GPM卫星降水产品在长江流域应用的精度估算

为评价GPM卫星降水产品在长江流域的探测精度,利用长江流域224个气象站点2014年4月1日至2017年12月31日的逐日实测降水数据和GPM卫星遥感探测数据,通过相关系数R、平均绝对误差MAE、均方根误差RMSE、相对偏差RB四种指标评价了GPM卫星降水产品在长江流域年、月、日尺度上的探测精度,并运用探测率POD、误报率FAR、偏差率BIAS、公正先兆评分ETS四种指标衡量了GPM对不同量级降水的捕捉能力。结果表明:①年尺度上,GPM卫星与实测降水的R、MAE、RMSE和RB值分别为0.92,0.44,0.57 mm/d和5.68%,表现出较高的探测精度;②月尺度上,GPM卫星在冬夏两季月份与实测值的一致性较差,并明显低估了冬季月份的降水,且对夏季月份的降水估计存在较高误差;③日尺度上,GPM对弱降水的捕捉能力较强,对强降水探测能力较差;④总体而言,GPM在年月尺度上通过表现出较高的相关系数R和较低的MAE和RMSE误差值,显示出比日尺度上更高的探测精度。     

标准化径流指数在阿克苏河水文干旱特征识别中的应用

阿克苏河位于丝绸之路经济带重要通道,是典型的中亚跨境河流,阿克苏丰富的水资源成为沿岸各国争夺的焦点。针对阿克苏河未来水资源评估和管理的迫切需要,以阿克苏河干流月径流为数据基础,结合径流距平百分比,采用标准化径流指数(Standardized Runoff Index,SRI)辨识阿克苏河水文干旱事件,并验证了水文干旱识别的合理性。结果表明:SRI丰枯等级划分临界值在阿克苏河能够有效地识别水文干旱事件及其干旱等级,SRI趋势分析发现未来阿克苏河春、夏季洪水和冬旱现象的可能性在逐渐增大,水资源季节差异将越来越明显,这将是未来水资源合理利用和管理的一个新挑战。     

泾河流域水沙联合分布特征分析及其不确定性评估

径流与泥沙是非独立的二维随机变量,若要对流域实现水沙并举的科学管理方案,开展水沙联合概率分析显得尤为必要。而在联合概率分析中,水沙样本系列容量一般较小,使得联合设计值估计具有不确定性。以泾河流域为例,本文提出基于蒙特卡洛法的两变量联合设计值不确定性量化方法。该方法基于Copula函数建立水沙联合分布模型,推求两变量联合设计值的最可能组合模式,利用蒙特卡洛抽样法分析样本不确定性对水沙联合设计值的影响,计算两变量设计值置信区间。结果表明,OR重现期为20年的情况下,联合设计值95%二元置信区间表现出较大的不确定性,对流域工程设计值的确定提出了巨大挑战,且随着重现期水平的增加,联合设计值的不确定性随之增加。     

Changes in the flow regimes associated with climate change and human activities in the Yangtze River

Hydrologic regimes are increasingly altered under the impacts of climate change and human activities. Streamflow data from 1960 to 2014 were analysed to investigate changes in the flow regimes in the Yangtze River using multiple hydrologic metrics and the Budyko framework. The long‐term data were separated into two periods: the preimpact period (1960–2002) and the postimpact period (2003–2014), according to the year the Three Gorges Dam began operation. The results showed that both indicators of hydrologic alteration and ecoflow metrics were clearly altered. The highly changed indicators included flow in February, annual minimum 1‐, 3‐, 7‐, 30‐, and 90‐day flows, base flow index, date of annual minimum flow, and low pulse duration. The integrated degree of hydrologic alteration ranged from 41% to 61%, indicating a moderate alteration of the flow regimes in the Yangtze River. The regulation of the Three Gorges Dam increased low flow and weakened peak flow, which resulted in autumn ecodeficit and winter ecosurplus increasing dramatically since the 2000s. The ecoflow metrics were more sensitive to precipitation than to potential evapotranspiration. The joint effects of human activities and climate change varied among the river reaches in the different decades. The streamflow was mainly affected by human activities in the upper reach during the 1970s–1990s, with a contribution ratio ranging from 63% to 77%. Climate change shifted to a major contributor in the middle and lower reaches since the 1980s as well as in the upper reach in 2000–2014, accounting for 50–82% of the streamflow changes. These different responses were primarily caused by the variations of precipitation and intensive human activities, particularly the rapid growth of reservoirs and other large projects since the 1970s in the upper Yangtze River. These results provide interesting insights into the spatio‐temporal hydrologic alteration across the Yangtze River.     

Professor Geoffrey Petts (1953–2018): An outstanding interdisciplinary river scientist

This paper provides an introduction and an editorial to this special issue of River Research and Applications by documenting the contributions made by Professor Geoffrey Petts to our interdisciplinary understanding of the functioning of rivers and their floodplains and their sustainable management. We outline Geoff's career, which framed not only his research but its communication through his inspirational teaching but also included very high level and innovative contributions to the management and development of several UK universities. We then explain how and why Geoff was an outstanding interdisciplinary river scientist and how he communicated his science through both integrative books and book chapters and also research papers that developed eight complementary research themes. Lastly, we introduce the papers in this special issue and show how they provide inputs to Geoff's areas of research interest.     

赣江流域非一致性条件下设计洪水估计

赣江流域年最大日径流量在过去60a呈现出显著的变异特征,以此为样本序列,选用广义极值(GEV)分布来对其进行拟合,并基于五种气候模式输出结果对未来设计洪水的变化情况进行分析。所选协变量包括时间t、洪水前N日降水量和下垫面信息。相关关系分析表明,N=10时降水与洪水关系最为密切,但流域内土地利用类型仅呈现出微弱的变化趋势。模拟结果表明,洪水序列服从Weibull分布,其中形状参数ξ=-0.169、尺度参数σ=2 078.9、位置参数μ=65.1c+437.1。非一致性条件下的设计洪水值与传统方法计算的设计值存在很大区别,设计洪水值在1994年要偏大4 000m~3/s以上,其面临的洪水风险要远超普通年份。未来的设计洪水在低、中、高三种排放情景下均呈现出上升趋势,峰值出现于2040年前后,较1994年估计值偏大1 000～2500 m~3/s。     

变化环境下雅砻江流域水文极值演变及不确定性分析

为了探讨环境变化前后雅砻江流域的水文极值演变特征及不确定性,以雅砻江流域雅江水文站和洼里水文站为代表站,基于年极大值和超门限阈值样本,结合序列变异理论、多种极值统计模型(GEV、GPD、P-III)和轮廓似然函数参数估计及不确定性分析方法,分析了变化环境下雅砻江水文极值序列演变特征。结果表明:受气候变化和人类活动的影响,雅江水文站和洼里水文站环境变化前后的最优分布线型由P-III型分布转变为GEV分布。环境变化后的水文极值序列相应设计流量增大,重现期变小。设计值估算中,重现期越长,相应设计流量的不确定性也越大,其中参数的不确定性对于设计值的影响最为显著,但极值选样及分布函数的不确定性也不容忽视。轮廓似然函数法的使用可有效降低设计值不确定性,基于极值理论与轮廓似然函数估计法进行变化环境下水文极值演变分析可提高设计值的可靠性。研究成果可为雅砻江流域水库设计管理及防洪规划等提供参考。     

Monitoring water level and volume changes of lakes and reservoirs in the Yellow River Basin using ICESat-2 laser altimetry and Google Earth Engine

Monitoring the water level and volume changes of lakes and reservoirs is essential for deepening our understanding of the temporal and spatial dynamics of water resources in the Yellow River Basin, with a view to better utilizing and managing water resources. In recent years, there have been many studies on monitoring water level and volume changes in inland waters, but they were mainly focused on radar altimetry and the full waveform LiDAR ICESat, which was retired in 2010. Few studies based on the latest photon-counting LiDAR ICESat-2 have been reported. Compared with previous sensors, ICESat-2 has great advantages in footprint size, transmitting frequency, pulse number, etc, but its performance in monitoring water level and volume changes in inland waters has not been fully explored. Here we investigated the spatial distribution of water level and volume changes of 11 lakes and 8 reservoirs in the Yellow River Basin based on ICESat-2 and Google Earth Engine, and analyzed the factors affecting the measurement uncertainties. In-situ validation of lake level in Lake Qinghai indicates that the Root Mean Square Error (RMSE) of our result is only 7 cm after the reference coordinate system conversion. We found that the water level trend of the natural lake shows significant seasonal variations, while the water level trend of the reservoir shows a sharp rise and fall. In addition, precipitation plays a decisive role in the changes in natural lake levels and indirectly affects the artificial control of reservoirs’ water discharges. The uncertainty of water volume change monitoring is mainly affected by water level measurement uncertainty for lakes, while for reservoirs, that is affected by the combination of water level and area measurement uncertainties. The stability of lake level measurement increases with the increase in photon counts. The introduction of ICESat-2 ATL13 Significant Wave Height might lead larger standard deviation in water level measurement. According to the law of propagation of uncertainty, the uncertainty of the water volume change estimation by the combination of ICESat-2 and GEE is less than 9 %.     

赣江流域洪水峰量演变规律及联合分布研究

为研究赣江流域洪水特征,基于赣江流域外洲水文站1950-2019年共70年逐日流量资料,对年最大洪峰流量和1日洪量进行研究,通过Copula函数研究其洪水峰量联合分布情况。结果表明：赣江洪峰和洪量保持良好的一致性,均呈减少趋势;洪峰和洪量的最优分布均为gamma分布函数;Frank copula函数可以很好的拟合赣江洪峰和洪量的相关关系;洪水单变量重现期为5年一遇时,实际重现期为4.89～5.12年;当单变量重现期为100年一遇时,实际重现期为72.51～161.05年。     

Lake Sturgeon (Acipenser fulvescens) in Goulais Bay,Lake Superior: Cohort strength determinants and population viability

Lake Sturgeon (Acipenser fulvescens) is a species of conservation concern throughout North America, and healthy populations are rare. Earlier sampling efforts identified the Goulais Bay population in Lake Superior as a potentially healthy population after three years of sampling. With seven additional years of sampling, we updated the earlier analysis and developed a matrix population model to conduct a population viability analysis (PVA). We identified a non-linear relationship between cohort strength and May river discharge rate which was incorporated into the population model to evaluate the influence of future discharge scenarios on population persistence. Population size was estimated, with an open-population mark-recapture model, at approximately 5,200 juvenile Lake Sturgeon. This estimate equates to approximately 440 mature females and 625 mature males in the population. A population of this size has a probability of extinction of 4 % and 18 % over 250 and 1000 years under status quo conditions. If the May river discharge were to decrease in the future, which may represent the most likely scenario under future climate conditions, our model predicts an increased risk of population extirpation. This indicates that increased management actions may be required to ensure this population remains resilient.