A thorough understanding of the ecological impacts behind the hydrologic alteration is still insufficient and hinders the watershed management. Here, we used eco-flow indicators, multiple hydrological indicators, and fluvial biodiversity to investigate the ecological flow in different temporal scales. The case study in the Han River shows a decrease in high flows contributed to the decrease in eco-surplus and increase in eco-deficit in summer and autumn, while the decrease in eco-deficit can be attributed to the change of low flow in spring. An integrated hydrologic alteration was over 48% degree and was under moderate ecological risk degree in impact period I, while DHRAM scores showed the Huangzhuang station faced a high ecological risk degree in impact period II. The decrease (increase) in total seasonal eco-surplus (eco-deficit) was identified after alteration with the change in seasonal eco-flow indicators contributions. Shannon index showed a decreasing trend, indicating the degradation of fluvial biodiversity in the Han River basin. Eco-flow indicators such as eco-surplus and eco-deficit are in strong relationships with 32 hydrological indicators and can be accepted for ecohydrological alterations at multiple temporal scales. This study deepens the understanding of ecological responses to hydrologic alteration, which may provide references for water resources management and ecological security maintenance.

After the operation of the Xinglong Water Control Project at Hanjiang River, the low water level near the downstream of the dam has significantly decreased compared to that before the construction of the dam. Under a flow rate of 500-800 m3/s, the cumulative water level under the dam has decreased by 2.47-2.55 m in 2021 compared to that before the operation. Such water level decrease had adverse effects on the safety and efficiency of the Hydro-junction. Based on the observation data of hydrology, cross section and underwater topography, the causes of low water level decline were analyzed. The results showed a limited sediment retention of the Xinglong Water Control Project. Reduction of sediment flux throug Huangzhuang was an important factor enhancing riverbed erosion below Xinglong. The decrease in the probability of dry water reaching the beach during the year caused by high water level regulation, the channel regulation and protection engineering were critical factors of "beach sedimentation and channel erosion" in the process of strong erosion. The direct reasons for the decrease of dry water level in the Xinglong near dam section were the erosion of the low water channel downstream of the dam and the decrease in the lowest water level in Hankou. The random forest algorithm analysis showed that the most critical factor affecting the changes in water level under Xinglong Dam was the sharp decrease of sediment flux at Xinglong Station. In addition, the waterway regulation project and the boundary conditions of the riverbed also played a critical role in the decrease of low water level. The riverbed composition at the Xinglong Dam site and downstream reaches was relatively fine. Although the riverbed was severely eroded from 2012 to 2022, there was no coarsening of the sediment composition. Therefore, it was expected that the riverbed will continue to be eroded and cut down. The low water level has not yet reached a stable state.

基于Budyko框架及径流变化情势指标同气象因子的拟合关系,拓展Budyko方程并得到微分方程.选择汉江上游安康和白河水文站的年均径流、汛期平均径流和非汛期平均径流资料系列,开展径流情势变化及归因研究.结果表明:所有径流指标均发生变异且明显减小;多元对数线性回归模型拟合的相关系数大于0.90,能够较好预估径流变化情势指标,并捕捉到径流变化情势指标同气象参数之间的非线性关系;基于Budyko假设的互补关系法性能优于全微分法,气候(流域下垫面)变化对安康站年均径流量、汛期平均径流量和非汛期平均径流量贡献的绝对值分别为35.89％(64.11％)、34.58％(65.42％)和71.12％(28.88％),对白河站年均径流量、汛期平均径流量和非汛期平均径流量贡献的绝对值分别为34.82％(65.18％)、26.29％(73.71％)和35.11％(64.89％).

Most watersheds around the world have been changing their natural flow patterns because of the coupled effects of climate change and human activities. Understanding the quantitative impacts of projected climate and human factors on future runoff variations is essential for adaptability assessment of water resource management, especially at the seasonal scale where their intra-annual changes are detected. In this study, an extended Budyko framework that combines traditional elasticity and decomposition methods is developed to analyze future sea-sonal runoff variations. The upper reach of the Hanjiang River basin (UHRB) in China is used as a case study. The case results are quantified and compared with the monthly ABCD model using historical hydrometeorological observations over 1961-2020 and near-future climate projections over 2031-2060 from the multi-model ensemble of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b). We find that: (1) human ac-tivities including the operation of the Han-to-Wei inter-basin water transfer (IBWT) and reforestation projects have a substantial negative impact on runoff reduction in this region, accounting for a proportion of-70% in energy-limited seasons and-65% in water-limited seasons; and (2) the role of climate change projected by ISIMIP3b will intensify in energy-limited seasons, especially under the high-emission scenario with the increasing trend of effective precipitation,. Additionally, the performance of our extended Budyko framework is sufficiently robust to parameter disturbance experiments, indicating its applicability as an alternative for exploring future seasonal runoff variations.

根据汉江流域水生态文明特征,以行政单元为评价分区,建立汉江流域水生态文明评价指标体系,包括自然和社会2个系统,山区、平原和水域3种流域地貌单元,水安全、水生态、水环境、水节约、水监管和水文化6类人水关系子系统以及25项指标.引入基于AHP法和熵值法的融合权重,采用模糊综合评价法和灰色关联分析,评价2017年汉江流域水生态文明建设水平.结果表明汉江流域水生态文明建设具有较强的社会属性,二者关联度达0.844,因而呈中下游相对领先、上游略有滞后的空间格局,其中水安全、水环境和水节约是影响水生态文明建设的要因.评价结果可为汉江生态经济带建设发展规划提供参考与依据.

The hydrological cycle, affected by climate change and rapid urbanization in recent decades, has been altered to some extent and further poses great challenges to three key factors of water resources allocation (i.e., efficiency, equity and sustainability). However, previous studies usually focused on one or two aspects without considering their underlying interconnections, which are insufficient for interaction cognition between hydrology and social systems. This study aims at reinforcing water management by considering all factors simultaneously. The efficiency represents the total economic interests of domesticity, industry and agriculture sectors, and the Gini coefficient is introduced to measure the allocation equity. A multi-objective water resources allocation model was developed for efficiency and equity optimization, with sustainability (the river ecological flow) as a constraint. The Non-dominated sorting genetic algorithm II (NSGA-II) was employed to derive the Pareto front of such a water resources allocation system, which enabled decision-makers to make a scientific and practical policy in water resources planning and management. The proposed model was demonstrated in the middle and lower Han River basin, China. The results indicate that the Pareto front can reflect the conflicting relationship of efficiency and equity in water resources allocation, and the best alternative chosen by cost performance method may provide rich information as references in integrated water resources planning and management.

As the water source for the middle route of the South-to-North Water Transfer Project, the Han River in China plays a role of the world’s largest inter-basin water transfer project. However, this human-interfered area has suffered from over-standard pollution emission and water blooms in recent years, which necessitates urgent awareness at both national and provincial scales. To perform a comprehensive analysis of the water quality condition of this study area, we apply both the water quality index (WQI) and minimal WQI (WQI min ) methods to investigate the spatiotemporal variation characteristics of water quality. The results show that 8 parameters consisting of permanganate index (PI), chemical oxygen demand (COD), total phosphorus (TP), fluoride (F-), arsenic (As), plumbum (Pb), copper (Cu), and zinc (Zn) have significant discrepancy in spatial scales, and the study basin also has a seasonal variation pattern with the lowest WQI values in summer and autumn. Moreover, compared to the traditional WQI, the WQI min model, with the assistance of stepwise linear regression analysis, could exhibit more accurate explanation with the coefficient of determination (R 2 ) and percentage error (PE) values being 0.895 and 5.515%, respectively. The proposed framework is of great importance to improve the spatiotemporal recognition of water quality patterns and further helps develop efficient water management strategies at a reduced cost.

确定河流生态流量既是保护河流生态系统的根本举措,又是开展梯级水库生态调度的重要依据.基于逐月最小生态流量法、RVA法、DC法和逐月频率法,分别计算了清江水布垭和隔河岩水库坝址的生态流量过程,并采用Tennant法对结果进行合理性分析.结果表明:RVA法优于逐月最小生态流量法和DC法,计算得到的最小生态流量在一般用水期和产卵育肥期的评价结果分别为"好"、"中"等级;逐月频率法第3种情景计算的适宜生态流量,其评价结果均为"最佳"等级.研究成果为清江流域保护和梯级水库生态调度提供技术参考.

Hydro-meteorological datasets are key components for understanding physical hydrological processes, but the scarcity of observational data hinders their potential application in poorly gauged regions. Satellite-retrieved and atmospheric reanalysis products exhibit considerable advantages in filling the spatial gaps in in-situ gauging networks and are thus forced to drive the physically lumped hydrological models for long-term streamflow simulation in data-sparse regions. As machine learning (ML)-based techniques can capture the relationship between different elements, they may have potential in further exploring meteorological predictors and hydrological responses. To examine the application prospects of a physically constrained ML algorithm using earth observation data, we used a short-series hydrological observation of the Hanjiang River basin in China as a case study. In this study, the prevalent modèle du Génie Rural à 9 paramètres Journalier (GR4J-9) hydrological model was used to initially simulate streamflow, and then, the simulated series and remote sensing data were used to train the long short-term memory (LSTM) method. The results demonstrated that the advanced GR4J9–LSTM model chain effectively improves the performance of the streamflow simulation by using more remote sensing data related to the hydrological response variables. Additionally, we derived a reservoir operation model by feeding the LSTM-based simulation outputs, which further revealed the potential application of our proposed technique.

Water environmental capacity (WEC) is an essential indicator for effective environmental management. The designed low water flow condition is a prerequisite to determine WEC and is often based on the stationarity assumption of low water flow series. As the low water flow series has been remarkably disturbed by climate change as well as reservoirs operation and water acquisition, the stationarity assumption might bring risk for WEC planning. As the reservoir operation and water acquisition under climate change can be simulated by a water resources allocation model, the low water flow series outputted from the model are the simulations of the disturbances and often show nonstationary conditions. After estimating the designed low water flow through nonstationary frequency analysis from these low water flow series, the WEC under the nonstationary conditions can be determined. Thus, the impacts of water resources allocation on WEC under climate change can be quantitatively assessed. The mid-lower reaches of the Hanjiang River basin in China were taken as a case study due to the intensive reservoir operation and water acquisition under the climate change. A representative concentration pathway scenario (RCP4.5) was employed to project future climate, and a Soil and Water Assessment Tool (SWAT) model was employed to simulate water availability for driving the Interactive River-Aquifer Simulation (IRAS) model for allocating water. Water demand in 2016 and 2030 were selected as baseline and future planning years, respectively. The results show that water resources allocation can increase the amount of WEC due to amplifying the designed low water flow through reservoir operation. Larger regulating capacities of water projects can result in fewer differences of WEC under varied water availability and water demand conditions. The increasing local water demand will decrease WEC, with less regulating capacity of the water projects. Even the total available water resources will increase over the study area under RCP4.5. More water deficit will be found due to the uneven temporal-spatial distribution as well as the increasing water demand in the future, and low water flow will decrease, which further leads to cut down WEC. Therefore, the proposed method for determining the WEC can quantify the risk of the impacts of water supply and climate change on WEC to help water environmental management.

Global warming and anthropogenic changes can result in the heterogeneity of water availability in the spatiotemporal scale, which will further affect the allocation of water resources. A lot of researches have been devoted to examining the responses of water availability to global warming while neglected future anthropogenic changes. What’s more, only a few studies have investigated the response of optimal allocation of water resources to the projected climate and anthropogenic changes. In this study, a cascade model chain is developed to evaluate the impacts of projected climate change and human activities on optimal allocation of water resources. Firstly, a large set of global climate models (GCMs) associated with the Daily Bias Correction (DBC) method are employed to project future climate scenarios, while the Cellular Automaton–Markov (CA–Markov) model is used to project future Land Use/Cover Change (LUCC) scenarios. Then the runoff simulation is based on the Soil and Water Assessment Tool (SWAT) hydrological model with necessary inputs under the future conditions. Finally, the optimal water resources allocation model is established based on the evaluation of water supply and water demand. The Han River basin in China was selected as a case study. The results show that: (1) the annual runoff indicates an increasing trend in the future in contrast with the base period, while the ascending rate of the basin under RCP 4.5 is 4.47%; (2) a nonlinear relationship has been identified between the optimal allocation of water resources and water availability, while a linear association exists between the former and water demand; (3) increased water supply are needed in the water donor area, the middle and lower reaches should be supplemented with 4.495 billion m 3 water in 2030. This study provides an example of a management template for guiding the allocation of water resources, and improves understandings of the assessments of water availability and demand at a regional or national scale.

As one of the most crucial indices of sustainable development and water security, water resources carrying capacity (WRCC) has been a pivotal and hot-button issue in water resources planning and management. Quantifying WRCC can provide useful references on optimizing water resources allocation and guiding sustainable development. In this study, the WRCCs in both current and future periods were systematically quantified using set pair analysis (SPA), which was formulated to represent carrying grade and explore carrying mechanism. The Soil and Water Assessment Tool (SWAT) model, along with water resources development and utilization model, was employed to project future water resources scenarios. The proposed framework was tested on a case study of China’s Han River basin. A comprehensive evaluation index system across water resources, social economy, and ecological environment was established to assess the WRCC. During the current period, the WRCC first decreased and then increased, and the water resources subsystem performed best, while the eco-environment subsystem achieved inferior WRCC. The SWAT model projected that the amount of the total water resources will reach about 56.9 billion m3 in 2035s, and the water resources development and utilization model projected a rise of water consumption. The declining WRCC implies that the water resources are unable to support or satisfy the demand of ecological and socioeconomic development in 2035s. The study furnishes abundant and valuable information for guiding water resources planning, and the core idea of this model can be extended for the assessment, prediction, and regulation of other systems.

欧洲中期天气预报中心近年发布了季节性的GloFAS Seasonal径流和SEAS5降水集合预报产品.选取长江上游6个控制站的径流预报及4个分区的面雨量预报为研究对象,通过计算分析AUC、ROCSS和可靠性等指标,评估了这2种产品对于长江上游水库群蓄水期的枯水情景的预报能力.结果 表明:2种产品提前一个月判断枯水雨情的效果较好,但产品倾向过度预测枯水事件发生的可能性,在实际生产运用中需得到重视.研究成果可为基于中长期预报的长江上游水库群提前蓄水调度提供科学依据与技术支撑.

Abstract. Joint and optimal impoundment operation of the large-scale reservoir system has become more crucial for modern water management. Since the existing techniques fail to optimize the large-scale multi-objective impoundment operation due to the complex inflow stochasticity and high dimensionality, we develop a novel combination of parameter simulation optimization and classification-aggregation-decomposition approach here to overcome these obstacles. There are four main steps involved in our proposed framework: (1) reservoirs classification based on geographical location and flood prevention targets; (2) assumption of a hypothetical single reservoir in the same pool; (3) the derivation of the initial impoundment policies by the non-dominated sorting genetic algorithm-II (NSGA-II); (4) further improvement of the impoundment policies via Parallel Progressive Optimization Algorithm (PPOA). The framework potential is performed on China's mixed 30-reservoir system in the upper Yangtze River. Results indicate that our method can provide a series of schemes to refer to different flood event scenarios. The best scheme outperforms the conventional operating rule, as it increases impoundment efficiency from 89.50 % to 94.16 % and hydropower generation by 7.70 billion kWh (or increase 3.79 %) while flood control risk is less than 0.06.

The dataset contains reservoir characteristic parameters, stream-flow series of reservoirs in the upper Yangtze River, the standard operating rules (SORs) and the seasonal top of buffer pools (seasonal TBPs) for these reservoirs, which were provided by the Yangtze River Commission. Moreover, annual hydropower of these reservoirs is tested to evaluate operation performance. These research materials are related to the research article in Advances in Water Resources, entitled 'Optimal impoundment operation for cascade reservoirs coupling parallel dynamic programming with importance sampling and successive approximation' (He et al., 2019). The dataset could be used to derive optimal operating rules to explore the potential benefits of water resources via our proposed algorithm (importance sampling - parallel dynamic programming, IS-PDP) in different runoff scenarios. It can also be further applied for water resources management and other potential users. (C) 2019 The Authors. Published by Elsevier Inc.

随着互联互通时代的兴起,手机成为大学课堂的"熟角",而由于社交需求、搜索服务、个人习惯等多方面的原因,手机已经严重影响到了学生尤其是大学生的课堂学习质量,并给传统授课模式带来了较大冲击.在对大学生课堂上使用手机情况详细调查的基础上,分析出现此现象的原因,并提出从意识树立、文化氛围建设、授课模式革新等不同方面改进该现状,尽可能使手机发挥正面作用.