Optimal land and water resources allocation policies for sustainable irrigated agriculture

Dams are amongst the most important components of water resource systems. In many places the water regulated by and stored in dams is essential to meet the development objectives of water supply, agriculture (i.e. irrigation and livestock), industry, energy generation and other sectors. However, in the absence of adequate foresight and planning for adverse impacts, past dam construction has often resulted in devastating effects for ecosystems and the livelihoods of affected communities. Participation of stakeholders in the decision-making process and increased equity in the distribution of benefits are prerequisites to mitigating dam related conflicts and ensuring sustainable projects. Appropriate use of decision support systems to assist in the planning and operation of dams can contribute to these objectives and can also enhance gains in economic, social and environmental benefits.

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Decision support systems for large dam planning and operation in Africa.

The ongoing changes in the society’s perception of the role and function of infrastructure systems as well as degradation of the state of natural resources, increasingly appoint new challenges to the management of water supply systems. Out of many, the main the main research objectives of this research are: the integration of multiple objectives and criteria, and the incorporation of uncertainty, risk and reliability considerations in the water supply systems analysis. In order to help to implement these objectives in everyday planning, design and operation of water supply systems, an unique optimisation methodology has been developed and implemented into corresponding computer models.
The methodology uses the network approach for conceptual and structural representation of water supply systems and define planning, design and operation management problems as Network Minimum Cost Flow problems with multiple objectives. Different impacts of water supply projects or actions such as economic costs, environmental consequence or social disapproval are add together according to the utilities (preferences) of decision makers by implementing theMulti Objective Simulated Annealing (MOSA) method. In order to improve the performance of the algorithm for complex combinatorial problems and reduce questioning of non-optimal alternatives, the MOSA algorithm is embedded into the Branch and Bound method. For optimisation problems defined on networks, the combination of the previous two algorithms provide for robust and efficient identification of Pareto-solutions.
The inclusion of uncertainty, risk and reliability considerations in the analysis is based on the Stochastic design approach. It provides for the inclusion of decision makers’s risk perception in evaluation of the satisfactory system’s performance. The accepted risk for some system configuration is obtained as a statistical expectation of the costs of expected failures. A deterministically defined failure of an individual system component is considered with an advanced Path Restoration method, while a probabilistically defined performance failure is addressed with stochastical simulation of system’s performances. An advanced sampling method (i.e. Latin Hypercube) is used for the creation of representative samples of uncertain and variable parameters. The system’s reliability is obtained form the statistical analysis of calculated system’s performances evaluated with predefined risk tolerance levels. Finally, a demonstration at a) a multi-objective planning problem of a system expansion, b) a NP-hard design problem of pipe diameters selection and c) a complex operation problem of pump scheduling is done on the basis of well known test studies from the literature.
These proved that network system representation, multi-objective problem formulation and inclusion of decision makers’ preferences and risk perception in the development of optimal alternatives improve the creation of Pareto-optimal solutions, increase the efficiency of optimisation procedure and add to the transparency of the system analyse.
 
Die verstarkte Nutzung der naturlichen Wasserressourcen und die weltweite Verunreinigung dieses kostbaren Schatzes im 20. Jahrhundert fuhrte zur Erschopfung und Verschmutzung vieler natuurlicher Wasserkorper. Die wachsende Spannung zwischen intensiver Wassernutzung und der naturlichen Funktion von Okosystemen, veranderte unsere Vorstellung uber die Aufgabe der Wasserversorgungssysteme. Die integrierte Betrachtung von gesellschaftlichen, okonomischen und okologischen Aspekten von Wasserversorgungssystemen und die Einbeziehung der Unsicherheiten und der Veranderlichkeit der Eingangsparameter wurden als Hauptbeweggrunde dieser Studie festgelegt. Um diese Herausforderungen in der alltaglichen Planung, beim Entwurf und im Betrieb der Wasserversorgungssysteme einzusetzen, wurde hier eine Methodologie fur die modellbasierte Analyse und Optimierung dieser Systeme entwickelt.
Die Methodologie verwendet den Netzwerkansatz fur die konzeptionelle und strukturelle Darstellung der Wasserversorgungssysteme und definiert damit ein Network Minimum Cost Flow Problem mit mehrfachen Zielsetzungen, um Planungs-, Entwurfs- und Betriebsmanagementprobleme mathematisch zu formulieren. Unterschiedliche Aspekte von Wasserversorgungsprojekten und -aufgaben, wie Minimierung von okonomischen Kosten, Umweltauswirkungen oder negativen soziale Folgerungen, werden den Praferenzen von Entscheidungstragern entsprechend, mit der Multi-objective Simulated Annealing (MOSA) Methode (Ulungu et al., 1995; Kirkpatrick et al., 1983; Cerny, 1985) zusammengefuhrt. Um die Leistungsfahigkeit des Algorithmus fur komplizierte kombinatorische Probleme zu verbessern und das Abfragen der nicht-optimalen Alternativen zu verringern, wird der MOSA Algorithmus in die Branch and Bound Methode (Land 1960) eingebettet. Fur gut strukturierte Netzwerk-Optimierungsprobleme gewahrleistet die Kombination der beiden genannten Algorithmen eine robuste und leistungsfahige Ermitllung der Pareto-optimalen Losungen. 
Eine methodische Einbeziehung der Unsicherheiten und der Veranderlichkeit der Eingangsparameter wird erreicht, indem man unterschiedliche mogliche Systemalternativen mit Hilfe der stochastischen Simulationsverfahren evaluiert. Die dafur notigen reprasentativen Stichproben der Eingangsparameter wurden mit der Latin Hypercube Sampling Technik (Iman and Shortencarier 1984) generiert. Eine statistische Analyse der berechneten Systemsleistungen fur diese Stichproben wird dann fur die Einschatzung der Systemzuverlassigkeit verwendet. Zusammen mit der Ausfallanalyse, welche durch das Pat Restoration Verfahren (Iraschko et al. 1998) eingefuhrt worden ist, wird die Kompromissfindung zwischen der Systemzuverlassigkeit und Kriterien wie okonomische Kosten ermoglicht. 
Die beschriebene Methodologie wurde in drei entsprechenden Computermodellen umgesetzt. Sie sind an die spezifischen Aspekte der Wasserversorgungsplanung, des Entwurfes und des Betriebsmanagements angepasst und ermoglichen im Verbund eine volle Entscheidungsunterstutzung im Management von Wasserversorgungssystemen. Die Teilmodelle wurden anhand von folgenden Fallstudien erlautert: a) Planung der Entwicklung der Wasserversorgungsstruktur, b) Bestimmung der Kapazitat des Wasserversorgungsnetzes und c) Identifizierung des optimalen Pumpbetriebs desWasserversorgungssystems.

Multi-objective and risk-based modelling methodology for planning, design and operation of water supply systems

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State-of-the-Art Report on Systems Analysis Methods for Resolution of Conflicts in Water Resources Management

Water quality management is inevitably complicated since it involves a number of environmental, socio-economic, technical, and political factors with dynamic and interactive features. In planning water quality management systems, uncertainties exist in many system components and may affect the system behaviours. It is thus desired that such complexities and uncertainties be effectively addressed for providing decision support for practical water quality management. The objective of this study is to develop a model-based decision support system for supporting water quality management under hybrid uncertainties, named FICMDSS, which is based on a hybrid uncertain programming (HFICP) model with fuzzy and interval coefficients. The system provides an effective tool for the decision makers in dealing with water quality management problems and formulating desired policies and strategies. The user can easily operate the system and obtain the decision support through user-friendly graphical interfaces. The HFICP model improves upon the existing inexact programming methods through incorporation of hybrid fuzzy and interval uncertainties into the optimization management processes and resulting solutions. Results of a water quality management case study indicated that the developed FICMDSS can facilitate the decision making in planning agricultural activities for water quality management in agricultural systems. Feasible decision alternatives for cropping area, amounts of manure and fertilizer application, and sizes of livestock husbandry can be generated for achieving the maximum agricultural system benefit subject to the given water-related constraints. The user can better make the decisions for water quality management under hybrid uncertainties with the help of FICMDSS.

Model-based decision support system for water quality management under hybrid uncertainty

A decision support system (DSS) for the integration of hydrologic process modeling and risk evaluation of the surface water management alternatives in a river basin is developed. The DSS, named CTIWM, is aimed at supporting the testing and evaluation of water management policies and at facilitating integration of user-selected scenarios into planning strategies of the water resource system in the Chikugo River basin, a multipurpose multireservoir system. CTIWM uses a module library that contains compatible modules for simulating a variety of hydrologic processes. Different numerical models are invoked through a user interface menu, which facilitates communications between users and models in a friendly way. The source code was developed by using object-oriented programming techniques. The result shows that the use of DSSs may effectively improve the speed and quality of water management and give users more flexibility in analyzing different scenarios.

T. Kojiri

Papers

Decision support system for surface water planning in river basins