Pressure management (PM) is commonly used in water distribution systems (WDSs). In the last decade, a strategic objective in the field has been the development of new scientific and technical methods for its implementation. However, due to a lack of systematic analysis of the results obtained in practical cases, progress has not always been reflected in practical actions. To address this problem, this paper provides a comprehensive analysis of the most innovative issues related to PM. The methodology proposed is based on a case-study comparison of qualitative concepts that involves published work from 140 sources. The results include a qualitative analysis covering four aspects: (1) the objectives yielded by PM; (2) types of regulation, including advanced control systems through electronic controllers; (3) new methods for designing districts; and (4) development of optimization models associated with PM. The evolution of the aforementioned four aspects is examined and discussed. Conclusions regard...

Dam safety assessment is typically made by comparison between the outcome of some predictive model and measured monitoring data. This is done separately for each response variable, and the results are later interpreted before decision making. In this work, three approaches based on machine learning classifiers are evaluated for the joint analysis of a set of monitoring variables: multi-class, two-class and one-class classification. Support vector machines are applied to all prediction tasks, and random forest is also used for multi-class and two-class. The results show high accuracy for multi-class classification, although the approach has limitations for practical use. The performance in two-class classification is strongly dependent on the features of the anomalies to detect and their similarity to those used for model fitting. The one-class classification model based on support vector machines showed high prediction accuracy, while avoiding the need for correctly selecting and modelling the potential anomalies. A criterion for anomaly detection based on model predictions is defined, which results in a decrease in the misclassification rate. The possibilities and limitations of all three approaches for practical use are discussed.

The System of Environmental-Economic Accounting for Water (SEEA-W) consists of an agreed international framework for organizing hydrological and economic information in a coherent and consistent manner. The methodology yields to the SEEA-W physical tables focusing on the quantitative assessment of the stocks and their changes in a river basin during the accounting period. For that purpose, the information on the abstraction and water discharge is linked with the environment water stocks, which assesses how current levels of abstraction and discharge affect such water stocks. This study presents the methodology and results to fill out the SEEAW tables for asset accounts on the Spanish Duero basin. Duero is a transboundary river between Spain and Portugal where 80% of its basin area (78,860km(2)) runs into the Spanish territory. The Spanish part is divided in five zones and 13 management systems. The methodology applied the three models used by the Spanish Water Authorities for the planning and allocation of water resources in Spain: 'SIMPA' model (rainfall-runoff model), 'ASTER' model (hydro-meteorological model related to snow processes) and 'SIMGES' model (water management simulation model). The required information was collected with the support from the Duero River basin Authority and the Spanish Ministry of Agriculture. Special care was paid to issues such as: inter-annual variability, the selection of spatial and temporal scale, seasonality, disaggregation of human abstractions into use's type, and transboundary agreements. The results highlighted some drawbacks in the SEEAW methodology for the Duero basin. However, the developed balances are a valuable tool to support the decisions of the Spanish Duero basin Authority on the management and allocation of water in the basin and in the transboundary area with Portugal. Finally, the paper outlines some recommendations for future work.