Z. X. Xu

Bio: Z. X. Xu is an academic researcher from Ruhr University Bochum. The author has contributed to research in topics: Decision support system & Water resources. The author has an hindex of 2, co-authored 2 publications receiving 40 citations.

Decision support system for surface water planning in river basins

Abstract: 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.

Development of a Decision Support for Integrated Water Management in River Basins

Abstract: The application of computers for the planning and operation of water resource systems is a rapidly advancing field of research. In recent years, decision support system (DSS) has gained much attention in civil engineering, in which the output can be displayed in high quality and easy to be understood. In this study, the decision support system for integrated water management, CTIWM, is developed with particular reference to Chikugo River basin, a multipurpose multireservoir system in Japan. It uses a module library that contains compatible modules for simulating a variety of water and physio-chemical processes. Different kinds of numerical models may be invoked through user interface menu, which facilitates communications between users and models in a friendly way. It demonstrates that the integration of DSS technique, simulation and optimization models is an efficient way for water resources management.

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

Abstract: 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.

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

Abstract: 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.

Water Resources Allocation Considering the Water Use Flexible Limit to Water Shortage—A Case Study in the Yellow River Basin of China

Abstract: Water resources allocation in a river basin is customarily determined based on long-term mean water availability. However, inter-annual variability of water resources caused by climate fluctuation should also be considered in order to keep an effective and flexible allocation policy. This paper analyzes the historical evolution of the water resources allocation system in the Yellow River basin of China. Based on the concept of water use flexible limit to water shortage and actual water use data from 1988–2006, a set of flexible limits to water shortage adapted to the Yellow River basin has been proposed. This includes total water use flexible limit to water shortage for all provinces, which is approximately 70%; and the different water use flexible limits to water shortage for each social sector, which are approximately 90% for agriculture, 85% for domestic use, and 50% for other industries. It offers a simple, yet effective, method for future water resources allocation in the Yellow River basin to achieve the optimal use of water resources. It likewise provides a beneficial reference for water resources management in the water deficient regions of China.