SITE SELECTION FOR AQUACULTURE ACTIVITIES IN ABU DHABI

2013 SITE SELECTION FOR AQUACULTURE ACTIVITIES IN ABU DHABI A multi-criteria GIS approach

Document Control DOCUMENT CONTROL DOCUMENT ISSUE Project Number ---- Project Name / Title Site selection for Aquaculture Activities Name Signature Date Prepared by Hossam El Alkamy Submitted by Approved by Authorised for Issue by Issue Status Recommended Citation El Alkamy, H. (2013). Site selection for Aquaculture Activities in Abu Dhabi: A GIS Multi-criteria Approach, Internal Report, Environment Agency- Abu Dhabi, UAE File Reference Number DOCUMENT REVISION Revision No. Date Affected Pages Date of Change By 1- First Review 15/9/2013 23/9/2013 Ayesha El Bloushi 2- Second Review 6/10/2013 19/11/2013 By Anil Kumar Page i

CONTENTS INTRODUCTION... 1 CRITERIA FOR SELECTION... 1 DATASETS & ANALYSIS... 2 INLAND AQUACULTURE SUITABILITY ANALYSIS... 3 SEA-CAGE AQUACULTURE SUITABILITY ANALYSIS... 5 INTERTIDAL AQUACULTURE SUITABILITY ANALYSIS... 6 RESULTS... 7 CONCLUSION & RECOMMENDATION... 15

Site Selection for Aquaculture activities in Abu Dhabi A M U L T I - C R I T E R I A G I S A P P R O A C H INTRODUCTION Aquaculture industry is growing at a rapid rate in the Emirate of Abu Dhabi. The reason for this rapid growth could be attributed to the increase in population, together with increased nutritional demand, and associated over-exploitation of the local fish stock. The industry provides an obvious alternative solution for protein and is also considered as an activity that could provide opportunities for economic growth and entrepreneurship among the local community. It is against this backdrop that Environment Agency Abu Dhabi decided to undertake an analysis to select and prioritize areas suitable for aquaculture along the coast as well as inland areas. The selection approach involved analysis for three different types of aquaculture, namely inland aquaculture systems (ponds, raceways RAS), sea cages and intertidal aquaculture. Accordingly, there were three distinct analysis domains defined to enable the process of site selection leading to three sets of suitability predictors and classifications. For example, the distance to critical marine habitats such as mangrove, sea grass and coral reefs were considered when processing for coastal aquaculture, while these had no value when modeling for inland aquaculture suitability. The approach resulted in three sets of prioritized areas to be used for the purposes of the specified aquaculture activity. CRITERIA FOR SELECTION Distinct sets of criteria were selected for the three aquaculture activities under consideration. For inland aquaculture, the criteria identified were: Soil in Aquaculture sites should have low water infiltration or permeability characteristics (for pond systems). Avoid close proximity to urban residential areas (towns and cities), at least 3-5 Km away. Good Access and proximity to main highway and roads. Preferred to be within reach of water network and power grid. To avoid close proximity to high density wildlife areas. Favor areas with groundwater of high quality (low salinity, shallow water table) and avoid ground water depleted zones. For suspended sea cages, the main drive was to select areas where water depth is over 10 m meters, and avoiding areas close to sources of pollutants (mainly sewage outfalls) and sites of reoccurring harmful algal blooms. Thus the selection criteria identified were: Favor the depth of over 10 meters with the least favorable depth class being 0-5 meters. P a g e 1

Avoid proximity to discharge sources, at least 3 Km away from the nearest discharge outfall. Avoid proximity to reoccurring harmful algal bloom locations. Avoid proximity to heavy traffic shipping lanes. Shipping density of 0 vessel/km 2 during recording period of October 2004 - October 2005. (This data was used due to non-availability of more recent data). Maintain socio-economic compatibility with ongoing marine activities, at least 2 Km from established Buhoor (traditional fishing right zones). Avoid Proximity to Marine Protected Areas (MPAs) and critical marine habitats - at least 2 Km away from known coral reefs, at least 3 Km from known ranges of large groups of marine mammals (Dugongs) and at least 4 Km away from known turtle nesting sites. For the intertidal type of aquaculture, a third set of criteria were identified. The main limiting factor for this type of aquaculture is the shore line. The shore lines of non-private islands were also included, and an analysis domain of 20 Km max from the nearest shore line was selected. Accordingly the selection criteria identified were: Favor areas that are at maximum of 2 Km away from nearest shoreline, while areas of 15 Km and beyond from being least favorable. Favor depth class of 0-5 meters while the least favorable depth class being 10 meters and deeper. Avoid proximity to discharge sources, at least 3 Km away from the nearest discharge outfall. Avoid proximity to reoccurring harmful algal blooms - at least 5 Km. Maintain socio-economic compatibility with ongoing marine activities, at least 2 Km from established Buhoor (traditional fishing right zones). Avoid proximity to Marine Protected Areas (MPAs) and critical marine habitats, at least 2 Km away from known coral reefs, and at least 4 Km away from known turtle nesting sites. DATASETS & ANALYSIS The analysis involved 3 separate domains where different criteria and layer weights were applied. The inland aquaculture suitability analyses were applied to an analysis domain that involved the main landmass of Abu Dhabi emirate excluding the islands. The sea cages category involved a domain incorporating the total marine territory of Abu Dhabi Emirate, excluding the terrestrial parts of the islands. Finally, the Intertidal category was prepared over a domain that comprised of a buffer area of 20 Km off of all Abu Dhabi shorelines including non-private islands. Map (1) shows the three domains of the analyses. All area calculation conducted in this analysis is done in ArcGIS 10.1 using XTOOLS 7.1 and in WGS84 World Mercator Projection. EAD s Environmental Database (EDB) holds rich geospatial data that was utilized in multi-criteria selection model. The selection process was applied, guided by the above listed criteria. For the inland aquaculture activities suitability, the utilized datasets included major roads, residential areas, wildlife centers, soils types and related data, and groundwater salinity & depth to water table. Page 2

Inland Aquaculture Suitability Analysis Map 1) delineation of analyses domains for three aquaculture suitability classifications Additional datasets such as depth to sea floor (bathymetry (GEBCO-8 Grid)) were used for the site suitability analysis for sea cages. Other data elements derived by interpolating the distance measured to the nearest feature of interest (e.g. nearest Buhoor area, coral reef etc.) over a point grid spaced by 1Km were also used in the analysis. The method of analysis involved overlaying multiple raster grids representing the defined selection criteria in a weighted manner, to produce a measure of site suitability for each cell within the analysis extent. Weighted overlay is a process where all data has to be brought into a comparable format that allows for direct comparison. To achieve this objective, the datasets had to be converted to raster format at a comparable scale before applying the weighted overlay analysis. A grid of 1 Km spaced points of the analysis extent were used to assess proximity to roads, towns & cities and wildlife density areas using the NEAR function of ArcGIS Spatial Analyst. In addition a layer of soil characteristic of depth to hardpan was used as a proxy for permeability. Depth to Hardpan of 15,000 sites collected during the soil survey was interpolated using Inverse Distance Weighting (IDW) to produce a continuous surface of the property over the study domain. In order to run weighted overlaying, all raster explanatory layers had to be reclassified into one common scale. A scale of suitability ranks was deviced where the lowest grade1 being unsuitable, 4 barely suitable 7 moderately suitable and 10 being highly suitable. These classification tables are shown in Annex I for the three types of analyses. INLAND AQUACULTURE SUITABILITY ANALYSIS Raster of proximity to roads was reclassified into 4 categories on a scale of 1 10; 10 being the nearest to major roads and 1 being the farthest. The four classes were 1 farthest (least favorable), 4 and 7 in between and 10 being the nearest to roads (most favorable). The layer of depth to hardpan was reclassified into 10 categories with the shallow impermeable soil being classified as highly suitable (10) and deep soils of distant hardpan classified as (1). However, a minimum of 4m soil was maintained to allow for ponds excavation. Wildlife concentrations were treated differently to combine both the effect of proximity and the numbers of wildlife populations simultaneously. In other words, the proximity was transformed into a measure termed wildlife influence where the distance to nearest wildlife concentration is multiplied by the number of wildlife populations in that nearest wildlife concentration. The product is Page 3

then reclassified into the usual 1-10 classes with 1 being the least favorable (nearby / big wildlife population) and 10 being most favorable (distant/ small wildlife population). Maps 2 to 7 show the datasets used in the analysis for the required site selection purpose Map 2 Proximity to main Cities & towns Map 3 Proximty to Main Roads Map 4 Depth to Hardpan (permeability) Map 5 Influence of Wildlife concentrations Map 6 Groundwater level 2010 Map 7 Groundwater Salinity 2008 Analysis for suitability was done using the WEIGHTED OVERLAY function of ArcGIS Spatial Analyst 10. In each category of the aquaculture activities 2 rival scenarios were specified. The first scenario applies an equal weights approach were all the explanatory data layers are given equal influence towards a sum of 100%. In the second scenario, termed hereafter as the Adjusted Scenario, weights are modified in a Page 4

Sea-cage Aquaculture Suitability Analysis way to fulfill a certain rational or to derive the suitability classification process to favor areas of certain merits over others. For example, the adjusted scenario in the case of inland aquaculture was built to give higher influence to the layers of groundwater quality (both salinity and depth to water table) in an endeavor to select areas with high water quality, away from the depleted areas. This scenario is termed the Groundwater Conservation Scenario. The equal weights scenario in all cases is used as a general bench mark for the selection process while the adjusted scenario is usually considered as more favorable as it is derived from a management point of view or ecological sustainability rationale. The adjusted weights are shown in table (1) SEA-CAGE AQUACULTURE SUITABILITY ANALYSIS All involved rasters were reclassified into 4 categories on a scale of 1 10. The four classes were 1 is least favorable, 4 and 7 in between and 10 being the most favorable. This is to provide a unified scale for weighted overlaying assessment. From a technical point of view, the most influential factors in this aquaculture activity are the depth and proximity to discharge outfalls. The ideal site would lie in depth band of 15 to 45 meters. The second consideration is to maintain quite a sufficient distance from pollutants. Thus a minimum distance of at least 3Km from the nearest discharge outfall is required. For the same reason, a minimum distance of 5Km from reoccurring harmful algal blooms is also specified. In addition to these three main considerations, avoidance of high shipping traffic, proximity to sensitive habitats and ecologically sensitive zones was observed by the incorporation of the other respective data layers as mentioned in the criteria section earlier. The analyses involved two scenarios for all categories, the first assuming equal weights for all involved datasets, while the second scenario (i.e. adjusted weight scenario), adopts the technical approach of emphasizing the role of some predictors in accordance with the inputs from aquaculture specialists and environmental regulators. This shift in emphasis of the predictor is controlled by assigning a biased weight within the modeling process. The equal and adjusted weights are shown in table (1). Scenarios: In the first scenario, all layers were given equal weights. Thus each layer was given a 12% or 11% weight in the analysis resulting in a total of 100%. While in the second scenario, adjusted weight scenario, emphasis was given to depth (bathymetry) changing its weight to 25%, and also enlarging the effect of proximity to discharge outfalls giving it higher weight of 15%. Maps 8 to 13 showing the datasets used in the analysis for the required site selection purpose. Map 8 Bathymetry dataset Map 9 Proximty to Buhoor Page 5

Map 10 Proximity to discharge outfalls mammals Map 11 Proximity to large groups of marine Map 12 Shipping Traffic density Map 13 Proximity to coral Reefs INTERTIDAL AQUACULTURE SUITABILITY ANALYSIS All involved rasters were reclassified into 4 categories on a scale of 1 10. The four classes were 1 is least favorable, 4 and 7 in between and 10 being the most favorable. In this category again emphasis is given particular water depth band (0-5) in addition to avoiding sources of discharge and potential pollutants such as harmful algal blooms. These where the main drives in changing the weights from the equal weights scenario into the adjusted scenario for this category. Table (1) Scenario definition & weights of different data layers as used in the three selection scenarios tested. Data layer Equal Weights Adjusted Scenario Page 6

Inland Aquaculture Proximtiy to main Cities & towns 14% 10% Proximty to Main Roads (Access) 15% 10% Depth to Hardpan (permeability) 14% 10% Proximty to Wildlife concentrations 14% 10% Groundwater Salinity 14% 30% Depth to Ground water level 14% 20% Proximity to Protected Areas 15% 10% Total 100% 100% Proximity to big marine mammals (>10) 11% 3% Proximity to coral reefs 11% 3% Proximity to MPAs 11% 6% Proximity to discharge outfalls 11% 15% Sea-cage Aquaculture Proximity to Buhoor 11% 12% Distance to nearest shore line 11% 16% Shipping traffic density 11% 10% Bathymetry 12% 25% Proximity to reoccurring Algal Blooms 11% 10% Total 100% 100% Proximity to big marine mammals (>10) 11% 3% Proximity to coral reefs 11% 3% Proximity to MPAs 11% 6% Proximity to discharge outfalls 11% 15% Intertidal aquaculture Proximity to Buhoor 11% 12% Distance to nearest shore line 11% 16% Shipping traffic density 11% 10% Bathymetry 12% 25% Proximity to reoccurring Algal Blooms 11% 10% Total 100% 100% RESULTS The results for the three categories were quite different. Equal weights scenario for the inland ponds selected an area of 9309 Km 2 as suitable, over the different classes of suitability. Most of the suitable areas were allocated to the barely suitable class. However, these conditions where enhanced in the water Page 7

conservation scenario that involved relaxing the criteria for soil depth to hard pan and selecting for areas of higher water quality. This resulted in a higher total suitable area of 13,304 Km 2 and larger proportion being in the moderately suitable class rather than the barely suitable class. Spatially the two scenarios were fairly similar in how they allocated suitable regions. In case of the sea cages category both the equal weights scenario and the adjusted scenario allocated a relatively similar total area of suitable sites over the three suitability classes. Equal weights scenario resulted in 44,590 Km 2 while the adjusted scenario resulted in slightly higher 44,615 Km 2 suitable area. However, a major difference between the two scenarios is that much more of the suitable sites were classified as highly suitable in the adjusted model, compared to the equal weights model. In the intertidal category also, the area classified as suitable was enhanced by the adjusted approach compared to the equal weights approach where the suitable area increased from 10,470 Km 2 to 15,470 Km 2 an increase of approximately 30%. The greatest increase was observed in the moderately suitable class with a slight decrease in the highly suitable class. Table 2 lists the classified suitable areas in all categories and across all scenarios. Table 2 Outcomes of the different selection in 3 aquaculture categories scenarios Highly suitable (Km 2 ) Moderately suitable (Km2) Barely Suitable (Km2) Total suitable (Km2) Inland aquaculture Equal Weights Scenario Inland aquaculture Water Conservation Scenario Sea cage aquaculture Equal Weights Sea cage aquaculture Adjusted Scenario Intertidal aquaculture Equal Weights Scenario Intertidal aquaculture Adjusted Scenario 5.93 730.82 8572.33 9,309.08 1.18 1014.91 12288.39 13,304.48 3606 18220 22764 44,590.00 23855 17192 3568 44,615.00 6171 3140 1159 10,470.00 5784 9338 348 15,470.00 Page 8

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CONCLUSION & RECOMMENDATION It is recommended to use the outcome of the adjusted scenarios for all aquaculture categories over those of the equal weights scenarios. Equal weight scenarios are provided to serve as bench marks to assess the effect of adjusting the weights towards the preferable conditions of some parameters and how it would affect the suitability classification process when compared to equal weights classification. Terrestrial and Marine Protected Areas are treated differently in the course of this analysis. Terrestrial protected areas were treated as no go zones and were given a status of (Restricted) during the analysis. On the other hand, marine protected areas were not given the Restricted status and were included as available to select from in the suitability analysis. This differentiation was applied upon the request of the aquaculture domain experts in EAD. It is noticed that the inland adjusted scenario has yielded into more total suitable area compared to the equal weights scenario. This could be interpreted as due to the effect of demoting the weight of the layer Depth to Hardpan which affected the selection by the low availability of deep enough soil with suitable impermeable conditions. This was also an instruction from the domain experts in EAD to allow for more suitable sites where this drawback could be overcome by construction mitigations during the establishment of aquaculture farms by isolative lining of the ponds. In the intertidal category it is recognized that some relatively away from shore areas are given high suitability status versus those that are closer to shore line. This is evident in the areas near the urban mass of Abu Dhabi Island and some urban centers along the coast of the western region. This is mainly due to the effect of abundance of discharge outfalls in this vicinity which derived the selection algorithm away from these vicinities and away from the shore. P a g e 15

Annex 1A classes of favorability of different values in data layers in the Sea cages used in suitability analysis. Classes of distance to blooms (Km) Classes of distance to Turtles nests 0.03-149Km Class FROM TO OUT Class FROM TO Favorability 1 0 5 1 1 0.03 2 1 2 5 10 5 2 2 4 4 3 10 20 7 3 4 7 7 4 20 170 10 4 7 149 10 Classes of distance to corals (Km) Classes of bathymetry sea cages Class FROM TO OUT Class FROM TO Favorability 1 0 2 1 1-45 -15 10 2 2 5 5 2-15 -10 8 3 5 15 7 3-10 -5 2 4 15 85 10 4-5 0 1 Classes of Proximity to MPAs Classes of distance to marine mammals (grp of +10) in Km Class FROM TO Favorability Class FROM TO Favorability 1 0 0.5 1 1 0 3 1 2 0.5 5 4 2 3 5 5 3 5 10 7 3 5 40 7 4 10 130 10 4 40 200 10 Classes of Shipping Density Ship/Km.sq Classes of Distance to outfalls (in Km) Class FROM TO Favorability Class FROM TO Favorability 1 0 0 10 1 0 5 1 2 0 2 7 2 5 10 5 3 2 4 5 3 10 50 7 4 4 8 1 4 50 170 10 Classes of Distance to Buhoor (in Km) Class FROM TO Favorability 1 0 2 1 2 2 5 5 3 5 10 7 4 10 140 10 Page 16

Conclusion & Recommendation Annex 1B classes of favorability of different values in data layers in the Intertidal category suitability analysis. Classes of distance to blooms (Km) Classes of distance to Turtles nests 0.03-149Km Class FROM TO OUT Class FROM TO Favorability 1 0 5 1 1 0 2 1 2 5 10 5 2 2 4 4 3 10 20 7 3 4 7 7 4 20 170 10 4 7 149 10 Classes of distance to corals (Km) Classes of Proximity to MPAs Class FROM TO OUT Class FROM TO Favorability 1 0 2 1 1 0 0.5 1 2 2 5 5 2 0.5 5 4 3 3 15 7 3 5 10 7 4 15 185 10 4 10 130 10 Classes of bathymetry inter/sub-tidal (in meters) Classes of distance to marine mammals (grp of +10) in Km Class FROM TO Favorability Class FROM TO Favorability 1-59 -10 1 1 0 3 1 2-10 -5 8 2 3 5 5 3-5 0 10 3 5 40 7 4 40 200 10 Distance to nearest shore (Km) Classes of Distance to outfalls (in Km) Class FROM TO Favorability Class FROM TO Favorability 1 0 2 10 1 0 5 1 2 2 10 7 2 5 10 5 3 10 15 5 3 10 50 7 4 15 20 1 4 50 170 10 Classes of Distance to Buhoor (in Km) Class FROM TO Favorability 1 0 2 1 2 2 5 5 3 5 10 7 4 10 140 10 Page 17

COPYRIGHT All rights reserved. No part of this report may be Reproduced in any material from (including photocopying or storing in any medium by electronic means) without The written permission of the copyright holds. Application for the copyright holders written permission to Reproduce any part of this publication should be addressed to the Environment Agency Abu Dhabi, in accordance with the international copyright Act 1956 and the UAE Federal Law No. (7) Of 2002, concerning copyrights and Neighboring rights, and person acting in contravention of this will be liable to criminal prosecution and civil claims for damages. Page 18