Applying GIS in the UAE’s Flood Hazard Zonation
Abstract
The study attempts to analyze the application of GIS in flood hazard zonation in Ras Al Khaima and Fujairah in the United Arab Emirates. Data used in the analysis include Digital Elevation Model, DEM, Differential Global positioning system points, discharge data from the ministry of water. The use of GIS analysis in flood risk mapping occurs in stages of storing, managing, and presenting hydrological data that shows flood inundation and areas of action for flood management. This study evaluates the use of GIS and remote sensing datasets such as classified satellite imagery in an integrated environment to map flood risk areas in United Arab Emirate, Ras AL Khaima and Fujaira states. Raster datasets was dominantly used from an image analysis if the terrain, land cover, drainage and precipitation rates.
Key Words: GIS, Flood Risk Mapping, Satellite imagery
- Introduction
Flooding is one of the hazardous natural disaster in the common occurrences in the world. Flooding leads to destruction of property, loss of lives, and destruction of biodiversity. In the recent years, flooding has increased greatly owing to hydrological changes. According to a study done by the UNDP in 2004, about 82% of the population in the world live in areas with high risk of flooding (Wade, 2005). In most areas, the flood zones are mainly known as flood plains, which are characterized by repeated floods that cause silting and destruction of the land surface. The damages and losses caused by flooding can be reduced using reliable information for planning through flood mapping and inundation. In understanding flood prone areas, the information is useful in preventing floods, managing emergencies, planning, and managing of facilities.
In 2018, unstable weather characterized by heavy rains was experienced in various places in the United Arabs Emirates. In some instances, the government found it suitable to close some roads in Sharjah, Ras Al Khaimah, Wadis, Jebel and Fujaira due to flash floods. The destruction caused by the rains on human lives as well as infrastructure led the government to intensify the efforts of coordinating and working with relevant agencies to deal with emergencies caused by unstable weather. In their studies, the government identified that the instability in the weather state was a result of low pressure in the Red Sea and the upper air on the Western side that causes the hot humid air to blow towards the southern part causing the winds to push stronger waves up to nine feet offshore (Aghaddir, 2018). In some instances, the damages caused by the flooding is severe on houses, drainage and road infrastructure.
Figure 1: Damages caused by Flooding in the UAE, source Khaeejtimes
According to the Khaleejtimes, the government advised on the need to study the region to enable the state prepare for emergencies. The roads department had previously developed some mitigation measures that seemed effectively in reducing the risks associated with the rains in the southern mountainous side. In imploring a critical approach by understanding prone areas, it is possible to develop sustainable mitigation measures. The experiences in Ras Al Khaima and Fujairah form a basis for this study in analyzing the potential risk of flooding to enable proper planning and zonation of areas prone to flooding.
GIS and Remote sensing
Several studies implore the use of remote sensing data such as satellite imagery and LIDAR data, Shuttle Radar Topography Mission, SRTM, geomorphological data, geological and field data supported in a GIS environment to estimate flooding (Ahmed, et al, 2009). GIS plays a key role in understanding the trends of flooding and modelling of the flood plain to enhance the understanding causes of flooding and mitigations measures. GIS offers benefits such as centralized data storage system, ability to prepare multiple models, post processing of the data, multivariability of datasets, automation of operations and digital representation of the data in a user-friendly format.
The models adopted by different researchers vary depending on the available datasets. Fowze et al, applied the one dimension model that simulated the flood zones over fifty years using the HECRAS software (Fowze, 2008). Another study by Bashir adopted the HEC-RAS and HEC- GeoRAS models that studied 19 flooding scenarios by mapping and evaluating the trend through a set period (Bashir et al., 2008). Overall, the studies reveal that an integration model is efficient as it consolidates hydrological models enhancing the graphical valuation of the models. Commonly, the datasets used in the analysis are DEM generation, land cover, soil, and geological maps overlaid and calculated in a GIS environment to prepare flood maps or zones (Gomaa, 2011).
Objective
The study aims to assess the flood risk cases in Ras Al Khaima and Fujairah using GIS software and compatible datasets.
- Study area
The study area for the flood risk zoning and analysis is Ras Al Khaima and Fujairah in the United Arab Emirates as shown in the map below. Ras Al Khaima, commonly known as RAK, has two major settlements, along the coastlines and on the southern side of the mangroves. RAK is characterized by heavy rainfall and underground streams of water that contributes to the fertility of the region compared to other places in the UAE. On average, precipitation increases up to 35.7 mm during the months of December and March. Fujairah, on the other hand is adjacent to Ras Al Khaima and it is characterized by precipitation rises up to 23.9mm. The country experiences heavy precipitation as caused by Hajjar Mountains and the prevailing winds from the Indian Ocean. The two states are surrounded by water bodies namely the Persian Gulf and the Arabia Sea. This is critical in understanding the implication of winds and causes of flooding within the region.
Figure 2: Study Area, Source owner
- Materials and methods
The flood plains are identifiable through continuous observation and modelling the observed parameters. The observed parameters include precipitation (rainfall or snow), water surface elevation and over flows. The observation of the parameters can be achieved through traditional approaches of using gauges and sensors or remote sensing techniques, satellite imagery analysis.
Methodology
The flood zone delineation was achieved using ArcGIS 10.2. Software. The Steps involved in the flood zone delineation
- Data collection
The datasets used in the analysis of the flood risk zones vary from vector data in form of shapefiles, satellite imagery, and reclassified raster datasets. The conversion of the datasets into a compatible file facilitated the analysis in a GIS environment. The datasets are as represented in the chart below:
| Data | Source | Type |
| SRTM/ DEM | NOAA | Raster |
| Administrative Boundary | geoportal.abudhabi.ae | Vector |
| Land Use | Mapcruzin | Raster |
| Population | UAE public data | Shapefile |
| Water Bodies / Coastal Lines | Mapcruzin | Shapefile |
| Tide levels | Climate-modelling | CSV |
| Precipitation data | Climate data | CSV |
- Delineating flood plain areas and preparation of the digital elevation model (using the DEM, point data of samples places, discharge data, and stream centerline)
TIN Technique – the TIN model uses the elevation data converted into raster similar to the DEM that defines the flooding depths. The elevation influences flooding in that fairly flat areas encourage flooding compared to elevated region that are higher above the sea level. The DEM map below shows the terrain of the area:
The data was changed into a raster dataset, reclassified, and weighted over several parameters that indicate the probability of flooding. The analysis was compiled in a model builder weight overlay was used to give values to key elements that causes flood. Some of the key parameters evaluated were areas with high rainfall, flat areas, along the coast shoreline and areas with poor drainage. Modelling was then achieved using HEC-GeoRAS to develop a simulation of the flood scenario in a GIS using rivers, catchment data, and flow path and bank stations from the available weather data (Silva et al., 2014). The combination of the topographical datasets and other GIS supported data enables the RAS to create and generate geometry files in ArcMap.
Figure 3: Water Surface Profile, Source Owner
Figure 4: Map Showing Flood Risk Analysis in Ras Al Khaima
Figure 5: Model Builder Analysis in Arc GIS, Source owner
The maps below show the analysis process and the overlaying of the datasets to identify key flood risk zones in Ras Al Khaima and Fujairah.
Area of interest (Map)
Figure 6: Area of Interest, Source owner
Area of interest (Image)
Figure 7: Satellite Imagery of the study area, Source Google
Area of interest (DEM)
Figure 8: DEM analysis if the study area, Source owner
- Results
The study shows that the probability of floods increases with the proximity to the coastal shoreline as shown in the map below.
Figure 9: Flood Risk map of the study area, Source owner
The output map shows the high flood risk areas with darker variations. Flooding is predominant in Ras Al Khaima as compared to Fujairah.
- Discussion
In a bid to reduce emergencies and plan I advance, the shoreline on the east side of Ras Al Khaima slopes towards the Fujairah and the region is surrounded by a raised elevation. The terrain can facilitate the restructuring of the storm water drain channeling the excess water towards the Southern East side of the country. Interestingly, dense development and population has settled along the Western shoreline despite the probability of high rates of flooding. The flood zoning will enable the official plan preventative measures along the Western side to ensure that in the events of heavy rains, the adjacent population and infrastructure is well protected.
In Fujairah, floods are mainly experienced towards the East shoreline, which is relatively flat. The effect of ocean winds contributed to the high precipitation along the shoreline in both countries. The flooding is experienced on the flat zones, which are conducive for settlement as compared to the mountainous regions in the study area.
Notably, the northern area, indicated by the faint shade, has least risks of flooding which can be attributed to the availability of efficient drainage systems such as rivers and stream that drain the excess water. The channels are effective in offloading excess water from the area.
- Conclusions
The data evaluated for the study was not tested in varying different times to assess if the flood risk as increasing or decreasing within the region. A more advanced study over the flood zones concerning imagery analysis will enable proper predictive modeling of the events. The map identified can focus the attention of the relevant governing authorities on areas suitable for preventative actions, flood management centers and this will provoke more preparedness in the event of a flood emergency. The zones can also help the authorities to advice on the ideal infrastructure to be developed that is least affected by flooding this reducing damages.
References
Aghaddir, A. (28 October 2018). Weather in UAE: Heavy rain floods wadis around Jebel Jais in RAK . https://gulfnews.com/uae/weather/weather-in-uae-heavy-rain-floods-wadis- around-jebel-jais-in-rak-1.2294647
Ahmed M. Y, Biswajeet P., & Abdallah M. (2011) Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery, Environ Earth Sci 62:611–623 DOI 10.1007/s12665-010-0551-1
Fowze J S M., Gunashekara I P A., Liyange PP., Haziraka M. K., Samarakoon L. (2008). Flood Hazard Mapping In Lower Reach of Kelani River, Sri Lanka. Proceedings of 29th Asian Conference on Remote Sensing 3:1 731-736.
Bashir A., Muhammmad S. K., Mohsin J. B., Zakir H. D. (2010). Proceedings of Academic of Sciences. 47(4): 215-226
Adel O., Dietrich S., Ahmed E. R., & Mohammad G. (2011). Flood hazard in Wadi Dahab, Egypt based on Basin Morphometry using GIS Techniques. GI Forum ISBN 978-87907- 509-6
Wade, Dr Steven et al. (2005). Risks to People: Developing New Approaches For Flood Hazard and Vulnerability Mapping, Defra Flood & Coastal Management Conference, NewYork.
“United Arab Emirates: Emirates & Major Cities – Population Statistics, Maps, Charts, Weather and Web Information”. citypopulation.de. Retrieved 15 March 2019.
Shaaban, A. (21 October 2018). New bridges to come up in UAE valley after man drowns in flash floods. https://www.khaleejtimes.com/nation/ras-al-khaimah/new-bridges-to-come- up-in-uae-valley-after-man-drowns-in-flash-floods
