气候变化影响下极端水文事件的多变量统计模型研究

以黄河流域太原气象站和淮河流域鲁台子水文站为研究对象,利用Copula函数构建气候要素（降水）同极端水文事件（干旱和洪水）之间的多元统计模型,分析不同降水条件下不同等级干旱和洪水的发生概率变化。结果表明,Gumbel Copula能够较好地描述太原站7月份的前期累加降水量和帕默尔干旱指数（PDSI）的相关结构。随着降水量的增加,极端干旱的发生概率逐渐减小,重旱、中旱和轻旱的发生概率则先增加后减小。Clayton Copula能够较好地描述鲁台子水文站前期累加降水量和洪峰流量之间的相关结构。当前期累加降水量大于等于某一定值时,随着年最大洪峰x的增大,发生洪峰≥x的极端洪水事件的概率逐渐减小。在同一个极端洪水发生概率下,前期累加降水量越大,洪峰流量出现大值的可能性越大。     

基于卫星遥感的太湖蓝藻水华时空分布规律认识

由于大尺度水文模型和无资料区水文研究是当前国际水文研究的重点和难点,通过参数区域化方法来估计大尺度区域和无资料区的模型参数值成为了研究的热点之一将HBV模型应用于东江流域及其子流域,采用代理流域法和全局乎均法来估计该区域内无资料流域的模型参数研究表明：HBV模型能较好得用于东江流域径流模拟;交叉检验中,较小的序和ME值对应的参数,其转移效果不一定比较大的R^2和ME值对应的参数转移效果差;全局平均法中,面积权重平均值和泰森多边形插值后平均并不能明显改进子流域算术平均值估计无资料流域的模型参数的模拟结果;两者都能有效用于东江流域无资料流域的参数估计,且效果相差不大。     

Runoff change of Naoli River in Northeast China in 1955–2009 and its influencing factors

Runoff change and trend of the Naoli River Basin were studied through the time series analysis using the data from the hydrological and meteorological stations. Time series of hydrological data were from 1957 to 2009 for Bao′an station, from 1955 to 2009 for Baoqing station, from 1956 to 2009 for Caizuizi station and from 1978 to 2009 for Hongqiling station. The influences of climate change and human activities on runoff change were investigated, and the causes of hydrological regime change were revealed. The seasonal runoff distribution of the Naoli River was extremely uneven, and the annual change was great. Overall, the annual runoff showed a significant decreasing trend. The annual runoff of Bao′an, Baoqing, and Caizuizi stations in 2009 decreased by 64.1%, 76.3%, and 84.3%, respectively, compared with their beginning data recorded. The wet and dry years of the Naoli River have changed in the study period. The frequency of wet year occurrence decreased and lasted longer, whereas that of dry year occurrence increased. The frequency of dry year occurrence increased from 25.0%-27.8% to 83.9%-87.5%. The years before the 1970s were mostly wet, whereas those after the 1970s were mostly dry. Precipitation reduction and land use changes contributed to the decrease in annual runoff. Rising temperature and water project construction have also contributed important effects on the runoff change of the Naoli River.     

树轮记录的自公元1200年以来强火山喷发事件与高亚洲南部河流源区气候水文变化的关联

强火山喷发作为气候变化重要的外强迫因素,其所造成的气候环境效应一直是气候变化研究热点,而其对于流域水循环影响较少受关注。本文利用采自高亚洲南部河流源区麦吊云杉（Picea brachytyla）树轮样本,研制出一个长达885 a的树木年轮标准宽度年表。基于树轮气候响应分析结果,利用线性回归模型重建研究区自公元1200年上年11月至当年2月平均最低气温变化,重建方程方差解释量47.1%。该气温重建序列显示,研究区自公元1200年经历了8个冷期和9个暖期,包含有10个极冷年和23个极暖年。同时,该气温重建序列验证了自公元1200年来27次强火山喷发（VEI≥5）对于青藏高原东南部河流源区气候的影响,包括1257年Samalas和1815年Tambora等强火山喷发事件。该气温重建序列与相关河流径流数据对比结果表明强火山喷发在引起高亚洲南部河流源区气温出现明显下降的同时,也可能会进一步导致水循环减缓,使得高亚洲南部河流径流量出现减少。

     

一种旋转塑性势面模型及非关联塑性流动法则

为了较好地描述软土塑性应变发展规律,提出了一种改进的塑性流动模型。该模型采用了与屈服函数形式相同,但具有一定倾角γ的塑性势函数。土体在变形过程中,塑性流动方向会依赖于塑性势面的旋转而变化,直至达到破坏状态。通过对常规三轴试验结果的分析可以发现:在剪切过程中,塑性势面旋转角的初值γ₀与终值γ_d较为稳定,不受围压变化影响。在此试验观察基础上,引入了归一化的旋转角参数γ’以及描述土体应力状态的参数ξ,在采用蛋形势函数的情况下二者具有良好的分段线性关系。利用该关系,建立了改进的塑性流动法则,只需要2个额外的模型参数。对所提出的塑性流动模型进行了验证,计算结果表明该模型能较好地反映塑性应变的变化趋势。     

滇东断陷盆地南洞岩溶地下水系统地下河水文动态特征与资源量评价

本文对滇东断陷盆地南洞岩溶地下水系统各地下河的水文动态特征进行了分析,推断了南洞岩溶地下水系统的结构特征.根据岩性构造、地下河发育以及补径排关系,将其划分为四个子系统.分别采用降雨入渗系数法和径流模数法对南洞岩溶地下水系统的天然资源量进行计算,计算结果分别为35610.7万m3/a和33460.2万m3/a.用枯季径流模数法对南洞岩溶地下水系统的可采资源量进行了计算,计算结果为23407.3万m3/a,其可开采资源量巨大.南洞地下河在没有天然补给量的情况下,120天消耗的调蓄量为4503.3万m3,南洞地下河日允许开采资源量为49.4万m3/d.二号暗河建库蓄水条件下库区上游的日允许开采量为75.9万m3/d,蓄水库容来源于工程设计,资源保证程度高.本次研究可为南洞岩溶地下水资源的开发利用和调配提供科学依据.     

Modelling surface runoff to evaluate the effects of wildfires in multiple semi‐arid,shrubland‐dominated catchments

Wildfires change the infiltration properties of soil, reduce the amount of interception and result in increased runoff. A wildfire at Northeast Attica, Central Greece, in August 2009, destroyed approximately one third of a study area consisting of a mixture of shrublands, pastures and pines. The present study simultaneously models multiple semi‐arid, shrubland‐dominated Mediterranean catchments and assesses the hydrological response (mean annual and monthly runoff and runoff coefficients) during the first few years following wildfires. A physically based, hydrological model (MIKE SHE) was chosen. Calibration and validation results of mean monthly discharge presented very good agreement with the observed data for the pre‐wildfire and post‐wildfire period for two subcatchments (Nash–Sutcliffe Efficiency coefficient of 79.7%). The model was then used to assess the pre‐wildfire and post‐wildfire runoff responses for each of seven catchments in the study area. Mean annual surface runoff increased for the first year and after the second year following the wildfires increased by 112% and 166%, respectively. These values are within the range observed in similar cases of monitored sites. This modelling approach may provide a way of prioritizing catchment selection with respect to post‐fire remediation activities. Additionally, this modelling assessment methodology would be valuable to other semi‐arid areas because it provides an important means for comprehensively assessing post‐wildfire response over large regions and therefore attempts to address some of the scaled issues in the specific literature field of research. Copyright © 2015 John Wiley & Sons, Ltd.     

The role of climate change and human interventions in affecting watershed runoff responses

Identifying the role of the two main driving factors—climate change and human interventions—in influencing runoff processes is essential for sustainable water resources management. For this purpose, runoff regime change detection methods were used to divide the available hydroclimatic variables into a baseline and a disturbed period. We applied hydrological modelling and the climate elasticity of runoff method to determine the contribution of climate change and human interventions to changes in runoff. The hydrological model, SWAT, was calibrated during the baseline period and used to simulate the naturalized runoff pattern for the disturbed period. Significant changes in runoff in the study watershed were detected from 1982, suggesting that human interventions play a dominant role in influencing runoff. The combined effects of climate change and human interventions resulted in a 41.3 mm (23.9%) decrease in runoff during the disturbed period, contributing about 40% and 60% to the total runoff change, respectively. Furthermore, analysis of changes in land cover dynamics in the watershed over the past four decades supported these changes in runoff. Contrary to other decades, the discrepancy between naturalized and observed runoff was small in the 2010s, likely due to increased baseflow as a result of storage and/or release of excess water during the dry season. This study contributes to our understanding of how climate change and human interventions affect hydrological responses of watersheds, which is important for future sustainable water management and drought adaptation.     

Using raw regional climate model outputs for quantifying climate change impacts on hydrology

General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.     

Soil property variation mapping through data mining of soil category maps

Spatial information on soil properties is an important input to hydrological models. In current hydrological modelling practices, soil property information is often derived from soil category maps by the linking method in which a representative soil property value is linked to each soil polygon. Limited by the area‐class nature of soil category maps, the derived soil property variation is discontinuous and less detailed than high resolution digital terrain or remote sensing data. This research proposed dmSoil, a data‐mining‐based approach to derive continuous and spatially detailed soil property information from soil category maps. First, the soil–environment relationships are extracted through data mining of a soil map. The similarity of the soil at each location to different soil types in the soil map is then estimated using the mined relationships. Prediction of soil property values at each location is made by combining the similarities of the soil at that location to different soil types and the representative soil property values of these soil types. The new approach was applied in the Raffelson Watershed and Pleasant Valley in the Driftless Area of Wisconsin, United States to map soil A horizon texture (in both areas) and depth to soil C horizon (in Pleasant Valley). The property maps from the dmSoil approach capture the spatial gradation and details of soil properties better than those from the linking method. The new approach also shows consistent accuracy improvement at validation points. In addition to the improved performances, the inputs for the dmSoil approach are easy to prepare, and the approach itself is simple to deploy. It provides an effective way to derive better soil property information from soil category maps for hydrological modelling. Copyright © 2014 John Wiley & Sons, Ltd.