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.
引用
收藏
相关论文
共 191 条
[31]  
Moramarco T(2011)Flood monitoring using multi-temporal COSMO-SkyMed data: Image segmentation and signature interpretation Remote Sens Environ 115 990-2722
[32]  
Wagner W(2014)SAR and InSAR for flood monitoring: Examples with COSMO-SkyMed data IEEE J Select Topics Appl Earth Obs Remote Sens 7 2711-904
[33]  
Naeimi V(2014)Estimation of near surface soil moisture in a sloping terrain of a Himalayan watershed using ENVISAT ASAR multi-incidence angle alternate polarisation data Hydrol Process 28 895-161
[34]  
Bartalis Z(2010)Investigating soil moisture–climate interactions in a changing climate: a review Earth Sci Rev 99 125-244
[35]  
Hasenauer S(2005)Impacts of flooding and climate change on urban transportation: a systemwide performance assessment of the Boston Metro Area Transp Res Part D Transp Environ 10 231-151
[36]  
Brocca L(2001)Simulating the impact of road construction and forest harvesting on hydrologic response Earth Surf Process Landf 26 135-948
[37]  
Hasenauer S(1999)A study of vegetation cover effects on ERS scatterometer data IEEE Trans Geosci Remote Sens 37 938-207
[38]  
Lacava T(1999)A method for estimating soil moisture from ERS scatterometer and soil data Remote Sens Environ 70 191-1197
[39]  
Melone F(2008)Temporal stability of soil moisture and radar backscatter observed by the Advanced Synthetic Aperture Radar (ASAR) Sensors 8 1174-3696
[40]  
Moramarco T(2002)An efficient method for mapping flood extent in a coastal floodplain using Landsat TM and DEM data Int J Remote Sens 23 3681-204