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.

Application of TOPMODEL in Buliu River Basin and comparison with Xin’anjiang model

Along with the rapid development of computer and GIS technology, hydrological models have progressed from lumped to distributed models. TOPMODEL, a bridge between lumped and distributed models, is a semi-distributed model in which the predominant factors determining the formation of runoff are derived from the topography of the basin. A test application of TOPMODEL in the Buliu River Basin is presented. For the sake of comprehensively evaluating the TOPMODEL, the Xin’anjiang model, a classic lumped hydrological model, was also applied in the basin. The structural differences and the simulation results of the two models are compared and analyzed.

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.

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.

Flood Forecasting Experiment Based on EC and WRF in the Bailian River Basin

In order to extend the forecasting period of flood and improve the accuracy of flood forecasting,this paper took Bailian River Reservoir which located in Huanggang City of Hubei Province as an example and carried out basin flood simulation and forecasting by coupling the quantitative precipitation forecasting products of numerical forecast operation model of Institute of Heavy Rain in Wuhan(WRF)and the European Center for Medium-range Weather Forecasts(ECMWF)with the three water sources Xin an River model.The experimental results showed that the spatiotemporal distribution of rainfall predicted by EC is closer to the actual situation compared to WRF;the efficiency coefficient and peak time difference of EC used for flood forecasting are comparable to WRF,but the average relative error of flood peaks is about 14%smaller than WRF.Overall,the precipitation forecasting products of the two numerical models can be used for flood forecasting in the Bailian River basin.Some forecasting indicators have certain reference value,and there is still significant room for improvement in the forecasting effects of the two models.

Real-time flood forecasting of Huai River with flood diversion and retarding areas

A combination of the rainfall-runoff module of the Xin’anjiang model, the Muskingum routing method, the water stage simulating hydrologic method, the diffusion wave nonlinear water stage method, and the real-time error correction method is applied to the real-time flood forecasting and regulation of the Huai River with flood diversion and retarding areas. The Xin’anjiang model is used to forecast the flood discharge hydrograph of the upstream and tributary. The flood routing of the main channel and flood diversion areas is based on the Muskingum method. The water stage of the downstream boundary condition is calculated with the water stage simulating hydrologic method and the water stages of each cross section are calculated from downstream to upstream with the diffusion wave nonlinear water stage method. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The faded-memory forgetting factor least square of error series is used as the real-time error correction method for forecasting discharge and water stage. As an example, the combined models were applied to flood forecasting and regulation of the upper reaches of the Huai River above Lutaizi during the 2007 flood season. The forecast achieves a high accuracy and the results show that the combined models provide a scientific way of flood forecasting and regulation for a complex watershed with flood diversion and retarding areas.

微分形式新安江模型

现有新安江模型数学上是代数方程并限于一阶差分方法求解,不可避免存在数值误差,探索数值求解误差控制新途径,对于提高模型计算精度具有重要意义。基于微分系统框架,识别新安江模型的状态变量和通量,推导其控制方程和本构方程,提出微分形式的新安江模型(ODE-XAJ),并采用四阶显式Runge Kutta法求解。数值实验结果显示,以解析解为基准,ODE-XAJ绝对误差处于或小于10^(-4)mm量级,可实现对解析解的高阶近似;以ODE-XAJ结果为基准,按归一化平均绝对误差评价,现有新安江模型的数值求解误差约为8.7%。典型流域应用结果显示,ODE-XAJ确定性系数提升0.02,洪量相对误差降低4.3%。研究表明,ODE-XAJ理论上分离了模型的数学方程与具体解法,可有效控制数值求解误差,提升模型模拟精度。

基于等容瞬时单位线的水文模型研究

流域下垫面空间分布的不均匀性对径流的形成有较大影响,流域蓄水容量曲线解决了流域产流空间异质性的问题,但在采用瞬时单位线进行地表汇流计算时,又将其作为空间分布均匀的净雨处理,局部产流并没有实现局部的汇流。考虑汇流时间与蓄水容量的空间相关性,通过Copula函数构造二者的联合分布,以条件概率的形式反映不同蓄水容量处汇流时间的空间分布特征,进而以等蓄水容量为计算单元,提出了等容瞬时单位线的概念,相当于采用变单位线的方式计算单元产流量的地表径流,从而可以实现局部产汇流计算过程的统一。由此,创建了基于等容瞬时单位线的水文模型IIUHH,并根据Copula函数的类型构建了多种形式的IIUHH,最后选择清江上游作为案例进行验证。结果表明:Clayton型的IIUHH在研究区域表现更优,相比于新安江模型,Nash效率系数可以提高4%~12%,Kling-Gupta效率系数可以提高13%~27%,洪峰相对误差则可降低26%~36%,较大程度上提高了洪峰和洪水过程的模拟精度。研究成果可为流域高精度径流预报提供技术支撑。

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。

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。

基于SWAT与新安江模型场次洪水模拟研究及评估

中小河流洪水大多位于资料短缺的山丘区,具有突发性强,汇流时间短的特点,已成为当前防洪工作的重点和难点。新安江模型和SWAT(Soil and Water Assessment Tool)模型都是应用广泛的水文模型,但其在中小河流洪水模拟中的对比分析及效果评估方面还鲜有研究。以北潦南河为例,建立了日尺度和小时尺度的新安江模型和SWAT模型,评估2种模型在径流深、洪峰流量和峰现时间等关键要素方面的计算效果,分析各自优缺点。结果表明,在率定期间,新安江模型相对径流误差(RRE)、洪峰流量相对误差(RPE)和峰现时间误差(PTE)平均值分别为-2.6%、-4.3%、-0.3 h, SWAT模型RRE、RPE和PTE平均值分别为-4.3%、-3.3%、-0.1 h,新安江模型在RRE方面优于SWAT模型,但SWAT模型在RPE、PTE和多峰洪水模拟方面则优于新安江模型;在验证期得出了与率定期相同的结论。

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。

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。

考虑融雪及土壤冻融的新安江模型及其应用——以雅砻江上游径流模拟为例

寒区为中国大江大河的主要产流区,其径流预报精度直接影响下游水利工程调度和水资源科学管理。针对传统概念性水文模型较少考虑积雪融雪及土壤冻融过程对径流的叠加影响这一问题,以新安江模型为基础,以降水量和气温为驱动数据,提出了基于“等效土壤温度”和“土壤冻融特征曲线”的概念性土壤冻融模块来刻画积雪融雪及土壤冻融共同影响下的流域产流过程,构建了考虑融雪产流和土壤冻融的新安江模型。以雅砻江甘孜水文站以上流域为典型研究区,开展了流域2017—2022年冰雪消融期逐小时的径流模拟分析。结果表明,相比于HBV模型,考虑融雪产流和土壤冻融的模型可以显著提升流域冰雪消融期的水文模拟精度,各年份消融期径流的纳什效率系数中位数由0.69提升至0.83,相关系数中位数由0.88上升至0.92。本研究所提出的考虑融雪及土壤冻融的新安江模型可以为寒区的水文业务预报提供科学支撑。

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。