A model-based groundwater recharge zone mapping for food security: a case study of Notwane sub-catchment in Botswana
A model-based groundwater recharge zone mapping for food security: a case study of Notwane sub-catchment in Botswana
The understanding of groundwater recharge occurrence in drylands is central to water resources management for various uses. This study uses Remote Sensing and GIS techniques to understand where groundwater recharge occurs, and its implications for water and food security in Notwane River Basin located in the Botswana drylands. WetSpass, a distributed hydrological model was applied to map the potential groundwater recharge zones. Crop yield was predicted using the Commonwealth Science and Industrial Research Organization (CSIRO) precision weighing system. Model inputs were land use, soil texture class, topology, slope, groundwater level and catchment hydro meteorological patterns from 1987 to 2017- all sourced from satellite images. Image based classification was done to map the land cover changes in the catchment using ILWIS 30 software. Model outputs were evapotranspiration, surface runoff and groundwater recharge zone maps. The results of image-based land cover classification showed an increase of Settlements/buildup area (22.35%), grassland (5.24%) and a decline in forest cover (3.64%), agricultural land (22.23%) and bareland (3.16%). The results indicate that high recharge zones are associated with low surface runoff in rural, forested areas with sandy soils and the opposite is true for urban, buildup with clay soils. CSIRO predicts yield estimation of up to 2.037 × 103 tonnes of drought resistant maize or sorghum annually using 1100 × 106 L of the available 517.32–434.32 mm/year and 532.64–426.50 mm/year potential surface runoff and groundwater recharge, respectively. Runoff and potential recharge in Notwane sub-catchment suggest an existence of water resources worthy to be explored for food security in water scarce drylands.
Evaporation, Geographic information system, Groundwater recharge zones, Land use land cover, Remote sensing, WetSpass model
Kerapetse, Catherine Tlotlo
e2509900-e851-463e-9551-7e8c262cde63
Kileshye Onema, Jean Marie
26f4c667-9d60-4ae8-834a-2d623fa7634e
Gumindoga, Webster
3746f725-7fcd-46de-a170-a4e525067114
Ngongondo, Cosmo
745fdb58-cb31-434a-84c1-1a457bd4ed6e
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
29 June 2023
Kerapetse, Catherine Tlotlo
e2509900-e851-463e-9551-7e8c262cde63
Kileshye Onema, Jean Marie
26f4c667-9d60-4ae8-834a-2d623fa7634e
Gumindoga, Webster
3746f725-7fcd-46de-a170-a4e525067114
Ngongondo, Cosmo
745fdb58-cb31-434a-84c1-1a457bd4ed6e
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Kerapetse, Catherine Tlotlo, Kileshye Onema, Jean Marie, Gumindoga, Webster, Ngongondo, Cosmo and Sheffield, Justin
(2023)
A model-based groundwater recharge zone mapping for food security: a case study of Notwane sub-catchment in Botswana.
Physics and Chemistry of the Earth, 131, [103434].
(doi:10.1016/j.pce.2023.103434).
Abstract
The understanding of groundwater recharge occurrence in drylands is central to water resources management for various uses. This study uses Remote Sensing and GIS techniques to understand where groundwater recharge occurs, and its implications for water and food security in Notwane River Basin located in the Botswana drylands. WetSpass, a distributed hydrological model was applied to map the potential groundwater recharge zones. Crop yield was predicted using the Commonwealth Science and Industrial Research Organization (CSIRO) precision weighing system. Model inputs were land use, soil texture class, topology, slope, groundwater level and catchment hydro meteorological patterns from 1987 to 2017- all sourced from satellite images. Image based classification was done to map the land cover changes in the catchment using ILWIS 30 software. Model outputs were evapotranspiration, surface runoff and groundwater recharge zone maps. The results of image-based land cover classification showed an increase of Settlements/buildup area (22.35%), grassland (5.24%) and a decline in forest cover (3.64%), agricultural land (22.23%) and bareland (3.16%). The results indicate that high recharge zones are associated with low surface runoff in rural, forested areas with sandy soils and the opposite is true for urban, buildup with clay soils. CSIRO predicts yield estimation of up to 2.037 × 103 tonnes of drought resistant maize or sorghum annually using 1100 × 106 L of the available 517.32–434.32 mm/year and 532.64–426.50 mm/year potential surface runoff and groundwater recharge, respectively. Runoff and potential recharge in Notwane sub-catchment suggest an existence of water resources worthy to be explored for food security in water scarce drylands.
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Accepted/In Press date: 24 June 2023
e-pub ahead of print date: 26 June 2023
Published date: 29 June 2023
Additional Information:
Funding Information:
Catherine Tlotlo Kerapetse: Conceptualization, Methodology, Software, validation, formal analysis, writing original draft, Writing and editing, Jean-Marie Kileshye Onema: partial funding from WaterNet, project administration, conceptualization, methodology, supervision, Webster Gumindoga: Software, resources, supervision, Review, Cosmo Ngongondo: Writing-Review and editing, Justin Sheffield: Partiaal funding from GCRF_BRECcIA project, Review. All authors contributed to the work and agreed to the submission.
The work was partially funded by the SADC WaterNet secretariat Masters scholarship and the Building REsearch Capacity for sustainable water and food security in drylands of subsaharan Africa (BRECcIA) which is supported by UK Research and Innovation as part of the Global Challenges Research Fund, grant number NE/P021093/1.
Keywords:
Evaporation, Geographic information system, Groundwater recharge zones, Land use land cover, Remote sensing, WetSpass model
Identifiers
Local EPrints ID: 482189
URI: http://eprints.soton.ac.uk/id/eprint/482189
ISSN: 1474-7065
PURE UUID: d1c6ef51-e751-49b3-829b-c6231bb7d757
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Date deposited: 20 Sep 2023 16:51
Last modified: 18 Mar 2024 03:33
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Contributors
Author:
Catherine Tlotlo Kerapetse
Author:
Jean Marie Kileshye Onema
Author:
Webster Gumindoga
Author:
Cosmo Ngongondo
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