Description: The hydraulic projects, such as reservoirs, ponds, and paddy fields, have a marked influence on the generation of floods, causing a number of difficulties where hydrological forecasting is concerned. To consider the influence of the hydraulic projects in hydrological forecasting, a modified TOPMODEL is presented in the paper, based on the simulation rules of the aggregate reservoir’s retaining and discharging (ARRD). In the new purposed model, termed as ARRD-TOPMODEL, the hydraulic projects are first aggregated as an equivalent reservoir, then the simulation rules of the aggregate reservoir’s retaining and discharging are determined, finally, the simulation rules are combined with an original TOPMODEL model calibrated using the floods not influenced by the hydraulic projects for flood forecasting. The ARRD-TOPMODEL was tested on the upstream of Wudaogou station basin in Northeast China. The results show that compared to the original model, the qualified rate (i.e., the ratio of the number of floods that meet acceptable criteria and the total number of floods) of runoff forecasting was increased from 73% to 100%. The problems that the overestimation of the runoff at beginning of flood season and after a long drought, as well as that the underestimation of the large flood in middle flood season are both solved, and the flood processes predicted by the new model are more consistent with the observed ones. All of these demonstrate that the newly developed model is superior to the original one and the simulation rules of the aggregate reservoir’s retaining and discharging are capable of accurately accounting for the influence of the hydraulic projects on the floods.

Description: The paper presents a set of experiments on the Rolling Horizon Technique (RHT), applied to the management of a multi-reservoir, multipurpose water resources system with over-year behaviour. In the RHT, decisions on releases from reservoirs are taken for a number of time steps ahead (the Forecasting Horizon – FH) through an optimization model, based on the present water availability in reservoirs and on some forecasts of future inflows over the FH. Only the decision concerning the first time step (the current month) is then implemented, as new information on reservoir levels and forecasts becomes available so that the process can start again with updated information. The paper investigates how the quality of forecasts and the length of the FH impact on the effectiveness of the decisions taken. The evaluation exercise is carried out in two different demand scenarios considering some deficit-related indices, such as TSSD, the Sum of Squared Standardized Deficits, over an Operation Horizon (OH) of forty years. The scenarios are designed to evaluate the role of different demand levels (corresponding to higher/lower stress) on system’s behaviour. Results show that in systems with over-year behaviour, effective forecasts (here simulated through the best possible: actually occurred inflows from the current month up to the end of water year) seem to add little value to system’s operation compared to the most naive forecast (average monthly values), especially in contexts characterized by high pressure on resources. Where there is less pressure on resources, good-quality forecasts are more effective to improve operation. A FH of 24 months seems to enhance significantly system’s performances compared to a FH of 12 months, while FHs longer than two years produce no improvements in system’s performances. The paper also tries to define the limits of a finite-horizon operation technique such as the RHT by benchmarking it with an idealistic release schedule obtained by a model that performs allocation with Perfect Foresight over the whole Operation Horizon.

Description: The planning and operational performance evaluation of water supply reservoirs routinely use the volume-based (R v ) and time-based (R t ) reliability indices but decision making is often complicated by trade-off necessitated by the fact that the two are never the same, with R v  ≥ R t . This study has resolved the problem by harmonising the two indices. Using data from ten global rivers, simulations of hypothetical reservoirs were carried out to determine capacity for specified demands and R t values. The corresponding R v values were then evaluated and the resulting reliability biases (i.e. R v – R t ) were found. To harmonise the two indices, i.e. to nullify the biases, the concept of water shortage threshold was introduced, which is the minimum quantity of water shortage that can be taken as constituting real failure for the purpose of R t evaluation; shortage quantities below this will be disregarded. The results showed that the water shortage threshold that nullifies the reliability bias can be as high as 60% of the demand, depending on the runoff variability, the demand and the specified R t . When averaged over all the situations analysed, the water shortage threshold was found to be 51% of the demand. Although this might appear high, it is argued that it is plausible both within the context of developed economies, where unaccounted-for-water can be much higher than 51%, and of underdeveloped economies where large sections of the population have no access to adequate water supply. In the latter case, a reduction of 50% in water supplied that guarantees uninterrupted supply of the other 50% will be deemed satisfactory and reliable, while for the former, a shortage of 50% that forces a change in behaviour to waste less water will also be deemed satisfactory. The significance and novelty of this study stem from the fact that it has removed the need for the trade-off between the two reliability indices, thus enabling unequivocal characterisation of water supply reservoir performance for effective decision making.

Description: This paper explores the impact on water demand of the adoption of deficit and precision irrigation as a farmer’s attempt to respond to water scarcity by maximising water productivity. The case study is characterised by the intensive use of deficit irrigation techniques in olive groves, which account for 50% of all irrigated land in southern Spain. These technologies have an important influence on the structure of the water demand. This study reveals that following the adoption of such technologies, water demand does not respond to moderate changes in water price, unless price increases become so great that they reach a threshold price representing a disproportionate and unaffordable social impact. This fact has significant consequences for water policy as water pricing becomes an ineffective instrument for managing water demand in a context characterised by resource scarcity and farmers’ adoption of deficit irrigation techniques.

Description: There are increasing concerns on the impact of population growth on sustainable use of water resources utilization. In this context, this paper aims to develop a conceptual framework for understanding the human-water system from the contradiction and co-evolutionary perspective. In this paper, the three contradiction relationships including those of human-water system, climate change and war condition, productive forces and production relations are analyzed by choosing six proxy indicators, and a set of historical data during 722 B.C.-1911 A.D., in China is used as the case study. Human and water is a co-evolution system as the coefficient of determination (R 2 ) between population and water governance activities is 0.9. Advanced productive forces and production relations play an important role in promoting population growth and water governance activities evidenced by high R 2 between any two of them. Generally, the co-evolutionary process of these three contradictions can be divided into three stages: slow development, moderate development and fast development. The conceptual framework developed in this study can be used to analyze the evolution of similar human-water systems in the world. Moreover, further research should be done through the simulation of the form and cycles of the three contradiction relationships.

Description: The work presented herein addresses the automatic detection of water losses in water distribution networks (WDN), through the dynamic analysis of the time series related to water consumption within the network and the use of a wavelet change-point detection classifier for identifying anomalies in the consumption patterns. The wavelet change-point method utilizes the continuous wavelet transform (CWT) of time-series (signals) to analyze how the frequency content of a signal changes over time. In the case of water distribution networks the time-series relates to streaming water consumption data from automatic meter reading (AMR) devices, at either the individual consumers’ level or at an aggregated district meter area (DMA) level. The wavelet change-point detection method analyzes the provided time-series to acquire inherent knowledge on water consumption under normal conditions at household or area-wide levels, to then make inferences about water consumption under abnormal conditions. The method is demonstrated on several abnormal WDN operating conditions and anomaly detection cases.

Description: This study derives tri-level programming model for multi-reservoir optimal operation in inter-basin transfer-diversion-supply project. Considering the complexity, uncertainty and dynamic nature of the transfer-diversion-supply project, the tri-level programming model is explored in this study to deeply reveal the independency and Inter connectedness of Stackelberg’s decision among transfer, diversion and supply, which is denoted with a set of rule curves of donor reservoirs and recipient reservoirs. Except that the reservoir operation rule can be devised, the model also indicates that it’s possible to establish a greater sustainability. In order to verify the utility of the tri-level programming model, an inter-basin water transfer-diversion-supply project in China is used as a case study. A particle swarm optimization can be easily integrated with simulation models to improve the performance of non-linear optimization. But PSO has premature convergence. IEA has excellent global search performance. So, the IEA-PSO is adopted for optimizing the decision variables. The result shows that the suggested method can achieve operation goal effectively and also improve the operation performance of the inter-basin multi-reservoir system. This article highlights the superior results compared with the current operating control rules.

Description: China is currently facing water scarcity issues, which can partially be relieved with improvements in efficiency in its urban water supply sector. Using a manually collected utility-level dataset for 2009–13, we examine the performance of Chinese urban water utilities, taking into account their regulatory environment. Our main findings are that: (1) an increase in the number of non-technical staff does not increase output levels, while an increase in the number of technical staff, length of pipe or electricity usage can increase output; (2) customer density and non-household user rates are associated with lower levels of inefficiency (or higher levels of measured efficiency), while outsourcing staff rate, non-revenue water rate, and average piped water pressure do not significantly affect efficiency. These results suggest that Chinese urban water utilities can be improved through performance-based regulation and incentives that take into account environmental factors of utilities.

Description: During recent two decades, Artificial Neural Network (ANN) has become one of the most widely used methods in hydrology. One solution for better capturing the existing non-linear and complex nature of data is to develop new hybrid approaches. These hybrid models can be developed in a way that two or more techniques are combined in order to benefit from the advantages of these available approaches and eliminate their limitations. The main scope of this paper is to improve the performance of rainfall-water level modeling by combining ANN with Self Organizing Map (SOM) as an unsupervised clustering method. The proposed method in this study consists of two phases. In the first phase, with the aim of reducing the complexity and dimensionality of input data, a two-step clustering using SOM technique is carried out. Then, in the second phase, separate ANN models are used to model each cluster of data, and final results are obtained by combining the outputs of all models. The proposed new hybrid approach is evaluated using real hydrological data of Johor River. The results of the study indicate that the new proposed SOM-ANN hybrid model has a better performance in daily rainfall-water level forecasting compared to ANN model alone.