Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment
Many wetlands in East Africa are farmed and wetland reservoirs are used for irrigation, livestock, and fishing. Water quality and agriculture have a mutual influence on each other. Turbidity is a principal indicator of water quality and can be used for, otherwise, unmonitored water sources. Low-cost...
| Main Authors: | , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
IEEE
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/168457 |
| _version_ | 1855538344097742848 |
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| author | Steinbach, S. Rienow, A. Chege, M. W. Dedring, N. Kipkemboi, W. Thiong’o, B. K. Zwart, Sander J. Nelson, A. |
| author_browse | Chege, M. W. Dedring, N. Kipkemboi, W. Nelson, A. Rienow, A. Steinbach, S. Thiong’o, B. K. Zwart, Sander J. |
| author_facet | Steinbach, S. Rienow, A. Chege, M. W. Dedring, N. Kipkemboi, W. Thiong’o, B. K. Zwart, Sander J. Nelson, A. |
| author_sort | Steinbach, S. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Many wetlands in East Africa are farmed and wetland reservoirs are used for irrigation, livestock, and fishing. Water quality and agriculture have a mutual influence on each other. Turbidity is a principal indicator of water quality and can be used for, otherwise, unmonitored water sources. Low-cost turbidity sensors improve in situ coverage and enable community engagement. The availability of high spatial resolution satellite images from the Sentinel-2 multispectral instrument and of bio-optical models, such as the Case 2 Regional CoastColor (C2RCC) processor, has fostered turbidity modeling. However, these models need local adjustment, and the quality of low-cost sensor measurements is debated. We tested the combination of both technologies to monitor turbidity in small wetland reservoirs in Kenya. We sampled ten reservoirs with low-cost sensors and a turbidimeter during five Sentinel-2 overpasses. Low-cost sensor calibration resulted in an R2 of 0.71. The models using the C2RCC C2X-COMPLEX (C2XC) neural nets with turbidimeter measurements (R2 =0.83) and with low-cost measurements (R2 = 0.62) performed better than the turbidimeter-based C2X model. The C2XC models showed similar patterns for a one-year time series, particularly around the turbidity limit set by Kenyan authorities. This shows that both the data from the commercial turbidimeter and the low-cost sensor setup, despite sensor uncertainties, could be used to validate the applicability of C2RCC in the study area, select the better-performing neural nets, and adapt the model to the study site. We conclude that combined monitoring with low-cost sensors and remote sensing can support wetland and water management while strengthening community-centered approaches. |
| format | Journal Article |
| id | CGSpace168457 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | IEEE |
| publisherStr | IEEE |
| record_format | dspace |
| spelling | CGSpace1684572025-10-26T13:00:53Z Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment Steinbach, S. Rienow, A. Chege, M. W. Dedring, N. Kipkemboi, W. Thiong’o, B. K. Zwart, Sander J. Nelson, A. wetlands turbidity monitoring remote sensing water quality agricultural water management satellite observation Many wetlands in East Africa are farmed and wetland reservoirs are used for irrigation, livestock, and fishing. Water quality and agriculture have a mutual influence on each other. Turbidity is a principal indicator of water quality and can be used for, otherwise, unmonitored water sources. Low-cost turbidity sensors improve in situ coverage and enable community engagement. The availability of high spatial resolution satellite images from the Sentinel-2 multispectral instrument and of bio-optical models, such as the Case 2 Regional CoastColor (C2RCC) processor, has fostered turbidity modeling. However, these models need local adjustment, and the quality of low-cost sensor measurements is debated. We tested the combination of both technologies to monitor turbidity in small wetland reservoirs in Kenya. We sampled ten reservoirs with low-cost sensors and a turbidimeter during five Sentinel-2 overpasses. Low-cost sensor calibration resulted in an R2 of 0.71. The models using the C2RCC C2X-COMPLEX (C2XC) neural nets with turbidimeter measurements (R2 =0.83) and with low-cost measurements (R2 = 0.62) performed better than the turbidimeter-based C2X model. The C2XC models showed similar patterns for a one-year time series, particularly around the turbidity limit set by Kenyan authorities. This shows that both the data from the commercial turbidimeter and the low-cost sensor setup, despite sensor uncertainties, could be used to validate the applicability of C2RCC in the study area, select the better-performing neural nets, and adapt the model to the study site. We conclude that combined monitoring with low-cost sensors and remote sensing can support wetland and water management while strengthening community-centered approaches. 2024 2024-12-31T22:34:45Z 2024-12-31T22:34:45Z Journal Article https://hdl.handle.net/10568/168457 en Open Access IEEE Steinbach, S.; Rienow, A.; Chege, M. W.; Dedring, N.; Kipkemboi, W.; Thiong’o, B. K.; Zwart, Sander Jaap; Nelson, A. 2024. Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17:8490-8508. [doi: https://doi.org/10.1109/JSTARS.2024.3381756] |
| spellingShingle | wetlands turbidity monitoring remote sensing water quality agricultural water management satellite observation Steinbach, S. Rienow, A. Chege, M. W. Dedring, N. Kipkemboi, W. Thiong’o, B. K. Zwart, Sander J. Nelson, A. Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment |
| title | Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment |
| title_full | Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment |
| title_fullStr | Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment |
| title_full_unstemmed | Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment |
| title_short | Low-cost sensors and multitemporal remote sensing for operational turbidity monitoring in an East African wetland environment |
| title_sort | low cost sensors and multitemporal remote sensing for operational turbidity monitoring in an east african wetland environment |
| topic | wetlands turbidity monitoring remote sensing water quality agricultural water management satellite observation |
| url | https://hdl.handle.net/10568/168457 |
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