Incorporating geomorphic knowledge in the management of wetlands in Africa’s drylands: a rapid assessment of the Kafue Wetland
- Lidzhegu, Z, Ellery, William F N, Mantel, Sukhmani
- Authors: Lidzhegu, Z , Ellery, William F N , Mantel, Sukhmani
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/157108 , vital:40087 , https://doi.org/10.1007/s13157-019-01172-9
- Description: Limited knowledge of wetland geomorphic processes often results in poor wetland management. This study aims to illustrate the importance of incorporating geomorphic knowledge of wetland origin in their management. The geomorphic origin and dynamics of the Kafue wetland were determined from the analysis of remotely sensed and geological data. The wetland is a remnant of a paleo-lake that was captured by the tributary of the middle Zambezi River. At the point of capture, resistant Muva Group metavolcanic rocks dominate narrow valleys characterised by straight channels. The resistant lithology prevents the lower Kafue River to cut into the wetland thus maintaining wetland conditions upstream. Sedimentation regime through overbank and bed deposits shaped the wetland’s structure, ecological diversity, and hydrological functioning. The operation of the Itezhi-tezhi dam has negatively impacted the wetland’s hydrological and sedimentological regime. The dam starves the system of sediment needed for promoting levee and channel bed aggradation. Regulated discharge with reduced sediment load can lead to channel incision and therefore reduce flood frequency, which may ultimately lead to wetland desiccation.
- Full Text:
- Date Issued: 2020
- Authors: Lidzhegu, Z , Ellery, William F N , Mantel, Sukhmani
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/157108 , vital:40087 , https://doi.org/10.1007/s13157-019-01172-9
- Description: Limited knowledge of wetland geomorphic processes often results in poor wetland management. This study aims to illustrate the importance of incorporating geomorphic knowledge of wetland origin in their management. The geomorphic origin and dynamics of the Kafue wetland were determined from the analysis of remotely sensed and geological data. The wetland is a remnant of a paleo-lake that was captured by the tributary of the middle Zambezi River. At the point of capture, resistant Muva Group metavolcanic rocks dominate narrow valleys characterised by straight channels. The resistant lithology prevents the lower Kafue River to cut into the wetland thus maintaining wetland conditions upstream. Sedimentation regime through overbank and bed deposits shaped the wetland’s structure, ecological diversity, and hydrological functioning. The operation of the Itezhi-tezhi dam has negatively impacted the wetland’s hydrological and sedimentological regime. The dam starves the system of sediment needed for promoting levee and channel bed aggradation. Regulated discharge with reduced sediment load can lead to channel incision and therefore reduce flood frequency, which may ultimately lead to wetland desiccation.
- Full Text:
- Date Issued: 2020
Towards SDG 15.3: The biome context as the appropriate degradation monitoring dimension
- Xoxo, Sinetemba, Mantel, Sukhmani, de Vos, Alta, Mahlaba, Bawinile, le Maître, David, Tanner, Jane
- Authors: Xoxo, Sinetemba , Mantel, Sukhmani , de Vos, Alta , Mahlaba, Bawinile , le Maître, David , Tanner, Jane
- Date: 2022
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/415961 , vital:71304 , xlink:href="https://doi.org/10.1016/j.envsci.2022.07.008"
- Description: Accurate and reliable estimation of terrestrial ecosystem degradation is critical to meeting the challenge of reversing land degradation. Remote sensing data (especially land productivity dynamics) is commonly used to estimate land degradation, and this study uses the TRENDS.EARTH toolbox for the period covering 2000–2018, demonstrating the benefit of tracking the degradation process (SDG 15.3.1) at a biophysical unit. Contributing to the country’s SDG 15.3.1 monitoring, anthropogenic degradation was estimated based on RESTREND land productivity, biome-specific land cover trends, and soil organic carbon (SOC) stocks. Underlying degradation was evaluated by reclassifying a 28-year national land cover change dataset to match the UNCCD land cover legend. Analysis results indicate that land productivity changes (especially in stable grasslands, afforested, and cropland areas) mainly influenced the degradation status of the biome (19.9% degraded and 25.6% improvement). Global datasets also suggest that land cover and SOC had a minimal contribution (more than 2%) to anthropogenic degradation dynamics in the biome between 2000 and 2018. The GIS analysis showed that long-term, the major contributors to the biome’s underlying 9% anthropogenic degradation were woody proliferation into the Grassland Biome, urban expansion, and wetland drainage.
- Full Text:
- Date Issued: 2022
- Authors: Xoxo, Sinetemba , Mantel, Sukhmani , de Vos, Alta , Mahlaba, Bawinile , le Maître, David , Tanner, Jane
- Date: 2022
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/415961 , vital:71304 , xlink:href="https://doi.org/10.1016/j.envsci.2022.07.008"
- Description: Accurate and reliable estimation of terrestrial ecosystem degradation is critical to meeting the challenge of reversing land degradation. Remote sensing data (especially land productivity dynamics) is commonly used to estimate land degradation, and this study uses the TRENDS.EARTH toolbox for the period covering 2000–2018, demonstrating the benefit of tracking the degradation process (SDG 15.3.1) at a biophysical unit. Contributing to the country’s SDG 15.3.1 monitoring, anthropogenic degradation was estimated based on RESTREND land productivity, biome-specific land cover trends, and soil organic carbon (SOC) stocks. Underlying degradation was evaluated by reclassifying a 28-year national land cover change dataset to match the UNCCD land cover legend. Analysis results indicate that land productivity changes (especially in stable grasslands, afforested, and cropland areas) mainly influenced the degradation status of the biome (19.9% degraded and 25.6% improvement). Global datasets also suggest that land cover and SOC had a minimal contribution (more than 2%) to anthropogenic degradation dynamics in the biome between 2000 and 2018. The GIS analysis showed that long-term, the major contributors to the biome’s underlying 9% anthropogenic degradation were woody proliferation into the Grassland Biome, urban expansion, and wetland drainage.
- Full Text:
- Date Issued: 2022
Towards SDG 15.3: The biome context as the appropriate degradation monitoring dimension
- Xoxo, Sinetemba, Mantel, Sukhmani, de Vos, Alta, Mahlaba, Bawinile, le Maître, David, Tanner, Jane
- Authors: Xoxo, Sinetemba , Mantel, Sukhmani , de Vos, Alta , Mahlaba, Bawinile , le Maître, David , Tanner, Jane
- Date: 2022
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/416462 , vital:71350 , xlink:href="https://doi.org/10.1016/j.envsci.2022.07.008"
- Description: Accurate and reliable estimation of terrestrial ecosystem degradation is critical to meeting the challenge of reversing land degradation. Remote sensing data (especially land productivity dynamics) is commonly used to estimate land degradation, and this study uses the TRENDS.EARTH toolbox for the period covering 2000–2018, demonstrating the benefit of tracking the degradation process (SDG 15.3.1) at a biophysical unit. Contributing to the country’s SDG 15.3.1 monitoring, anthropogenic degradation was estimated based on RESTREND land productivity, biome-specific land cover trends, and soil organic carbon (SOC) stocks. Underlying degradation was evaluated by reclassifying a 28-year national land cover change dataset to match the UNCCD land cover legend. Analysis results indicate that land productivity changes (especially in stable grasslands, afforested, and cropland areas) mainly influenced the degradation status of the biome (19.9% degraded and 25.6% improvement). Global datasets also suggest that land cover and SOC had a minimal contribution (more than 2%) to anthropogenic degradation dynamics in the biome between 2000 and 2018. The GIS analysis showed that long-term, the major contributors to the biome’s underlying 9% anthropogenic degradation were woody proliferation into the Grassland Biome, urban expansion, and wetland drainage.
- Full Text:
- Date Issued: 2022
- Authors: Xoxo, Sinetemba , Mantel, Sukhmani , de Vos, Alta , Mahlaba, Bawinile , le Maître, David , Tanner, Jane
- Date: 2022
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/416462 , vital:71350 , xlink:href="https://doi.org/10.1016/j.envsci.2022.07.008"
- Description: Accurate and reliable estimation of terrestrial ecosystem degradation is critical to meeting the challenge of reversing land degradation. Remote sensing data (especially land productivity dynamics) is commonly used to estimate land degradation, and this study uses the TRENDS.EARTH toolbox for the period covering 2000–2018, demonstrating the benefit of tracking the degradation process (SDG 15.3.1) at a biophysical unit. Contributing to the country’s SDG 15.3.1 monitoring, anthropogenic degradation was estimated based on RESTREND land productivity, biome-specific land cover trends, and soil organic carbon (SOC) stocks. Underlying degradation was evaluated by reclassifying a 28-year national land cover change dataset to match the UNCCD land cover legend. Analysis results indicate that land productivity changes (especially in stable grasslands, afforested, and cropland areas) mainly influenced the degradation status of the biome (19.9% degraded and 25.6% improvement). Global datasets also suggest that land cover and SOC had a minimal contribution (more than 2%) to anthropogenic degradation dynamics in the biome between 2000 and 2018. The GIS analysis showed that long-term, the major contributors to the biome’s underlying 9% anthropogenic degradation were woody proliferation into the Grassland Biome, urban expansion, and wetland drainage.
- Full Text:
- Date Issued: 2022
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