An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation
The assimilation of satellite-derived soil moisture estimates (soil moisture–data assimilation, SM–DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those c...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-11-01
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| Series: | Advances in Geosciences |
| Online Access: | https://www.adv-geosci.net/44/89/2017/adgeo-44-89-2017.pdf |
| Summary: | The assimilation of satellite-derived soil moisture estimates (soil
moisture–data assimilation, SM–DA) into hydrological models has the
potential to reduce the uncertainty of streamflow simulations. The improved
capacity to monitor the closeness to saturation of small catchments, such as
those characterizing the Mediterranean region, can be exploited to enhance
flash flood predictions. When compared to other microwave sensors that
have been exploited for SM–DA in recent years (e.g. the Advanced
SCATterometer – ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1)
mission provides an excellent opportunity to monitor systematically soil
moisture (SM) at high spatial resolution and moderate temporal resolution.
The aim of this research was thus to evaluate the impact of S1-based SM–DA
for enhancing flash flood predictions of a hydrological model (Continuum)
that is currently exploited for civil protection applications in Italy. The
analysis was carried out in a representative Mediterranean catchment prone to
flash floods, located in north-western Italy, during the time period October
2014–February 2015. It provided some important findings: (i) revealing the
potential provided by S1-based SM–DA for improving discharge predictions,
especially for higher flows; (ii) suggesting a more appropriate
pre-processing technique to be applied to S1 data before the assimilation;
and (iii) highlighting that even though high spatial resolution does provide
an important contribution in a SM–DA system, the temporal resolution has the
most crucial role. S1-derived SM maps are still a relatively new product and,
to our knowledge, this is the first work published in an international
journal dealing with their assimilation within a hydrological model to
improve continuous streamflow simulations and flash flood predictions.
Even though the reported results were obtained by analysing a relatively
short time period, and thus should be supported by further research
activities, we believe this research is timely in order to enhance our
understanding of the potential contribution of the S1 data within the SM–DA
framework for flash flood risk mitigation. |
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| ISSN: | 1680-7340 1680-7359 |