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| A groundwater level-based filtering to improve the accuracy of locating agricultural tile drain and ditch networks Yimer, E.A.; Yadollahi, S.; Riakhi, F.-E.; Alitane, A.; Weerasinghe, I.; Wirion, C.; Nossent, J.; Van Griensven, A. (2023). A groundwater level-based filtering to improve the accuracy of locating agricultural tile drain and ditch networks. International Journal of Applied Earth Observation and Geoinformation 122: 103423. https://dx.doi.org/10.1016/j.jag.2023.103423
In: International Journal of Applied Earth Observation and Geoinformation. International Institute for Aerial Survey and Earth Sciences: Enschede. ISSN 1569-8432; e-ISSN 1872-826X, meer
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Literature and desktop study Numerical modelling Water management > Hydrology > Physically based models Water management > Risk > Low water strategies Water management > Water quantity > Water system knowledge België, Kleine Nete R. [Marine Regions] |
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The remote sensing method resulted in 87.8% accuracy in the first study area, while the decision tree classification achieved 96.7% accuracy. Although the RS approach was not successful in following the ditch network, the DTC was able to indicate ditch networks with up to 58% accuracy. However, the additional filtering using groundwater level measurements increased the drainage unit identification accuracy in the first study area (corresponds to finding an additional 19.4 km2 area of drains). A final quantitative assessment for the second study area revealed a close follow-up of the ditch network to the shallow groundwater table maps. In general, it can be concluded that both the remote sensing and the DTC method have tremendous potential to identify drainage units, although with limitations in particular cases, such as low accuracy. Moreover, it can be advised that a local visit to the study area is required to investigate what type of drainage system is used. Next, the novel use of groundwater level-based filtering further improves the drainage identification procedure. Finally, combining several data and techniques allows for accurately identifying drainage units, which is ultimately useful for the sustainable management of drained water from agricultural fields. |
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