River width and depth as key factors of diurnal activity energy expenditure allocation for wintering Spot-billed Ducks in the Xin'an River Basin

Rivers are important habitats for wintering waterbirds.However,they are easily influenced by natural and human activities.An important approach for waterbirds to adapt to habitats is adjusting the activity time and energy expenditure allocation of diurnal behavior.The compensatory foraging hypothesis predicts that increased energy expenditure leads to longer foraging time,which in turn increases food intake and helps maintain a constant energy balance.However,it is unclear whether human-disturbed habitats result in increased energy expenditure related to safety or foraging.In this study,the scan sample method was used to observe the diurnal behavior of the wintering Spot-billed Duck(Anas poecilorhyncha) in two rivers in the Xin’an River Basin from October 2021 to March 2022.The allocation of time and energy expenditure for activity in both normal and disturbed environments was calculated.The results showed that foraging accounted for the highest percentage of time and energy expenditure.Additionally,foraging decreased in the disturbed environment than that in the normal environment.Resting behavior showed the opposite trend,while other behaviors were similar in both environments.The total diurnal energy expenditure of ducks in the disturbed environment was greater than that in the normal environment,with decreased foraging and resting time percentage and increased behaviors related to immediate safety(swimming and alert) and comfort.These results oppose the compensatory foraging hypothesis in favor of increased security.The optimal diurnal energy expenditure model included river width and water depth,which had a positive relationship;an increase in either of these two factors resulted in an increase in energy expenditure.This study provides a better understanding of energy allocation strategies underlying the superficial time allocation of wintering waterbirds according to environmental conditions.Exploring these changes can help understand the maximum fitness of wintering waterbirds in response to nature and human influences.

Assessment of temporal and spatial variations in water quality using multivariate statistical methods： a case study of the Xin＇anjiang River, China

This study evaluated the temporal and spatial variations of water quality data sets for the Xin＇anjiang River through the use of multivariate statistical techniques, including cluster analysis （CA）, discriminant analysis （DA）, correlation analysis, and principal component analysis （PCA）. The water samples, measured by ten parameters, were collected every month for three years （2008-2010） from eight sampling stations located along the river. The hierarchical CA classified the 12 months into three periods （First, Second and Third Period） and the eight sampling sites into three groups （Groups 1, 2 and 3） based on seasonal differences and various pollution levels caused by physicochemical properties and anthropogenic activ- ities. DA identified three significant parameters （tempera- ture, pH and E.coli） to distinguish temporal groups with close to 76% correct assignment. The DA also discovered five parameters （temperature, electricity conductivity, total nitrogen, chemical oxygen demand and total phosphorus） for spatial variation analysis, with 80.56% correct assignment. The non-parametric correlation coefficient （Spear- man R） explained the relationship between the water quality parameters and the basin characteristics, and the GIS made the results visual and direct. The PCA identified four PCs for Groups 1 and 2, and three PCs for Group 3. These PCs captured 68.94%, 67.48% and 70.35% of the total variance of Groups 1, 2 and 3, respectively. Although natural pollution affects the Xin＇anjiang River, the main sources of pollution included agricultural activities, industrial waste, and domestic wastewater.

Public Policy Supply for Successful Practice of the Xin’anjiang River Ecological Compensation Mechanism

The ecological protection of the inter-provincial river basin of Xin’anjiang River takes the ecological compensation mechanism as the starting point and achieves good results.The success of the mechanism is best reflected in its innovation of public policy supply,which is not only a vivid practice of Xi Jinping’s ecological civilization thought in the new era,but also establishes a model for absorption,transformation and export of policy supply.The effective supply of public policies on ecological environment is the realistic choice for the construction of ecological civilization in the new era.

Hydrological daily rainfall-runoff simulation with BTOPMC model and comparison with Xin'anjiang model

A grid-based distributed hydrological model, the Block-wise use of TOPMODEL （BTOPMC）, which was developed from the original TOPMODEL, was used for hydrological daily rainfall-runoff simulation. In the BTOPMC model, the runoff is explicitly calculated on a cell-by-cell basis, and the Muskingum-Cunge flow concentration method is used. In order to test the model＇s applicability, the BTOPMC model and the Xin＇anjiang model were applied to the simulation of a humid watershed and a semi-humid to semi-arid watershed in China. The model parameters were optimized with the Shuffle Complex Evolution （SCE-UA） method. Results show that both models can effectively simulate the daily hydrograph in humid watersheds, but that the BTOPMC model performs poorly in semi-humid to semi-arid watersheds. The excess-infiltration mechanism should be incorporated into the BTOPMC model to broaden the model＇s applicability.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

Macrobenthic assemblage characteristics under stressed waters and ecological health assessment using AMBI and M-AMBI:a case study at the Xin'an River Estuary,Yantai,China

To understand the ecological status and macrobenthic assemblages of the Xin＇an River Estuary and its adjacent waters, a survey was conducted for environmental variables and macrobenthic assemblage structure in September 2012（Yantai, China）. Several methods are adopted in the data analysis process： dominance index,diversity indices, cluster analysis, non-metric multi-dimentional scaling ordination, AMBI and M-AMBI. The dissolved inorganic nitrogen and soluble reactive phosphorus of six out of eight sampling stations were in a good condition with low concentration. The average value of DO（（2.89±0.60） mg/L） and p H（4.28±0.43） indicated that the research area faced with the risk of ocean acidification and underlying hypoxia. A total of 62 species were identified, of which the dominant species group was polychaetes. The average abundance and biomass was577.50 ind./m^2 and 6.01 g/m^2, respectively. Compared with historical data, the macrobenthic assemblage structure at waters around the Xin＇an River Estuary was in a relatively stable status from 2009 to 2012.Contaminant indicator species Capitella capitata appeared at Sta. Y1, indicating the animals here suffered from hypoxia and acidification. AMBI and M-AMBI results showed that most sampling stations were slightly disturbed,which were coincided with the abiotic measurement on evaluating the health conditions. Macrobenthic communities suffered pressures from ocean acidification and hypoxia at the research waters, particularly those at Stas Y1, Y2 and Y5, which displays negative results in benthic health evaluation.

红水河龙滩水电站区间河系洪水预报方案研究

龙滩水电站是珠江流域防洪控制性工程,但目前缺乏较完整的河系洪水预报方案。为充分发挥龙滩水电站的防洪调蓄作用,选取了雷公滩、沫阳、平里河、平湖和仙人桥等支流控制站点,通过重要子区间分析确定重点关注区域,利用新安江三水源产流模型、三水源滞后演算汇流模型和马斯京根汇流演算法构建龙滩水电站区间河系洪水预报方案。研究结果表明:龙滩水电站最大入库洪水洪量占比通常为无控区间,其次为贵州区支流(蒙江、坝王河、曹渡河、六硐河),两者是洪水预报的关注重点;本研究构建的河系洪水预报方案整体洪峰流量、场次洪量的平均相对误差均为10%,平均确定性系数均在0.75以上,总体结果较好。因此,构建的龙滩水电站区间河系洪水预报方案能够应用于实时洪水作业预报中,也为进一步提升“四预”能力筑牢基础。

1987—2022年新安江水库(千岛湖)水面面积时空变化及其与水位、蓄水量的响应关系

水面面积、水位、蓄水量是水库水资源管理的重要基础数据,遥感是湖库水体提取、水位和蓄水量估算的重要技术手段。由于不同水体提取方法的适用性差异、测高卫星数据的有限时间覆盖度和开源数据集的时空分辨率不足等原因,湖库水面面积、水位、蓄水量的长时序、高频率时空变化监测仍存在一定挑战。本研究以新安江水库为研究区,结合多源遥感、气象、水文和土地利用等数据,基于Google Earth Engine云平台,运用水体指数法,分析1987—2022年新安江水库水面面积时空变化特征,构建水位—水面面积、水位—蓄水量和水面面积—蓄水量响应关系,探究水面面积时空变化成因。结果表明:(1)Landsat 5、Landsat 8和哨兵2号数据的最佳水体提取指数分别为AWEIsh和GNDWI,F1-score分别为91.93%、91.03%和93.14%。相比于开放数据集GSWED(32.61%)、JRC GSW(76.17%)和ReaLSAT(69.76%),基于最优水体指数的水体提取结果具有最高的F1-score(91.26%);(2)时间上,1987—2022年新安江水库水面面积呈显著上升趋势(R^(2)=0.20,P=0.01),总体增长速率为0.96 km^(2)/a;空间上,永久性水体(淹没频率大于75%)面积占比为73.44%,主要分布在湖心等水体开阔区域;季节性水体(淹没频率>25%且≤75%)面积占比为10.17%,主要分布在湖汊区域;(3)三次多项式函数可以较好地模拟新安江水库水位—水面面积、水位—蓄水量和水面面积—蓄水量的响应关系;(4)千岛湖流域上游降水和人类活动导致的土地利用变化是影响新安江水库水面面积动态变化的主要因素。

1960—2020年千岛湖流域蒸散发演变特征及驱动因素解析

为探究淡水湖库及其所属流域蒸散发演变特征,以及气象因子对蒸散发的影响规律。以长三角地区最大的淡水人工湖和重要的水源地--千岛湖为研究对象,采用Penman-Monteith等方法与WEP-L分布式水文模型,分别计算千岛湖流域1960-2020年潜在蒸散发(ET_(0))与实际蒸散发(ET_(a)),分析二者年际变化趋势及突变年份;采用偏微分方法分析气象因子对ET_(0)的敏感性和贡献度;采用归因分析法分析突变前后气象因子对ET_(a)变化的贡献度,并利用蒸发表面水分指数(EM_(1))解析流域蒸发互补关系。结果表明:ET_(0)与ET_(a)多年平均值分别为1021.7和857.5 mm,整体皆呈减少趋势,倾向率分别为-0.77和-1.03 mm/a,二者均在1980和2000年左右发生突变;ET_(0)对相对湿度变化最为敏感,ET_(0)增加的月份主要是由于相对湿度、平均气温的正贡献,风速呈负贡献但相对较小,ET_(0)减少的月份主要是由于日照时数和风速的负贡献,平均气温呈正贡献但相对较小;ET_(a)空间分布呈现东高西低格局,驱动因素按贡献率大小为相对湿度>风速>日照时数>气温;流域整体存在“蒸发悖论”现象,日照时数和风速的减小是引起ET_(0)近年来下降的主要原因;EM1愈趋近于1时,反映流域ET_(0)和ET_(a)取值愈加接近,蒸散发互补理论在千岛湖流域适用。

概念性水文模型与智能模型在中小河流洪水模拟中的比较研究

相较于大江大河的流域水文预报研究,中小流域的研究相对匮乏。以沅江河溪水文站以上流域为例,研究LSTM(Long Short-Term Memory)模型和新安江模型在场次洪水中的模拟效果。通过对比,新安江模型的整体模拟精度较高,洪量、洪峰、峰现时间的平均相对误差分别为9.39%、9.55%、1.6h,确定性系数为0.73,综合合格率为100%,达到甲级精度标准;LSTM模型的模拟精度较低,洪量、洪峰、峰现时间的平均相对误差分别为11.76%、12.33%、2.3 h,确定性系数为0.60,综合合格率为75%,达到乙级精度标准。结果表明,新安江模型和LSTM模型是中小河流洪水预报的有效方法,均可用于河溪流域的正式预报,且对于河溪流域,新安江模型的模拟精度比LSTM模型更高。

流域水资源和生态环境综合治理启示--千岛湖及新安江流域案例

流域生态综合治理对推动流域生态文明建设具有重要意义。文章基于浙江千岛湖及新安江流域水资源与生态环境保护项目,对其在流域水环境综合治理中获得的成果及经验进行总结,并对后续流域生态综合治理提出建议。研究表明,项目采用SWAT模型进行污染特征识别,明确了主要污染形式及来源,给出了针对性生态修复意见,提高了综合治理效率。进而以小流域治理为单元,通过农业面源污染控制、森林生态系统修复、水资源管理等工作修复了流域生态系统。同时,基于《新安江流域水环境补偿协议》及千岛湖水基金,构建了多元化的流域生态补偿机制,为全国生态补偿体系贡献了浙江经验。

机器学习模型在岩溶地区水文预报中的适用性分析

现有岩溶地区的水文预报主要采用基于物理机制的水文模型,而机器学习模型的应用较为罕见。为了探索机器学习模型在岩溶地区水文预报的适用性,以云南省沙甸河流域为研究区,采用了LSTM模型与随机森林模型对倘甸水文站的逐日径流量与场次洪水进行了模拟,并以针对岩溶地区的改进型新安江模型做参照。研究表明:机器学习模型与改进型新安江模型在日径流过程模拟方面都取得较好的效果,LSTM模型模拟效果更优;场次洪水模拟方面,改进型新安江模型达到了甲级预报精度,机器学习模型6 h预见期预报结果整体优于改进型新安江模型,但24 h预见期的预报结果不能满足预报业务的精度需求。对2种机器学习模型和水文模型的特点及预报精度进行的研究,为岩溶地区水文预报工作提供了参考。

基于并行自适应遗传算法的水文模型率定研究

【目的】参数率定是影响水文模型预报精度的重要因素,采用人工智能算法可以有效提高水文模型参数的率定效果。【方法】采用基于种群离散程度的自适应算子,对GA算法的交叉、变异和迁移过程进行自适应优化,并利用粗粒度并行计算模型提高种群进化效率,综合以上手段研究了一种基于自适应策略的并行遗传算法。将传统遗传算法(GA),串行自适应遗传算法(AGA)和并行自适应遗传算法(PAGA),应用于屯溪流域新安江模型的参数率定,从率定效率、率定收敛性、率定稳定性和率定效果四个方面,验证PAGA算法的综合性能。【结果】结果表明:PAGA算法的计算加速效果显著,在10核环境下相对于AGA算法计算时间减少了87.9%;在进化后期,PAGA算法能够更加稳定的收敛于最优解,收敛后的目标函数值具有更好的稳定性;在验证期的场次洪水模拟中,采用PAGA算法率定的模型模拟效果最优,总体洪水合格率大于90%,确定性系数均值为0.85。【结论】PAGA算法能够明显降低模型参数寻优耗时,改善模型率定效果和收敛性能,为水文模型参数的率定提供了新思路。

肇兰新河河流生态系统健康评价及改善对策

为诊断肇兰新河的水环境问题,从水质、底质、水生态状况3个方面开展对肇兰新河流域为期1年(2021年夏季—2022年春季)的系统调研、监测与数据分析。采用多指标综合分析法,构建三层次递阶评价体系,选取物理完整性、水资源与安全、水质等7项指标构建肇兰新河河流生态系统健康综合评价指标体系,评价其健康状况。结果表明:肇兰新河源头青肯泡污染严重,干流沿岸以农业面源污染为主,水生态系统受到人类干扰强度较高,河流生态系统脆弱。肇兰新河河流健康总体评价得分为0.26,介于0.20~0.40,等级评级为“差”,其中河流上游、中游和下游健康总体评价的7个方面得分均低于0.4,部分评分低于0.2,评价等级为“差”或“极差”。从河流管理、水污染控制和水生态修复方面提出治理策略,采取优化断面布设、深度控制污染来源、清淤治理等措施改善肇兰新河生态环境。

基于PSO算法的新安江模型在永宁河洪水预报中的应用研究

根据嘉陵江一级支流永宁河流域的气候特征,利用永宁镇水文站2002-2021年连续20年的逐日水文观测资料,基于粒子群算法(PSO)对新安江模型进行参数率定,基于此对永宁镇水文站日流量进行模拟,探讨该模型在永宁镇水文站洪水预报中的应用。结果表明:新安江模型在永宁镇水文站径流模拟中的成果较好,率定期确定性系数平均值为0.53,合格率为71%,验证期验证期确定性系数平均值为0.59,合格率为100%,模拟成果合格率达到乙级,确定性系数达到丙级预报精度,符合规范要求,可用于该站的洪水预报,为该站洪水预报提出了新的方向,并为新安江模型在嘉陵江上游应用积累了经验。

基于逻辑回归模型的流量计算方法优选

在推求水位流量关系时,不同水流状况适用的计算方法往往不同。为自动优选流量计算方法,以新安江水库库区街口水文站为研究对象,提出了基于逻辑回归模型的流量计算方法优选模型。分别采用二线能坡法和落差指数法进行流量计算,借用逻辑回归模型的大数据分析,依据实时水流状况进行流量计算结果优选,并根据率定结果自我学习,不断优化参数,提升优选准确率。结果表明:新安江水库库区回流状况的准确判定对流量计算结果精度影响较大,模型能够依据实时的上下游水位差、代表线流速等水流状况判断当前水流是否出现回流,从而智能优选流量计算方法。该方法推流结果合理,精度高于单一算法。

新万福河济宁段河道堤防管理的对策措施

河道堤防质量对防洪防汛、资源保护等起着积极的作用,对当地经济水平的提升有着现实意义。文章从新万福河现状着手,从源头出发,分析问题,结合当地区域情况,从管理制度、工程治理、生态修复和信息控制等方面提出建议,旨在提升新万福河河道堤防的综合防御能力。

无资料地区水文模型参数移植不确定性分析

无资料地区降水径流模拟是水文学研究的国际前沿和热点问题。水文模型参数移植是无资料地区降水径流模拟的重要方法,对径流模拟精度具有重要的影响。利用核密度估计和蒙特卡罗随机模拟等方法,构建了一种水文模型参数移植误差驱动的无资料地区径流模拟不确定性定量评估框架。以广西壮族自治区42个有水文监测站点的典型中小河流为研究对象,率定新安江模型参数并模拟日径流和洪水过程,将42个典型流域依次假定为无资料流域,利用基于回归分析、相似流域和机器学习的参数移植方法,模拟无资料地区的洪水过程并识别最优的参数移植方法,分析移植法估算的模型参数值和直接率定值相比误差的概率分布特征,定量评估模型参数移植误差带来的径流模拟不确定性。研究结果表明:(1)基于回归分析的参数移植法模拟无资料地区洪水过程的精度优于相似流域法,优选的机器学习算法比传统回归分析法和相似流域法的计算精度提高了7%~15%;(2)与模型参数率定值相比,移植方法计算的模型参数具有一定的误差,对洪水模拟敏感参数的误差小于不敏感参数;(3)受模型参数移植误差的影响,利用蒙特卡罗法随机模拟的洪水过程具有一定的不确定性,洪量和洪峰相对误差的主要区间分别为10%~30%和10%~40%。相关成果为无资料地区的径流概率模拟及不确定性评估提供了一种新的技术,对中小河流洪水预报与防洪减灾具有一定的支撑作用。