Soil moisture-based drought monitoring using remote sensing over Africa
Agricultural droughts, or persistent deficits in soil moisture, can have severe consequences on crop production and can result in economic crisis and widespread food insecurity. The impacts of drought are especially relevant in Africa, where agriculture is largely supported by rainfall. Currently, d...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/157005 |
| _version_ | 1824457860733468672 |
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| author | Lu, Catherine S. |
| author2 | Entekhabi, Dara |
| author_facet | Entekhabi, Dara Lu, Catherine S. |
| author_sort | Lu, Catherine S. |
| collection | MIT |
| description | Agricultural droughts, or persistent deficits in soil moisture, can have severe consequences on crop production and can result in economic crisis and widespread food insecurity. The impacts of drought are especially relevant in Africa, where agriculture is largely supported by rainfall. Currently, drought monitoring systems for Africa are not as prevalent on the continental scale and are limited in the number of in-situ observations for model validation, in contrast to developed regions. In this study, we use soil moisture data gathered from the Soil Moisture Active Passive (SMAP) mission with dates ranging from April 2015 to December 2023, in order to develop a drought monitoring system that incorporates seasonality and climatology. Monthly drought thresholds are developed based on percentiles of soil moisture found in previous literature, creating location-specific thresholds of drought for each month. This data was applied at the continental, regional, and country level to reconstruct historical records of drought throughout the SMAP time record (time series) and localities of drought intensities for a given time period (drought maps). Additionally, a methodology of exponential time filtering is explored to convert surface soil moisture from SMAP into root-zone soil moisture, which can be more relevant for agricultural production. The reconstructed historical drought results align with literature on drought events in regions of Africa (e.g. 2017-18 drought anomalies). For future events, this study could inform drought monitoring through remote sensing and allow for measures of drought response to improve overall food security. |
| first_indexed | 2025-02-19T04:16:43Z |
| format | Thesis |
| id | mit-1721.1/157005 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2025-02-19T04:16:43Z |
| publishDate | 2024 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1570052024-09-25T04:10:28Z Soil moisture-based drought monitoring using remote sensing over Africa Lu, Catherine S. Entekhabi, Dara Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Agricultural droughts, or persistent deficits in soil moisture, can have severe consequences on crop production and can result in economic crisis and widespread food insecurity. The impacts of drought are especially relevant in Africa, where agriculture is largely supported by rainfall. Currently, drought monitoring systems for Africa are not as prevalent on the continental scale and are limited in the number of in-situ observations for model validation, in contrast to developed regions. In this study, we use soil moisture data gathered from the Soil Moisture Active Passive (SMAP) mission with dates ranging from April 2015 to December 2023, in order to develop a drought monitoring system that incorporates seasonality and climatology. Monthly drought thresholds are developed based on percentiles of soil moisture found in previous literature, creating location-specific thresholds of drought for each month. This data was applied at the continental, regional, and country level to reconstruct historical records of drought throughout the SMAP time record (time series) and localities of drought intensities for a given time period (drought maps). Additionally, a methodology of exponential time filtering is explored to convert surface soil moisture from SMAP into root-zone soil moisture, which can be more relevant for agricultural production. The reconstructed historical drought results align with literature on drought events in regions of Africa (e.g. 2017-18 drought anomalies). For future events, this study could inform drought monitoring through remote sensing and allow for measures of drought response to improve overall food security. M.Eng. 2024-09-24T18:26:19Z 2024-09-24T18:26:19Z 2024-05 2024-07-25T13:44:16.503Z Thesis https://hdl.handle.net/1721.1/157005 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Lu, Catherine S. Soil moisture-based drought monitoring using remote sensing over Africa |
| title | Soil moisture-based drought monitoring using remote sensing over Africa |
| title_full | Soil moisture-based drought monitoring using remote sensing over Africa |
| title_fullStr | Soil moisture-based drought monitoring using remote sensing over Africa |
| title_full_unstemmed | Soil moisture-based drought monitoring using remote sensing over Africa |
| title_short | Soil moisture-based drought monitoring using remote sensing over Africa |
| title_sort | soil moisture based drought monitoring using remote sensing over africa |
| url | https://hdl.handle.net/1721.1/157005 |
| work_keys_str_mv | AT lucatherines soilmoisturebaseddroughtmonitoringusingremotesensingoverafrica |