DEM generalization with profile simplification in four directions

The DEM generalization is the foundation of expressing and analyzing the terrain and the basis of multi-scale observation. Meanwhile, it is also the core of building the multi-scale geographic database. This paper would like to propose a new algorithm using profile simplification in four directions(4-DP). This algorithm is composed of two parts, namely extraction of terrain feature points in local window as well as in global profile line and reconstruction of DEMs. The paper used the 5 m resolution DEM of the Suide in Loess Plateau of China as the original data. In the experiment, this paper has achieved the generalized DEM with 5 m and 25 m resolution by removed small details and computed out the optimal threshold. In contrast to the classic algorithms, VIP and Aggregate, based on three evaluation methods. The results show that this method is able to retain the main geographical information effectively in terrain surface.     

Mapping of settlements in high-resolution satellite imagery using high performance computing

Classifying urban land cover from high-resolution satellite imagery is challenging, and those challenges are compounded when the imagery databases are very large. Accurate land cover data is a crucial component of the population distribution modeling efforts of the Oak Ridge National Laboratory’s (ORNL) LandScan Program. Currently, LandScan Program imagery analysts manually interpret high-resolution (1–5 m) imagery to augment existing satellite-derived medium (30 m) and coarse (1 km) resolution land cover datasets. For LandScan, the high-resolution image archives that require interpretation are on the order of terabytes. The goal of this research is to automate human settlement mapping by utilizing ORNL’s high performance computing capabilities. Our algorithm employs gray-level and local edge-pattern co-occurrence matrices to generate texture and edge patterns. Areas of urban land cover correlate with statistical features derived from these texture and edge patterns. We have parallelized our algorithms for implementation on a 64-node system using a single instruction multiple data programming model (SIMD) with Message Passing Interface (MPI) as the communication mode. Our parallel-configured classifier performs 30–40 times faster than stand-alone alternatives. We have tested our system on IKONOS imagery. The early results are promising, pointing towards future large-scale classification of human settlements at high-resolution.     

Research of Terrain 3D Visulization Method Based on IDL and Arcengine

Study on 3D terrain visualization is a hot research topic in GIS, virtual reality, computer graphics, digital photogrammetry and other fields, is also an important part of the digital earth strategy. Try to take advantage of IDL data processing and graphic display function and ArcEngine spatial analysis function, in the Visual c# under the environment of hybrid programming mechanism, use of component design and development of integrated development technologies analysis of terrain visualization application operating environment, realized the 3D digital terrain expression and spatial analysis function. The results show that the IDL and ArcEngine integrated development method applied to the 3D terrain visualization analysis software platform developed operability and extension force with strong, both in terms of space efficiency and image data analysis , development costs advantages.     

遥感与GIS技术支持下的机场选址与工程地质分析

研究将“3S”技术（RS、GIS、GPS）应用到机场地址勘察中,主要是采用现代化遥感技术,以最新遥感图像LANDSATETM（最高空间分辨率15m）,SPOT图像（2．5m）和QUICKBIRD图像（0．61m）等作为信息源,通过遥感图像数据融合、数字镶嵌和影像增强等数字处理,制作不同类型、不同波段和不同分辨率的正射遥感影像及正射影像地图,为机场工程地质勘察提供最佳图像资料。通过遥感图像增强处理、信息提取及GIS空间分析等,对研究区的地质构造,地质灾害等进行解译。并借助GPS进行野外现场调研,查明研究区地质构造的特征,尤其是隐伏断裂、活动性断裂的分布,以及岩溶漏斗、洼地等水文地质现象,为小哨机场工程地质勘察工作提供了基础资料。     

Application of remote sensing and GIS for delineating groundwater recharge potential zones of Kovilpatti Municipality,Tamil Nadu using IF technique

During the last three decades, remotely sensed data (both satellite images and aerial photographs) have been increasingly used in groundwater exploration and management exercises. An integrated approach has been adopted in the present study to delineate groundwater recharge potential zones using RS and GIS techniques. IRS-1C satellite imageries and Survey of India toposheets are used to prepare various thematic layers viz. geology, soil, land-use, slope, lineament and drainage. These layers were then transformed in to raster data using feature to raster converter tool in ArcGIS 9.3 software. The raster maps of these factors are allocated a fixed score and weight computed from Influencing Factor (IF) technique. The weights of factors contributing to the groundwater recharge are derived using aerial photos, geology maps, a land use database, and field verification. Subjective weights are assigned to the respective thematic layers and overlaid in GIS platform for the identification of potential groundwater recharge zones within the study area. Then these potential zones were categories as ‘high’, ‘moderate’, ‘low’, ‘poor’. The resulted map shows that 19 % of the area has highest recharge potential, mainly confined to buried pediplain, agriculture land-use and river terraces (considerable amount of precipitated water percolates into subsurface), 28 % of the area has moderate groundwater recharge potentiality and rest of the area has low to poor recharge potentiality. The residual hills and linear ridges with steep slopes are not suitable for artificial recharge sites. Finally, 13 % of total average annual precipitated water (840 mm) percolates downward and ultimately contributes to recharge the aquifers in the Kovilpatti Municipality area. The paper is an attempt to suggest for maintaining the proper balance between the groundwater quantity and its exploitation.     

Flood monitoring, mapping and assessing capabilities using RADARSAT remote sensing, GIS and ground data for Bangladesh

Remote sensing is the most practical method available to managers of flood-prone areas for quantifying and mapping flood impacts. This study explored large inundation areas in the Maghna River Basin, around the northeastern Bangladesh, as determined from passive sensor LANDSAT data and the cloud-penetrating capabilities of the active sensors of the remote imaging microwave RADARSAT. This study also used passive sensor LANDSAT wet and dry images for the year 2000. Spatial resolution was 30 m by 30 m for comparisons of the inundation area with RADARSAT images. RADARSAT images with spatial resolution of 50 m by 50 m were used for frequency analysis of floods from 2000 to 2004. Time series images for 2004 were also used. RADARSAT remote sensing data, GIS data, and ground data were used for the purpose of flood monitoring, mapping and assessing. A supervised classification technique was used for this processing. They were processed for creating a maximum water extent map and for estimating inundation areas. The results of this study indicated that the maximum extent of the inundation area as estimated using RADARSAT satellite imaging was about 29, 900.72 km² in 2004, which corresponded well with the heavy rainfall around northeast region, as seen at the Bhairab Bazar station and with the highest water level of the Ganges–Brahmaputra–Meghna (GBM) Rivers. A composite of 5 years of RADARSAT inundation maps from 2000 to 2004, GIS data, and damage data, was used to create unique flood hazard maps. Using the damage data for 2004 and the GIS data, a set of damage maps was also created. These maps are expected to be useful for future planning and flood disaster management. Thus, it has been demonstrated that RADARSAT imaging data acquired over the Bangladesh have the ability to precisely assess and clarify inundation areas allowing for successful flood monitoring, mapping and disaster management.     

Riverine flood assessment in Jhang district in connection with ENSO and summer monsoon rainfall over Upper Indus Basin for 2010

Pakistan has experienced severe floods over the past decades due to climate variability. Among all the floods, the flood of 2010 was the worst in history. This study focuses on the assessment of (1) riverine flooding in the district Jhang (where Jhelum and Chenab rivers join, and the district was severely flood affected) and (2) south Asiatic summer monsoon rainfall patterns and anomalies considering the case of 2010 flood in Pakistan. The land use/cover change has been analyzed by using Landsat TM 30 m resolution satellite imageries for supervised classification, and three instances have been compared, i.e., pre-flooding, flooding, and post-flooding. The water flow accumulation, drainage density and pattern, and river catchment areas have been calculated by using Shutter Radar Topography Mission digital elevation model 90 m resolution. The standard deviation of south Asiatic summer monsoon rainfall patterns, anomalies and normal (1979–2008) has been calculated for July, August, and September by using rainfall data set of Era interim (0.75° × 0.75° resolution). El Niño Southern Oscillation has also been considered for its role in prevailing rainfall anomalies during the year 2010 over Upper Indus Basin region. Results show the considerable changing of land cover during the three instances in the Jhang district and water content in the rivers. Abnormal rainfall patterns over Upper Indus Basin region prevailed during summer monsoon months in the year 2010 and 2011. The El Niño (2009–2010) and its rapid phase transition to La Niña (2011–2012) may be the cause of severity and disturbances in rainfall patterns during the year 2010. The Geographical Information System techniques and model based simulated climate data sets have been used in this study which can be helpful in developing a monitoring tool for flood management.     

River sinuosity in a humid tropical river basin,south west coast of India

The variability in ground water potential at different regions of the Meenachil River basin and the remarkable distribution of palaeodeposit of sand at its middle to lower reaches have led to interpret the sinuosity indexes of the main channel as well as the tributaries of the River for elucidating the relationship between mathematical expressions and filed observations. The measurement of digital elevation model-derived river sinuosity was carried out for 846 km² of the basin area of Meenachil River. The drainage networks of 10 major sub-watersheds and four mini-watersheds were delineated using remote sensing data—geocoded false colour composite of Indian Remote Sensing satellite (IRS)-1D (LISS III) data with a spatial resolution of 23.5 m—coupled with the Survey of India toposheets (1:50,000). The calculation of the sinuosity indexes were carried out using Arc GIS (8.3 version) software. Hydraulic sinuosity indexes, topographic sinuosity index and standard sinuosity index were calculated. The study depicts the remarkable correlation between theoretical data sets with field observations and the influence of tectonic control on river planforms. Three structurally controlled regions of Meenachil River basin were established using Remote Sensing and Geographical Information System.     

LiDAR-supported prediction of slope failures using an integrated ensemble weights-of-evidence and analytical hierarchy process

The present study investigates a potential application of different resolution topographic data obtained from airborne LiDAR and an integrated ensemble weight-of-evidence and analytic hierarchy process (WoE–AHP) model to spatially predict slope failures. Previously failed slopes of the Pellizzano (Italy) were remotely mapped and divided into two subsets for training and testing purposes. 1, 2, 5, 10, 15, and 20 m topographic data were processed to extract nine terrain attributes identified as conditioning factors for landslides: slope degree, aspect, altitude, plan curvature, profile curvature, stream power index, topographic wetness index, sediment transport index, and topographic roughness index. Landslide (slope failure) susceptibility maps were produced using a single WoE (Model 1), an ensemble WoE–AHP model that used all conditioning factors (Model 2), and an ensemble WoE–AHP model that only used highly nominated conditioning factors (Model 3). The validation results proved the efficiency of high-resolution (≤ 5 m) topographic data and the ensemble model, particularly when all factors were used in the modeling process (Model 2). The average success rates and prediction rates for Model 2 that used ≤ 5 m resolution datasets were 84.26 and 82.78%, respectively. The finding presented in this paper can aid in planning more efficient LiDAR surveys and the handling of large datasets, and in gaining a better understanding of the nature of the predictive models.     

A numerical comparison of enhancing horizontal resolution (EHR) technique utilizing 2D resistivity imaging

The effectiveness of inversion apparent resistivity data to determine accurately the true resistivity distribution over 2D structures has been investigated using a common inversion scheme based on smoothness-constrained nonlinear least-squares optimization with enhancing horizontal resolution (EHR) technique by numerical simulation. The theoretical model generates in RES2DMOD software at specific distance and depth using Wenner, Wenner–Schlumberger, and pole–dipole arrays were inverted. The inversion model was compared with the original 2D model in RES2DINV software. The study model includes horizontal layering, vertical resolution, and horizontal two layers with different resistivity. Also, the response to variations in data density of these arrays was investigated. The study shows the best array suitable to be used in the survey was chosen for real data acquisition at the actual site. Subsequently, the results from borehole were used to verify the results of 2D resistivity imaging method with and without EHR technique. Saturated zone (0–40 Ω-m) was found scattered at the depth of 10–20 m. The borehole is located at 63 m at 2D resistivity imaging survey which shows at depth 10–20 m is sandy silt. Highly weathered sandstone was found at 6 m depth with resistivity value of 800 Ω-m and SPT N value of 20. The bedrock was found at 27 m depth with resistivity value of 3,000 Ω-m and SPT N value of 50. The application of 2D resistivity imaging with EHR technique indicate the ability of the proposed approach in terms of density, depth, and resistivity value of anomalous and layer in a computationally and numerically efficient manner and to exhibit good performance in the data inversion.     

Classifying inundation limits in SE coast of India: application of GIS

A study on the possible inundation limit in SE coast of India was carried out using various physical, geological and satellite imageries. The coastal inundation hazard map was prepared for this particular region as it was affected by many cyclones, flooding, storm surge and tsunami waves during the last six decades. The results were generated using various satellite data (IRS-P6 LISS3; LANDSAT ETM; LANDSAT-5 ETM; LANDSAT MSS) and digital elevation models (ASTER GLOBAL DEM), and a coastal vulnerability index was generated for the entire coastal stretch of Nagapattinam region in SE coast of India. The coastal area which will be submerged totally due to a 1–5 m rise in water level due to any major natural disaster (tsunami or cyclone) indicates that 56–320 km² will be submerged in this particular region. The results suggest that nearly 7 towns and 69 villages with 667,477 people will be affected and indicate that proper planning needs to be done for future development.     

通过遥感对矿产资源开采中环境影响的研究--以阜新煤矿和排山楼金矿为例

阜新地区地处华北地台,富含煤和金矿床.呈东西向分布的太古宙和元古宙变质地层在华力西期、印支期和燕山期的变形和岩浆活动中发生隆起.金矿赋存于隆起的前寒武纪变质岩石中.成煤期为晚石炭-早二叠纪、早中侏罗纪、晚侏罗-早白垩纪.阜新煤矿和排山楼金矿是辽宁省的主要煤、金产地.
由于开采物中的有用物质只占很小的比例,因此提取有用物质的方式不可避免地要破坏当地的环境.矿山开采的每一步骤都对环境产生着负面影响.应用遥感资料进行矿山管理,是采用基于地表物体光谱反射的可视近红外(VNIR)遥感和短波红外(SWIR)遥感,以及基于物体热发光的热红外(TIR)遥感,利用不同的地表光谱反射,将相似的物体区分、分类、填图,并进行土地资源分析.野外工作包括在阜新煤矿和排山楼金矿确定岩石蚀变类型,采集标本,构造测量,对矿山环境进行数码拍照.陆地卫星MSS、TM和ETM+数据是分析研究的基础.应用ERDAS IMAGING软件处理卫星数据.并用ERDAS MapSheets和ViewFinder软件划图.应用各种图像处理技术进行图像增强和物体分辨.从卫星图像上直接测量排山楼金矿和阜新煤矿露天采场的多边形周长和面积.从卫星图像上可以看出,阜新煤矿从1980年到2000年环境的恶化.矿山开采产生的废矿堆不仅对矿区造成破坏,由于它们邻近市区,也通过视觉污染和噪音污染构成了潜在的环境污染源.开采活动对环境影响的另一个方面就是地面下沉,这是由地下开采造成的.它对地表的影响是明显的.本研究的重点是煤矿开采造成的地面下沉.与金矿脉的开采不同,煤矿的开采要移去数米厚的整个煤层.其结果不可避免地导致上覆地层的垮塌.排山楼金矿和阜新煤矿的另一个环境污染源来自矿石的处理(提纯和浓缩).金矿和煤矿都采用重力分离和浮选的方法.排山楼金矿目前采用先进的氰化-碳吸附选矿方法.作为补救措施,现在对用于浮选的化学剂的选择不仅要考虑其效益,而且要将其对环境的损害降到最低.尾矿处理也是影响环境的一个重要问题.阜新煤矿和排山楼金矿通常将尾矿倾倒地附近的人工坑内.这些区域虽然不至于对景观造成严重破坏,但很难在其表面恢复植被.而且,从该区域排出的水含有强酸和有毒的金属离子,一旦流入自然水系,将给水生生物造成大面积损害.堆放尾矿的区域一旦干燥,将产生另一个环境问题——粉尘污染.基于这些发现,提出如下建议：
（ 1）采矿过程中环境不断恶化的事实说明,两个矿山在控制露天开采方面仍有不足.虽然移动矿体上覆岩石或盖层是矿山开采的必要前提,但矿产资源的采掘必须对自然的保护给予更多的重视.应更加注重盖层的回填,植被、湿地、沼泽的恢复,控制溢出物,合理利用废物.
（2）地方政府应参与地区内矿产资源开发项目的立项、审批工作.政府在法律框架内干预、控制矿山开采行为中的环境和土地利用问题.     

A web-based real-time and full-resolution data visualization for Himawari-8 satellite sensed images

It has been almost four decades since the first launch of geostationary meteorological satellite by Japan Meteorological Agency (JMA). The specifications of the geostationary meteorological satellites have shown tremendous progresses along with the generations, which are now entering their third generation. The third-generation geostationary meteorological satellites not only yield basic data for weather monitoring, but also globally observe the Earth’s environment. The development of multi-band imagers with improved spatial resolution onboard the third-generation geostationary meteorological satellites brings us meteorological data in larger size than those of the second-generation ones. Thus, new techniques for domestic and world-wide dissemination of the observational big data are needed. In this paper, we develop a web-based data visualization for Himawari-8 satellite sensed images in real time and with full resolution. This data visualization is supported by the ecosystems, which uses a tiled pyramid representation and parallel processing technique for terrain on an academic cloud system. We evaluate the performance of our techniques for domestic and international users on laboratory experiments. The results show that our data visualization is suitable for practical use on a temporal preview of observation image data for the domestic users.     

Adaptive DTM generalization methods for tangible GIS applications

Several international studies attempt to construct tangible GIS systems, forming real 3D surfaces using a large number of mechanical parts along a matrix formation. Most of these attempts suffer in cost, accuracy, resolution and/or speed. In order to facilitate data handling in GIS tangible systems, the generalization process becomes crucial, accommodating compression, visualization and comprehension of spatial data under various scales. Under this perspective, the main objective of the proposed adaptive generalization approach is to provide optimized representation of 3D digital terrain models with minimum loss of information, serving specific applications. That is, to minimize the number of pixels in a raster dataset used to define a DTM, while reserving surface information and enhancing the important semantic features. To this aim, this paper presents specific computationally efficient surface generalization approaches, which can be incorporated in applications of tangible GIS systems, due to their low processing time, facilitating real-time results. The research methods developed and tested include adaptive variations of a) the Douglas-Peucker line simplification algorithm in 3D data and b) the spatial Laplace filter that estimates the significance of each node, based on its nearest neighbors. The proposed strategy also dynamically incorporates topology and semantic restraints, in order to preserve important information and depict it with variable detail level, according to the application at hand. The algorithms are evaluated on their accuracy for a specific wildfire application and for different reduction levels in two different types of terrain data. They are also compared to their original-basic implementations in terms of performance.     

Mapping potential areas for groundwater storage in Wadi Aurnah Basin, western Arabian Peninsula, using remote sensing and geographic information system techniques

Water shortage has become a problem in many arid regions where rainfall is low. Wadi Aurnah Basin, in Saudi Arabia (Arabian Peninsula), where the Holy Islamic cities are located, was selected for study, since it represents a water-scarce region. The potential for groundwater storage was investigated. This was achieved using remote sensing and geographic information system (GIS) techniques to cover the whole area (3,113 km²). Satellite images with high spatial resolution were processed to recognize terrain elements controlling the subsurface rock behavior. Landsat 7 ETM+, ASTER and SRTM satellite images were processed using ERDAS IMAGINE software. The influencing factors on groundwater storage were determined and digitally mapped as thematic layers. This included rainfall, lithology, rock fractures, slope, drainage and land cover/use. These factors were integrated in the GIS system (ArcView). A map was produced, indicating potential areas for groundwater storage. The map shows that 12–15% of Wadi Aurnah Basin has potential for groundwater storage, mainly in areas where intensive fracture systems exist.     

Effect of digital elevation model on Mohr-Coulomb geophysical flow model output

Digital elevation models (DEMs) used in geospatial analysis like the simulation of geophysical flows, such as floods, landslides, and block and ash flows, differ in resolution, acquisition time and generation methodology, which results in varied representation of topographic features. This study investigates the effects of DEMs on the output of a granular flow model, TITAN2D by comparing the output using different DEMs to that obtained with a “true” representation of the terrain, which is considered to be that obtained by using TOPSAR 5 m data. Seven DEMs at four resolutions from four sources were used for Mammoth Mountain, California, a cumulodome volcano. TITAN2D was run for seven different locations of an eruption of a potential dome and two different collapse volumes. The resulting outputs were subsequently compared with TOPSAR 5 m output, and qualitative and statistical inferences were drawn. DEMs with different resolutions and sources generated different outputs that led to different flow maps. For moderate and smaller scale flows ( $\mathcal{O}(10^4)$ m³ – $\mathcal{O}(10^5) \,\text{m}^3$ ), different representations can affect the computation of accurate footprint of the flow and fine DEM resolution is critical for correct characterization of these flows.     

Lineament extraction from multi-resolution satellite imagery: a pilot study on Wadi Bani Malik, Jeddah, Kingdom of Saudi Arabia

The study of structural lineaments is important for mineral exploration, geotectonic and geotechnical studies, and for the mitigation of geologic hazards. The present work deals with the extraction of lineaments from satellite imageries of different spatial resolutions as well as the analysis of these extracted lineaments. Wadi Bani Malik area located to the east of Jeddah city on the Red Sea coastal plain is chosen for such a study. Six types of digital satellite imagery data were used in the present study. These comprise satellite imagery of low spatial resolution (LSR) including Landsat MSS of 80-m resolution, Landsat TM of 30-m resolution, and Landsat TM of 25-m resolution; satellite imagery of moderate spatial resolution (MSR) including Landsat ETM+ panchromatic of 15-m resolution and SPOT panchromatic of 10-m resolution; and satellite imagery of high spatial resolution (HSR) including the Indian Remote Sensing satellite IRS data of 5-m resolution. As expected, the analysis of the extracted lineaments from different data sets shows that the imagery data of HSR of the Indian IRS data give the highest frequency of the extracted structural lineaments (N?=?3,235), while the imagery data of LSR of the Landsat MSS data give the lowest frequency of the extracted lineaments (N?=?89). The imagery data of MSR give moderate frequency (N?=?1,643) in average. Due to the present study, it is recommended to use the imagery data of HSR and MSR for the extraction of structural lineaments for detailed and regional studies, respectively. The imagery data of LSR are not recommended for such studies due to the fact that most of the real structural lineaments framework cannot be extracted; accordingly, it is not useful in the analyses of lineaments for geological purposes.     

祁连山区云光学特征的遥感反演与云水资源的分布特征分析

利用Terra和Aqua卫星上载的MODIS探测器接收资料和祁连山区及周边气象台站6 h降水量资料,应用6S辐射传输模式和Mie模式,针对2002—2005年以来的18次大范围云覆盖的祁连山区,反演了云的光学厚度、云粒子有效半径以及云液态含水量等参数,结合地理信息系统分析了其随海拔高度变化的分布特征及其与地面降雨量的关系.结果表明:祁连山区云的光学厚度、云粒子有效半径以及云液态含水量分布受地形影响具有显著的地域差异,最大值分布在海拔4 300 m以下的山区,是云水资源丰富区和易降水区;云宏观特征参数与地面6 h降水量成正相关关系,产生降水概率较大的云光学厚度在8~20之间,云粒子有效半径在6~12μm之间,云液态含水量在0.04 g·m^-3就能产生降水.祁连山区云液态含水量可高达0.15 g·m^-3,表明山区云水资源具有很大的开发潜力.     

多维GIS矿产评价数据管理系统设计和实现

矿产资源评价需通过各种物探、化探、航空磁法、遥感、地质和实地调查资料综合分析以确定钻井孔位.针对多源、多时相、多尺度矿产资源勘探资料一体化管理和可视化分析,提出了一种基于分布式多维GIS模型的矿产资源评价数据管理方法.首先,分析了矿产资源预测评价数据资料特征,提出基于多维GIS模型的矿产资源评价数据管理模型;其次,提出了多源矿产资源评价数据处理策略,设计了一种全球瓦片金字塔模型的栅格和地形数据处理方法;再次,设计了分布式多维GIS矿产资源评价数据管理系统体系结构和功能模块,提出了双缓存性能优化方案;最后,开发实现了一个典型的矿产资源评价数据管理系统,实现了多达40种二维、三维数据、文档、多媒体等矿产资源评价数据一体化管理和可视化分析,可用于分布式矿产资源勘探评价的全球协同办公.     

Assessment of flood inundation mapping of Surat city by coupled 1D/2D hydrodynamic modeling: a case application of the new HEC-RAS 5

Surat city of India, situated 100 km downstream of Ukai Dam and 19.4 km upstream from the mouth of River Tapi, has experienced the largest flood in 2006. The peak discharge of about 25,770 m³ s^?1 released from the Ukai Dam was responsible for a disaster. To assess the flood and find inundation in low-lying areas, simulation work is carried out under the 1D/2D couple hydrodynamic modeling. Two hundred ninety-nine cross sections, two hydraulic structures and five major bridges across the river are considered for 1D modeling, whereas a topographic map at 0.5 m contour interval was used to produce a 5 m grid, and SRTM (30 and 90 m) grid has been considered for Surat and the Lower Tapi Basin. The tidal level at the river mouth and the release from the Ukai Dam during 2006 flood are considered as the downstream and upstream boundaries, respectively. The model is simulated under the unsteady flow condition and validated for the year 2006. The simulated result shows that 9th August was the worst day in terms of flooding for Surat city and a maximum 75–77% area was under inundation. Out of seven zones, the west zone had the deepest flood and inundated under 4–5 m. Furthermore, inundation is simulated under the bank protection work (i.e., levees, retaining wall) constructed after the 2006 flood. The simulated results show that the major zones are safe against the inundation under 14,430 m³ s^?1 water releases from Ukai Dam except for the west zone. The study shows the 2D capability of new HEC-RAS 5 for flood inundation mapping and management studies.