REMOTE SENSING, GIS AND HEC-RAS TECHNIQUES, APPLIED FOR FLOOD EXTENT VALIDATION, BASED ON LANDSAT IMAGERY, LIDAR AND HYDROLOGICAL DATA. CASE STUDY: BASEU RIVER, ROMANIA

被引:0
作者
Enea, A. [1 ,2 ]
Urzica, A. [1 ]
Breaban, I. G. [1 ,2 ]
机构
[1] Alexandru Ioan Cuza Univ, Dept Geog, Fac Geog & Geol, 20A Carol I Blvd, Iasi 700505, Romania
[2] Alexandru Ioan Cuza Univ, Integrated Ctr Environm Sci Studies North Eastern, 11 Carol I Blvd, Iasi 700506, Romania
来源
JOURNAL OF ENVIRONMENTAL PROTECTION AND ECOLOGY | 2018年 / 19卷 / 03期
关键词
flood; GIS; HEC-RAS; remote sensing; validation; PRUT RIVER; RISK; EXTRACTION; RESERVOIR; BASIN;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Floods have always posed great threat to human settlements, and their monitoring has always been a very important step in the understanding, managing and predicting similar, future events, in order to mitigate flood risk and the concrete impact it has on communities and the environment. Modern techniques of analysing flood extent include remote sensing, by extracting flood limits from satellite imagery, and Geographical Information Systems (GIS), which are used in tandem, to generate cartographic material, depicting areas suffering from flood damage. Unfortunately, the results are not always precise, and can induce significant errors, due to which, the results are questionable and cannot be efficiently included in management plans, by authorities. The current study addresses the validation process of digitally generated GIS layers, based on statistical data derived from hydrological field recordings, with satellite images that reveal the proper flood extents, from the same time period, as the case study flash flood. The emphasis was put on comparing absolute and relative accuracy values, in order to validate several results, such as digital, HEC-RAS generated water levels (based on statistical analysis) with recorded water levels; 5% recurrence interval flood extents of HEC-RAS model, correlated withreal-world flood extent, and through satellite imagery.
引用
收藏
页码:1091 / 1101
页数:11
相关论文
共 19 条
[1]   Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery [J].
Feyisa, Gudina L. ;
Meilby, Henrik ;
Fensholt, Rasmus ;
Proud, Simon R. .
REMOTE SENSING OF ENVIRONMENT, 2014, 140 :23-35
[2]   Application of Remote Sensing in Water Resource Management: The Case Study of Lake Trasimeno, Italy [J].
Giardino, Claudia ;
Bresciani, Mariano ;
Villa, Paolo ;
Martinelli, Angiolo .
WATER RESOURCES MANAGEMENT, 2010, 24 (14) :3885-3899
[3]  
Hapciuc OE, 2016, INT J CONSERV SCI, V7, P501
[4]  
Iosub M, 2015, INT C AIR WATER COMP
[5]   FLOOD RISK ANALYSIS IN SUCEAVA CITY, APPLIED FOR ITS' MAIN RIVER COURSE [J].
Iosub, Marina ;
Tomasciuc, Anamaria Ioana ;
Hapciuc, Oana Elena ;
Enea, Andrei .
2ND INTERNATIONAL SCIENTIFIC CONFERENCE GEOBALCANICA 2016, 2016, :111-118
[6]  
Iosub M, 2014, INT MULTI SCI GEOCO, P315
[7]   Flood risk, uncertainty, and scientific information for decision making - Lessons from an interdisciplinary project [J].
Morss, RE ;
Wilhelmi, OV ;
Downton, MW ;
Gruntfest, E .
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2005, 86 (11) :1593-1601
[8]   Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery [J].
Rokni, Komeil ;
Ahmad, Anuar ;
Selamat, Ali ;
Hazini, Sharifeh .
REMOTE SENSING, 2014, 6 (05) :4173-4189
[9]  
ROMANESCU G., 2018, J FLOOD RISK MANAG
[10]   Exceptional floods in the Prut basin, Romania, in the context of heavy rains in the summer of 2010 [J].
Romanescu, Gheorghe ;
Stoleriu, Cristian Constantin .
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2017, 17 (03) :381-396