Characterization of agriculture-related land degradation in eastern and western parts of Botswana

Kayombo, B.; Meulenburg, F; Moganane, BG; Dikinya, Oagile; Aliwa, JN; Nsinamwa, M.; Gaboutloeloe, Gilbert Kabelo; Patrick, Carl D.; Mzuku, M.; Machacha, S

doi:10.4314/bjt.v14i1.15405

Cited by 4 publications

(3 citation statements)

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“…Botswana has no confirmed estimate of the national extent of degraded lands as results from various studies vary considerably due to differences in methods and scales of assessment (Foster, 2006). Kayombo et al (2005) put LD affected land in Botswana at 69%. Using a three-point nominal scale (low, moderate, severe) to rate LD indicators, Sebego, Atlhopheng, Chanda, Mulale, and Mphinyane (2019) found moderate to severe degradation in high utilization areas due to soil degradation and vegetation structure change in Boteti, north-central Botswana.…”

Section: Introductionmentioning

confidence: 99%

Assessing UN indicators of land degradation neutrality and proportion of degraded land for Botswana using remote sensing based national level metrics

2020

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Achieving land degradation neutrality (LDN) has been proposed as a way to stem the loss of land resources globally. To date, LDN operationalization at the country level has remained a challenge both from a policy and science perspective. Using an approach incorporating cloud-based geospatial computing with machine learning, national level datasets of land cover, land productivity dynamics, and soil organic carbon stocks were developed. Using the example of Botswana, LDN and proportion of degraded land were assessed. Between 2000 and 2015, grassland lost approximately 17% of its original extent, the highest level of loss for any land category; land productivity decline was highest in artificial surface areas (11%), whereas 36% of croplands show early signs of decline. With the use of national metrics (NM), degraded areas were found to be 32.6% compared to 51.4% of the total land area when global default datasets (DD) were used.Estimates of degraded land computed with NM and DD were validated in Palapye, an agro-pastoral region in eastern Botswana, where Composite Land Degradation Index (CLDI) field-based data exists. Comparing land degradation (LD) in the three datasets (NM, DD, and CLDI), NM estimates were closest to the field data. The extra efforts put into developing national level data for LD assessment in this study is, thus, well-justified.Beyond demonstrating remote sensing viability for LD assessment, the study developed procedures for generating and validating national level datasets. Using these procedures, LD monitoring will be enhanced in Botswana and elsewhere since these remote sensing datasets can be updated using freely available satellite datasets.

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Section: Introductionmentioning

confidence: 99%

Assessing UN indicators of land degradation neutrality and proportion of degraded land for Botswana using remote sensing based national level metrics

2020

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“…Use of unsustainable farming techniques has led to land degradation which can be revealed by poor yields. The findings of the Desert Margin Programme indicated a deterioration of soil quality, both in terms of nutrient depletion and poor physical properties for cultivated soils in comparison to the virgin soil, as a result of continuous cultivation [2]. Although the impact of cultivation is known to cause soil nutrient loss worldwide, the magnitude of the change in the study area is not known.…”

Section: Introductionmentioning

confidence: 93%

Eleven-year soil fertility changes in Dinogeng agricultural extension area of Kgatleng District in Botswana

Lucky Sitayelo,

Benedict Kayombo,

Cecil Patrick

et al. 2024

Global J. Eng. Technol. Adv.

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This study was conducted in Dinogeng Agricultural Extension Area (DAEA) in the Kgatleng District located in the eastern part of Botswana. The objective of the study was to assess soil fertility changes over an eleven-year period (2009–2020) in the extension area. In the meantime, the Integrated Support Programme for Arable Agricultural Development (ISPAAD) was launched and is continuing. Soil test data of 18 arable-farming sites for the period after inception of ISPAAD in 2009 until 2020 was obtained from the Department of Agricultural Research Soil Analytical Laboratory and Ministry of Agriculture. Geographical coordinates of the ploughing fields were taken during field work using a Geographical Positioning System (GPS). Based on availability of information, soil reaction (pH), Organic carbon (OC) and Cation Exchange Capacity (CEC) of soils for the 18 arable-farming sites were compared with data acquired from National Soil Map of Botswana (1988), scale 1: 250 000. The results showed an average significant decline of 1.55 for soil pH (P < 0.05), 0.16 % for OC (P < 0.01) and 6.75 Cmol/kg for CEC (P < 0.01). Farming practices have however, undergone some remarkable transformation including the use of fertilizers for replacing nutrient loses. The findings from this study may be useful to guide the development of functional soil fertility management plan for Dinogeng Agricultural Extension Area.

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“…Population explosion, deforestation, unsustainable agricultural cultivation, and overgrazing are among the main factors causing soil erosion hazards. A study by Kayombo et al [4] observed that the deterioration of soil quality, in terms of nutrient depletion and poor physical properties for cultivated as compared to virgin soils was a result of continuous cultivation. The average crop yield from a piece of land in Botswana is very low mainly due to soil fertility decline associated with removal of topsoil by erosion.…”

Section: Introductionmentioning

confidence: 99%

Integrating GIS and remote sensing in mapping soil erosion risk using SLEMSA model: A case study of Dinogeng Agricultural Extension Area of Kgatleng District, Botswana

Sitayelo¹,

Kayombo²,

Patrick³

et al. 2022

World J. Adv. Eng. Technol. Sci.

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A study was conducted in Dinogeng Agricultural Extension Area (DAEA) of Kgatleng District, Botswana, with the objective of assessing current soil erosion risk (using 2020 Landsat imagery) resulting from the Integrated Support Programme for Arable Agricultural Development (ISPAAD) that was launched in 2009. The Soil Loss Estimation Model for Southern Africa (SLEMSA) tool integrated with Geographical Information System (GIS) and Remote Sensing assessed the soil erosion risk in the study area. The results indicated that 88% of DAEA has low to moderate soil erosion risk (0 – 2 tha-1yr-1). Only 12% of the study area experience very high to extreme high erosion risk (5 - ≥10 tha-1yr-1) along the streams, at steep slopes and areas of bare land. Common practice calls for conservation measures to be applied on areas with high soil loss. This study has underscored the role of topography and soil erodibility, as natural factors, in driving soil erosion.

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Characterization of agriculture-related land degradation in eastern and western parts of Botswana

Cited by 4 publications

References 0 publications

Assessing UN indicators of land degradation neutrality and proportion of degraded land for Botswana using remote sensing based national level metrics

Assessing UN indicators of land degradation neutrality and proportion of degraded land for Botswana using remote sensing based national level metrics

Eleven-year soil fertility changes in Dinogeng agricultural extension area of Kgatleng District in Botswana

Integrating GIS and remote sensing in mapping soil erosion risk using SLEMSA model: A case study of Dinogeng Agricultural Extension Area of Kgatleng District, Botswana

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