Soil moisture remote-sensing applications for identification of flood-prone areas along transport infrastructure

被引:0
作者
Anna-Klara Ahlmer
Marco Cavalli
Klas Hansson
Alexander J. Koutsouris
Stefano Crema
Zahra Kalantari
机构
[1] Trivector Traffic,Research Institute for Geo
[2] Stockholm,Hydrological Protection
[3] Sweden and KTH,Department of Physical Geography
[4] National Research Council,Department of Physical Geography and Bolin Centre for Climate Research
[5] Swedish Transport Administration (Trafikverket),undefined
[6] Stockholm University,undefined
[7] Stockholm University,undefined
来源
Environmental Earth Sciences | 2018年 / 77卷
关键词
Flooding; Road infrastructure; Soil moisture; Remote sensing; Precipitation;
D O I
暂无
中图分类号
学科分类号
摘要
The expected increase in precipitation and temperature in Scandinavia, and especially short-time heavy precipitation, will increase the frequency of flooding. Urban areas are the most vulnerable, and specifically, the road infrastructure. The accumulation of large volumes of water and sediments on road-stream intersections gets severe consequences for the road drainage structures. This study integrates the spatial and temporal soil moisture properties into the research about flood prediction methods by a case study of two areas in Sweden, Västra Götaland and Värmland, which was affected by severe flooding in August 2014. Soil moisture data are derived from remote-sensing techniques, with a focus on the soil moisture-specific satellites ASCAT and SMOS. Furthermore, several physical catchments descriptors (PCDs) are analyzed and the result shows that larger slopes and drainage density, in general, mean a higher risk of flooding. The precipitation is the same; however, it can be concluded that more precipitation in most cases gives higher soil moisture values. The lack, or the dimensioning, of road drainage structures seems to have a large impact on the flood risk as more sediment and water can be accumulated at the road-stream intersection. The results show that the method implementing soil moisture satellite data is promising for improving the reliability of flooding.
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[1]  
Albergel C(2012)Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations Remote Sens Environ 118 215-226
[2]  
de Rosnay P(2012)Use of TerraSAR-X Data to Retrieve Soil Moisture Over Bare Soil Agricultural Fields IEEE Geosci Remote Sens Lett 9 512-516
[3]  
Gruhier C(2007)Initial soil moisture retrievals from the METOP-A Advanced Scatterometer (ASCAT) Geophys Res Lett 34 20-13
[4]  
Muñoz-Sabater J(2016)Creation of a high resolution precipitation data set by merging gridded gauge data and radar observations for Sweden J Hydrol 541 6-831
[5]  
Hasenauer S(2009)How crucial is it to account for the antecedent moisture conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments Hydrol Earth Syst Sci 13 819-393
[6]  
Isaksen L(2005)Monitoring flood extent and forecasting excess runoff risk with RADARSAT-1 data Nat Hazards 35 377-642
[7]  
Wagner W(2008)On the estimation of antecedent wetness conditions in rainfall–runoff modelling Hydrol Process 22 629-1893
[8]  
Baghdadi N(2010)Improving runoff prediction through the assimilation of the ASCAT soil moisture product Hydrol Earth Syst Sci 14 1881-3408
[9]  
Aubert M(2011)Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe Remote Sens Environ 115 3390-2555
[10]  
Zribi M(2012)Assimilation of surface- and root-zone ASCAT soil moisture products into rainfall-runoff modeling IEEE Trans Geosci Remote Sens 50 2542-2306