By: Keith Morrison-Department of Meteorology & Will Maslanka-Department of Geography & Environmental Science
Everyone knows about the impacts from intense and/or prolonged rainfall – flooding, like that experienced in the Thames Basin during the Summer of 2007, and the Winter of 2013/14. Whilst hard-engineering defences (such as raising the height of riverbanks, or construction of flood defences) can be good at dealing with flooding events by keeping water within the river, they can have negative impacts upon natural processes, such as increased deposition and erosion of sediment, and changes to the wildlife habitat. Some hard-engineering practices, such as straightening river meanders, cause river flows to speed up, potentially leading to greater flood risks downstream. Rather than exacerbating flood risk downstream, soft-engineering practices, such as Natural Flood Management (NFM) can be used to slow the flow of water before it enters the watercourse and store the water upstream.
The NERC-funded LANDWISE project (LAND management in lowland catchments for risk reduction) seeks to assess the impact and effectiveness of realistic and scalable land-based NFM measures, to reduce the risk from surface run-off, and groundwater within the Thames Basin. These land-based measures include the planting of more trees in riparian zones (the area along the riverbank), floodplain restoration, and soil and land management changes. The LANDWISE research is done in a multi-disciplinary fashion, by joining together the collective expertise of hydrologists, geologists, farmers, local flood forums, conservation Non-governmental organisations (NGOs) and policy makers, to maximise the impact of the research, and to ensure that the resulting research is greater than the sum of the individual efforts.
One area of focus is that of soil and land management changes; the impact that differing farming practices (such as crop choice and tillage practices) can have on altering infiltration or storage of rainfall in the soil as soil moisture. Soil moisture retrieval from satellite-based radar observations is well established, with various in-service satellite products. However, the resolution of the products are coarse (>1 km), as they are based on spatially averaged measurements from. Instead, this study utilises the higher resolution available from the Sentinel-1 synthetic aperture radar satellite constellation, to work within farmers’ fields, at scales between 1 km and 100 m.
The radar reflectivity of a soil arises from the dielectric contrast at the air/soil boundary, which is set by the soil type and its moisture state. However, moisture retrieval is complicated by the additional sensitivity of the radar to the surface roughness of the soil. To get around this issue, rather than dealing with absolute soil moisture, the LANDWISE project has been looking at relative surface soil moisture (rSSM) using the TU Wien Change Detection Algorithm [1]. This assumes that both the soil type and surface roughness are static parameters. Thus, short-timescale fluctuations present in the backscatter are indicative only of soil moisture changes. By looking at the relative soil moisture, it is possible to create a moisture time series. In this scheme, observations are scaled between the wettest and driest periods, and assuming that the wettest and driest periods are associated with the largest and smallest backscatter values, respectively.
The LANDWISE project has used data from Sentinel-1 to produce an rSSM time series over the Thames basin between October 2015 to December 2020. Some resolution is sacrificed in order to reduce randomly occurring fluctuations, by spatially averaging the imagery onto a 100m grid. Figure 1a shows a snapshot of the rSSM differences across the Thames Basin on 11th of September 2018. A clear band of higher rSSM values can be seen, with lower values to the north and south of it. This band of higher rSSM values can be attributed to a localised shower (Figure 1b) that passed over prior to the time of the satellite acquisition (approx. 18:00 UTC).
Figure 1a: rSSM values across the Thames Basin for the 11th September 2018. Areas denoted in grey are neglected as they are associated with urban areas.
Figure 1b: 12-hourly rainfall accumulation, before the orbit overpass. Rainfall amounts below 0.25mm in 12 hours have not been plotted for clarity.
Rather than looking at a snapshot, Figure 2 looks at the catchment for the river Kennet, a sub-catchment of the Thames Basin, in terms of the temporal changes in rSSM, in both the spatial (top) and in a 7-orbit smoothing (bottom). The expected annual cycle can be seen in the timeseries; an increase in rSSM during the winter before decreasing over the spring and summer as the weather becomes drier, before increasing again during the autumn and winter. However, the soil moisture appears to increase over the summer, when anecdotally it can be expected to be at its lowest during this time of the year. This can be seen during the summer of 2018, when the rSSM values increase slightly over the course of the summer; a period of time when very little rainfall fell over the Thames region [2]. This apparent increase is not due to an increase in soil moisture, but due to an increase in radar backscatter, as the contribution from vegetation (predominately agricultural crops) increases over the growing season, before dropping away after the harvest. Current work is focussed on deriving a correction for seasonal variations in vegetation cover, based on multiple satellite viewing geometries.
Figure 2: (Top) rSSM images for the Kennet Catchment area. Areas denoted in grey are either outside the Kennet Catchment, or have been neglected as urban areas. (bottom) Spatially average rSSM values for the individual orbit (black line) and for a 7-orbit moving average (red line).
References
[1] Bauer-Marshallinger, B., Freeman, V., Cao, S., Paulic, C., Schaufler, S., Stachl, T., Modanesi, S., Massari, C., Brocca, L., and W. Wager, 2019: Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing Assets and Overcoming Obstacles, IEEE Trans. Geosci. Remote Sens., 57, 520-539, https://doi.org/10.1109/TGRS.2018.2858004
[2] Turner, S., Barker, L., Hannaford, J., Muchan, K., Parry, S., and C. Sefton, 2021: The 2018/2019 drought in the UK: a hydrological appraisal., Weather, 99, 1-6, https://doi.org/10.1002/wea.4003