Evidence of successful river spawning by lake trout (Salvelinus namaycush) in the Lower Niagara River,Lake Ontario

Restoration of a wild-produced lake trout Salvelinus namaycush population in Lake Ontario has not been successful despite the adult population often meeting or exceeding restoration targets. Lack of high-quality spawning habitat in Lake Ontario is suggested as one impediment to recruitment of wild lake trout, although the quantity and location of spawning habitat is poorly understood. If high-quality spawning habitat is limited in Lake Ontario, lake trout may be using uncommon spawning locations such as rivers. Anecdotal angler accounts point to the Niagara River as a lake trout spawning location. To better understand the potential of the Niagara River as a spawning location, egg and juvenile fish collections were conducted 12–14 river kilometers from the mouth of the Niagara River from 2010 to 2012; and mature female lake trout with surgically implanted acoustic tags were monitored from 2015 to 2019. Genetic analyses confirmed 60% of collected eggs and 93% of collected post-hatch juvenile fish in the Niagara River were lake trout. Tagged female lake trout returned to the Niagara River over consecutive years during the spawning season. The short duration of lake trout presence in the river (mean = 56 days/year) suggests female lake trout use the Niagara River primarily for spawning. Diversity in spawning locations may provide lake trout population’s resilience against environmental variability through a portfolio effect. Improved identification of riverine spawning locations, including their overall contribution to wild recruitment, may be a useful tool for managers to restore a wild-produced population of lake trout in Lake Ontario.     

基于LMDI和STIRPAT模型的区域用水影响因素定量分析研究

区域用水影响因素分析对落实最严格水资源管理制度、实现节水型社会建设具有重要意义。为定量表征区域用水变化和影响因素之间的关系,通过LMDI因素分解识别人口规模、经济发展水平、节水技术水平对用水变化的影响程度,采用STIRPAT模型解析用水总量对人口规模、经济发展水平、节水技术水平变化的变动响应关系,以榆林市2000—2017年用水及影响因素变化为例开展了实证研究。结果显示:人口规模和经济发展水平对用水增长起到正向促进作用,节水技术水平起到负向抑制作用。人口规模、经济发展水平、节水技术水平效应依次为8 163.124万m~3、144 238.924万m~3、-126 161.049万m~3;人口规模、经济发展水平、节水技术水平每变化1%,用水将分别变化1.208%、0.061%和0.037%;经济发展水平和节水技术水平是用水变化的主要影响因素,但用水对人口规模变化敏感程度最高。最后,结合榆林市水资源特点提出针对性措施和建议,以期为榆林市水资源规划与管理提供参考。     

冻融循环下云母石英片岩三轴力学特性与强度预测模型

为探究云母石英片岩物理力学特性受冻融循环作用的影响,对饱水云母石英片岩开展了0、25、50、75、100次冻融循环试验,并对试样分别进行了4级围压下的常规三轴压缩试验,研究了其动弹性参数、三轴压缩破坏形式及三轴抗压强度的变化规律,取得如下成果:①随着冻融循环次数的增加,三轴抗压强度、动弹性模量、动剪切模量及动体积模量呈指数衰减,黏聚力及内摩擦角则呈线性衰减趋势;②随着冻融循环的进行,围压对试样强度的增大作用逐渐削弱,冻融循环对试样强度的劣化作用逐渐凸显;③冻融作用使云母石英片岩三轴压缩破坏形态由张拉破坏逐步演化为顺片理剪切破坏;④基于Jaeger破坏准则建立了一种以冻融循环次数、片理面倾角及围压为控制参数的斜交片理云母石英片岩三轴抗压强度预测模型,预测结果与实测数据具有较好的一致性。研究成果可为研究云母石英片岩冻融损伤劣化规律提供参考。     

土石坝工程领域的若干创新与发展

我国高土石坝数量居世界之首,保证高坝大库建设与长期运行安全是国家经济和公共安全保障的重大需求。系统总结了长江科学院近年来在土石坝工程领域的若干创新与发展。提出了基于“旁压模量当量密度法”的粗粒料级配相似理论试验方法;介绍了研发的系列CT三轴仪,实现了粗粒料组构要素的定量测量;提出了三轴试验中加载板与试样之间由滑动摩擦变为滚动摩擦、整体式接触变为分散式接触的减摩新方法,研发了相关减摩装置;研制了大尺寸、高压力、微摩擦、刚柔复合加载的土工真三轴仪;揭示了粗粒料真实三维应力条件下的强度与变形变化规律、湿化与蠕变变形特性;构建了粗粒料三参量非线性K-K-G剪胀模型、六参数湿化模型、九参数蠕变数学模型及相应的参数确定方法;基于当量密度法的原创思想,提出了利用旁压试验间接确定超百米级深厚覆盖层现场密度的试验方法。上述研究成果可为高土石坝工程建设提供重要科技支撑。     

基于TL矩法的洪水频率分布参数估计方法优选

为分析TL矩法在洪水频率分析中的普适性,以陕北地区神木、绥德、杏河、刘家河、黄陵和志丹6个水文站的年最大洪峰流量序列为例,选取广义Pareto分布、广义极值分布和广义Logistic分布,对线性矩法、极大似然法与TL矩法3种参数估计方法进行拟合优度评估。结果表明:除杏河站用广义极值分布外,其他5个水文站的年最大洪峰流量序列用广义Pareto分布拟合效果更佳;与线性矩法和极大似然法相比,TL矩法在各水文站均表现出更佳的拟合效果,是一种洪水频率分布参数估计的较好方法。     

土石坝渗压水位极值预测

渗压水位极值预测是监控土石坝安全的主要途径之一,目前用于渗压水位极值预测方法需给出正确的自变量。渗压水位极值最主要的影响因素是上游水位,当渗压水位极值与上游水位相关性弱时,预测模型准确度低。提出一种仅考虑测值序列、不考虑自变量的渗压水位极值预测及评价方法。该方法基于最大Lyapunov指数建立预测模型,利用马氏链的遍历性和平稳分布对该无自变量模型进行评价。算例表明:对于与自变量相关性弱的渗压水位极值,预测模型的预测效果优于常规方法,误差评估模型评价合理。基于混沌理论和随机过程的预测模型及评价方法能形成一套精度较高、实用性强的序列预测及评价方法,覆盖常规预测方法的弱能力区域,可用于建立自变量不明确的测值序列预测模型。     

旱情预报技术进展与展望

受全球气候变化影响和人类活动的加剧,干旱灾害发生频次增加且强度增大,严重威胁着我国的粮食安全和水安全。准确及时的旱情预报,对于制定科学有效的干旱应对策略、减少灾害造成的损失具有重大意义。从基于数理统计模型的预报技术和基于物理机制模型的预报技术两方面入手,梳理回顾了国内外研究进展,揭示了当前预报技术所存在的问题,并提出针对性的解决方案。未来研究应注重提高干旱监测数据的质量、突破核心关键技术、构建全国旱情预报业务化系统,为抗旱减灾事业提供强有力的科技支撑。     

宁夏汉延渠灌区灌溉水利用系数测算分析与评价

农田灌溉水利用系数表示从水源引水被农作物吸收利用的过程,是反应灌区灌溉用水效率的一项指标。本文以汉延渠灌区为例,综合考虑宁夏的气候环境、土壤类型、灌溉制度及作物种植结构等因素,选取典型渠段和样点灌区,分别采用"连乘法"和"首尾法"计算宁夏汉延渠灌区2018—2019年的灌溉水利用系数,并对其进行对比分析评价,从而确定灌区适宜的计算方法。     

河套盆地晚更新世以来黄河改道对高砷地下水分布的控制机制

针对河套盆地开展了历时多年的水文地质环境地质调查,利用采集的298组浅层地下水样品以及收集并甄选的382个水文地质钻孔记录分析发现:河套盆地内95%的高砷地下水(As质量浓度10μg/L)集中在黄河决口、改道形成的古河道影响带及黄河决口扇裙带。其中,盆地南部首次发现了较为集中的高砷地下水,其分布范围与黄河北岸的晚更新世以来黄河决口、改道形成的4个大型决口扇,在空间上有着良好的对应关系。黄河古河道带及决口扇裙带表现为较强的还原环境及蒸发浓缩作用以及较弱的地表水补给强度。受pH值、含铁氧化物的还原性溶解等因素影响,决口扇裙带浅层地下水中砷的含量略低于平原中部黄河古河道带。结果表明:黄河古河道带及决口扇裙带特定的沉积环境控制着地下水的水文地球化学过程,进而对高砷地下水的分布具有决定性的作用。     

Short-term load forecasting using bayesian neural networks learned by Hybrid Monte Carlo algorithm

This paper presents a short term load forecasting model based on Bayesian neural network (shorted as BNN) learned by the Hybrid Monte Carlo (shorted as HMC) algorithm. The weight vector parameter of the Bayesian neural network is a multi-dimensional random variable. In learning process, the Bayesian neural network is considered as a special Hamiltonian dynamical system, and the weights vector as the system position variable. The HMC algorithm is used to learn the weight vector parameter with respect to Normal prior distribution and Cauchy prior distribution, respectively. The Bayesian neural networks learned by Laplace algorithm and HMC algorithm and the artificial neural network (ANN) learned by the BP algorithm were used to forecast the hourly load of 25 days of April (Spring), August (Summer), October (Autumn) and January (Winter), respectively. The roots mean squared error (RMSE) and the mean absolute percent errors (MAPE) were used to measured the forecasting performance. The experimental result shows that the BNNs learned by HMC algorithm have far better performance than the BNN learned by Laplace algorithm and the neural network learned BP algorithm and the BNN learned by HMC has powerful generalizing capability, it can welly solve the overfitting problem.