大型水库重要站点的水位预测是水库防洪中的重要问题,目前主要采用水动力学方法计算。但是由于该方法对输入边界条件的准确性要求较高,而实时调度情况下又很难完全满足此条件,因此容易造成较大的水位计算误差。对此,提出了循环神经网络模型,从水库运行的历史数据中挖掘知识,学习入库流量和坝前水位到目标站点水位的映射关系,不需要使用地形资料等数据以避免系统性误差的影响,既可以降低模型对输入边界准确性的要求,又可以在一定程度上提升水位预测精度。以三峡水库长寿站水位计算为例,使用2009—2019年数据训练、验证和测试模型,试验结果显示长寿站水位在接近三峡水库土地征用线时,计算误差在±0.4 m以内,精度优于水动力学模型,可满足实时调度对水位精度的要求。

The prediction of water level for important stations of large reservoirs is an essential issue in flood control. At present, hydrodynamics method is mainly used to calculate the water level. However, due to the high accuracy requirements of input boundary conditions, which is difficult to meet under real-time dispatching, the calculation error is likely to be large. In view of this, we present a recurrent neural network model to mine the knowledge from historical data of reservoir operation and to learn the mapping relationship between inlet flow (including main stream and tributaries) and the water level from in front of the dam to the target station. This method does not use terrain data to avoid the effect of systematic error, thereby reducing the requirement for input boundary accuracy on one hand and improve prediction accuracy on the other. In the experimental part, we compute the water level of Changshou Station of Three Gorges Reservoir. The data sets (including training, validation and test sets) consist of the operation data from 2009 to 2019. When the water level is close to the land requisition line, the prediction error is within±0.4 m, which is better than the result of water dynamic model. Therefore, the proposed method can meet the accuracy requirement of the real-time scheduling of water level.

地下管网、水系等是城市重要的排水体系,直接决定着城市的洪涝安全。以武汉市光谷中心城为研究区域,采用一、二维耦合的水动力数学模型,进行了不同排水体系组合条件下的多方案城市雨洪模拟,量化分析了地下管网、规划水系建设对城市洪涝灾害的消减效果。结果表明:光谷中心城现状未形成成熟排水体系时,其内涝范围、淹没面积及受灾损失均最大,规划排水体系建设后,区域洪涝淹没面积和受灾损失消减率分别达56.58%,63.74%。由于作用范围及作用方式不同,单独建设水系对区域排涝的作用低于单独建设地下管网的作用。对不同土地利用类型比较,住宅用地减灾效果对城市排水体系的建设最为敏感。当下游湖泊水位较高时,湖泊对水系存在顶托作用,其对区域洪涝灾害影响的程度与河道纵向比降、河堤高程,以及地下管网和河道的连接状况有关。

As important drainage systems, underground pipe networks and water systems directly determine the flood safety in cities. In this study, 1D and 2D hydrological-hydrodynamic coupled numerical models are applied to simulate urban rainstorm of the Central Optical Valley in Wuhan, China in different schemes of factor combinations, such as with or without pipe networks, water system and so on. The abatement effects of urban underground pipe networks and planned water system construction on urban flood disasters are quantified. Results demonstrate that: in the absence of mature drainage system in the Central Optical Valley, the waterlogging scope, flooded area and disaster loss reach the maximum; in the presence of drainage system, the abatement rates of flooded area and disaster loss reach 56.58% and 63.74%, respectively. Due to different scopes and action modes, the effect of separate construction of water system on regional drainage is smaller than that of separate construction of underground pipe network. Among different land use types, the disaster reduction effect of residential land is the most sensitive to the construction of urban drainage system. When the water level of downstream lake is high, the lake has a backwater jacking effect on the water system. Such influence on urban flood disaster is related to river longitudinal slope, river embankment elevation, linkage between underground pipe networks and river channel.

湖泊的水位数据作为评价湖泊变化的重要指标,对于研究区域水资源变化和生态环境状况具有重要意义。但绝大多数高原湖泊位于人烟稀少、自然条件恶劣的高海拔地区,往往难以获取基础观测数据。以卫星测高数据和遥感影像数据为基础,获得2008—2018年库赛湖水位和面积数据,并结合气象数据对水位变化原因进行分析。结果表明:库赛湖水位变化先后主要经历了缓慢上涨(2008—2011年)→急剧上涨(2011年)→趋于稳定(2013—2018年) 3个阶段。2008—2011年是湖泊水位的缓慢上升期,气候暖湿化是主要原因;2011年由于上游卓乃湖发生溢流,水位短时间内急剧上涨;2012—2018年,在接收大量来水后库赛湖也发生外溢,与上下游湖泊串联成一体,水位开始趋于稳定。对水位数据和气象特征因子进行相关性分析,可见湖泊水位与气象因子的变化情况具有较好的相关性,初步分析认为区域降水量增加是库赛湖水位上涨的主要原因,而气候变暖引起的冰川融水增加、冻土水分释放可能是次要原因。

The water level data of lakes, as an important indicator for evaluating changes in lakes, are of great significance for studying regional water resources changes and ecological environment conditions. However, most of the plateau lakes are located at high altitudes where population are sparse and natural conditions are harsh, and it is often difficult to obtain basic observation data. Based on satellite altimetry data and remote sensing image data, we obtained the water level and area data of Kusai Lake from 2008 to 2018, and analyzed the causes of water level change in association with meteorological data. Results manifested that the water level of Kusai Lake had gone through three stages from slow rise (2008-2011) to sharp rise (2011), and then to stabilization (2012-2018). The slow rise in the 2008-2011 stage was mainly triggered by warming and humidification of climate; the sharp rise stage in 2011 was caused by overflow in the upstream of Zhuonai Lake; in the 2012-2018 stage, the water level began to stabilize due to overflow in the Kusai Lake after receiving a large amount of incoming water and hence integrating with the upstream and downstream lakes in series. Correlation analysis of water level data and meteorological characteristic factors showed good correlation between lake level and changes in meteorological factors, and preliminary analysis suggested that the increase in regional precipitation was the main reason for the rise in water level of Kusai Lake, while the increase in glacial meltwater and permafrost moisture release caused by climate warming might be secondary causes.

针对水位时间序列具有线性与非线性混合、不确定性高等特点带来的预测困难问题,提出了一种基于经验模态分解(EMD)、长短时记忆网络(LSTM)和深度极限学习机(DELM)的EMD-DELM-LSTM组合模型,其中DELM和LSTM采用并联结构预测,并与EMD串联连接。首先使用EMD将原始信号分解为若干个具有单一特征的本征模态函数(IMFs),再将IMFs分类重组为高、中、低频信号后输入DELM-LSTM并联结构中进行预测并重构。以广州某大学重要湖泊为例验证模型的有效性,结果表明,与EMD-LSTM、EMD-DELM、LSTM、DELM和BiLSTM模型相比,本模型在不同时间尺度下的预测性能均有显著提升,其中40 min时间尺度下的预测性能提升效果最为明显,分别较对比模型提升43.08%、22.92%、45.79%、30.92%和47.31%。可见,本模型对于不同时间尺度的水位预测具有良好的可靠性和稳定性。

The Mann-Kendall method, moving t-test technique, and wavelet analysis were used to determine the water level mutation point of Dongping Lake, analyze the trend of the annual average water level change, and characterize the daily water level change based on the daily water level sequence of Dongping Lake from 1960 to 2020. The impact of water level change on the spatial evolution of Dongping Lake wetland was discussed. The ecological water level of Dongping Lake was studied using the annual spreading method and the variability range method (RVA) in combination. The results showed that (1) the abrupt change of water level occurred in 1989, and the rise of the water level has caused a significant evolution in the wetland space at the entrance and exit of Dongping Lake; (2) the monthly ecological water levels calculated with the annual spreading methods 1 and 2 before the water level mutation varied between 38.11 and 39.46 m and between 36.94 and 38.24 m, respectively,the monthly protection degree of the ecological water level before the mutation was relatively high, and the water level remained high for a long time after the water level mutation; (3) the ecological water level of Dongping Lake was calculated based on the water level sequence after the abrupt change, the monthly ecological water level calculated by the annual spreading methods 1 and 2 within the year ranged from 39.83 to 40.55 m and from 37.59 to 38.27 m, and the duration of high and low water levels varies greatly in different years; (4) the ecological water level of Dongping Lake calculated with annual spreading method 1 during the year ensured that the wetland will not degrade, at the same time, by combining the underwater elevation of the wetland with the growth period of the reeds, the suitable water level of Dongping Lake can be determined; (5) by setting the dynamic water level of the Dongping Lake flood limit, the Dawen River flood can be resourced and the health of Dongping Lake ecosystem can be guaranteed.

Water level management is an effective tool for the ecological restoration of shallow lakes. In this study, we developed an ecologically-based approach to estimate the monthly suitable ecological water levels (EWLs). This approach took both the lake topographic features and aquatic plants' growth characteristics into account. The aquatic vegetation coverage was used to characterize the degree of the lake ecological restoration. The relationship between water level and vegetation coverage was established. We chose the Tangxun Lake as a testbed, and the recommended lowest EWL was 16.6 m, as the minimum threshold for water level regulations. The results revealed that the predicted vegetation coverage decreased with the rise of water level during the germination period (February and March). To achieve the vegetation coverage goal of 30% and 50%, the lake's water levels must be lowered to 17.1 m and 16.8 m respectively during germination. The EWLs were recommended to be low in spring and high in summer, which was matched with the natural water level regimes. The proposed approach can provide a reliable reference for water level regulation of shallow lakes especially the lakes with insufficient data.

为了使年内展布法更合理的计算季节性河流的生态流量，对原年内展布法进行了改进。以松花江支流西北河为例，基于西北河水文站1956-2016年逐月径流量资料，以90%保证率下各月的径流量代替各月最小径流量，并依据季节、丰枯月份、径流量3种标准分别划分时段，从而计算各划分标准下各时段的同期均值比，结合各月多年平均径流量进而对其生态流量进行计算，得到3种标准下最好的改进方法，使其与原年内展布法进行对比分析，并用Tennant法以及逐月最小径流法和90%保证率法对其结果验证。结果表明，3种标准下计算得出的生态流量与原年内展布法计算得出的生态流量年内变化趋势基本一致，其总体趋势为：改进方法一（按季节划分）＞改进方法三（按径流量划分）＞原年内展布法＞改进方法二（按丰枯月份划分）；与Tennant法及其他水文学方法（逐月最小径流法、90%保证率法）进行对比，改进方法一计算的生态流量较原年内展布法有了较好的改善，其既能够满足鱼类繁衍生存的需求和河流生物生长的需要，又能够保障河流的基本生态功能，因此对年内展布法的改进是合理可行的。综合来看，用改进方法一改进的年内展布法计算生态流量，更能体现河流的变化特征，更符合北方季节性河流生态流量的计算，更适用于西北河生态流量的计算，可以作为河流生态流量研究的一个新思路。

In order to make the annual distribution method more reasonable to calculate the ecological discharge of seasonal rivers, the original annual distribution method was improved. Taking the Northwest River, a tributary of the Songhua River, as an example, based on the monthly runoff data of the Northwest River hydrological station from 1956 to 2016, the monthly runoff at 90% guarantee rate was used to replace the monthly minimum runoff, and the period was divided according to the three criteria of season, abundant and dry months, and runoff, so as to calculate the mean ratio of each period under each partition criteria. The ecological flow was calculated by combining the annual average runoff of each month, and the best improved method under the three standards was obtained, which was compared and analyzed with the original annual distribution method, and the results were verified by Tennant method, monthly minimum runoff method and 90% guarantee rate method. The results show that the ecological flow calculated under the three standards is basically consistent with the annual change trend of the ecological flow calculated by the original year distribution method. The overall trend is: improved method 1 (divided by season) > improved method 3 (divided by runoff) > original year distribution method > improved method 2 (divided by wet and dry months). Compared with Tennant method and other hydrology methods (monthly minimum runoff method and 90% guaranteed rate method), the ecological flow calculated by improved method 1 is better than the original annual distribution method. It can not only meet the needs of fish reproduction and survival and river biological growth, but also guarantee the basic ecological function of the river. Therefore, it is reasonable and feasible to improve the intra-year distribution method. In conclusion, using the improved method - the improved annual distribution method to calculate the ecological discharge can better reflect the change characteristics of the river, conform to the calculation of the seasonal river ecological discharge in the north, and be more suitable for the calculation of the northwest river ecological discharge, which can be used as a new idea for the study of river ecological flow.

为更合理地适应我国季节性河流的径流分布特征，对原有的年内展布法进行改进。在计算河流的生态需水量之前，先对天然径流资料进行三性审查，并依据丰平枯的划分标准划分计算时段，以各时段90%保证率下的多年平均月径流量与该时段多年平均月径流量的比值计算各时段同期均值比，最后结合各月多年平均流量计算生态需水量。以松花江干流上游段的下岱吉断面为例，运用改进后的年内展布法计算该断面的生态需水量，将其计算结果与原年内展布法、最小月平均流量法、流量历时曲线法以及90%保证率法作对比，并用Tennant评价标准评价其计算结果。对比分析后发现，改进的年内展布法计算得出的生态需水量较好地反映了河流径流年内分布特征，符合河流丰平枯的变化规律，且在枯水期能更好满足河道内水生生物的生存需求，整体上更利于河流的生境。

In order to adapt to the runoff distribution characteristics of seasonal rivers in China more reasonably， the original dynamic calculation method is improved. Before calculating the ecological water demand of the river， the reliability， representativity and consistency analysis of the natural runoff data is done， and the calculation period is divided according to the division standard of wet， normal and dry period. Meanwhile， based on the ratio of annual average monthly runoff with 90% guarantee rate and annual average monthly runoff， the ratios of the same periods are calculated， and the ecological water demand can be determined combined with the monthly average runoff. Taking Xiadaiji station in the Songhua River basin as an example， the ecological water demand of the station is calculated by using the improved annual dynamic calculation method. The calculation results are compared with those of the original annual dynamic calculation method， the monthly minimum value method， the flow duration curve method and the 90% guarantee rate method. The Tennant evaluation standard is used to evaluate the calculation results. After comparative analysis， it is found that the ecological water demand calculated by the improved annual distribution method better reflects the annual distribution characteristics of river runoff， which conforms to the changeable rule of river flood. It can also better meet the survival needs of aquatic organisms in the river in the dry period， which is more conducive to the river habitat as a whole.

近年来青藏高原暖湿化加剧了江河源区产汇流和侵蚀输沙过程的变化，而冰冻圈要素的变化使得该过程更加复杂。采用突变检验与IHA-RVA分析了沱沱河1986—2017年径流量和输沙量的变化程度，并基于PLS-PM结合其他环境因子对水沙通量的变化进行归因分析，结果表明：①沱沱河水沙通量于1998年突变后显著增加，整体改变度分别为71.2%和67.5%，为高度改变，表明气候变化对河源区水沙通量的影响不亚于人类活动对中下游的影响。②在气温与降水的驱动下，5~10月水沙通量显著增加，各月变化程度受到土壤、河道冻结程度以及植被变化的影响；年输沙量的变化由极端输沙事件的增加主导，降水量、冰川融水量和土壤解冻程度是主要影响因素。③寒区水沙过程受降水、冰川、土壤冻融及植被的综合影响，有待对其进一步研究以保障青藏高原生态屏障建设与周边区域的可持续发展。

In recent decades, the warming and humidification of the Tibetan Plateau have aggravated changes in the runoff and sediment transport processes in the headwater area, and the uniqueness of the cryosphere has made them more complex. In this study, abruption tests and IHA-RVA were performed to assess the variation in the runoff and sediment flux of the Tuotuo River before and after the abrupt change from 1986 to 2017. PLS-PM attribution analysis was performed using environmental factors for runoff and sediment flux change attribution. The following three important conclusions were drawn: first, from 1986 to 2017, the runoff and sediment flux of the Tuotuo River changed abruptly around 1998, and the overall degrees of change were 71.2% and 67.5%, respectively; both were highly altered. This indicates that the impact of climate change on runoff and sediment flux in the headwater was not smaller than that of human activity downstream. Second, under the influence of temperature and precipitation, runoff and sediment fluxes from May to October increased significantly, and the degree of abruption was affected by the thawing degree of the soil, river channel, and vegetation coverage. The variation in the sediment flux was dominated by extreme sediment transport events, which were primarily caused by increased rainfall, ice melting, and soil thawing. Third, the runoff and sediment processes in cold regions are complex because of the combined influence of rainfall, glaciers, soil freeze-thaw, and vegetation. Therefore, it is necessary to further study the local region's ecological security and sustainable development downstream.