Implementing fuzzy decision making technique in analyzing the Nile Delta resilience to climate change

Alexandria Engineering Journal (2015) xxx, xxx–xxx

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Alexandria University

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ORIGINAL ARTICLE

Implementing fuzzy decision making technique in analyzing the Nile Delta resilience to climate change Ayman F. Batisha Environment and Climate Research Institute, National Water Research Center, Cairo, Egypt Received 12 November 2013; revised 16 April 2015; accepted 25 May 2015

KEYWORDS Climate change; Nile Delta resilience; Fuzzy decision making; Sea level rise; Egypt

Abstract In terms of the importance of Egypt’s natural resources, the prominence of minimizing the risks and the significance of taking an action to adapt to climate change, a multi-criterion analysis (i.e. in ranking the effectiveness of adaptation strategy) was proposed and implemented. The strategy is fuzzy decision making technique (FDMT). Primarily, the literature was reviewed. A study area was chosen. The impact of sea level rise was investigated. The vulnerability and adaptation of the study area was examined. The vulnerability index of the Nile Delta was investigated. The vulnerability indicators of the study area were examined. The available techniques were investigated and the FDMT was chosen to be incorporated to the study area. The FDMT was studied and applied to the Nile Delta. It was found that this technique is suitable in evaluating situations that deal with ambiguity and vagueness, involve subjectivity, and imprecise information. It was thus concluded that fuzzy decision making technique enables maximum benefit from practical knowhow as it takes into account several variables and it could perform ‘‘weighted merging’’ to influencing variables. ª 2015 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction In Egypt, the coastal zone of the Nile Delta is subjected to the impact of climate change (i.e. sea level rise). It is a vulnerable area, especially the low land areas in Alexandria, Beheira, Port-Said and Damietta Governorates. For example, in Alexandria, if the sea level rises between 0.5 m and 1.0 m, over this century, and if no action was taken, an area of about 30% of the city will be lost due to inundation [19]. Due to the low Peer review under responsibility of Faculty of Engineering, Alexandria University.

elevation in the Nile Delta region in Egypt, it is considered to be one of the top five countries expected to be mostly impacted by sea level rise [13,14] and [21]. Consequently, adaptation to climate change in Egypt is a major issue from the perspectives of water resources development, food production, and rural population stabilization. Therefore; Egypt should identify the most endangered regions and propose a measure to protect them. Figs. 1 and 2 show the climate system and the global temperature record. Traditionally, the adaptation measures that were identified to deal with the impact of climate change on coastal zone areas included beach nourishment, construction of groins

http://dx.doi.org/10.1016/j.aej.2015.05.019 1110-0168 ª 2015 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Please cite this article in press as: A.F. Batisha, Implementing fuzzy decision making technique in analyzing the Nile Delta resilience to climate change, Alexandria Eng. J. (2015), http://dx.doi.org/10.1016/j.aej.2015.05.019

2 and breakwaters, tightening legal regulations, integrated coastal zone management and introducing changes in land use. These traditional measures are counted to be obsolete. For that reason, a multi-criterion analysis, in ranking the effectiveness of the adaptation strategy, was proposed and implemented. This strategy is the fuzzy decision making. It was found that such a model is suitable in evaluating situations that deal with imprecise information. Using fuzzy decision making technique enables maximum benefit as it takes into account several variables. Primarily, the literature in the field of climate change and decision making was revised. A study area was chosen to be investigated. The decision-making approach was studied. The set of alternatives was steadfast and evaluated. A comparison between the alternatives was established. The investigation phases are displayed in the present paper as follows:  Reviewing the literature in the fields of climate change adaptation techniques and sea level rise.  Choosing a study area (Nile Delta).  Investigating the impact of sea level rise on the study area.  Examining the vulnerability and adaptation of the study area.  Investigating the vulnerability index in the study area.  Examining the vulnerability indicators in the study area.  Investigating the available techniques and choosing the Fuzzy Decision Making Technique (FDMT) to be implemented in the Nile Delta.  Studying the FDMT and applying it to the study area.

1.1. The climate system and global climate change The elements of the global climate system include the atmosphere, the hydrosphere, the cryosphere (ice and snow), the pedosphere (soil), the lithosphere (rocks), and the biosphere (animals and plants) (Fig. 1a) [7]. The climate system components interact at many spatial and temporal scales [35]. All of these elements together compose the Earth’s climate system. Influenced by many factors, including solar radiation, wind, and ocean currents, Earth’s climate system is a very complex framework. The climate system, its sub-systems and relevant processes and interactions is shown in (Fig. 1b) [45]. Fig. 2 shows the global temperature record. Based on Hansen et al. [31,33,32] and Smith et al. [62], GISS (2015) has updated Surface Temperature Analysis. NASA (2015) ‘‘represented by GISS’’ plot monthly mean global surface temperature anomaly, with the base period 1951–1980, as shown in Fig. 2.1. The Global Annual Mean Surface Air Temperature Change is plotted from 1880 to present. The black line is the annual mean and the red line is the five-year mean. The green bars show uncertainty estimates. Despite different approaches, baseline period and their own methods to estimate global temperatures, NASA, NOAA, Japan Meteorological Agency and the Met Office Hadley Centre in the United Kingdom all come up with very similar records. Based on NASA Earth Observatory [47], Fig. 2.2 shows yearly temperature anomalies from 1880 to 2014 as recorded by those four institutions. Though there are minor

A.F. Batisha variations, all show rapid warming in the past few decades, and all show the last decade as the warmest. 2. Literature review Literature, in the field of climate change and the vulnerability of low lands was reviewed. Many researchers, investigators and organizations dealt with these subjects. The reviewed literature covered the following aspects:  climate change adaptation techniques  sea level rise

2.1. Climate change adaptation techniques Many researches, reports and text books about the climate change and the adaptation techniques were issued by many researchers and organizations. Some of them are displayed here, as follows:  The UN Framework Convention on Climate Change (UNFCCC), [65] released Compendium of Methods and Tools to Evaluate Impacts of, and Vulnerability and Adaptation to, Climate Change.  IPCC [35] defined ‘‘Adaptation’’ as initiatives and measures to reduce the vulnerability of natural and human systems against actual or expected climate change effects.  ICLEI [34], Shaw et al. [55] and USAID [68] prepared practical perspective guides for climate change. These guides are comprehensive to adaptation planning, including awareness of the complexity of vulnerability and its reduction, and understanding what is necessary for adaptation planning.  Rivero Vega [54] defined adaptation as impact assessment as ‘‘The practice of identifying the effects of climate change at a given location’’. Impact assessments require a reference baseline and a projected climate change scenario.  Olhoff and Schaer [49] prepared a stocktaking report for UNDP. It targets development organizations, practitioners and development agencies.  Barnett and O’Neill [3] described ‘‘Maladaptation’’ as any change in natural or human systems that inadvertently increase vulnerability to climatic stimuli, an adaptation that increases vulnerability to climate change instead of reducing it. Maladaptation can take place when the development context is not considered explicitly in designing and implementing adaptation measures. Maladaptation is also described as actions that have positive impacts on a target group or generation but, as a consequence, have adverse impacts on another group or generation. On the other hand, a collection of methods and tools are available (i.e. updated Compendium on Methods and Tools to Evaluate Impacts of climate change, and Vulnerability and Adaptation to Climate Change). Some of them are listed here, as follows:  UNFCCC [66] serves as reference documents on adaptation methods and tools. The UNFCCC provides observations on the use of methods and tools for adaptation in a background document prepared for an expert meeting.

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Implementing fuzzy decision making technique in analyzing the Nile Delta resilience

Figure 1a

Figure 1b

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The global climate system.

The global climate subsystems and relevant interactions.

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 Figure 2.1 Change.

Global Annual Mean Surface Air Temperature

 UNFCCC [67] reflects not only on the aspects of methods and tools dealt with by the UNFCCC but also emphasizes key areas that need to be improved for adaptation planning, including the importance of an understanding of model limitations and increasing local level data collection.



 Also, in the academic literature, the shift in emphasis in practitioner-focused documents from impacts to vulnerability is reflected (i.e. a recent study of extreme sea-level rise and public perception). Among these documents were the following:  Luers et al. [43] proposed an approach for quantifying vulnerability. Qualitative descriptions of vulnerability are not always useful to plug into tools that require data to be quantified.  Luers [42] suggested an initial analytical framework for doing this.  Fu¨ssel and Klein [25] pointed to an increasing degree of stakeholder participation in vulnerability assessments.  Polsky et al. [52] provided an overview of different approaches and attempt to draw out commonalities between them in an effort to highlight the usefulness of a universal approach.  Eakin and Bojo´rquez-Tapia [18] offered an approach for weighting disparate factors of vulnerability. This provided a more sophisticated assessment of vulnerability, because it draws out the most important drivers, recognizing that

Figure 2.2



these are different in different places. The authors based their approach on multi-criteria decision analysis and fuzzy logic. Mukheibir and Ziervogel [46] reported an experience of developing a municipal adaptation plan for Cape Town in South Africa led to the conclusion that making plans should be applied as a tool to educate key actors (This recognizes the need for raising the awareness and sensitization about climate change before any planning activities takes place). The important principle of ownership as a requirement for the planning process was reflected. Toth and Hizsnyiks [63] used a participatory assessment approach, which reflects recognition of the importance of social aspects for determining risk. Van Aalst et al. [70] described the application of community risk assessment, noting that in order to keep it participatory, it needs to be simple enough for a wide application. Learning process provided by adaptation planning has been highlighted as an important outcome. De Chazal et al. [15] described a method for taking multiple stakeholders’ perspectives into account for vulnerability assessment and difficulty of dealing with conflicting values. Hahn et al. [30] provided another approach to measure vulnerability at a household level, describing the Livelihood Vulnerability Index (LVI), which they applied in Mozambique. Deressa et al. [17] provided a useful study discussing why farmers make certain choices about adaptation options. This provided further insight into what motivates people to initiate an adaptation process.

Based on the above publications, it can be seen that most of the tools and methods cannot be easily compared. They target different users (e.g. donors versus city governments), different levels of governance (e.g. national versus local level), different institutions (NGOs versus community leaders) and are based on different conceptual approaches to adaptation.  Fu¨ssel [26] summarized thinking about adaptation planning, he defined it as being making recommendations about who should do what, more, less, or differently, and with what resources.  Olhoff and Schaer [49], Klein et al. [38] and Kropp and Scholze [39] focused on mainstreaming tools specifically targeted at donors.

Yearly temperature anomalies from 1880 to 2014.

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Implementing fuzzy decision making technique in analyzing the Nile Delta resilience  Tyler and Fajber [64] discussed how land and water management in Asia can inform adaptation to climate change. The World Resources Institute, in National Adaptive Capacity Framework [74] suggests an approach that starts by assessing the functions of the ‘adaptation system’, which includes assessment of vulnerability, impacts, adaptation practices and climate sensitivity of development activities.  Olhoff and Schaer [49] proposed the impact approach which is based on understanding how climate change will affect a system or group, while vulnerability approach deals with development deficit that is causing people to be vulnerable to climate change is the focus. This diversity makes it difficult to have an overview of the methods and the available tools.

2.2. Sea level rise Sea level rise was revised in the literature. Fig. 3 shows the recent sea level rise trends. Current sea level rise potentially impacts human populations (e.g., those living in coastal regions and on islands) and wider natural environment (e.g., marine ecosystems). Global average sea level rose at an average rate of around 1.8 mm per year over 1961–2003 and at an average rate of about 3.1 mm per year from 1993 to 2003. It is unclear whether or not the increased rate observed between 1993 and 2003 reflects an increase in the underlying long-term trend. Many organizations studied the sea level rise. They also investigated its impacts on the land system. The following are some of the publications that dealt with sea level rise:  IPCC’s Fourth Assessment Report (2007) mentioned that the climate system is a complex interplay between atmosphere, oceans, ice sheets, and land systems. The Earth’s climate system has demonstrably changed on both global and regional scales since the pre-industrial era, with some of these changes attributable to human activities. The impact of different SLR scenarios on the Nile Delta was assessed by producing maps for the inundated areas due

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to a 0.5, 1, 1.5, 2.0 and 2.5 m SLR [29]. An inundation model was developed using GIS that accounts for connectivity with the sea or lakes. The main input to the inundation model was a Digital Elevation Model ‘‘DEM’’. In their study, topographic maps of scale 1:25,000 were digitized together with the surveying of key features using GPS leveling to produce the data required for the DEM. The study showed that initially the water will mainly enter the low areas from the coastal lakes. NCAR addresses the most-pressing problems in Sun-Earth system science. NCAR’s research activities include the study of the atmosphere, the Earth system, the Sun and solar-terrestrial physics, and the coupling of the atmosphere with oceans, biosphere, cryosphere and human activities. NCAR’s strategic plan focuses on two grand challenges. The first is ‘‘Improved understanding and prediction of atmospheric, chemical and space weather hazards and their impacts on ecosystems, people and society’’ and the second is ‘‘Improved understanding, prediction and projection of the consequences of natural and anthropogenic climate variability and change at regional and global scales’’ [48]. Basic information and access details for temperature and precipitation datasets for Africa are provided by [44]. Sea-level rise is a response to increasing concentrations of greenhouse gases in the atmosphere and the consequent changes in the global climate. Sea-level rise contributes to coastal erosion and inundation of low-lying coastal regions, particularly during extreme sea level events. It also leads to saltwater intrusion into aquifers, deltas and estuaries. Regions at most risk include heavily populated deltaic regions, small islands, and sandy coasts backed by major coastal developments [11]. CMAR attempts to bring together information on sea level rise and its causes. CMAR estimates global sea level as shown in Fig. 3. Since 1993, changes in global averaged sea level are estimated from satellite altimeter data (red) and since 1880 by combining in situ sea level data from coastal tide gauges and the spatial patterns of variability determined from satellite altimeter data (blue). Error bars have not been shown for the altimeter data (red curve) for clarity, but are about ±5 mm. 3. Choosing Nile Delta as a study area

Figure 3

Sea Level Rise Trends.

Studies that aim to understand the impacts and benefits that result from the present-day variability in climate can be important in helping to reduce uncertainty surrounding the consequences of future climate change [72]. For example, estimates of changes to Nile flow volumes relative to today range from +60% to 50% [9,5]. [13] and El-Raey [20] provide estimates on the decline of national income and other physical and socio-economic impacts for a range of SLR scenarios. The Nile Delta was chosen to be the study area. This is attributed to the fact that it is vulnerable to the impacts of climate change and sea level rise. Due to the low elevation in the Nile delta region in Egypt, it is considered one of the top five countries expected to be mostly impacted with sea level rise resulting from global warming. With just a one-meter rise in the Mediterranean Sea, the Nile Delta stands to suffer tremendously. To predict what is contributing to sea-level rise, to simulate how ice sheets will respond to a warming climate, and to understand the processes that are causing rapid changes on

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earth, research data are essential. Collecting data may be achieved with the help of satellites, aircraft systems, sophisticated sensors, field programs, maps and research projects. Fig. 4 shows potential impact of sea level rise on the Nile Delta modified from map entitled ‘‘Inundation from Sea Level Rise’’ with respect to Mediterranean which was designed by CReSIS [10]. 4. Investigating the impact of sea level rise on the study area The impact of sea level rise on the Nile Delta was investigated. It was found that:  The rising seas would destroy parts of the protective offshore sand belt, which has already been weakened by the reduced sediment flows resulting from the construction of the Aswan High Dam in 1970.  Without the sand belt, water quality in coastal freshwater lagoons will be altered (threatening one-third of Egypt’s fisheries), groundwater will be salinized, and recreational tourism and beach facilities will be inundated.  It is predicted that 6.1 million people will be displaced and 4500 square kilometers of cropland will be lost.  The estimated impact on Gross Domestic Product (GDP) exceeds 6% for a 1 m rise and 16% for 5 m [13].  Land subsidence means that the sea surface is rising relative to the land at a rate currently at about 2 mm yr1 (0.08 m by 2050 [50]. Remote sensing and GIS analysis depict areas of the Nile Delta at risk of 1 m SLR and the extreme case of 5 m SLR. Based on that investigation, Fig. 5 is modified from [27]. It presents the impact of sea level rise on the Nile Delta according to 5 scenarios of 1 m to 5 m sea level rise. Based on this figure, it is estimated that a sea level rise of only 1 m would flood much

1 Meter Inundation

of the Nile Delta, inundating about one third (34%) of its land, and about 8.5% of the nation’s population (7 million people) will be displaced. In the extreme case of 5 m SLR, more than half (58%) of the Nile Delta will be facing destructive impacts, and forcing about 14% of the country’s population (11.5 million people) into more concentrated areas. 5. Examining the vulnerability and adaptation of study area The vulnerability and adaptation of the study area was examined. Based on this examination, it was clear that:  The developing adaptation strategies are vital to Egypt in order to deal with the impending climate change.  In the coastal city of Alexandria, Egypt, authorities are spending US$300 million to construct concrete sea walls to protect beaches from rising seas.

6. Investigating the vulnerability index in the study area The vulnerability index was investigated in the study area in order to have an insight into its order of magnitude. Based on the investigation, it was found that:  The Egyptian ministry of environmental affairs is preparing a ‘‘national strategy study’’ on adaptation, including a vulnerability index to pinpoint the most endangered regions. A number between 0 and 10 represents the intensity of resistance at a site where 10 is excellent.  The vulnerability index is a composite of indices, also referred to as integrated indices, which are quantitative indicators similar to scales, which, when entered into a formula, deliver a single numerical result which can be used for

2 Meter Inundation

4 Meter Inundation

5 Meter Inundation

3 Meter Inundation

6 Meter Inundation

Inundated Area Figure 4

Potential impact of sea level rise on the Nile Delta.

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Implementing fuzzy decision making technique in analyzing the Nile Delta resilience

Figure 5

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Impact of sea level rise on the Nile Delta.

triage (prioritization) and policy analysis. Through their use, ‘‘diverse issues could be combined into a standardized framework . . . making comparisons possible’’. Also, based on the investigation, it was found that many researchers discussed the vulnerability index. For example:  Bindoff et al. [6] mentioned that a variable from physical science can be combined with social, medical and even psychological variables to evaluate potential complications in disaster planning contexts.  Fischlin [23] stated that the development of vulnerability indexes as a policy planning tool occurred at the instance of the United Nations Environmental Program. Also, one of the participants in the early task forces conducted secondary research documenting the evolution of the analytic tool through various stages. Based on the present investigation, it was clear that most of the areas in the Nile Delta have a vulnerability index that indicates a poor intensity of resistance. 7. Examining the vulnerability indicators in the study area Vulnerability indicators were investigated in the study area. It was found that all indicators are very poor. This indicates that the study area is very vulnerable. Indicators are a way of quantifying the level of vulnerability. An indicator is a single measure of a characteristic where an index is a composite measure of several indicators or indices. Many researchers discussed the vulnerability index. For example:  Barnett et al. [4] mentioned that indicators need to reflect an explicit conceptual framework of vulnerability. Many

scientists are very cautious about the use of indicators. Indicators and indexes can be useful to guide decisionmaking and prioritize intervention, as they allow characteristics to be compared.  Eriksen and Kelly [22], Brooks et al. [8], Lioubimtseva and Henebry [41] and Swanson et al. [60] stated that the use of indicators has been one of the most widely proposed approaches, which has been primarily applied to adaptive capacity (as well as to vulnerability).  Luers et al. [43] and Cutter et al. [12] stated that the development of indicators can be seen as a way to identify proxies for adaptation. Indexes of vulnerability should be treated with caution, precisely because of complex nature of vulnerability that results in many factors being at play and the difficulty in capturing diversity and sensitivity of vulnerability.  Tearfund [61] defined both Vulnerability and Indicator. Vulnerability is the conditions determined by physical, social, economic, political and environmental factors or processes, which increase the susceptibility of a community to the impact of hazards. Indicator is an indication of progress that has been reached in any given topic. Within disaster management and disaster risk reduction, there may be a wide range of social, physical and economic indicators identifying stages in development which will enable disaster managers to recognize where they now stand, defining what stage they have reached or where they need to go next.

8. Investigating the available techniques and choosing FDMT Based on the revised literature, a compendium of approaches and techniques were available. These approaches and techniques were investigated to choose an appropriate technique that could be applied to the study area. From these techniques,

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8 the Fuzzy Decision Making Technique (FDMT) was chosen to be implemented in the study area. The coming section is devoted to display this technique. Fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms [71]. What fuzzy sets are, why they work, when they should be used (and when they should not), and how to design systems using them are explained [51]. The principles of fuzzy logic (FL), Multiple attribute decision making, fuzzy sets, fuzzy membership functions and fuzzy multiple attribute decision making are introduced in [2]. Formal concept analysis and its capabilities when generalized by using fuzzy logic are introduced [53]. The concepts of fuzziness on decision making and problem solving with uncertainty, and knowledge on fuzzy technique to solve decision problems, particularly, multiple objectives, and multiple attribute decision problems are introduced in [1]. He also develops a flexible model to deal with vagueness, lack of data, or subjectivity of opinion that can be applied in many areas of modern applied science for certain type of decision problems with uncertainty to find an acceptable solution. 9. Studying the FDMT and applying it to the Nile Delta The Fuzzy Decision Making Technique was studied in order to be applied to the study area. In this section: the Fuzzy Logic Approach (FLA) is introduced; the membership function is presented and the Fuzzy rules are displayed, in terms of the aspects incorporated in the Nile Delta problem. Interdisciplinary assessment of impacts of sea level rise and climate change on the lower Nile Delta is presented [58], and they highlights that Sea level rise causes complex, interrelated issues in the region. 9.1. Fuzzy logic approach (FLA) in terms of the Nile Delta Fuzzy logic provides a method to formalize reasoning when dealing with vague terms such as the aspects contributing in the Nile Delta problem. Traditional computing requires finite precision which is not always possible in real world scenarios. Not every decision is either true or false, or as with Boolean logic either 0 or 1. Fuzzy logic allows for membership functions, or degrees of truthfulness and falsehoods. Or as with Boolean logic, not only 0 and 1 but all the numbers that fall in between. The purpose of fuzzy rule bases is to formalize and implement a human being’s method of reasoning. The tool most commonly used in fuzzy logic applications is the fuzzy rule base. A fuzzy rule base is made of rules which are normally used in parallel but can also be concatenated in some applications. 9.2. Membership function in terms of the Nile Delta A fuzzy set is defined by its ‘‘membership function’’ which corresponds to the notion of a ‘‘characteristic function’’ in classical logic. Let us assume that it is required to define the set of people of ‘‘medium height’’. In classical logic, we would agree for example that people of medium height are those between 1.60 m and 1.80 m tall. The characteristic function of the set

A.F. Batisha gives ‘‘0’’ for heights outside the range [1.60 m; 1.80 m] and ‘‘1’’ for heights in that range. The fuzzy set of people of ‘‘medium height’’ will be defined by a ‘‘membership function’’ which differs from a characteristic function in that it can assume any value in the range [0;1]. Each possible height will be assigned a ‘‘degree of membership’’ to the fuzzy set of ‘‘medium heights’’ between 0 and 1. Fig. 6 presents Membership Function for sea level Rise. A fuzzy set is defined by a membership function, mapping objects in a universe U to a membership value: S : U ! ½0; 1 9.3. Fuzzy rules in terms of the Nile Delta Fuzzy rules were put forward to the study area. It should be mentioned that a rule is of the type: IF ‘‘predicate’’ THEN ‘‘conclusion’’. For example: IF ‘‘high temperature and high pressure’’ THEN ‘‘strong ventilation and wide open valve’’. It is thus needed to capture the essentials of the problem in the Nile Delta, leaving aside all the factors that could be arbitrary. If a list was made of what really matters in the Nile Delta problem, the following rule descriptions might be ended up with the following.

Intensity of Resistance Problem Rules –– adaptation Factor If adaptation is bad, then Resistance is defective If adaptation is average, then Resistance is standard If adaptation is good, then Resistance is high-quality

The order in which the rules are presented here is arbitrary. It does not matter which rules come first. If it is desired to include the sea level rise effect on the intensity of resistance, the following three rules should be added.

Intensity of Resistance Problem Rules –– Sea Level Rise Factor If Sea Level Rise is low, then Resistance is high-quality If Sea Level Rise is average, then Resistance is standard If Sea Level Rise is high, then Resistance is defective

For the study area, two different lists of rules could be combined into one tight list of three rules like this list.

Intensity of Resistance Problem Rules –– adaptation Factor If adaptation is bad and Sea Level Rise is high, then Resistance is defective If adaptation is average and Sea Level Rise is average, then Resistance is standard If adaptation is good and Sea Level Rise is low, then Resistance is high-quality

These three rules are the core of the solution to the problem area. Fig. 7 shows Fuzzy rules for the study area.

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Implementing fuzzy decision making technique in analyzing the Nile Delta resilience

Figure 6

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Membership Function of sea level rise.

After the rules for a fuzzy logic system were defined, a mathematical meaning to the linguistic variables should be given. It is to be noted that, following the above sequence, a complete fuzzy inference system (FIS) could be established. The methodology of fuzzy logic must also consider:  How the rules all are combined?  How the standard intensity of resistance is defined, mathematically? The view of surface allows for the examination of the output surface of a FIS stored in a file, for any inputs. Because it does not alter the fuzzy system or its associated FIS structure

Figure 7

in any way, the two input variables Sea Level Rise and adaptation are selected and were assigned to the two input axes (Sea Level Rise X and adaptation Y), as well the output variable that assigns to the output (intensity of resistance or Z) axis. Fig. 8 shows the reliability surface.

9.4. Discussion Climate change impact, adaptation, and vulnerability assessments offer a specific platform for exploring long-term future scenarios in which climate change is considered along with other projected changes of relevance to long-term planning [37]. Climate change poses a moderate threat to current

Fuzzy rules.

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Figure 8

The reliability surface.

sustainable development and a severe threat to future sustainable development [16]. Government planning and provision can facilitate shifts to less energy and GHG-intensive infrastructure and lifestyles [56]. Coastal systems and low-lying areas will increasingly experience adverse impacts such as submergence, coastal flooding, and coastal erosion due to relative sea level rise [73]. Sea level rise is an important issue [36]. As a result of current uncertainties in climate projections and subsequent impact models, an incomplete understanding of the impact of a climate change signal is being imposed on water-related decision-making under conditions of climate change [36]. Climate change is impacting the Mediterranean region in myriad and distinct ways including increased frequency of flash flood events, droughts or periods of water shortages and rising temperatures [28]. The impact of SLR on water, economic and food security is directly modeled. Detailed descriptions of the model development, structure, data and assumptions, results and analysis can be found in Susˇ nik et al. [59]. Launched by ICSU in 1986, IGBP is a research program that studies the phenomenon of global change. IGBP aims to describe how the physical, chemical and biological processes regulate the Earth system. IGBP research focuses on representing the Earth system – land, atmosphere, ocean and where they meet (land–atmosphere, land–ocean. atmosphere–ocean). IGBP published a landmark synthesis, Global Change and the Earth System [57]. The synthesis stated that humanity was now the main driver of change at the planetary scale. ‘‘Global change’’ is focusing on planetary-scale changes in the Earth system. From the perspective of ‘‘Global change’’, Nile Delta may be considered a suitable specified area as a

study area. The U.S. Global Change Research Program (USGCRP) defines ‘‘Global change’’ as Changes in the global environment that may alter the capacity of the Earth to sustain life. Global change encompasses climate change, but it also includes other critical drivers of environmental change that may interact with climate change, such as land use change, the alteration of the water cycle, changes in biogeochemical cycles, and biodiversity loss [69]. The integrated scientific research in the field of ‘‘Global change’’ may assist both the Nation and the world to understand, assess, predict, and respond to the processes of global change. The results of such type of integrated research may contribute to enabling modifications in natural or human systems to a changing environment in a way that exploits beneficial opportunities or mitigates negative effects. Geoengineering, also, may be used as a scientific research discipline as a means to reduce future climate change. The results of this study may be used as an indicator to allow both scientists and decision makers to observe and understand key factors that influence the Nile Delta environment to identify effects on to reduce the amount and/or speed of future climate change for the benefits of both ecosystems and society. Based on the pros and cons of a given set of scenarios and/or possibilities, the results of such a study focus on the likelihood of specific sets of global change/change events occurring to manage the effects of the change to increase positive impacts and decrease negative impacts. So, the results are concerned with the degree to which a Nile Delta system is susceptible to or unable to cope with the effects of climate change. Sustainable development SD, a central framing issue in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change, is intimately connected to climate change [24]. Decision makers in developing countries

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Implementing fuzzy decision making technique in analyzing the Nile Delta resilience often face a particular set of challenges associated with implementing mitigation policies under risk and uncertainty [40].

11

Appendix A List of abbreviations and acronyms.

10. Conclusions A multi-criterion automated assessment method was proposed to be implemented in the study area (Nile Delta). Based on the examinations and investigations, it was concluded that:  Fuzzy logic might be implemented in the study area.  The proposed method is intended for the assessment of the intensity of resistance (reliability) and is intended for use as a supplement to on-site inspection.  The probability combination method in conjunction with the proposed multi-criterion approach provides a logical way of resolving conflicting probability statements from different rules of adaptation strategies.  The model is exemplified by simple criteria comprising sea level rise and adaptation.  Modification of the model to cover other criteria such as desertification, water resources availability and cost could be easily incorporated.  The model could be used by decision-makers to choose the most appropriate reliability strategy.  The model emphasized the multi-criterion aspect of climate change evaluation, the qualitative, subjective, and noninteractive nature of these criteria, and their aggregation in the evaluation process. It should be emphasized that non-interactivity is one of the important features that underline the fuzzy aggregation procedure. Non-interactivity simply means the ratings assigned to major criteria (i.e. sea level rise and adaptation) that do not compensate each other. Nile Delta region is in the eye of the hurricane of change. Nile Delta faces massive challenges such as a climate changing in alarming ways, declining natural resources, growing unmet need, and economic globalization. The low-lying coastal areas and deltas zones are inherently vulnerable to both Climate and Global changes. Large concentrations of people and capital stocks are at risk in hazard-prone Nile Delta settings. Climate change makes the Nile Delta more vulnerable. Yet it can also spur efforts to make Egyptian coastal cities and fertile lands even more attractive and resilient. 11. Recommendations Based on the above, it was recommended to investigate thoroughly:  The proposed procedure using fuzzy sets as it is just an addition to the range of multi-criterion decision methodologies.  The particular characteristic of the present procedure as it emphasizes on the human perception nature, the qualitative or subjective criteria used in reliability, and the theoretical basis for aggregation of these criteria.

No. 1 2 3 4

Term AR5 CReSIS CMAR CSIRO

5 6 7 8 9 10 11 12 13 14 15

DEM EEAA FDMT FIS FL FLA FLS GDP GISS GPS ICLEI

16 17 18 19 20

ICSU ICZM IGBP IPCC NASA

21 22 23

NCAR NGOs NOAA

24 25 26 27

SD SLR UKCIP UNFCCC

28

USAID

29 30

USGCRP WRI

Definition IPCC Fifth Assessment Report Center for Remote Sensing of Ice Sheets CSIRO Marine and Atmospheric Research Commonwealth Scientific and Industrial Research Organisation Digital Elevation Model Egyptian Environmental Affairs Agency Fuzzy Decision Making Technique Fuzzy Inference System Fuzzy logic Fuzzy Logic Approach Fuzzy logic systems Gross Domestic Product Goddard Institute for Space Studies Global Positioning System International Council for Local Environmental Initiatives, Center for Science in the Earth System, University of Washington, King County, US International Council for Science Integrated Coastal Zone Management International Geosphere-Biosphere Programme Intergovernmental Panel on Climate Change National Aeronautics and Space Administration National Center for Atmospheric Research Non-governmental organizations National Oceanic and Atmospheric Administration Sustainable Development Sea Level Rise United Kingdom Climate Impacts Programme United Nations Framework Convention on Climate Change United States Agency for International Development U.S. Global Change Research Program The World Resources Institute

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