近30年洞庭湖季节性水情变化及其对江湖水量交换变化的响应

江湖水量交换的变化影响着通江湖泊洞庭湖的水情,进而影响湖区社会经济及生态的可持续发展.以洞庭湖城陵矶站、南咀站以及长江干流宜昌站、螺山站1981-2012年逐日水位、流量观测数据为基础,采用单位根检验、方差分析和水位-流量绳套曲线等方法对洞庭湖季节性水情变化特征进行提取,并探究江湖水量交换变化对其产生的影响.研究表明:近30年来洞庭湖水情呈阶段性特征,与相对稳定的1981-2002年相比,2003-2012年湖泊水位总体呈下降趋势,年均水位下降0.43 m;枯、涨、丰、退水期各季水情变化特征为:2003年以后洞庭湖丰水期水位平均下降0.60 m,呈现出"高水不高"现象;退水期水位平均下降1.49 m,退水加快;枯水期水位略有上升,平均上升0.18 m;涨水期水位变化不明显.湖泊退水期水位降幅最为明显,尤其是10月大幅下降,平均下降2.03 m,有提前进入枯水期的趋势.水情变化与江湖水量交换变化密切相关:丰水期,三口(松滋、太平和藕池)分流量减小在一定程度上降低湖泊水位;退水期,三口分流量减小叠加城陵矶出口长江水位下降对洞庭湖产生拉空作用,湖泊出流加快水位被拉低;枯水期,主要是1 3月,城陵矶出口长江水位上升对湖泊顶托作用增强,湖泊出流减缓水位略有抬升.     

近100年来长江与洞庭湖汇流河段水文特征演变

洞悉长江洞庭湖汇流河段的水文关系及其变化规律对确保长江中下游的防洪安全至关重要.为了掌握汇流河段水文特征演变情况,本文结合汇流河段处监利、城陵矶、螺山等国家重要水文控制断面的近百年水文资料,通过M-K检验、Morlet小波分析等方法研究了该河段逐日水位、流量等水文数据,分析了汇流河段年内分配、年际变化、变化趋势、突变点及变化周期等水文特征,并探讨了具体成因.研究结果表明:①长江与洞庭湖汇流河段年最高水位一般出现在7月,年最低水位一般出现在1、2月;②汇流河段年径流量主要集中在59月,占年径流总量的63.64%~73.44%;③近50年城陵矶水位高、中、低水分别约抬升0.98、0.56、1.46 m;④近10年城陵矶与监利年径流比降至0.66.⑤在长江中下游水利开发历程中,经突变检验表明,下荆江裁弯取直和三峡蓄水175 m对江湖水文特征的影响较为明显.⑥城陵矶站和螺山站的年径流量、水位平均周期约为16 a,监利站的年径流量、水位平均周期约为8 a.⑦19542017年间,汇流比最大值一直在降低,其发生时间在逐渐提前.以上成果为深入研究流域复杂的江湖演变规律提供了科学参考.     

三峡水库运行对洞庭湖水位影响分析

洞庭湖的水情是长江和四水共同作用的结果,三峡蓄水运行必将导致洞庭湖的水情变化.本文利用BP神经网络对洞庭湖出口城陵矶站的水位过程进行模拟,以区分城陵矶水位变化中三峡的影响分量.模型训练阶段以三峡出库日均流量、洞庭湖四水合成日均流量为输入,城陵矶站的日水位过程为输出,应用阶段用三峡入库流量代替出库流量,从而还原自然状态下...     

洞庭湖近30a水位时空演变特征及驱动因素分析

洞庭湖地处北亚热带季风湿润气候区,水情时空变化尤为明显.为了探明洞庭湖水位时空演变特征,以洞庭湖6个水位站(城陵矶、鹿角、营田、杨柳潭、南咀、小河咀)、出入湖流量("三口"总入湖流量、"四水"总入湖流量、城陵矶出湖流量)和长江干流流量(宜昌、螺山)等1985-2014年逐日数据为基础,通过构建泰森多边形计算湖泊水位,运用Morlet小波分析、层次聚类分析和地统计理论研究湖泊水位的周期性变化规律及空间分布格局和自相关性.研究结果表明:洞庭湖水位变化具有典型的季节性,且年际变化具有28和22 a的多时间尺度特征;水位空间分布格局呈现出小河咀、南咀、杨柳潭(Group 1)以及城陵矶、鹿角、营田(Group 2)两种聚类,且在不同水文季节的空间自相关性依次表现为丰水期退水期涨水期枯水期.通过建立两类水位在不同水文季节与径流量的多元逐步回归模型揭示了洞庭湖水位时空演变的驱动因素,其中Group 1水位演变主要受长江干流水文情势的影响,Group 2水位演变由出入湖径流量和长江干流径流量共同作用,并随着不同水文季节江湖关系的改变以及湖泊自身水力联系的变化而变化.研究结果对于科学认识洞庭湖水位的时空演变规律以及湖泊生态系统保护和水资源的规划、管理与调控具有重要意义.     

三峡水库175 m试验性蓄水期调度运行对洞庭湖蓄水量变化的影响

长江干流与洞庭湖存在复杂的并联型分汇关系,当三峡水库调度改变长江径流过程时,会引起洞庭湖年内槽蓄量的变化,对于洞庭湖地区防洪、水资源配置和水环境保护产生显著的影响.本文建立了枝城至螺山站的荆江-洞庭湖水流模型,利用2008-2017年的三峡水库实际调度日数据,分析有、无三峡水库调度两种情况下洞庭湖槽蓄量的变化过程,同时利用建库前和近期的水位流量关系反映河道过流能力,分析了河道调整的影响.结果表明:由河道调整引起的槽蓄量变化在汛前消落期、汛期、汛末蓄水期和枯水期分别为-3.06%、0.12%、-0.01%和-13.31%.有三峡水库影响情况下,汛前消落期由于荆江"三口"进入洞庭湖的多年平均总径流增加23.94%,洞庭湖出口处城陵矶多年平均水位升高0.53 m,阻碍了洞庭湖出流,洞庭湖多年平均槽蓄量增长13.30%;汛期由于荆江"三口"分流量减少3.54%,城陵矶水位降低0.02 m导致出湖流量增多,因此洞庭湖多年平均槽蓄量减少0.20%;在汛末蓄水期,荆江"三口"分入洞庭湖的多年平均总径流量减少37.18%,城陵矶多年平均水位降低1.33 m,导致出湖流量增多,因而洞庭湖多年平均槽蓄量减少27.74%;在枯水期,荆江"三口"多年平均总径流量增加5.61%,城陵矶多年平均水位上升0.07 m,最终洞庭湖多年平均枯期槽蓄量增加2.96%.     

洞庭湖生态水位及其保障研究

湖泊生态水位是维持湖泊生态系统健康的重要因素.基于洞庭湖城陵矶、杨柳潭、南咀3个水文站1959-2016年日平均水位序列进行分析,采用Mann-Kendall法、累积距平法和滑动T检验法综合确定洞庭湖水位变异时间节点,结合生态水位年内展布法以及IHA-RVA法,计算分析湖泊最小和适宜生态水位,并且采用Tennant法进行合理验证,在此基础上对水文变异前、后湖泊生态水位保障度进行研究.研究结果表明:(1)洞庭湖城陵矶和杨柳潭水文站年均水位呈上升趋势,而且城陵矶站水位上升趋势显著,南咀站年均水位呈显著下降趋势.(2)洞庭湖3个典型水文站水位年际变化突变年份为2003年,突变年份基本上与三峡工程蓄水时间相符.(3)城陵矶、南咀和杨柳潭年均最小生态水位分别为21.41、28.95和27.84 m,分别占多年平均水位的86.3%、95.9%和95.7%,城陵矶、南咀和杨柳潭年均适宜生态水位分别为23.29、29.51和28.36 m,分别占多年平均水位的93.9%、97.8%和97.5%,生态水位计算结果考虑了天然湖泊水位年内丰枯变化,满足了湖泊生态目标需求.(4)洞庭湖最低生态水位保障程度较高,基本能达到80%以上,但适宜生态水位保障程度相对较低,其中2003年以后洞庭湖10月和11月生态水位保障程度显著下降,与上游水利工程蓄水有关,建议在此期间采取调度措施适当增加洞庭湖水量,以保障湖泊生态系统的健康与生物多样性.     

三峡工程运行对鄱阳湖水位影响试验

三峡工程运行改变了长江中下游水沙情势,影响了鄱阳湖湖区水位,造成了水资源利用、水质、湿地和生态等方面的新问题.实测日水位资料分析认为:湖区水位年内变化可分为低水、涨水、顶托倒灌和退水4个阶段;顶托倒灌阶段湖区水位基本由长江干流控制,另外3个阶段湖区水位受湖口流量和长江干流的共同影响,受影响程度与水位站位置、湖口流量和长江干流相互作用强弱有关;三峡工程运行没有改变鄱阳湖水位"高水湖相、低水河相"的基本特征,但对水位造成了一定影响.开展物理模型试验探索三峡工程运行对湖区水位的影响程度,结果表明:蓄水期三峡工程运行造成湖区水位降幅较大,枯水年都昌站平均(最大)降幅为0.94 m(2.58 m),枯水年湖区水面面积减小68%;增泄期会增加湖区水位,都昌水位最大增幅约1 m,平水年湖区面积增加约32%;枯水期三峡工程运行对鄱阳湖水位基本无影响.     

洞庭湖水面面积与城陵矶水位之间的绳套关系

洞庭湖是我国第二大淡水湖,与长江连通,在防洪抗旱和湿地生态保护等方面具有重要的现实意义.采用Terra/MODIS L1B遥感数据,提取了2000-2012年洞庭湖水面面积,结合同期城陵矶水位观测数据,建立了城陵矶水位与洞庭湖水面面积的绳套关系曲线.分析结果表明:2000-2012年间,洞庭湖水面面积呈现总体减少的趋势;在季节上表现为规律性的涨落,具有明显的涨(4-6月)-丰(7-9月)-退(10-12月)-枯(1-3月)的水文特征;在空间格局上表现为由湖体中心向外扩张,随后由外向湖体中心逐渐收缩的变化过程;洞庭湖水面面积与城陵矶水位之间具有较高的相关性,但不同时期的相关系数存在一定的差异:枯水期二者相关性较低,丰水期相关性最高,涨水期和退水期相关性较高;这种差异与各个时期的主导因素不同有关,长江来水对枯水期、丰水期的绳套关系影响较大,其中东洞庭湖最为明显;不论丰水年(2002年)或干旱年(2011年),洞庭湖水面面积变化与城陵矶水位之间的相关性均较高.研究结果对于深入认识江湖关系的宏观复杂性、长江中下游地区以及洞庭湖水域洪涝灾害的预防和治理都具有积极的意义.     

从防御2020年长江洪水看新时代防洪战略

长江防洪是国家水安全的重要部分.2020年受持续强降雨影响,7月长江中下游沿线及洞庭湖、太湖水位长时间超警戒水位,太湖超保证水位,鄱阳湖湖区部分站点达到历史最高水位;8月长江上游岷江和嘉陵江发生特大洪水,重庆等沿江城市部分地区被淹,防汛压力和灾害损失大.社会舆论持续关注,并对三峡等水库调控提出一些质疑.文章从应对1954年洪水、1998年洪水与2020年洪水比较,分析长江防洪格局变化,提出新时代长江防洪总体战略仍然应该坚持"蓄泄兼筹,以泄为主".在工程体系方面,以堤防为基础,以三峡等控制性水库为重要调控手段,加快推进重点蓄滞洪区安全建设,保证行洪区畅通,维护好洲滩生态环境质量.在非工程措施方面,加强适应气候变化的洪水风险管理,规范防洪区土地利用方式,给洪水以空间,推动洪水风险图及洪水保险制度,将常遇洪水可适应、特大洪灾风险可承受作为防洪体系建设的最终目的.     

[专稿]近年长江中下游径流节律变化、效应与修复对策

近十余年长江上游大量兴建大型水库,蓄水、调节和拦沙对中下游河川径流和泥沙产生了深刻影响.河川径流减少,径流季节提前,伏秋（特别是10月）流量显著降低、变差系数增大,97%严重干旱频率情景变成80%~85%.同时,宜昌和出海输沙量分别减少93%和70%,中下游河槽冲刷下降1~3 m,三峡蓄水后仅13年清水冲刷幅度和范围已超过三峡预期30年的冲刷上限,目前仍呈加速趋势.干流各站平均水位下降2~4 m,与此同时河道同流量洪水位反而升高.水库调节是水位降低的主要原因,河道冲刷更加剧水位降低,当前水位变化对防洪和生态都不利.汛后流量和干流水位提前降低使洞庭湖和鄱阳湖（两湖）提前干枯、松滋等"三口"入湖水量减少,伏秋高热季节两湖生态环境面貌发生了根本变化.汛后流量减少甚至显著增加长江大通十月流量小于15000 m³/s几率和上海长江水源受咸潮影响风险,10月咸潮入侵变成最严重时段必须引起高度重视.我们认为,径流和径流节律变化是当前长江生态环境最主要问题之一.建议以"水资源工程"重新定位上游大型工程、以"水资源优先"优化流域管理和切实回归既定三峡工程运行原则等统一调度和改善中下游水情;通过水库挖泥等措施修复长江物质通量,抑制中下游剧烈冲刷和稳定河流格局;加强中下游蓄滞洪区等防洪能力建设,为最大限度降低上游水库防洪和蓄水压力创造条件;主要通过改善上游水库调度维护两湖环境条件,"引清水入洞庭"和"增加供水设施建设"加强两湖适应能力.这是长江修复和保护重点.     

德都台地磁观测与温度影响关系的分析

选用德都台2011—2012年的地磁基线值数据,来分析绝对观测数据、相对记录数据和温度数据对基线值的影响。通常基线值的主要影响因素除温度外,还与人为观测误差、湿度和记录墩的稳定性有关。首先保证绝对观测固定为同一人员,确保人为观测误差忽略不计,再排除湿度与记录墩的不稳定性,最后利用回归分析计算方法,得到基线值数据与温度数据的回归方程,并对该方程进行显著性检验,表明地磁基线值与温度之间存在良好的线性关系,再以此回归方程来判断我台地磁数据的好坏,为更好的改进我台地磁观测数据质量提供依据。     

Regionalization of unit hydrograph parameters: 1. Comparison of regression analysis techniques

Hydrologic regionalization is a useful tool that allows for the transfer of hydrological information from gaged sites to ungaged sites. This study developed regional regression equations that relate the two parameters in Nash's IUH model to the basin characteristics for 42 major watersheds in Taiwan. In the process of developing the regional equations, different regression procedures including the conventional univariate regression, multivariate regression, and seemingly unrelated regression were used. Multivariate regression and seeming unrelated regression were applied because there exists a rather strong correlation between the Nash's IUH parameters. Furthermore, a validation study was conducted to examine the predictability of regional equations derived by different regression procedures. The study indicates that hydrologic regionalization involving several dependent variables should consider their correlations in the process of establishing the regional equations. The consideration of such correlation will enhance the predictability of resulting regional equations as compared with the ones from the conventional univariate regression procedure.     

Regionalization of unit hydrograph parameters: 1. Comparison of regression analysis techniques

Hydrologic regionalization is a useful tool that allows for the transfer of hydrological information from gaged sites to ungaged sites. This study developed regional regression equations that relate the two parameters in Nash's IUH model to the basin characteristics for 42 major watersheds in Taiwan. In the process of developing the regional equations, different regression procedures including the conventional univariate regression, multivariate regression, and seemingly unrelated regression were used. Multivariate regression and seeming unrelated regression were applied because there exists a rather strong correlation between the Nash's IUH parameters. Furthermore, a validation study was conducted to examine the predictability of regional equations derived by different regression procedures. The study indicates that hydrologic regionalization involving several dependent variables should consider their correlations in the process of establishing the regional equations. The consideration of such correlation will enhance the predictability of resulting regional equations as compared with the ones from the conventional univariate regression procedure.     

Regionalisation of the parameters of the log‐Pearson 3 distribution: a case study for New South Wales,Australia

The index flood method is widely used in regional flood frequency analysis (RFFA) but explicitly relies on the identification of ‘acceptable homogeneous regions’. This paper presents an alternative RFFA method, which is particularly useful when ‘acceptably homogeneous regions’ cannot be identified. The new RFFA method is based on the region of influence (ROI) approach where a ‘local region’ can be formed to estimate statistics at the site of interest. The new method is applied here to regionalize the parameters of the log‐Pearson 3 (LP3) flood probability model using Bayesian generalized least squares (GLS) regression. The ROI approach is used to reduce model error arising from the heterogeneity unaccounted for by the predictor variables in the traditional fixed‐region GLS analysis. A case study was undertaken for 55 catchments located in eastern New South Wales, Australia. The selection of predictor variables was guided by minimizing model error. Using an approach similar to stepwise regression, the best model for the LP3 mean was found to use catchment area and 50‐year, 12‐h rainfall intensity as explanatory variables, whereas the models for the LP3 standard deviation and skewness only had a constant term for the derived ROIs. Diagnostics based on leave‐one‐out cross validation show that the regression model assumptions were not inconsistent with the data and, importantly, no genuine outlier sites were identified. Significantly, the ROI GLS approach produced more accurate and consistent results than a fixed‐region GLS model, highlighting the superior ability of the ROI approach to deal with heterogeneity. This method is particularly applicable to regions that show a high degree of regional heterogeneity. Copyright © 2014 John Wiley & Sons, Ltd.     

Suspended sediment concentration controlling factors: an analysis for the Argentine Pampas region

ABSTRACT

In the Argentine Pampas region, there is little information about sediment concentration in agricultural catchments. The aims of this work are: (1) to analyse fluctuations in sediment concentration and discharge, as a first attempt to characterize hysteresis patterns; and (2) to study sediment concentration controlling factors and to assess the importance of these factors using principal component analysis and a multiple regression model. Twenty-five events registered during 4 years in a 560 ha gauged basin of Argentina were studied. Analysis of data suggested a positive clockwise pattern. The multiple regression model was performed with three factors obtained by principal component analysis: runoff, precipitation and antecedent conditions. The model explained 83% of the variability of sediment concentration. The runoff factor contributed to modelled sediment concentration with the highest magnitude, followed by precipitation and antecedent condition factors. Although the watershed is under conservation tillage, rill erosion seems to be the main source of sediment concentration.

Editor M.C. Acreman; Associate editor X. Fang     

The separation of the influence of nutrients and climate on the varve time-series of baldeggersee, Switzerland

The varve data-set from a freeze-core taken in the deepest part of Baldeggersee was subjected to different multivariate statistical analyses in order to estimate the amount of variance in the varve thickness measures explicable by past climate and by the trophic state of the lake. A comparison of two different time-periods (1902 to1992 versus 1920 to 1980) revealed that the lake restoration programme since 1982 has had a significant impact on the formation of the seasonal layers. Results of the partitioning of the variance in the varve thickness measures showed that about two thirds of the variance are unexplained by a climate and trophic state model and that trophic state explains 6%, whereas climate accounts for about 28% of the variance before the effect of lake restoration had a strong impact on the varves. Among the climate parameters the amount of annual precipitation is a strong predictor for explaining the thickness of both dark layer and total couplet thickness, whereas summer precipitation is important for the thickness of the light layer.     

精河定点形变受气象因素影响探索

收集整理新疆精河地震台数字化形变资料和该地区的气象要素观测资料,利用相关和回归分析,研究精河定点形变与气象要素之间的关系和气象因素对精河数字化形变观测资料的影响特征,并给出精河数字化形变观测资料与气象要素之间的回归方程.     

Differences in throughfall drop size distributions in the presence and absence of foliage

ABSTRACT

Throughfall drop size distributions (DSDs) are important for plant–soil interactions. This is the first known study to quantify differences in throughfall DSDs with the presence and absence of foliage. Employing a disdrometer, three parameters solely representing throughfall drip were measured and calculated: maximum drop diameter (D_MAX), median volume diameter of drops (D₅₀D_R) and relative volume percentage of drops (pD_R). Beneath Liriodendron tulipifera L. in Maryland (USA), D_MAX, D₅₀D_R and pD_R were substantially larger when the canopy was unfoliated. In fact, the presence or absence of foliage was one of the primary factors affecting all three throughfall DSDs along with air temperature, according to the boosted regression tree analysis. Experimental results were attributed to differing physical properties of intercepted water between foliated and unfoliated periods and differential water behavior on leaves and bark. Future work should examine the effects of concentrated drip points on the development of throughfall-induced hot spots.

Editor M.C. Acreman; Associate editor F. Hattermann     

Classifying the flow regimes of Mediterranean streams using multivariate analysis

Rivers in the Mediterranean region often exhibit an intermittent character. An understanding and classification of the flow regimes of these rivers is needed, as flow patterns control both physicochemical and biological processes. This paper reports an attempt to classify flow regimes in Mediterranean rivers based on hydrological variables extracted from discharge time series. Long‐term discharge records from 60 rivers within the Mediterranean region were analysed in order to classify the streams into different flow regime groups. Hydrological indices (HIs) were derived for each stream and principal component analysis (PCA) and then applied to these indices to identify subsets of HIs describing the major sources of variations, while simultaneously minimizing redundancy. PCA was performed for two groups of streams (perennial and temporary) and for all streams combined. The results show that whereas perennial streams are mainly described by high‐flow indices, temporary streams are described by duration, variability and predictability indices. Agglomerative cluster analysis based on HIs identified six groups of rivers classified according to differences in intermittency and variability. A methodology allowing such a classification for ungauged catchments was also tested. Broad‐scale catchment characteristics based on digital elevation, climate, soil and land use data were derived for each long‐term station where these data were available. By using stepwise multiple regression analysis, statistically significant relationships were fitted, linking the three selected hydrological variables (mean annual number of zero‐flow days, predictability and flashiness) to the catchment characteristics. The method provides a means of simplifying the complexity of river systems and is thus useful for river basin management. Copyright © 2015 John Wiley & Sons, Ltd.     

Modeling the potential distribution of shallow-seated landslides using the weights of evidence method and a logistic regression model： a case study of the Sabae Area, Japan

A number of statistical methods are typically used to effectively predict potential landslide distributions. In this study two multivariate statistical analysis methods were used （weights of evidence and logistic regression） to predict the potential distribution of shallow-seated landslides in the Kamikawachi area of Sabae City, Fukui Prefecture, Japan. First, the dependent variable （shallow-seated landslides） was divided into presence and absence, and the independent variables （environmental factors such as slope and altitude） were categorized according to their characteristics. Then, using the weights of evidence （WE） method, the weights of pairs comprising presence （w^＋（i）） or absence （w^-（i））, and the contrast values for each category of independent variable （evidence）, were calculated, Using the method that integrated the weights of evidence method and a logistic regression model, score values were calculated for each category of independent variable. Based on these contrast values, three models were selected to sum the score values of every gird in the study area. According to a receiver operating characteristic curve analysis （ROC）, model 2 yielded the best fit for predicting the potential distribution of shallow-seated landslide hazards, with 89% correctness and a 54.5% hit ratio when the occurrence probability （OP） of landslides was 70%. The model was tested using data from an area close to the study region, and showed 94% correctness and a hit ratio of 45.7% when the OP of landslides was 70%. Finally, the potential distribution of shallow-seated landslides, based on the OP, was mapped using a geographical information system.