THE WATER STRATEGY MAN DECISION SUPPORT SYSTEM A. Peruffo ∗ E. Todini ∗∗
Protezione e GEstione Ambientale, via Don Bedetti 20 Bologna, Italy ∗∗ Department of Earth and Geo-Environmental Sciences, University of Bologna, P.zza di Porta S. Donato 1, Italy ∗
Abstract: The WaterStrategyMan project aims at supporting Decision Makers and Water Managers in multi-objective planning of water resource systems based on simulation of alternative scenarios of water availability and water demand and the application of problem-specific policy measures. Water strategies and management options, including structural and non-structural interventions, for Supply Enhancement, Demand Management and Institutional Policies are evaluated on the basis of demand satisfaction, environmental and economical indicators. A prototype decision support system, which incorporates a geographic information system, a data base and a complex set of models and interactive tools has been developed. The DSS which is designed to simulate the consequences of the different management options takes into account Following the Water Framework Directive, a full Water and Environmental Cost approach has been included in the economic analysis. Keywords: Decision Support System, Water Resource, Scenarios, Strategic Option, Evaluation
1. INTRODUCTION
The WaterStrategyMan Decision Support System (WSM DSS) has been developed within the WaterStrategyMan Project (2002 - 2005), funded by the European Commission under the Fifth Framework Programme. It is a Gis-based package that aims at supporting Decision Makers and Water Management Authorities at planning water resources and solving water conflicts between competing users, especially in water deficient arid and semi-arid regions. This paper introduces the architecture and components of the DSS as well as the methodology used. An extensive bibliographic search allowed to retrieve several decision support systems devel-
oped by different organisations in the last decade. The following DSSs were found: - MIKE BASIN, by the Danish Hydraulic Institute (DHI); - BASINS, by the U.S.- Environmental Protection Agency - DSS for Water Resources Planning Based on Environmental Balance, developed within a project funded by the Italian Cooperation with Egypt - A Spatial Decision Support System for The Evaluation of Water Demand And Supply Management Schemes, by the Technical University of Athens - IQQM, by the New South Wales Department of Land and Water Conservation, with col-
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laborative assistance from the Queensland Department of Natural Resources (QDNR). ENSIS, by the Norwegian Institute for Water Research (NIWA) and the the Norwegian Institute for Air Research (NILU) REALM, by the Victoria University Of Technology and the Department of Natural Resources and Environment, in The State of Victoria, Australia MULINO, main objective of the related European Mulino Project RIBASIM, by Delft Hydraulics WEAP, by the Stockholm Environment Institute’s Boston Center at the Tellus Institute WATERWARE, main objective of the European research program Eureka-EU487 AQUATOOL, by the Universidad Politecnica de Valencia, Spain IRAS, by the Civil and Environmental Engineering Department of Cornell University and the Resources Planning Associates Inc of Ithaca, New York State
All the mentioned DSSs have been analysed in detail as possible candidate tools for sustainable water resources planning, within the frame of the Water Framework Directive. A critical review report (ProGeA, 2003a) was issued, which showed the inadequacy of all the above mentioned packages for a comprehensive and sustainable water resources planning. This critical review allowed to set the basis for the development of a new DSS, which would incorporate all the required components. The structure and the functionalities of the new package, extensively described in ProGeA, (ProGeA, 2003b) have then been designed to reflect some conceptual steps to go through in order to make analyses of present and future water resources for planning and management. These steps are: S1) assessment of the present status of the resource system, S2) definition of future water demand and water availability scenarios, based upon analyses of the past historic events, S3) simulation of the system under the assumed normal conditions, S4) investigation of the simulation results and identification of unsatisfying forecast circumstances, S5) construction of alternative sets of strategic measures as responses to the negative impacts, and their time of implementation in the simulated planning horizon, S6) simulation of the system under the same normal scenarios modified by the strategic options, S7) evaluation of the alternative solutions with the assessment of the best choice.
Along the whole procedure, the assessment of current and future state and impacts implies the use of appropriate indicators, which objective is to provide the Decision Maker with a picture of the existing water system, resources, consumers and treatment facilities. These indicators not only describe the water quantity aspects but also the water quality patterns, the social constraints and agreements in the use of water as well as the sustainable development and impacts of policy measures on the environment. Economic issues are accounted for as well, in order to track the estimation of direct costs in the water network and estimate the cost recovery for water services. 2. FRAMEWORK OF THE WSM DSS The WaterStrategyMan approach and its modules have been framed under the Driving Forces - Pressures - State - Impacts - Response (DPSIR) structure of indicators as proposed at European level by the European Environmental Agency (Smeets et al., 1999). Two pre-processors of the WSM DSS, namely the Water Availability and the Water Demand Modules, are used for the analysis of Driving Forces and the definition of the Pressures they exert on the water resource system. The Driving Forces, defined as natural phenomena and anthropogenic activities that are not easily manipulated (Walmsley, 2002), are here represented by climate changes, demographic growth and land use patterns. The Pressures, are identified in water quality of supply sources and pollutant loads generated by human activities. Downstream of the preprocessors, the kernel of the WSM package is the Water Allocation Module that is responsible for simulating the water distribution throughout the water network and for calculating the indicators that assess the State of the system. The postprocessor of the DSS is the Evaluation module, whose main function is to present the Impacts on the system caused by Driving Forces and Pressures under the normal conditions, and to compare the sustainability of the impacts generated under alternative strategic measures, taken as the Responses in the DPSIR approach. 3. SCHEMATIZATION AND MANAGEMENT OF THE WATER NETWORK The generic water resource system is schematized within the WSM DSS by a set of nodes connected by arcs. This network of nodes and links is drawn upon a map of the area the under development. The nodes represent: 1) different kinds of user demanding water, such as settlements, irrigation sites, industries etc, which are grouped under the
name of Demand Nodes, 2) different kinds of water resource, namely storage reservoirs, river reaches, aquifers etc, which constitute the Supply Nodes, and 3) different kinds of water treatment, such as waste water, drinking water and desalination plants, which go under the name of Treatment nodes. The links may represent: 1) open surface channels, used to delivery water for agricultural purposes, 2) pipelines, 3) flows incoming and outgoing the renewable aquifers and 4) all the return flows exiting the demand nodes and going to the treatment plants or to rivers, sea and lakes. The map of the area and the water network visualized in the Map Panel of the DSS interface are not images, but geographic features stored in ESRI shapefiles vector format, and loaded as geographic layers. All nodes or links of the same type are grouped into a shapefile, and these information are all stored into a Geodatabase (ESRI, 2001) directly linked to the graphical user interface. The user is allowed to modify the water network by placing new nodes or links on the map, or by moving or deleting already existing elements. The analysis and visualization of the geographic features is supported by basic GIS functions such as zooming, panning, refreshing maps, viewing full extent, labelling and distance measuring. The different demand or supply nodes are characterized by the appropriate data, some of which being general and descriptive, i.e. name and identifier, while others are used to model the node within the water resource simulation, i.e. water quality parameters and various economical parameters. Demand nodes are characterized in terms of water quality by average concentrations of predefined variables typical of the return flows, different according to the node type, each one representing a different water use. The quality data for supply nodes specify the initial conditions of the system before simulating the water allocation, while the economical data for demand nodes address pricing methods, water selling prices and the demand elasticity of water users. This latter defines the reaction of the users to the change of price, according to the rule that an increase of price corresponds to a decrease of demand. Costs for supply nodes include: depreciation period and construction cost of the infrastructure, which are used to calculate the Annual Equivalent Capital Cost, costs for operation, maintenance and energy consumed per unit water volume abstracted, which form the Running Costs. Demand nodes require specific information concerning the variables that drive their water requirements, based on the type of water use. Demand driving forces for settlements are the residential and seasonal population as well as the per
capita daily consumption rate. For irrigation sites and animal breeding sites, they are respectively the cultivated area and the crop area shares for the former, and the number of animals and consumption rate per head. Units of total production, together with the consumption rate per unit and the share of consumptive demand determine the demands for industry nodes, while the energy requirements of hydroelectricity plants drive their non-consumptive demand. Among the demand nodes, the river minimum flow requirements of river reaches has been also considered under the name of Environmental Demand, which stands for the water volume necessary to preserve both the aquatic life and the geomorphologic and hydraulic characteristics of the rivers. Other demands affecting the river reaches symbolize requirements for navigation and for recreational purposes. Data for these three nodes concern the water volumes that have to be assured on a monthly basis. Supply nodes not only require specific information in terms of operational data, as in the case of artificial reservoirs, described on the basis of capacity, dead volume, release rule, stage area and loss parameters, but also they require descriptive physical data such as distance from sources and catchment area for river reaches. As far as the aquifers are concerned, they are described and modelled in an extremely simplified way, and their data requirement is: capacity, initial storage, number of wells, rate of sustainable production, catchment area and specification of conceptual connections with rivers. All the data charactering the nodes and links are stored in the Geo-database and loaded in dedicated panels of the WSM DSS graphical user interface. From this interface, the values can be entered to define the case study or to update it. The navigation through the list of nodes, in order to access the data panel for the single geographic element or to highlight it on the map, is supported by the Object Manager Panel of the graphical interface: the nodes and links of the water network are listed in a tree shaped view, similar to the Folder Tree View of Windows Explorer, and they are classified by type, according to their water function with respect to the allocation (e.g. demand nodes, supply nodes or treatment nodes) and according to their specific water use or resource type (e.g. industrial, domestic, aquifers, storage reservoirs etc). Categories can be expanded by clicking on the plus sign or collapsed, by clicking on the minus sign, according to the desired level of detail. Each type of node is marked with its own colored symbol, such as circles, squares or rhombi. This symbol characterizes each node on the regional map that displays the water network and the physical features. Each network node/link has a user-defined name, and
its unique identifier (ID) that appears next to the name in brackets. The schematization of the water network within the WSM DSS and the data entry for all the geographic elements contribute to the first step of the water resource analysis procedure: assessment of the present status of the resource system. It is the basis for the development of step two, namely the selection of water scenarios.
4. WATER AVAILABILITY AND WATER DEMAND SCENARIOS Monthly time series of available and demanded water, estimated respectively at each source and demand node in the network, represent the Driving Forces and the Pressures affecting the water system. The time series output of the availability preprocessor of the DSS are the natural recharge for renewable groundwater and surface runoff for reservoirs and river reaches. The results can be obtained in the following two ways: 1) by defining a set of customized years of recharge and runoff to be repeated in time, based upon the real observations at existing monitoring stations, that is the discharge scenario approach, or 2) by estimating runoff and natural recharge from a surface water balance performed on a monthly time step, in the climatic scenario approach. In the first case, twelve monthly values of runoff and recharge must be defined for each reservoir, river reach and renewable groundwater node in the network. These data should represent a Normal (Average) Year, obtained from existing recorded data. Given the normal year, the DSS user can create and customize new years, by editing monthly positive or negative rates with respect to the normal year. Customized years are then combined into the sequence that identify the scenario. The alternative way for defining water availability scenarios is based on a lumped water balance at the watershed scale, performed by the Soil Moisture Balance Module of the ARNO rainfall-runoff model (Todini, 1996). A set of maps are required in this case, among which the definition of the hydro-geological catchments relevant to aquifers and lakes, the Digital Elevation Model (DEM) of the area, the saturated hydraulic conductivity of soils and soil moisture capacity as a function of soil types, land use map, monthly maps of precipitation, reference evapotranspiration and temperature, containing monthly data for the normal year. Given the DEM and the geographical position of the river reaches that have been previously located by the DSS user in the Map panel, the availability
module generates the maps of the corresponding upstream sub basins, through the use of common GIS functions. Once watershed maps are ready for all the water source elements (namely river reach nodes, lakes and aquifers) mean values of climatic and pedologic information required by the water balance routine are calculated for each of them. The water balance runs at a monthly time step over the entire simulation horizon of the DSS. As a consequence it requires, as input data, rainfall, temperature and reference evapotranspiration along the simulation horizon. These inputs can be generated with the functionalities of the water availability module in three different ways: 1) by repeating the average climatic year, or a user-customized Base Year, for the entire duration of the scenario, 2) by defining a total increment over the entire horizon, either annual or monthly, thus determining an yearly or monthly trend, 3) by building up a sequence of previously created base years, similarly to the discharge scenario approach. With respect to the generation of meteorological time series, the user can choose to work with reference ETP or temperature maps, according to data available. Since the water balance module expects potential evapotranspiration as input, if temperature scenarios are selected, an intermediate calculation is necessary. Temperature values are not independent from the height above the sea level (a gradient of 0.6 C /100 m has been introduced), therefore the altitude distribution of the area has to be calculated prior to estimating ETP from temperature. For this purpose, the DEM of the region is divided in a number of classes, each one ranging for a hundred metres, and mean temperature values are referred to each class according to the temperature gradient. Mean values of evapotranspiration for each class are then obtained from the mean corresponding temperature values by using the Thornthwaite formula. The time series of available runoff and infiltration correspond to the water availability scenarios for the selected river reach nodes, lakes and aquifers, and are used by the allocation module of the WSM DSS together with the water demand scenarios. Demand Scenarios are produced in the form of time-series of water demand for all the demand nodes that are part of the water resource network. Scenarios are generated by specifying appropriate growth rates to the key variables (Driving Forces) that govern the water demand of the nodes, such as population for the domestic use, cultivable area and livestock for agricultural practices, production growth and energy requirements for industries, and hydropower plants. Growth rates can be common to all the nodes of the same water sector, e.g. to all settlement nodes, or defined
Fig. 1. The Map Editor of the WSM DSS (on the right) shows the water network, whose elements are listed in the tree view of the Object Manager (on the left) node by node in the relevant Data Panel of the user interface. Because growth rates can be time variant and are here requested to refer yearly, an expression evaluator window has been included into the DSS, which aids for the building of the growing expressions as a function of the simulated year. The user can use a set of different growth functions to describe the expansion of population in time. Although the growing expression refer yearly, a monthly variation of the yearly increment can be specified as well. In order to simulate a variation of the water demand of the single node, which may happen during the simulation as a reaction and adaptation to deficit conditions, a Demand Feedback Loop functionality can be activated. The idea behind it assumes that the water demand can varying reasonably during shortage conditions for example because seasonal population or even the residential may prefer to migrate to places where water supplies are guaranteed. Within the WSM DSS, the Feedback option allows to modifying the demand scenarios during the simulated water allocation: the variables that drive the scenarios behavior, such as population for settlements or cultivable area for irrigation sites, are changed according to the demand deficits occurring in a user-defined number of previous years. In the case of settlements nodes, for instance, the feedback works as follows. If the supply delivered to the settlement is zero during the feedback interval, then permanent and seasonal populations are set to zero for the remaining simulation period; if the total volume of water received is not equal to zero, then the DSS estimates for each month of the interval, an upper limit of overnight stays
(seasonal population) that can be sustained with the volume of water delivered. This is performed through the calculation of the average value of overnight stays for that month of the interval that can be sustained with the volume of water delivered. 5. PRIORITIES, WATER ALLOCATION AND RESULTS ANALYSIS Once the initial setting of the water resource system has been assessed in step S1, and the scenarios of driving forces and pressures have been generated in step S2, the allocation of resource throughout the water network can be simulated, step S3, and the resulting indicators are investigated, step S4, in order to identify the assess the unsatisfactory circumstances of the status of the system at the end of and within the simulation horizon. The Water Allocation Module is the kernel of the Water Strategy Man package, having as a primary objective the simulation of water distribution in the water resource system. It operates based on the group of demand priorities and supply preferences attached respectively to the demand nodes and to the supplying links of the water network, reflecting pricing system, social preferences, environmental constraints and development priorities of a case study area. A demand priority is a number ranging from 1 (highest) to 99 (lowest), which establish the right of the generic demand node to receive water before all others with lower priorities. It is a sort of discriminating factor, being useful and determinant when handling water shortage situations and conflicts between competing
Fig. 2. The indicators for impact assessment are presented at the end of the simulated water allocation uses. In case the water available to a source node is not sufficient to cover the demands of all the connected users, demand sites with higher priority are satisfied as fully as possible, and the flows that minimizes the water shortage are searched in the network. This water allocation is solved by first constructing a reduction to a standard Maximum Flow problem and then using the Ford-Fulkerson method (Ford and Fulkerson, 1962), also known as the Augmenting-Path Maximum flow algorithm. Supply priorities are used when a demand site is connected to more than one water resource. They are attached to the links connecting the user to the sources and express its preference or constraint to receive water from one source rather than another. As for demand priorities, supply priorities range from 1 (highest), that is usually set as default to the links in the water network, to 99 (lowest). Both demand and supply priorities are defined by the DSS user during the editing of the new geographic elements in the Map Panel, or during the entry of the relevant data in the Data Panel. The same value can be specified for all the nodes that belong to the same category of water use, such as settlements and tourist sites for the domestic use, irrigation and animal breeding for the agricultural use etc. Alternatively, a different priority value can be assigned node by node, sweeping the list of nodes with the Object Manager Panel (tree view). At the end of the simulation, the DSS user is prompted with a window presenting all the indicators computed. The analyses of these indicators, and the investigation of the causes and effects in the forecast behaviour of the water resource system, are facilitated by reports in tabular and graphical form. The time series of forecast key
parameters are visualized at a monthly base or aggregated yearly, and the simulated periods of time they relate to can be selected to show just some years and some months per year. Specific indicators characterize the various spatial entities of the water network, such as settlements, industries, storage reservoirs and river reaches, and some of them are also visualized aggregated over the entire network. According to the type of node they refer to, different categories of indicators are loaded in the interface, such as: Exploitation, Dependencies, Water Quality, Pressures, Deficits, Cost/Revenues and Water Quantity. In the exploitation group, there are variables such as Total Water Production and Consumption index, Groundwater exploitation index and Non-sustainable production index. Dependencies relate to the needs for water imported from neighboring areas and the anthropogenic water produced over total water production. Annualized capital costs, rate of cost recovery, direct costs, environmental costs and running costs are economic figures included in the Cost/Revenues collection. Water quality of water sources, effluents from demand nodes and treatment plants, and of water carried in each water link in the network in general is described by the concentrations of the pollutant and variables considered, namely: Salinity, Chlorophyll , Ammonia nitrogen, Nitrate nitrogen, Coli forms bacteria, Total phosphorus, Heavy metals, Biochemical Oxygen Demand and Dissolved Oxygen, suspended and inhibiting matters, and adsorbable organic halogens. The key concentrations simulated are those at the water resource nodes of the network: groundwater, river reaches, artificial and natural lakes. These con-
centrations are distributed throughout the system together with the allocation of water to the nodes, according to the paths traced by the network links, and may be modified by the pollutant loads production of demand nodes and by the treatment process of the plants. The concentrations at supply nodes are updated at each time step using two different algorithms, according to the quality parameter type. For some of them, the continuity equation on the loads is applied: the variation of load in the volume stored in the supply equals the difference between the incoming and the outgoing loads. The total incoming derives from the loads of the links carrying water to the supply node, while the outgoing load is computed from its current concentration. For heavy metals, total phosphorus, suspended and inhibiting matters and adsorbable organic halogens a heuristic proportionality approach is used. Incoming loads are compared to the Most Recently Measured (MRM) values, which are used as a reference, and water quality is assumed to improve proportionally if incoming loads are lower than the MRM, and to worsen otherwise. As far as the economic analysis is concerned, it consists of a tentative implementation of the principles associated to the estimation of the Full Water Cost and its components, as clarified in article 9.1 of the Water Framework Directive 2000/60 (European Parliament, 2000). The full cost of water services comprises of supply cost, resource cost and environmental cost. The supply cost, also referred to as direct or financial cost, represents the costs of investments, operation and maintenance, labour, and administrative costs. Within the WaterStrategyMan DSS supply costs are computed for each water node according to the kind of water use, based on the present value of the different parts of its infrastructure and accounting both the fixed costs, such as capitalinvestment costs, and the variable running costs of Operation, Maintenance and Energy defined for each node in the schematic water network. The present value of quantities allocated to demand nodes, for the entire simulation time horizon, is computed through the annual real interest rate relevant for the investor, the price per unit of supplied water charged by the water company, and the annual quantity of supplied water. An additional direct cost is also considered in the estimation of the total direct cost of whatever demand node in the network, that is the cost for water distribution and delivery. This cost results from the summation of the direct costs of all the pipelines or canals entering the node and of the upstream nodes from which water comes from (for instance a storage reservoir or a drinking water plant). Indicators calculated by the DSS and shown in the economic analysis interface are:
direct costs for demand nodes, annualized capital costs and running costs for each supply node, costs for water treatment and for water transfers for plants and links respectively. The resource cost represents the loss of profit because of the restriction of available water resources. It is accounted in the DSS, through the estimation of the key figure of total benefits from water use, which is computed yearly and for each water sector. Benefits for the domestic use are calculated as a function of the value of water. Benefits for irrigation depend on the revenues from crop cultivation and the alternative value of land, whereas for animal breeding they are associated to market values of livestock. Economic benefits from water use for industries are a function of the yearly production and the value of the product unit. The estimation of environmental costs within the DSS follows the current practices of the French Agencies de l’Eau. Environmental costs are associated to: 1) abstraction and consumptive use of water from renewable groundwater and surface water resource, and 2) the costs of discharging water pollutants and the benefits coming from treating water before discharging to the final receiving bodies of water. The costs relative to the exploitation of water resources are a function of its sustainable use, vulnerability and unsatisfied environmental demand. The environmental cost for polluting water is quantified by assigning a cost per unit concentration of contaminant that is released daily by different users during an event of maximal discharge. A coefficient denoting the sensibility of the aquatic ecosystem is also involved. The environmental benefits gained from the treatment of waste water are measured with the same formulation as above, with the addition of an abatement rate coefficient for the single quality variable (Bonus Annual coefficient). An indicator of cost recovery is also visualized after the simulation, both at the water node level and aggregated over the entire water resource system. Cost recovery is defined as the percentage ratio of the total revenues from water billing over the total cost of water production.
6. STRATEGIES AND EVALUATION The WaterStrategyMan package is being used in the project case study regions, with the purpose of supporting the development of strategies for regulating and managing water resources and demand in water deficient regions (The WaterStrategyMan Project, 2004). A number of suitable strategic options have been identified and listed within the project, whose application intend to mitigate
Fig. 3. The evaluation of results for alternative water strategies water stress conditions and related impacts, minimize water shortages, distribute costs equitably among the urban, agricultural and industrial water users, aim at sustainable resource exploitation, and recover direct, resource and environmental costs for water services and use. These options have been grouped under four categories: a) Supply Enhancement, b) Demand Management, c) Regional Development and d) Institutional policies. The supply measures consist of the water availability increment by means of non structural interventions: a1) Unconventional/untapped resources, a2) Surface Waters and rainfall harvesting, a3) Expansion of groundwater pumping infrastructures, a4) Desalination, a5) Importing from the nearby regions and, a6) Water Reuse. The Demand Management measures aim at controlling and limiting water demands by means of: b1) b2) b3) b4) b5) b6)
Quotas and Regulated supply; Irrigation method improvements; Conservation measures in domestic sector; Recycling in industry and domestic use; Reduction of distribution losses; Raw material substitution and process changes in industry;
Regional Development measures involve: c1) Change in agricultural practices, such as cultivation of low demanding crops and c2) Change or limitation of regional development policy, according to the priority of each sector to use water before others.
The fourth category relate to Institutional policies, such as: d1) Education and awareness campaigns, Use of standards, Public participation, Stakeholder involvement, Conflict resolution, and Contingency planning, d2) Water pricing, Cost recovery, Incentives, d3) Environmental standards and legislation, Monitoring, Penalties and fines, Impact and risk assessment. Some of these options have been implemented and are currently available inside the DSS to perform step S5. A dedicated interface allows to define and confirm new pending measures, in order to make them active during the water network simulation. Some of these measures operate on a specific type of node: desalination supplies domestic and tourist users, waste water plants are supposed to feed irrigation sites, the change of process affects industries, etc. Other measures are designed to influence the allocation of all the demand nodes, such as for instance the importing from external administrative areas, the application of quotas, and the definition of water selling prices and demand elasticity factors. The common denominator for all the strategic options is the required dating of the implementation time step in the simulation horizon, namely the year from which the data featuring the generic option is recognized by the water allocation module, at runtime during the simulation. In practice, the implementation of a measure makes the Decision Maker able to introduce an external factor at a certain point of the simulation process, in order to face and overcome the unacceptable and/or inadequate conditions that are predicted to happen under historic-based demand and availability scenarios.
Alternative strategic options can be simulated as freestanding, applied to the basic schematization of the water resource system under the same scenarios or diverse extreme climatic and demographic conditions. The ensemble of scenarios plus a particular option is referred to as a Comprehensive scenario in the WaterStrategyMan approach. The analysis of freestanding strategic options within Comprehensive scenarios gives a first feedback of the more or less positive impact they have on the water network management, while the second phase consists in combining together several options, in order to build what in the project is called a Strategy. The construction of alternative sets of strategic measures as responses/solutions to negative unsustainable situations characterizes the fifth step (S5) of the water resource analysis procedure presented in the introduction. After simulating with the DSS the new strategies, (step S6), the evaluation of the outcomes and effects of the application of the alternative strategies is performed (step S7). The evaluation module of the DSS has been founded on an adaptation of a methodology based on Sustainability Criteria (Task Committee on Sustainability Criteria and Division, 1998). Alternative Water Management Schemes, formed by the base case study running under comprehensive scenarios, are given a score based on statistical criteria that describe the behavior of user-selected indicators with respect to a range of satisfactory values. The Water Management Scheme getting the highest sustainability score is considered the most sustainable with respect to the indicators selected, the satisfactory range of values set for each criterion and the relative weight. As a consequence, the corresponding strategy is established to be the one that better copes with the social, economic, climatic and environmental constraints of the resource system. More in details, the following steps are performed: 1) the user selects and activates a number of indicators from the three categories of Environment and Resources, Efficiency and Economics, 2) weights and least and maximum acceptable values are assigned to each of them according to the specific goals of the strategy simulated and the specific problems affecting the case study. An acceptability range delimits a field of values that each indicator can take during the simulation and that are considered satisfactory, 3) three statistical criteria namely Reliability, Resilience and Relative Vulnerability are calculated for each indicator, normalized where necessary, and aggregated in the sustainability index, 4) sustainability indexes for the respective indicators are weighted to get the Total Sustainability Index of the entire management scheme. Statistical criteria state if the simulation results, conditioned by certain
scenarios and strategies, can be considered reasonable and acceptable for the goals set out by the decision maker. The three above mentioned criteria are shortly defined as follows: • Reliability is the probability that any particular indicator value of its time series will be within the range of values considered satisfactory; • Resilience is a criterion describing the speed of recovery from an unsatisfactory condition. It is the probability that a satisfactory value will follow an unsatisfactory value; • The Vulnerability statistical index measures the extent and/or duration of failures (e.g. unsatisfactory values) in a time series. The extent of a failure can be based on the extent of failure of individual unsatisfactory values or the cumulative extent of failure of a continuous series of unsatisfactory values. In the latter case, each individual extent of failure is added together for the duration of each continuous failure sequence. From the graphical user interface point of view, the evaluation module allows the selection of the Water Management Schemes to be evaluated and compared, from a list of already simulated schemes. The DSS user can also choose the time period, within the limit of the scenarios horizon, for the evaluation of the time series of results. A window shows the table of indicators available for the evaluation process, which can be activated, and their weights and satisfactory ranges defined. The behavior of the time series, together with the partial and total sustainability scores of the compared alternative Schemes are visualized both in a table and plotted in graphical form.
7. CONCLUSIONS The WaterStrategyMan decision support system is a software package that allows for water resource assessment, identification of boundary social and economic conditions, climatic driving forces and demographic pressures, simulation and investigation of future forecasts and comparison of alternative policy measures. It embeds a GIS map editor and a Geodatabase. Its use is quite simple and intuitive, and the amount of data required to run it is reasonable and essential to the scopes. The package is not an optimization tool, neither it is based on complex physical modelling. It is supposed to work at a higher level of aggregation, which means that detailed basic analyses of the water resources here schematized and included are supposed to be already available, together with the relevant data. Moreover, it is not expected to give an absolute optimal answer; it provides some functionalities that aid interactively decision
makers in the critical examination of a range of possible solutions. The structure of the software is modular and open to expansion and improvements of the modelling core.
8. ACKNOWLEDGEMENTS The Project partners who were actively and directly involved in the DSS formulation, development and finalization are: the National Technical University of Athens (Prof. D. Assimacopoulos), the Ruhr-University (Prof. A. Schumann) and ProGEA S.r.l. (Prof. E Todini). An invaluable contribution also came from all the project partners, namely the Office International de l’Eau, the Hebrew University of Jerusalem, the Water Development Department (Governmental Department) of Cyprus, INSULA (International Scientific Council for Island Development), Aeoliki Ltd, the Faculdade de Engenharia da Universidade do Porto, in terms of methodological definitions and application and test of the software to their specific case studies.
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