Search

The tournament operator genetic algorithm (TGA) often shows poor convergence and easily gets trapped in a local optimum when solving optimized reservoir scheduling problems. The selection operation is the most important operation determining an algorithm's convergence; therefore, this study proposes a proportional reproduction selection-based operator genetic algorithm (RGA) and a steady-state reproduction selection-based operator genetic algorithm (SGA) as alternatives to TGA. This study used TGA, RGA, and SGA to solve the maximum power generation model for the Gezhouba hydropower station, the largest runoff hydropower station in the world. Then, by using the maximum hydropower station output under a given typical runoff scenario as the optimization criterion, this study evaluated the optimized solution performance of the GA using different selection operators. The results show that TGA, SGA, and RGA can be applied to solve the short-term reservoir scheduling model. As the number of iterations increases, the hydropower station output optimized by these three GAs increases. Based on the maximum power generated by the Gezhouba hydropower station, SGA and RGA provide better results than TGA, and between SGA and RGA, the former provides better results. [ABSTRACT FROM AUTHOR]

A method is presented for optimal load dispatch in large-scale hydropower plants using a genetic algorithm integrated with simulated annealing. The genetic algorithm overcomes dependence on an initial value and provides parallel processing and fast convergence, whereas simulated annealing prevents prematurity and retrieving of the local instead of the global optimum. Thus, the integrated genetic-simulated annealing algorithm improves efficiency and robustness to obtain solutions close to the global optimum. We evaluated the proposed algorithm to determine the optimal load dispatch of 32 units of the Three Gorges Hydropower Plant in China. Test results show that the minimum water consumption obtained using the proposed algorithm is similar to the optimum obtained from a previously proposed "improved" genetic algorithm when the total load of the plant is relatively high. However, for reduced load, the proposed algorithm clearly outperforms the "improved" genetic algorithm. [ABSTRACT FROM AUTHOR]

• A new method of online, real-time prediction of downstream water levels is posed. • The Gezhouba Hydropower Plant in China is used as a reregulation case study. • A back propagation neural network-based prediction model is utilized. • Model water level predictions could fully meet real-time station dispatching needs. The forecasting accuracy of downstream water levels greatly impacts the economic operation of reregulating hydropower stations. If present, large errors in water level forecasting may require the hydropower station to discard water, which decreases the revenue from hydropower generation. Especially when the reregulating hydropower station undertakes the task of peak load regulation of the power grid, its power output may change drastically over a short period of time. Such large changes in the discharged flow of the hydropower station may inevitably cause an unsteady flow, which can lead to large fluctuations in the water levels of downstream rivers. In this case, the current forecasting methods, such as standard rating curves and empirical formulae, may inevitably result in large deviations when forecasting the change in the downstream water level. In order to reduce the volume of water discarded as a result of forecasting errors, a back propagation neural network-based forecasting model for downstream water levels of a reregulating hydropower station was constructed. The model enabled the direct, accurate, real-time forecasting of changes in downstream water levels by using measurable operation data from a hydropower station and process data on downstream water level changes. This method was applied to the actual hydropower generation dispatch of the Gezhouba Hydropower Plant in China. The results showed that as the peak load regulation volume increased, the forecasting errors of two conventional methods (standard rating curves and empirical formulae) became continuously superimposed. However, the water level forecasting error of the neural network-based method was small and could fully meet the real-time dispatching requirements of the hydropower station. In particular, under large peak load regulations, the maximum absolute values of the forecasting errors of the two conventional methods were close to 1 m, while that of the neural network-based method could be controlled within 0.3 m. [ABSTRACT FROM AUTHOR]

The joint operation of cascaded reservoirs can generate various compensation benefits. How to calculate all compensation benefits scientifically and fairly, and how to share these benefits reasonably, will be of great importance for the sustainable development of the basin and for the rolling development of a cascaded reservoir of a hydropower station. This article examines the joint operation of Longyangxia and Liujiaxia reservoirs at the upper reaches of the Yellow River in China. To study the reservoir compensation benefits, the authors have built a compensative regulation model for the joint operation of the reservoir group. The electricity generation compensation economic effects of the joint operation of the Longyangxia and Liujiaxia reservoirs in 2005 were calculated. The results showed that the joint operation of cascaded reservoirs can generate remarkable economic benefits. [ABSTRACT FROM AUTHOR]

This paper presents a practical genetic algorithm (GA)-based solution for solving the economic load dispatch problem (ELDP) and further compares the performance of the improved GA (IGA) with that of dynamic programming (DP). Specifically, their performance is comprehensively evaluated in terms of addressing the ELDP through a case study of 26 turbines in the Three Gorges Hydropower Plant with a focus on calculation accuracy, calculation time, and algorithm stability. Evaluation results show that the improved GA method can significantly reduce the ineffectiveness of the GA in current use and could avoid the running of the turbines in the cavitation/vibration zone, thereby ensuring the safety of the turbines during generating operations. Further, the analysis comparing the performance of the IGA and DP show that the IGA is superior to DP when a small number of turbines are involved. However, as the number of turbines increases, the IGA requires more calculation time than DP; moreover, its calculation accuracy and convergence rate are significantly reduced. It is difficult to guarantee the stability of IGA in high-dimension space even though the population grows, on account of the exponential expansion of the calculation dimension, the algorithm’s premature convergence, and the lack of a local search capability. The improvement of the GA as well as the evaluation method proposed in this paper provide a new approach for choosing and improving optimization algorithms to solve the ELDP of large-scale hydropower plants. [ABSTRACT FROM AUTHOR]

In order to ensure economic development, China plans to build fourteen large-scale coal bases during the period of the 13th Five-Year Plan (2015–2020). Coal production and washing, coal-fired power generation, and coal chemistry are the major developing industries in relation to the coal bases. In this study, we predict that by 2020, the newly increased water demand of these three industries will reach 3.8 billion m 3 . Even if water saving measures are reinforced, the newly increased water demand will still be 2.3 billion m 3 . Water resources will become the weak link, restricting the energy industry development of coal bases in areas such as Xinjiang, Ordos, Northern Shaanxi, and Huanglong. In addition, according to current plans, the scale of development for coal bases in water-deficient areas such as Northern Shaanxi, Huanglong, Shendong, Eastern Mongolia, Eastern Ningxia, and Xinjiang is expected to increase substantially. This will drive increased water demand, intensifying competition for water among different industries and regions in the context of a limited capability to guarantee regional water resources. Severe water resources challenge China’s energy development strategies is foreseeable, and if we are to guarantee the water supply required by these coal bases, it is necessary to begin expanding supply and controlling demand now. [ABSTRACT FROM AUTHOR]

To ease the growing water crisis, Tianjin has pioneered the implementation of the most stringent water management system in China. Presently, Tianjin achieves the highest industrial water efficiency in China. In 2010, Tianjin was named the first “Water-Saving Society Construction Demonstration City” by the Chinese central government. To provide a theoretical basis and supporting data for the construction of “national water-saving cities”, a decomposition method is adopted to quantitatively analyze changing industrial water use in Tianjin. Data are decomposed using a refined Laspeyres model, highlighting changes associated with industrial restructuring, followed by detailed sectoral analysis. There are two distinct stages of industrial water use: before 2008, industrial water use decreased, driven predominantly by technological advances; after 2008, higher industrial output led to greater industrial water use that overshadowed the water savings achieved by technological development. Nevertheless, water efficiency showed limited improvement, despite the increasing industrial scale and output of certain industrial sectors. The findings show that in Tianjin, reduced industrial water use is not the primary objective, but an associated combination of industrial development and structural adjustment. [ABSTRACT FROM AUTHOR]

This study identifies the driving forces behind maximizing Tianjin’s industrial water use efficiency in China. For this purpose, a decomposition method is developed to quantify the degree of the impact of each factor. The results show that industrial expansion was responsible for an increase in annual water use of 78 million m³, while technical advances and water efficiency measures contributed annual water savings of about 76 million m³. Further, the results highlight that Tianjin has not considered the rise in water efficiency to be the primary goal of restructuring local industries over the past decade. [ABSTRACT FROM PUBLISHER]

Changes in industrial water use are of the utmost significance in rapidly developing countries. Such countries are experience rapid industrialization, which may stimulate substantial increases in their future industrial water use. Local governments face challenges in formulating industrial policies for sustainable development, particularly in areas that experience severe water shortages. This study addresses the factors driving increased industrial water use and the degrees to which these factors contribute, and determines whether the trend will change in the future. This study explores the options for quantitative analysis that analyzes changes in industrial water use. We adopt both the refined Laspeyres and the Logarithmic Mean Divisia Index models to decompose the driving forces of industrial water use. Additionally, we validate the decomposition results through a comparative study using empirical analysis. Using Tianjin, a national water-saving city in China, as a case study, we compare the performance of the two models. In the study, the driving forces of changes in industrial water use are summarized as output, technological, and structural forces. The comparative results indicate that the refined Laspeyres model may be preferable for this case, and further reveal that output and technology have long-term, stable effects on industrial water use. However, structure may have an uncertain influence on industrial water use. The reduced water use may be a consequence of Tianjin’s attempts to target water savings in other areas. Therefore, we advise the Tianjin local government to restructure local industries towards water-saving targets. [ABSTRACT FROM AUTHOR]

Coal is China's most important primary energy source, and is supporting the rapid economic growth going on there. However, the reverse geographical distribution of coal production and consumption results in a high cost of coal transportation and low efficiency of coal utilization. To ease the pressure on coal transportation, and to mitigate pollution in eastern coastal regions, China has kicked off a strategic west–east transfer of energy industries that requires the movement of coal power projects to the arid northwest regions. Under this strategic framework, the regulation is focused on “clean production”, “consumption reduction” and “reuse”, rather than conservation and protection of water resources. This study found that the northwest areas are unable to accommodate fully the planned scale of coal-fired power industry. Moreover, the subsidiary chemical industry, even if the scale of electric power development is determined according to the need for coal production, is problematic because the current water demand for the coal industry has exceeded “allowed water withdrawal”. Given limited water saving potential and the huge demand-and-supply gap, it is also unrealistic to balance water demand by combination of water conservation in the power industry and water right diversion from agriculture. This study on the synergies between energy and water is urgently needed, in order to provide scientific and technological support for laying out new energy industries. A critical change should involve conciliation of conflicting policies or plans before implementation begins. [ABSTRACT FROM AUTHOR]

Beijing's local water resources have been overexploited and the ecological and environmental pressures exceed the carrying capacity of this densely populated megacity. This article examines the current status of Beijing's water resources with respect to its industrial, residential, and eco-environmental water usage and the challenges it may face in the near future. The article describes the context of water uses, the steps taken by Beijing to alleviate the water shortage problems, and challenges to Beijing's abilities to meet its urgent and future water needs. A multipronged strategy is proposed that aims at both the present problems and the anticipated future challenges. In particular, engineering and institutional approaches for Beijing's successful transition from overexploitation to sustainable utilization of water resources are explained. Actions include reasonable water utilization, water conservation, reclaimed wastewater, and importing water from neighboring areas. We conclude that Beijing must take additional steps in water resource management to ensure its sustainable development that involves continued urbanization sprawls and population growth. Future water resource management strategies should focus on strengthening water demand management through water conservation, efficient interbasin water transfers, use of nontraditional water resources, strategically reserving water supply, and promoting rehabilitation of the eco-environments. [ABSTRACT FROM AUTHOR]

• Improvement of sediment transport capacity of lower reaches of silt-laden rivers. • Performed data analysis, empirical computation, and numerical simulation. • Refinement of reservoir operation for silt transport equilibrium and ecological benignity. • Operation mode optimization of the XiaoLangDi Reservoir in the lower Yellow River. • Achieved siltation reduction and facilitated water storage and sediment discharge. The inverse relationship between water and sediment is hindering the regulation of sediment in silt-laden rivers. Under natural conditions and insufficient water flow, sediment deposits along river channels, resulting in the accumulation of suspended river sediments above the ground level on both sides of the river. Then, during flooding, dam collapse and overflow can easily occur, threatening the life of residents in floodplain. The operation of upstream reservoirs to maximise the sediment transport capacity of downstream rivers into the sea is deemed the best strategy for the management of silt-laden rivers. However, as incoming water and sediment form a dynamic system, optimising the operation mode of reservoirs has become the most severe challenge in the field. This study proposes a method to remodel the water–sediment relationship of natural rivers by optimising the reservoir operation. First, data were collected and analysed to investigate sediment transport in the downstream river channel and the response relationship between erosion–deposition. Then, an empirical equation for calculating the desired incoming sediment was derived, and the threshold for sedimentary transport balance in the lower reach of silt-laden rivers was determined through mathematical modelling. Finally, the reservoir operation mode was optimised within the threshold range to study the discharge process of the reservoir with the highest sediment transport efficiency downstream. The Yellow River in China exhibits the highest sediment concentration worldwide and was used as a case study to verify the practicability of the proposed method. The critical threshold for sediment transport balance in the lower Yellow River was determined to be 250 million tons. The results demonstrate that the proposed method improved the sediment transport capacity of the lower reaches of the Yellow River. Moreover, it reduced the siltation of the XiaoLangDi Reservoir and the lower reaches of the Yellow River. The XiaoLangDi Reservoir can be jointly operated with the Guxian Reservoir, which is under construction and is expected to maintain the bankfull discharge of the lower reaches of the Yellow River at 4000 m3 for a long time. The optimisation process described in this study can be used to improve the management of silt-laden rivers. [ABSTRACT FROM AUTHOR]

This study proposes a novel method to improve the fault identification performance of transformers. First, to couple multiple factors, a high‐dimensional feature map composed of the feature gas concentrations and some associated variables is constructed. Second, the deep residual shrinkage network is revised using the updated alternating direction multiplier, and the newly constructed variable soft thresholding is proposed to eliminate constant deviations. In addition, the fast iterative shrinkage‐thresholding algorithm is adopted, as it can speed up the determination of the threshold. For the output end, the uniform manifold approximation and projection algorithm are adopted to ensure the integrity of the local optimal solution and the global solution. Compared with traditional dissolved gas analysis methods, the novel refined deep residual shrinkage network exhibits superior precision, which is justified through experiments. The results show that the recognition accuracy of the new model is more than 1.3% higher than that of the existing methods. The new method has good scalability in power applications and fault prevention. [ABSTRACT FROM AUTHOR]

Abstract Intense vibrations in hydraulic turbine generator unit draft tubes lead to a run-out of the unit shafting and threaten its safe and stable operation. Correct maintenance is therefore important for the safe operation of such units. This study involves assessing the condition of the turbine generator unit by extracting the feature information of its vibration signals. Based on previous research, we present an enhanced Hilbert–Huang transform (HHT) method with an energy-correlation fluctuation criterion to extract feature information and effectively verify the method with simulated signals. An inspection application based on the signal from a vortex strip in the draft tube of a prototype turbine under suboptimal operating conditions indicates that this method is more effective than the traditional one, with a better component identification capability and better suited to the analysis of the complex and dynamic feature information of hydro turbines. Highlights • Intense vibration in hydraulic turbine generator unit draft tubes leads to a run-out of the shafting of the unit. • It assessed the condition of the unit by extracting information concerning its vibration signal features. • An enhanced Hilbert Huang Transform (HHT) method with an energy-correlation fluctuation criterion was used. [ABSTRACT FROM AUTHOR]

The Middle Route of the South-to-North Water Diversion Project is important for China. Any sudden water pollution accident along the route would threaten normal water supply. We studied four technologies (hydrodynamic and water quality simulation, source identification, emergency regulation, and evaluation of emergency measures) and developed and implemented a decision support system that provides technical support in managing pollution accidents. The achievements, which include four technologies and a system, have practical significance for emergency management in the Middle Route as they can help deal with accidents and policy formulation, and can be applied to other water transfer projects. [ABSTRACT FROM AUTHOR]

Flash floods cause extensive loss of property and human life. Early warning systems present a more efficient approach to flood prevention and mitigation than engineering measures. This article reviews research on flash flood early warnings in China, including long-term prediction methods based on statistical regularity and flood mechanisms, and real-time warning indicators relying on multi-source data and automated systems. Current research shortcomings are discussed, and suggestions for future improvements are proposed. This research can provide public officials with knowledge of flash flood early warnings, influencing policy and protecting people from flash flood disasters. [ABSTRACT FROM AUTHOR]

Calibrating the coefficients of discharge formulas of gates has great significance for the simulation and control of water flow. By investigating three discharge formulas derived from the energy equation and one discharge formula derived from dimensionless analysis of radial gates, the new parameter identification models for these discharge formulas were established using the least squares method, and the coefficients of discharge formulas were obtained. Followed by that, these discharge formulas of radial gates were applied through a case study. The results showed that the mean relative errors of the four formulas were 18.99%, 34.26%, 24.10% and 21.11%, respectively; while the mean relative errors were reduced to 3.54%, 3.54%, 1.90% and 1.09% by the use of parameter identification technique, respectively, indicating that the accuracy was greatly improved. The results proved that the parameter identification method may have potential application to improve the accuracy of calculating the discharge under the radial gates, and can also be applied to the sluice gates. [ABSTRACT FROM AUTHOR]

The presence of native adsorptive substances (NAS) cause uncertainties in the analysis of sediment phosphorus (P) adsorptive capacity. Therefore, HCl washing pretreatment is now used to clean sediment NAS. However, uncertainties still exist because the concentration ( C ) varies widely, from pH 3.5–12 mol/L, among studies. In this study, sediment samples from four sites were washed with HCl at different concentrations ( C ), and then analyzed to evaluate washing effects on the native absorptive substances (phosphorus, metals, and organic matter), the phosphorus equilibrium adsorption capacity (EAC), and sediment skeleton erosion. Study results reveal that washing efficiency, sediment skeleton erosion, and adsorption capacity varied with C . Micromorphology analysis showed that sediment erosion increased with increasing C ; the optimum C value is 0.0–1.0 mol/L (STG1) level based on its small negative impact on the sediment skeleton. Additionally, NAS analysis further showed that washing efficiency increased with increasing C . Most native adsorptive substances (NAP, Fe, Al, Ca, and OM) were released when the HCl concentration was in the range of 0.5–1.0 mol/L. Therefore, 0.5–1.0 mol/L (in STG1) may be the best choice for sediment washing because of its fairly satisfactory washing efficiency. Finally, P equilibrium adsorption capacity (EAC) analysis showed that the sorption capacity varied greatly with C at 0.5–1.0 mol/L, due to the erosion of the sediment skeleton. Therefore, C at 0.5 mol/L is the optimal concentration because the skeleton erosion was minimized when C decreased to the minimum point in the 0.5–1.0 mol/L range. The HCl washing pretreatment ( C = 0.5 mol/L) can also be used for analyzing other basic physicochemical substances (P, Ca, OM, Fe, Al). Our findings are an important step in providing important data for ecological restoration of wetlands, streams, rivers, lakes, and reservoirs, especially for those controlled by the internal source. [ABSTRACT FROM AUTHOR]

Optimizing energy structure to reduce carbon intensity is an effective way to build the low-carbon city development model. To assess the contribution potential of energy structure optimization in order to achieve the carbon intensity target in Hangzhou City, the component data prediction, scenario prediction, GMI (1, 1) model and other multidisciplinary approaches were adopted to predict the carbon intensity trends in the above said City from 2014 to 2020. This contribution potential is evaluated based on 9 kinds of combined scenarios. The results show that: 1. Under the same economic growth rate, with the increase in energy structure adjustment range, the carbon intensity “decline range” becomes larger, and the higher is the “contribution potential” of energy structure optimization to achieve the carbon intensity target. 2. Within the same range of energy structure optimization, the economic growth rate is lower, the carbon intensity “decline range” is smaller, and the “contribution potential” of energy structure optimization is higher for the same carbon intensity objective. By optimizing energy structure and industrial structures adjustment, the technology upgrading for carbon emissions and the scientific and technological level of the systematic industrial policies are more conducive to supporting the realization of low-carbon city. [ABSTRACT FROM AUTHOR]

Macrophyte overgrowth in eutrophic lakes can hasten the decline of shallow water bodies, yet the impact of macrophyte deposition on sediment phosphorus (P) accumulation in the ice-on season remains unclear. Comparative analyses of P variations among 13 semi-connected sub-lakes in Wuliangsu Lake in China, a typical MDE lake, considered external flow and macrophyte decomposition as driving forces. Sediment P fractions and water total phosphorus (TP) were analyzed at 35 sampling points across three ice-on season stages, along with macrophyte TP content to assess debris contributions. Our findings reveal that phosphorus accumulation occurs during the ice-on season in the MDE lake, with an average TP content increase of 16 mg/kg. However, we observed a surprisingly small sediment nutrient accumulation ratio (ΔTP/ΔTN=0.006) compared to macrophyte nutrient levels before decomposition. Further analysis of the dominant species, Potamogeton pectinatus , indicates that a significant portion (55%) of macrophyte phosphorus is released before the ice-on season. This highlights the critical importance of timing macrophyte harvesting to precede the phosphorus leaching process, which has implications for lake management and ecosystem restoration efforts. Additionally, our research demonstrates similar transformations among different sediment fractions as previously reported. Macrophyte debris decomposition likely serves as the primary source of Residual P (Res-P) or TP accumulation. In addition, Ca-bound P (Ca–P) generally showed a decrease, which mainly caused by its transformation to Fe/Al-bound P (Fe/Al–P), Exchange-P (Ex-P), and sometimes to Res-P. However, we emphasize the significant impacts of flow dynamics on Ca–P transport and transformations. Its hydrodynamic action increases water dissolved oxygen, which accelerates the transformation of Ca–P to more easily released Fe/Al–P and Ex-P. Furthermore, hydrodynamic transport also leads to upstream Ca–P transport to downstream. This underscores the necessity of considering flow dynamics when estimating phosphorus variations and formulating phosphorus restoration strategies. [Display omitted] • Phosphorus (P) cycle in macrophyte-dominated eutrophic lakes remain understudied. • Comparatively analyzing P variations among 13 sub-lakes during ice-on season. • Residual P contributes to the P accumulation caused by macrophyte decomposition. • Fifty-five percent macrophyte P have been leached before the ice-on season. • Macrophyte harvesting remains necessary but should be done before P leaching. [ABSTRACT FROM AUTHOR]

In recent years, the optimization community has witnessed a surge in the popularity of population-based optimization methods. However, many of these methods suffer from various shortcomings, including unclear performance characteristics, incomplete validation, excessive reliance on metaphors, inadequate exploration and exploitation components, and compromised trade-offs between exploration and exploitation in real-world scenarios. As a result, users often find themselves needing to extensively modify and fine-tune these methods to achieve faster convergence, stable balance, and high-quality results. To shift the optimization community's focus towards performance rather than metaphorical changes, we propose a general population-based optimization technique called the Great Wall Construction Algorithm (GWCA). This study presents GWCA as a simple yet robust method with competitive performance for efficiently solving constrained and unconstrained problems. GWCA draws inspiration from the competition and elimination mechanisms observed among workers during the construction of the ancient Great Wall. It introduces a mathematical model of the labor movement to simulate the algorithm's dynamics. Unlike other methods that employ multiple models to generate new solutions, GWCA randomly assigns a single predefined motion model to each worker in every iteration. This unique approach showcases GWCA's dynamic nature, simple structure, high convergence performance, and ability to deliver satisfactory solution quality, thus outperforming existing optimization methods in terms of efficiency. To validate GWCA, we conduct extensive comparisons with popular and advanced algorithms on the IEEE CEC 2017 benchmark suite across different dimensions (D = 10, 30, 50, 100). Additionally, GWCA is applied to solve 16 constrained engineering problems and 6 NP-Hard problems, demonstrating its applicability in handling constrained and complex nonlinear problems. Finally, we compare GWCA's optimized solutions with those obtained from 33 advanced meta-heuristic algorithms, including the winner of CEC 2017. The results confirm the effectiveness of the proposed optimizer in solving a wide range of single-objective problems, surpassing popular base optimizers, advanced variants of existing methods, and several CEC winners. We present GWCA as an open-source population-based method that can serve as a standard optimization tool across various domains of artificial intelligence and machine learning. It exhibits a range of exploratory and exploitative features, offering high performance and optimization capabilities. The method is highly flexible, scalable, and can be further extended in terms of structure and application to accommodate diverse forms of optimization scenarios. https://github.com/guangian/Great-Wall-Construction-Algorithm-a-novel-meta-heuristic-algorithm-for-global-optimization. [ABSTRACT FROM AUTHOR]

This study proposes and tests a new approach to detect and analyze changes in flood regime using a distributed hydrological model (EasyDHM), using the Second Songhua River basin, China, as a case study. Model calibration and parameter sensitivity were used to represent flood regimes in a 60-year series (1954-2013), with three different flood regime periods identified. The changes in flood regime were estimated by model parameters, flood result residuals and the overall process in the hydrological model in the three periods. The results show that human activities significantly impacted flood regimes, with significant flood regime change largely attributed to increases in water storage in multiple small reservoirs. Flood volume was reduced significantly between the periods in all three watersheds. The parameters also changed in variety between the periods. The study highlights the importance of incorporating data on small-reservoir constructions in flood control systems. [ABSTRACT FROM AUTHOR]

The completion of Shuibuya, the last hydropower station to be constructed in the Qingjiang cascade, signifies China's successful development of the world's largest mixed cascade hydropower generation system. Joint operation of such cascaded hydropower stations is considered necessary to improve hydropower output in China. In this study, two modeling methods – routine and optimal operations – were adopted, based on existing rules of reservoir operation, to determine the effects of joint operation. To investigate the realistic and potential effects, the two models were computed using observed runoff data (1951–2009). The potential effects were identified by comparing the total hydropower generation two single cascades and their cogeneration. Under the routine operational mode, the incremental power generation of joint operation would be 5.73 × 10 8 kWh, an increase of 5‰ compared to isolated operation. However, even in isolation, if reservoir operation is optimized through the dynamic programming algorithm, the incremental power generation of the cascade would be 42.24 × 10 8 kWh, which is seven times that of joint operation with routine reservoir operation (5.73 × 10 8 kWh). The results showed that, under current reservoir operating rules, there is little room for improvement in hydropower generation, although joint operation could increase hydropower generation to a certain extent, especially in the reservoirs' refill and release stages. China must amend its existing operational mode for reservoirs to enhance the economic benefits of cascade hydropower stations. Furthermore, to meet increasing demands for both water and energy, carefully considered planning of constructing clusters of these stations is required. [ABSTRACT FROM AUTHOR]

China is a country with a serious water shortage. Irrigation water accounts more than 60% of total water use. With the nation’s population forecasted to peak approximately 2030, the production of food for additional people will require more water resources, which exacerbates water shortages. North China is a typical case for studying water-food nexus because water shortage has become a primary factor in restricting food production. From the perspective of virtual water, the study calculates the changing trend of the virtual water (VW) flow related to grain transfer in China, for which three primary crops of China, including rice, wheat and maize, are considered. The results demonstrate the impact of changing the spatial patterns of grain production on water resource utilization is large, and water resources are redistributed related to grain trade. Northern China imports water-intensive products from southern China and exports water-extensive products, and the VW flow from North to South from 2004 to 2013 was approximately 42.6 billion m 3 per year, about 10.2 billion m 3 irrigation water was transferred per year which accounts for about 10% of the water consumption for crop production in the North. Although the South–North Water Diversion Project, a mega-engineering scheme constructed from the Yangtze River Basin to the Huang-Huai-Hai River Basins, alleviates water pressure on the North to a certain extent, it is insufficient for exporting to provinces, and water resources for meeting grain production in the North is problematic. Based on the results, this paper suggests that virtual water flow among provinces should be linked to water resource management. The next step in water management should focus on water demand management, rather than increasing crop trade from the North to the South, which is governed by governmental policies and economy. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the authors discuss several article within the issue on topics which include water challenges for megacities in Asia and North America, water demand and scarcity in Beijing, China, and water quality model.