近50年鄱阳湖五大流域降水变化特征研究

基于鄱阳湖流域在江西省内部分对应的79县市气象站1960～2006年逐日降水观测资料,采用线性回归的方法分别研究五大流域的年降水量、降水日数、暴雨日数等3要素的变化趋势,并用Mann法进行了变化趋势的显著性检验,用距平与均方差之比达到15和20作为气候异常检验指标,对各流域的各时间序列进行了异常检验,采用了Mann Kendall法对各时间序列进行突变检测。结果表明：（1）各流域的年降水量变化趋势基本一致,年降水量与年暴雨日数密切相关;饶河流域强降水事件较多,降水强度大,赣江中游流域降水时间分布相对较均匀,强降水事件较少;（2）各流域年降水量、暴雨日数总体呈波动上升趋势,20世纪90年代以来暴雨日数异常偏多的概率最大;（3）年降水日数以20世纪80年代中期为界,之前呈波动上升趋势,之后呈波动下降趋势,2002年至今各流域降雨日数明显偏少;（4）各流域的年降水量、降水日数、暴雨日数均未出现趋势性的突变;（5）近50年来鄱阳湖流域降水时间分布不均的情况加剧,旱涝灾害风险增加。     

Influence of temporally variable groundwater flow conditions on point measurements and contaminant mass flux estimations

Monitoring of contaminant concentrations, e.g., for the estimation of mass discharge or contaminant degradation rates, often is based on point measurements at observation wells. In addition to the problem, that point measurements may not be spatially representative, a further complication may arise due to the temporal dynamics of groundwater flow, which may cause a concentration measurement to be not temporally representative. This paper presents results from a numerical modeling study focusing on temporal variations of the groundwater flow direction. “Measurements” are obtained from point information representing observation wells installed along control planes using different well frequencies and configurations. Results of the scenario simulations show that temporally variable flow conditions can lead to significant temporal fluctuations of the concentration and thus are a substantial source of uncertainty for point measurements. Temporal variation of point concentration measurements may be as high as the average concentration determined, especially near the plume fringe, even when assuming a homogeneous distribution of the hydraulic conductivity. If a heterogeneous hydraulic conductivity field is present, the concentration variability due to a fluctuating groundwater flow direction varies significantly within the control plane and between the different realizations. Determination of contaminant mass fluxes is also influenced by the temporal variability of the concentration measurement, especially for large spacings of the observation wells. Passive dosimeter sampling is found to be appropriate for evaluating the stationarity of contaminant plumes as well as for estimating average concentrations over time when the plume has fully developed. Representative sampling has to be performed over several periods of groundwater flow fluctuation. For the determination of mass fluxes at heterogeneous sites, however, local fluxes, which may vary considerably along a control plane, have to be accounted for. Here, dosimeter sampling in combination with time integrated local water flux measurements can improve mass flux estimates under dynamic flow conditions.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Evaluation of a Watershed Model for Estimating Daily Flow Using Limited Flow Measurements1

Abstract: The Soil and Water Assessment Tool (SWAT) model was evaluated for estimation of continuous daily flow based on limited flow measurements in the Upper Oyster Creek (UOC) watershed. SWAT was calibrated against limited measured flow data and then validated. The Nash‐Sutcliffe model Efficiency (NSE) and mean relative error values of daily flow estimations were 0.66 and 15% for calibration, and 0.56 and 4% for validation, respectively. Also, further evaluation of the model’s estimation of flow at multiple locations was conducted with parametric paired t‐test and nonparametric sign test at a 95% confidence level. Among the five main stem stations, four stations were statistically shown to have good agreement between predicted and measured flows. SWAT underestimated the flow of the fifth main stem station possibly because of the existence of complex flood control measures near to the station. SWAT estimated the daily flow at one tributary station well, but with relatively large errors for the other two tributaries. The spatial pattern of predicted flows matched the measured ones well. Overall, it was concluded from the graphical comparisons and statistical analyses of the model results that SWAT was capable of reproducing continuous daily flows based on limited flow data as is the case in the UOC watershed.     

混凝法深度处理印染废水中试研究

采用"高效混凝沉淀-过滤"深度处理工艺处理印染废水二级生化出水,并将混凝沉淀污泥回流.实验结果表明,混凝剂聚合氯化铝加入量为160 mg/L时,COD去除率平均可达34.6%,TP去除率平均达到87.9%,平均出水TP为0.3 mg/L.气相色谱-质谱分析和元素分析结果表明混凝沉淀工艺对有机物和TP的去除效果良好.     

Estimating the variance in before-after studies

Problem

To simplify the computation of the variance in before-after studies, it is generally assumed that the observed crash data for each entity (or observation) are Poisson distributed. Given the characteristics of this distribution, the observed value (x_i) for each entity is implicitly made equal to its variance. However, the variance should be estimated using the conditional properties of this observed value (defined as a random variable), that is, f(x_i|μ_i), since the mean of the observed value is in fact unknown.

Method

Parametric and non-parametric bootstrap methods were investigated to evaluate the conditional assumption using simulated and observed data.

Results

The results of this study show that observed data should not be used as a substitute for the variance, even if the entities are assumed to be Poisson distributed. Consequently, the estimated variance for the parameters under study in traditional before-after studies is likely to be underestimated.

Conclusions

The proposed methods offer more accurate approaches for estimating the variance in before-after studies.     

全球升温1.5℃与2.0℃情景下长江中下游地区极端降水的变化特征

基于长江中下游地区1961~2100年区域气候模式COSMO-CLM(CCLM)模拟与1961~2005年气象站观测的逐日降水数据,通过统计计算年降水量、强降水量、暴雨日数和极端降水贡献率4个极端降水指数,研究全球升温1.5℃与2.0℃情景下,长江中下游地区极端降水的时空变化特征。结果表明:(1)全球升温1.5℃情景下,年降水量相对于1986~2005年减少5%,强降水量、暴雨日数和极端降水贡献率分别增加7%、33%和4%;概率密度曲线表明,年降水量均值下降,强降水量、暴雨日数和极端降水贡献率均值上升,极端降水方差增大;年降水量、强降水量和暴雨日数在空间上表现为南部增加北部减少,极端降水贡献率则相反。(2)全球升温2.0℃情景下,年降水量下降3%,强降水量、暴雨日数和极端降水贡献率分别上升15%、46%和15%;年降水量均值稍有减少且方差稍有上升,强降水量、暴雨日数和极端降水贡献率均值和方差明显增加;年降水量减少区域位于长江主干以北,强降水量、暴雨日数和极端降水贡献率表现为绝大部分地区增加的空间变化特征。(3)全球升温由1.5℃至2.0℃时,年降水量、强降水量、暴雨日数和极端降水贡献率分别增加3%、7%、10%和11%;随升温幅度的增加极端降水均值和方差上升;极端降水呈增加态势的范围扩大。因此,努力将升温控制在1.5℃对降低极端降水的影响具有重要意义。     

1961~2015年西南地区降水及洪涝指数空间分布特征

利用西南地区98个气象站连续完整的日降水序列数据,整合降水强度、持续性指数及等级指数形成降水指数体系并研究该区域降水及洪涝指数的空间分布特征,得到以下主要结论：（1） 1961~2015年,西南地区年降水量（PRCPTOT）与极端降水量（R95PTOT）都呈现出“东多西少、南多北少”的分布形态;持续降水日数（CWD）则表现为“南高北低、西高东低”的分布格局。区域多年平 均PRCPTOT、R95PTOT、CWD分别以-13.12 mm/10 a、1.34 mm/10 a、-0.29 d/10 a的速率变化。（2）西南地区不同等级降水日数具有相似的空间分布特征,均呈现出“南高北低、东高西低”的分布形态。（3）西南地区洪涝强度指数呈由东北向西南递减的分布特征;降水总量越多的地区,洪涝强度反而越低,主要由于单站洪涝强度表征的是降水的波动情况,降水量越多波动越不明显。21世纪以来,该 地区洪涝等级以重级为主,2010年以来连续多年出现特重级洪涝。此外,洪涝强度越大,区域性年度灾害等级越高。该研究对于掌握西南地区极端气候变化规律,从而服务于防灾减灾具有一定的理论意义。     

湿法净化黑烟中添加剂对炭黑沉降性能的影响

湿法净化黑烟中炭黑颗粒物的关键在于降低吸收液的表面张力并以高性能絮凝剂使其从溶液中絮凝、沉降以利于分离。选用十六烷基三甲基溴化胺(CTAB)为主要表面活性剂,使之与十二烷基苯磺酸钠(SDBS)和月桂醇聚氧乙烯(9)醚(AEO-9)进行复配实验,研究了复配液的表面张力,再向最低表面张力的复配表面活性剂溶液中投加絮凝剂聚合氯化铝(PAC)和聚丙烯酰胺(PAM),探讨絮凝剂的添加对黑烟颗粒沉降和絮凝的影响.实验结果表明:同时添加表面活性剂CTAB,SDBS和PAC,并使之浓度分别为0.5 mmol/L,0.4 mmol/L和200 mg/L时,炭黑颗粒的沉降效果最好,沉降率高达94%,且絮凝体较大,沉降时间仅为2 min。