Ruonan Li

Review on water leakage control in distribution networks and the associated environmental benefits

Water supply is the primary element of an urban system. Due to rapid urbanization and water scarcity, maintaining a stable and safe water supply has become a challenge to many cities, whereas a large amount of water is lost from the pipes of distribution systems. Water leakage is not only a waste of water resources, but also incurs great socio-economic costs. This article presents a comprehensive review on the potential water leakage control approaches and specifically discusses the benefits of each to environmental conservation. It is concluded that water leakage could be further reduced by improving leakage detection capability through a combination of predictive modeling and monitoring instruments, optimizing pipe maintenance strategy, and developing an instant pressure regulation system. The environment could benefit from these actions because of water savings and the reduction of energy consumption as well as greenhouse gas emissions.

Deriving Optimal Daily Reservoir Operation Scheme with Consideration of Downstream Ecological Hydrograph Through A Time-Nested Approach

The ecological flow requirement (EFR) during special life stages of species, for instance the fish spawning period, concerns not only the flow rate, but also daily changes in the flow rate. Therefore, it is more appropriate to optimize ecologically-friendly reservoir operation on a daily base. Directly formulating and solving a daily-based optimization model would involve a large number of decision variables as well as constraints, which may lead to unfavourable time consumption and unreliable solutions. This study proposes a time-nested approach to derive an optimal daily reservoir operation scheme with consideration of the downstream ecological hydrograph. It scales down the decision variables from monthly-base to 10-day base and finally to daily-base. The proposed method was applied to two cascaded reservoirs in the Yalong River in southwest China, where a daily ecological flow is required to conserve the habitats of an indigenous fish Schizothorax chongi (S. chongi). The results showed that the developed method could efficiently derive a daily optimal operational scheme with the consideration of downstream EFR for fish habitat conservation. In addition, the method greatly improves global searching ability in dealing with complex optimization problems.

Optimizing the operation of the Qingshitan reservoir in the Lijiang River for multiple human interests and quasi-natural flow maintenance

For reservoir operation, maintaining a quasi-natural flow regime can benefit river ecosystems, but may sacrifice human interests. This study took the Qingshitan Reservoir in the Lijiang River as a case, and developed an optimization model to explore a trade-off solution between social-economic interests and nature flow maintenance on a monthly base. The objective function considered irrigation, cruise navigation and water supply aspects. An index of flow alteration degree was proposed to measure the difference between the regulated discharge and the natural flow. The index was then used as an additional constraint in the model besides the conventional constraints on reservoir safety. During model solving, different criteria were applied to the index, representing various degrees of alteration of the natural flow regime in the river. Through the model, a relationship between social-economic interests and flow alteration degree was established. Finally, a trade-off solution of the reservoir operation was defined that led to a favorable social-economic benefit at an acceptable alteration of the natural flow.

A Genetic Algorithm Parallel Strategy for Optimizing the Operation of Reservoir with Multiple Eco-environmental Objectives

Optimizing the operation of reservoir involving ecological and environmental (eco-environmental) objectives is challenging due to the often competing social-economic objectives. Non-dominated Sorting Genetic Algorithm-II is a popular method for solving multi-objective optimization problems. However, within a complex search space, the NSGA-II population (i.e., a group of candidate solutions) may be trapped in local optima as the population diversity is progressively reduced. This study proposes a computational strategy that operates several parallel populations to maintain the diversity of the candidate solutions. An improved version of the NSGA-II, called c-NSGA-II is implemented by incorporating multiple recombination operators. The parallel strategy is then coupled into the routine of the c-NSGA-II and applied to the operation of the Qingshitan reservoir (Southwest of China) which includes three eco-environmental and two social-economic objectives. Three metrics (convergence, diversity, and hyper volume index) are used for evaluating the optimization performances. The results show that the proposed parallel strategy significantly improves the solution quality in both convergence and diversity. Two characteristic schemes are identified for the operation of the Qingshitan reservoir for trade-off between the eco-environmental and social-economic objectives.

Uncertainty analyses on the calculation of water environmental capacity by an innovative holistic method and its application to the Dongjiang River

The estimation and allocation of water environmental capacity (WEC) are essential to water quality management and social-economic interests. However, there is inevitable uncertainty in the capacity estimation due to model conceptualization, data collection and parameter calibration. An innovative holistic approach was developed, which took both independence and relevance between parameters into account to analyze the uncertainties in WEC calculation and estimate the margin of safety. The Dongjiang River was taken as the case to demonstrate the method, focusing on the chemical oxygen demand and NH4(+)-N that were the two major water quality problems in the river. The results showed that the proposed holistic approach is very promising and applicable compared to traditional methods of uncertainty analysis.

Ecologically-friendly operation scheme for the Jinping cascaded reservoirs in the Yalongjiang River, China

Ecologically-friendly reservoir operation procedures aim to conserve key ecosystem properties in the rivers, while minimizing the sacrifice of socioeconomic interests. This study focused on the Jinping cascaded reservoirs as a case study. An optimization model was developed to explore a balance between the ecological flow requirement (EFR) of a target fish species (Schizothorax chongi) in the dewatered natural channel section, and annual power production. The EFR for the channel was determined by the Tennant method and a fish habitat model, respectively. The optimization model was solved by using an adaptive real-coded genetic algorithm. Several operation scenarios corresponding to the ecological flow series were evaluated using the optimization model. Through comparisons, an optimal operational scheme, which combines relatively low power production loss with a preferred ecological flow regime in the dewatered channel, is proposed for the cascaded reservoirs. Under the recommended scheme, the discharge into the Dahewan river reach in the dry season ranges from 36 to 50 m3/s. This will enable at least 50% of the target fish habitats in the channel to be conserved, at a cost of only 2.5% annual power production loss. The study demonstrates that the use of EFRs is an efficient approach to the optimization of reservoir operation in an ecologically friendly way. Similar modeling, for other important fish species and ecosystem functions, supplemented by field validation of results, is needed in order to secure the long-term conservation of the affected river ecosystem.

River basin water resource compensation characteristics by set pair analysis: the Dongjiang example

Flood and drought coexist in many river basins, thus analyses of water resource compensation characteristics become important, since they are the foundation for rational utilization of floodwaters. In this research, set pair analysis (SPA), a relatively new uncertainty analysis method, is used to study the dry and wet compensation characteristics of water resource parameters. In addition, fuzzy membership and grey correlation degree are adopted to test the result of set pair analysis. The Dongjiang River is taken as an example and the analyzed parameters include precipitation and mean discharge from different hydrological stations. The results show that there is a high homeotype-encountering chance for precipitation and mean discharge between different stations for both dry and wet conditions; thus the compensation capacity is small. Although the mean discharge is synchronous with the precipitation in the river basin, there exists a certain degree of shift, indicating possible utilization of floodwater on a small scale. The results from SPA are consistent with that from a traditional analysis method, showing that SPA is a promising alternative method for studying river basin water resource compensation characteristics, in particular for exploring potential complements embedded in noncomplementary general features.

A Derivative-Free Hybrid Optimization Model for Short-Term Operation of a Multi-Objective Reservoir System Under Uncertainty

Short-term operation of a multi-objective reservoir system under inflow uncertainty has been receiving increasing attention, however, major challenges for the optimization of this system still remain due to the multiple and often conflicting objectives, highly nonlinear constraints and uncertain parameters in which derivative information may not be directly available. Population-based optimization methods do not rely on derivatives while generally have a slow convergence. This study presents a hybrid optimization model for short-term operation of multi-objective reservoirs under uncertainty that is derivative free and has a relatively fast convergence. The model incorporates a local improvement method called Mesh Adaptive Direct Search (MADS) into a population-based method NSGA-II and has no requirement for differentiability, convexity and continuity of the optimization problem. The operation of a multi-objective and multi-reservoir system on the Columbia River under inflow uncertainty is used as a case study. Overall, the hybrid model outperforms optimization models based on either the NSGA-II only or the MADS only. The model is intended for conditions where derivative information of the optimization problem is unavailable, which could have a wide array of applications in water resources systems.