evaluated soil inherent properties for the development of gullies and their erodibility potential using the holistic field and laboratory sample investigation approach. The potential of negative impact of sedimentation on dam and water infrastructure performance has raised the need to evaluate the factors promoting soil erosion leading to land degradation. The study aimed to assess the relationship among the selected properties of soil and variability among various soil groups. A case study design approach was adopted at the T35D and T35E areas of Tsitsa hydrologic Basin, Eastern Cape, South Africa. The task was accomplished through detailed random soil sampling in the field, soil chemical analysis and comparative analysis of soil variables. Based on the scope of the study soil laboratory analysis included the following: particle size distribution, soil textural analysis, physicochemical parameters analysis, macro-and-micronutrient analysis, and micro-porosity analysis. Further spatial and scenario analysis of soil erodibility was done using selected erodibility indices such as Sodium Adsorption Ratio (SAR), Exchangeable Sodium Percentage (ESP), Dispersivity Ratio (DR), Clay Dispersion Ratio (CDR), Clay Flocculation Index (CFI), Water-Stable Aggregate analysis (WSA), and Soil Erodibility factor analysis (KEF). The findings of the study showed that the catchment hosts sixteen distinct soil forms categorized into seven unique soil groups. The results further indicated that the Katspruit soil form of the gleyic soil group has the highest clay-size particles and a considerably high clay dispersion attribute among others soil forms. It was further deduced that gleyic soil type exhibited the highest soil pH (6.36), a considerably low Ca:Mg ratio (1.43), a substantially high sodium ion (0.50 mg/kg), the highest SAR (0.5), lowest WSA (0.018percent) and a substantially high KEF (0.018ab). Similarly, saprolite soils exhibited the nature of the lixisol with a virtually equal amount of clay (43.63percent) and fine sands (41.68percent), the lowest amount of Ca:Mg ratio (1.35), the highest acid saturation (50.59), the highest ESP (8.39), and a considerably high WSA (38.75). Other remarkable problematic soils identified in the study include the lithic soil and the duplex soil. For instance, the Lithic soil is characterized by the highest fine sand-size texture (61.38percent), considerably low organic carbon (2.63percent), low cation exchange capacity (3.55 cmol(+)/kg), much high DR (0.75), very low WSA (0.027percent), and the highest KEF (0.027a). Whereas, the duplex soil is characterized by the highest DR (0.81), critically high CDR (38.19percent), very low WSA (0.019percent), and a considerably high KEF (0.019a). The relatively stable soils within the catchment are the oxidic, and melanic, where the WSA is highest in oxidic (38.19percent) and relatively high for melanic (36.6percent), CFI is highest in melanic (85.02percent), and oxidic (74.32percent), and KEF is relatively low (0.016b) for both. Correlation of the selected soil erodibility indices shows that CFI shares a perfect inverse relationship with CDR while maintaining a strong significant relationship with DR (R = -0.504). Findings also show that the SAR expectedly produced a robust significant relationship with ESP (R = 0.644), while KEF exhibited a solid inverse relationship with WSA (R = 0.913). The correlation across the physical and chemical properties suggests that DR and CDR can be firmly and positively influenced by dispersive clay. At the same time, the two factors maintain a significantly negative relationship with dispersive sand. Also, clay-sized particles depicted a significant relationship with WSA. Physicochemical and chemical parameters influence only the ESP and SAR. A remarkable finding is the influence of iron and its presence on SAR. On the other hand, ESP was distinguished from SAR due to the inverse influence of potassium. The lithic soils identify as members of the collapsible soil of South Africa, while the gleyic soils identify with duplex and saprolite soils in the class of dispersive soils. The vertic soils characterize as expansive soil, while the Duplex soil also exhibits a soft soil attribute. In general, the study suggests that T35D and T35E areas of Tsitsa catchment vary spatially in soil erodibility potential. T35D area is characterized by dominant oxidic soil cover of relatively stable aggregate whose iron oxide enrichment could be attributed to inculcation of dolerite debris. Overall, the soil erodibility indices showed that the development of gully erosion in Tsitsa catchment is driven by high clay dispersivity ratio of the soil (mean = 0.70; 24percent CV), and poor soil structure relative to the low WSA range (18.1 – 34.0). Erodibility due to high sodicity are associated with saprolite (ESP = 8.02) and gleyic soils (ESP = 7.43) while the high soil dispersion was due to the vertic (46percent), duplex (38percent), cumulic (30percent), and lithic (27percent) soil components. The poor soil aggregates (WSA) were mainly controlled by the lithic (10percent), vertic (27percent), duplex (28percent), cumulic (31percent), and gleyic (34percent) soil components. Meanwhile, the T35E area is dominated by the dispersive and collapsible soils dominated by saprolites and lithic soils. Therefore, the environmental stakeholders are advised to adopt the best management practices within the dam area considering the vulnerability of the catchment to the development of gullies and the potential impact of sedimentation on the adequate performance of Tsitsa dam and its water infrastructures. , Thesis (MSc) -- Faculty of Science and Agriculture, 2022
- Full Text:
- Date Issued: 2022-01
Understanding the contribution of Land Use/Cover (LUC) classes on soil erosion and sedimentation using sediment fingerprinting technique and RUSLE in a GIS interface at sub-catchment level
- Taeni, Thembalethu (https://orcid.org/ 0000-0001-7662-8652)
- Authors: Taeni, Thembalethu (https://orcid.org/ 0000-0001-7662-8652)
- Date: 2021-04
- Subjects: Geographic information systems , Soil erosion , River sediments
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/20920 , vital:46747
- Description: Soil erosion by water is the major source of soil degradation in the world, and South Africa (SA) is not an exception particularly in the Free State (FS) Province. In South Africa, the Caledon River Catchment in the FS Province has been identified as one of the regions where soil erosion has been prevalent for decades. Evidence across many parts of the catchment show a widespread of soil erosion and the contaminant flux associated with sediment into river systems and reservoirs; including the Welbedatcht dam and Carthcart-drift dam in Ladybrand. It is of these issues that the current work aimed at enhancing the understanding of sediment sources and soil erosion dynamics at the Caledon River Basin. The objectives of the study were to locate sources of suspended sediments and to assess and quantify the contribution of Land Use Cover (LUC) classes to water erosion and sediment yield at a sub – catchment level of the Caledon River Basin. To achieve the objectives set out for this research, a study was conducted at a sub - catchment level of the Caledon River Basin in the FS Province, South Africa. The sediment–fingerprinting approach and the Revised Universal Soil Loss Equation (RUSLE) model were used in the study under Geographic Information System (GIS) settings. A qualitative and quantitative interpretation of the geochemical data were used to evaluate the potential for distinguishing catchment sediment sources. The application of multivariate sediment mixing models incorporating Monte Carlo simulations was undertaken to investigate recent variations in sediment sources. Lastly, to document the impact of LUC change on soil erosion; data from soil profile database, Landsat 8 OLI–TIRS and climate (i.e. rainfall) were used to assess and map the spatial and temporal pattern changes of soil erosion at a sub – catchment level as related to LUC changes. In this study, the sub–catchment was classified into 6 LUC classes. Thereafter soil erosion was quantified for three consecutive years namely; 2015, 2016 and 2018 using the soil erosion factors as GIS–layers. The investigation of sediment source types and spatial provenance in the catchment showed that the grassland areas have consistently been the main sediment source (83 percent) throughout the study period. Findings further showed that there was an increase in contributions from cultivation and abandoned cultivated fields. Sediment contribution from surface sources was dominant (54 percent) and thereafter, subsurface sediment input increased (62 percent). This trend is indicative of increased severity of gully erosion in the area and thus is consistent with other studies. To comprehend the influence of LUC class modification dynamics on soil erosion, water erosion in particular at the sub-catchment commencing from 2015 to 2018 (4 years), multi-temporal Landsat 8 information jointly with the RUSLE model were used. A post-classification, LUC class alteration comparison revealed that water bodies, shrubs and forested region and grassland declined by 0.27 percent, 15.60 percent, and 37.60 percent, respectively. On the other hand, regions under Bad lands, and bare-soil and built-up regions including agricultural region expanded by 2.22 percent, 5.78 percent, and 45.67 percent respectively, between 2015 to 2018 study period. The average yearly soil loss decreased at the sub-catchment and was 10.23,5.71 and 5.82 t ⋅ ha -1 ⋅ yr-1 for 2015, 2016 and 2018 respectively. Although soil loss lessened for the duration of the perceived period, a closer scrutiny revealed that there were nonetheless seeming signs of persistent escalation in soil loss risk. These signs were mostly shown in the elevated parts of the sub-catchment as shown by the red regions on the soil loss map. Additional examination of soil loss findings by LUC classes categories further indicated that most LUC classes categories, including Bare-soil and built-up area, agricultural-land, grassland, and region under shrubs and forests, showed increased soil loss levels during the 4 years’ study period at the sub-catchment. The information on the comparative vividness of diverse sediment sources given by the study must be observed as a noteworthy development towards an understanding of the sediment source dynamics in agricultural river based catchments; more so of the Caledon River Basin. Further research is recommended for other erosion prone catchments in South Africa to identify additional evidence of the spatial and temporal variations in soil erosion and sediment sources. The results of the study suggest that the procedure of assimilating the GIS and RS with the RUSLE model is not just precise, time-efficient and exact in recognizing soil erosion susceptible regions in geospatial and temporal standings. However, it is a cost-efficient substitute to standard field-founded approaches. , Thesis (MSc) (Soil Science) -- University of Fort Hare, 2021
- Full Text:
- Date Issued: 2021-04
- Authors: Taeni, Thembalethu (https://orcid.org/ 0000-0001-7662-8652)
- Date: 2021-04
- Subjects: Geographic information systems , Soil erosion , River sediments
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/20920 , vital:46747
- Description: Soil erosion by water is the major source of soil degradation in the world, and South Africa (SA) is not an exception particularly in the Free State (FS) Province. In South Africa, the Caledon River Catchment in the FS Province has been identified as one of the regions where soil erosion has been prevalent for decades. Evidence across many parts of the catchment show a widespread of soil erosion and the contaminant flux associated with sediment into river systems and reservoirs; including the Welbedatcht dam and Carthcart-drift dam in Ladybrand. It is of these issues that the current work aimed at enhancing the understanding of sediment sources and soil erosion dynamics at the Caledon River Basin. The objectives of the study were to locate sources of suspended sediments and to assess and quantify the contribution of Land Use Cover (LUC) classes to water erosion and sediment yield at a sub – catchment level of the Caledon River Basin. To achieve the objectives set out for this research, a study was conducted at a sub - catchment level of the Caledon River Basin in the FS Province, South Africa. The sediment–fingerprinting approach and the Revised Universal Soil Loss Equation (RUSLE) model were used in the study under Geographic Information System (GIS) settings. A qualitative and quantitative interpretation of the geochemical data were used to evaluate the potential for distinguishing catchment sediment sources. The application of multivariate sediment mixing models incorporating Monte Carlo simulations was undertaken to investigate recent variations in sediment sources. Lastly, to document the impact of LUC change on soil erosion; data from soil profile database, Landsat 8 OLI–TIRS and climate (i.e. rainfall) were used to assess and map the spatial and temporal pattern changes of soil erosion at a sub – catchment level as related to LUC changes. In this study, the sub–catchment was classified into 6 LUC classes. Thereafter soil erosion was quantified for three consecutive years namely; 2015, 2016 and 2018 using the soil erosion factors as GIS–layers. The investigation of sediment source types and spatial provenance in the catchment showed that the grassland areas have consistently been the main sediment source (83 percent) throughout the study period. Findings further showed that there was an increase in contributions from cultivation and abandoned cultivated fields. Sediment contribution from surface sources was dominant (54 percent) and thereafter, subsurface sediment input increased (62 percent). This trend is indicative of increased severity of gully erosion in the area and thus is consistent with other studies. To comprehend the influence of LUC class modification dynamics on soil erosion, water erosion in particular at the sub-catchment commencing from 2015 to 2018 (4 years), multi-temporal Landsat 8 information jointly with the RUSLE model were used. A post-classification, LUC class alteration comparison revealed that water bodies, shrubs and forested region and grassland declined by 0.27 percent, 15.60 percent, and 37.60 percent, respectively. On the other hand, regions under Bad lands, and bare-soil and built-up regions including agricultural region expanded by 2.22 percent, 5.78 percent, and 45.67 percent respectively, between 2015 to 2018 study period. The average yearly soil loss decreased at the sub-catchment and was 10.23,5.71 and 5.82 t ⋅ ha -1 ⋅ yr-1 for 2015, 2016 and 2018 respectively. Although soil loss lessened for the duration of the perceived period, a closer scrutiny revealed that there were nonetheless seeming signs of persistent escalation in soil loss risk. These signs were mostly shown in the elevated parts of the sub-catchment as shown by the red regions on the soil loss map. Additional examination of soil loss findings by LUC classes categories further indicated that most LUC classes categories, including Bare-soil and built-up area, agricultural-land, grassland, and region under shrubs and forests, showed increased soil loss levels during the 4 years’ study period at the sub-catchment. The information on the comparative vividness of diverse sediment sources given by the study must be observed as a noteworthy development towards an understanding of the sediment source dynamics in agricultural river based catchments; more so of the Caledon River Basin. Further research is recommended for other erosion prone catchments in South Africa to identify additional evidence of the spatial and temporal variations in soil erosion and sediment sources. The results of the study suggest that the procedure of assimilating the GIS and RS with the RUSLE model is not just precise, time-efficient and exact in recognizing soil erosion susceptible regions in geospatial and temporal standings. However, it is a cost-efficient substitute to standard field-founded approaches. , Thesis (MSc) (Soil Science) -- University of Fort Hare, 2021
- Full Text:
- Date Issued: 2021-04
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