Giovanni Maria Sechi

Neural nets for modelling rainfall-runoff transformations

To obtain river flow data, a neural network (NN) is developed and applied to rainfall-runoff transformation. The NN has been built considering a hidden two layer net and the sigmoidal has been used as a response function. Training is conducted using a back-propagation learning rule. In the input layer, both areal and point data values may be considered. The capability to provide a suitable forecast of river runoff has been examined for the Araxisi watershed in Sardinia. Experiments have been made dividing the total extension of observed data into three ten-year periods, assuming each as a training set, learning the NN and simulating the other two decades over the same period. The obtained model efficiency confirms the capability of this approach to supplying a useful tool in the evaluation of rainfall-runoff transformations.

River flow forecast for reservoir management through neural networks

Abstract River flow forecasts are required to provide basic information for reservoir management in a multipurpose water system optimisation framework. An accurate prediction of flow rates in tributary streams is crucial to optimise the management of water resources considering extended time horizons. Moreover, runoff prediction is crucial in protection from water shortage and possible flood damages. In this paper, a neural approach is used to model the rainfall-runoff process when different time step durations have to be considered in reservoir management. Numerical comparisons with observed data are provided for runoff prediction in the Tirso basin at the S.Chiara section in Sardinia (Italy).

Comparison of generic simulation models for water resource systems

In water resource systems that frequently experience severe droughts, generic simulation models can provide useful information for developing drought mitigation measures. This paper is about modeling in practice rather than in theory. The emphasis is on the application of generic simulation models to a multi-reservoir and multi-use water system in Southern Italy where frequent droughts over the last two decades have necessitated the use of temporary and unsustainable user-supply restrictions. In particular, AQUATOOL (Valencia Polytechnic University), MODSIM (Colorado State University), RIBASIM (DELTARES), WARGI-SIM (University of Cagliari) and WEAP (Stockholm Environmental Institute) models are considered in a preliminary analysis, which considers series and parallel simple schemes and also evaluates the possibility of alternative plans and operating policies in complex real water system. Each model has its own characteristics and uses different approaches to define resources releases from reservoirs and allocation to demand centers. The proposed model comparison and application does not identify in detail all the features of each model, rather it provides insights as to how these generic simulation models implement and evaluate different operating rules.

Water Costs Allocation in Complex Systems Using a Cooperative Game Theory Approach

The management of complex water resource systems that address water service recovery costs and consider adequate contributions and priorities require methods that integrate technical, economic, environmental, social and legal aspects into a comprehensive framework. In Europe, the Water Framework Directive (WFD) 2000/60/EC recommends that the pricing politics in a river basin take into account the cost recovery and the economic sustainability of the water use. However, the current cost allocation methods do not consider the user’s willingness to pay and often do not permit a total cost recovery. Thus, a new approach is required that includes these requirements when defining water rates. This article presents a methodology to allocate water service costs in a water resource system among different users that attempts to fulfil the WFD requirements. The methodology is based on Cooperative Game Theory (CGT) techniques and on the definition of the related characteristic function using a mathematical optimisation approach. The CGT provides the instruments that are necessary to analyse situations that require a cost-sharing rule. The CGT approach can define efficient and fair solutions that provide the appropriate incentives among the parties involved. Therefore, the water system cost allocation has been valued as a game in which it is necessary to determine the right payoff for each player that is, in this case, a water user. To apply the CGT principles in a water resources system, the characteristic function needs to be defined and evaluated using an adequate modelling approach; in this study, it is evaluated using the optimisation model WARGI. (Sechi and Zuddas 2000). The so-called “core” represents the game-solution set. It represents the area of the admissible cost allocation values from which the boundaries on the cost values for each player can be supplied. Within the core lie all of the allocations that satisfy the principles of equity, fairness, justice, efficiency and that guarantee cost recovery. The core of a cooperative game can represent a useful instrument to define the water cost rates. Furthermore, it can be used as a valid support in water resource management to achieve the economic analysis required by the WFD. The methodology was applied to a multi-reservoir and multi-demand water system in Sardinia, Italy.

Cost/risk balanced management of scarce resources using stochastic programming

We consider the situation when a scarce renewable resource should be periodically distributed between different users by a Resource Management Authority (RMA). The replenishment of this resource as well as users demand is subject to considerable uncertainty. We develop cost optimization and risk management models that can assist the RMA in its decision about striking the balance between the level of target delivery to the users and the level of risk that this delivery will not be met. These models are based on utilization and further development of the general methodology of stochastic programming for scenario optimization, taking into account appropriate risk management approaches. By a scenario optimization model we obtain a target barycentric value with respect to selected decision variables. A successive reoptimization of deterministic model for the worst case scenarios allows the reduction of the risk of negative consequences derived from unmet resources demand. Our reference case study is the distribution of scarce water resources. We show results of some numerical experiments in real physical systems.

Water Resource Allocation in Critical Scarcity Conditions: A Bankruptcy Game Approach

Water resource allocation in critical scarcity conditions represents a common problem in water-system management in Mediterranean regions. This article describes a methodology for the allocation of scarce resources in a complex supply system by using the Bankruptcy Games techniques. A classical bankruptcy problem arises from a situation in which some agents have claims on the available estate to be divided, such that each agent might receive a non-negative amount that cannot exceed its claim. The methodological approach described in this article is linked to Cooperative Games Theory and allows the evaluation of a sharing rule for goods that are not sufficient to satisfy the total requests of the users in the system. Moreover, a new criterion is developed that, in resource allocation, privileges those users with higher priority. Users’ willingness to pay is considered to define priority; the methodology can be considered innovative in this field of research. This approach has been applied in water resource systems using critical scarcity scenarios: initially, a simplified water system is used; then, the complex and multi-purpose Tirso-Flumendosa-Campidano water system in southern Sardinia, Italy, is examined.

Assessment of evolutionary algorithms for optimal operating rules design in real Water Resource Systems

Two evolutionary algorithms (EAs) are assessed in this paper to design optimal operating rules (ORs) for Water Resource Systems (WRS). The assessment is established through a parameter analysis of both algorithms in a theoretical case, and the methodology described in this paper is applied to a complex, real case. These two applications allow us to analyse an algorithms properties and performance by defining ORs, how an algorithms termination/convergence criteria affect the results and the importance of decision-makers participating in the optimisation process. The former analysis reflects the need for correctly defining the important algorithm parameters to ensure an optimal result and how the greater number of termination conditions makes the algorithm an efficient tool for obtaining optimal ORs in less time. Finally, in the complex real case application, we discuss the participation value of decision-makers toward correctly defining the objectives and making decisions in the post-process. SCE-UA and Scatter Search are assessed in order to design optimal operating rules.An analysis of the parameters is carried out to determinate the best stop criteria.The analysis carried out shows the most influential parameters.SCE-UA algorithm, applied in real cases, seems to be the most efficient algorithm.A way to transmit results is presented in order to make the decision-making easier.

Trophic State and Toxic Cyanobacteria Density in Optimization Modeling of Multi-Reservoir Water Resource Systems

The definition of a synthetic index for classifying the quality of water bodies is a key aspect in integrated planning and management of water resource systems. In previous works [1,2], a water system optimization modeling approach that requires a single quality index for stored water in reservoirs has been applied to a complex multi-reservoir system. Considering the same modeling field, this paper presents an improved quality index estimated both on the basis of the overall trophic state of the water body and on the basis of the density values of the most potentially toxic Cyanobacteria. The implementation of the index into the optimization model makes it possible to reproduce the conditions limiting water use due to excessive nutrient enrichment in the water body and to the health hazard linked to toxic blooms. The analysis of an extended limnological database (1996–2012) in four reservoirs of the Flumendosa-Campidano system (Sardinia, Italy) provides useful insights into the strengths and limitations of the proposed synthetic index.

Using reservoir trophic-state indexes in optimisation modelling of water-resource systems

Water quality is an important factor to consider when attempting to reconcile mathematical optimisation modelling with the physical reality of water-resource systems. In particular, when the greater part of water resources in supply systems comes from artificial reservoirs, as in Mediterranean regions, a simplified approach based on the attribution of the trophic state of reservoirs can be developed to consider water quality in the optimisation model. Experimental studies have demonstrated that a measure of the trophic state can be given by the Trophic-State Index (TSI), which is evaluated by chlorophyll-a concentration. When certain families of microscopic phytoplanktonic algae produce algal toxins during eutrophication, limitations on resource use based solely on TSI values may be insufficient. In this paper, a linear optimisation model is presented that includes quality indexes estimated based on both TSI and concentration density of the most toxic species of algae in reservoirs. The application of the optimisation model to a multi-reservoir system, located in Sardinia, Italy, highlights the impacts of using different water-quality indexes on the results of the optimisation model.

Optimization of Water Distribution Systems by a Tabu Search Metaheuristic

A Tabu Search optimisation technique is proposed for designing, planning and maintaining water distribution systems. As design and maintenance of pipe networks for water supply distribution require high costs, achieving the highest level of performance of existing networks at minimum costs is mandatory. The problem involves setting a lot of variables, as location and diameters of new pipes, operations on existing pipes, and so on. The domain of variables is discrete in nature, due to the fact that pipes are available with unified dimensions. Furthermore, the objective function to be minimised, i.e., the total cost of the plant, is non linear, non differentiable, highly ill-conditioned, and presents a huge amount of local minima. Recently, increasing attention has been paid to heuristic optimisation techniques, such as genetic algorithms (GA), simulated annealing (SA), and tabu-search (TS) for large combinatorial optimisation problems. In particular, GA has been applied to the problem of designing and maintaining water distribution networks. Results show good performance of the GA in terms of objective function values, but high computation time. One of the most promising approaches to combinatorial optimisation problems is the TS metaheuristic, that showed flexibility and effectiveness in a lot of applications. The aim of this paper is to present a TS based algorithm to the design of water distribution systems, and to demonstrate its validity in this field.