花溪水库表层沉积物重金属污染及潜在生态风险评价

以现代工业化前正常颗粒沉积物中重金属含量的最高背景值为参比值,结合潜在生态风险指数法对花溪沉积物中重金属的生态危害进行了评价。结果表明,花溪水库沉积物中重金属的富集顺序为Cu>Zn>Pb>Cr>As>Cd>Hg,污染水平顺序为Hg>Cd>Cu>As>Pb>Cr>Zn;重金属的潜在生态风险系数(Eir)表明,除个别样点外,大多属于轻微生态危害范畴;多种重金属的生态系统的潜在生态风险指数(IR)表明,花溪水库沉积物重金属污染属于轻微生态危害。     

丹江口水库流域氮素时空分布特征

为全面了解丹江口水库流域氮素污染状况,对库区26个点位及10条主要入库河流入库口处的表层水样进行了丰水期、平水期、枯水期采样与监测,探讨了氮素时空分布特征。入库口总氮检出范围为1.31~10.96 mg/L,其中泗河和神定河入库口总氮最高。总氮为库区水质主要限制因子,年均总氮质量浓度为1.13~2.71 mg/L;汉江库区整体上总氮污染水平略高于丹江库区,且与丹江库区相比,汉江库区受点源排放的影响较大。10条入库河流总氮的总年均输入量为63 347.31 t/a,其中汉江的总氮输入量最大;入库河流总氮控制的关键在于溶解性有机氮和硝酸盐氮的控制。     

丹江口水库蓄水后汉江中下游水文时空变化的#br# 定量评估及其生态影响

采用变化范围法（RVA）定量研究了丹江口水库蓄水后汉江中下游水文情势的时空变化,评估出汉江干流变化度最大的江段和水文特征指标类别,分析了其对应的生态影响,并针对汉江流域的四大家鱼和水华问题进行了敏感水文指标的变化度分析。结果显示:丹江口大坝蓄水后,汉江下游河道流量是中变化度占主导,比例范围为47～63%;水位是高变化度占主导,襄阳站和皇庄站高变化度的水文指标所占比例远大于其它站点,依次为53% 和75%,各站水位较蓄水前下降了1～2 m。黄家港站高/低流量脉冲出现的频率减少（变化度为-0.49和 -0.62）,且持续的时间变短（变化度为-0.87和 -0.74）。皇庄站和襄阳站流量和水位的月均值和极值较蓄水前减少,逆转次数在高RVA范围内较蓄水前增加（变化度为1.82）。四大家鱼产卵的敏感水文指标出现频率较蓄水前减少,且为中高变化度。下游河道枯水期流量和水位减小,增加了水华发生几率。     

Relationship between antibiotic residues and occurrence of resistant bacteria in Nile tilapia (Oreochromisniloticus) cultured in cage-farm

The aim of this study was to investigate the relationship between antibiotic residues found in the muscle of cage-farm-raised Nile tilapia (Oreochromisniloticus), the occurrence of resistant bacteria, and the sanitary practices adopted by farmers in Ilha Solteira reservoir, Brazil. Nine fish (three small fish, 40–200 g; three medium-sized fish, 200–500 g; and three large fish, 500–800 g) were collected from four cage farms every three months from April 2013 to January 2014. Ten antibiotic residues were determined using liquid chromatography-mass spectrometry, and bacteria were isolated and tested for antibiotic resistance to determine the multiple antibiotic resistance (MAR) index. Only three antibiotics (oxytetracycline, tetracycline, and florfenicol) were detected in the muscle of Nile tilapia, and their residues were the highest in small fish; however, the MAR index was higher in large fish. In addition, a direct positive relationship between the MAR index and the concentration of antibiotic residues in Nile tilapia was found. Overall, the adoption of prophylactic management practices improved the sanitary status of cage farms, reducing bacterial infections and hampering the development of antibiotic-resistant bacteria.     

水库移民安置区土地补偿现状与补偿原理

随着农村土地制度的变化,安置区土地补偿问题对于协调水库移民安置中各相关主体之间的利益平衡具有重要的意义。本文基于实地调查,首先分析了水库移民安置区土地补偿的现状和存在的问题;其次,运用土地产权理论和福利经济理论,从安置区土地补偿的原因、范围和补偿原则等方面阐明了安置区土地补偿的基本原理;最后,在此基础上提出了完善相关法律法规、协调水利水电工程建设中利益相关者的关系和利益平衡、体现农地价值等政策建议。结果表明:其一,安置区的土地补偿,无论从现行法律、还是从实际获得的补偿来看,均未体现对安置区土地权益的保护;其二,安置区集体和居民理应获得相应的权益补偿,其补偿范围既包括转出土地使用权的补偿,也包括对共同拥有土地所有权带来的权益分配变化的补偿;其三,土地制度的建设和改进上,应依据安置区土地资源状况和调出土地的状况确定补偿标准,淹没区集体、移民和安置区集体、居民应获得同等补偿,并力求体现农地价值。     

Reservoir Operation with Feedback in a Coupled Land Surface and Hydrologic Model: A Case Study of the Huai River Basin,China

Regarding emerging large‐scale reservoir operation models, reports of reservoir operation feedback for hydrologic modeling are rare, and little attention has been paid to flood control. An operation scheme considering multilevel flood control (MLFC) was first proposed in this study, but more reservoir information was needed. Thus, an alternative scheme was proposed that consisted of a modified version of the reservoir operation scheme in the Soil and Water Assessment Tool Model (MSWAT scheme). These schemes were coupled to a land surface and hydrologic model system with feedback, i.e., a system in which reservoir operation can affect the subsequent simulation, and were investigated in the Huai River Basin. The results show reservoir storage and peak flow were generally overestimated by the original SWAT reservoir scheme (SWAT scheme). Compared with the SWAT scheme, the MSWAT scheme successfully reduced the simulated storage and peak flow at the reservoir stations. For the downstream stations, the streamflow simulations were improved at a significance level of 5%. The performances of the MSWAT and MLFC schemes at the reservoir stations were nearly equivalent. Importantly, reservoir operation feedback to hydrologic modeling was necessary because the reservoir operation effects could not be transferred downstream without it. The streamflow simulation of a reservoir station located on a flat plain was less sensitive to feedback than that of a mountain reservoir station.     

水库温室效应研究进展与主要影响因素分析

温室气体排放导致的全球变暖成为世界各国关注的焦点。目前,关于淡水水库的温室效应在全球气候变化中的作用也成为了科学家争论的问题。已有的研究表明,世界上很多为水力发电或其他目的建造的水库,因水库蓄水所导致土壤和植被的淹没而额外增加碳基温室气体二氧化碳（CO2）和甲烷（CH4）的释放。通过对国内外关于淡水水库温室气体研究方面文献的归纳,综述分析了水库温室效应观测研究案例、〖JP2〗水库温室气体的产生机制、排放过程及其主要影响因素等方面的研究进展。为进一步从事水库温室气体研究、把握水库温室气体排放提供参考     

基于AHP-FUZZY方法的锦屏一级水库生态系统服务功能综合评价

水利工程的生态系统服务功能涉及影响因素众多,各因素间相互关联、逻辑关系复杂,但往往具有层次结构。每个因素对系统服务功能贡献的大小有其自身属性所决定的确定性,但实际度量中又表现为模糊性特征,针对常用替代方法（如市场价值法、机会成本法、影子工程法、旅行费用法、防护费用法等）评价生态系统服务功能的缺点,将系统工程决策方法和模糊数学评价方法有机结合,提出了一种层次分析 模糊数学（AHP FUZZY）水库生态系统服务功能综合评价方法,该方法较全面地考虑了水库生态系统服务功能的多种影响因素,避免了仅考虑少数几种判据所带来的局限性,同时通过层次结构分析较为客观地给出了各种影响因素的影响度值,为提高水库生态系统服务功能综合评价的可靠性创造了条件。
     

Effects of drawdown scenario on retrogressive lateral erosion in a reservoir

The drawdown of reservoirs behind dams is an important management strategy (e.g., for removal of aging infrastructure, flushing of sediment), and an opportunity to study erosional processes. A numerical model was developed to examine retrogressive bank erosion across reservoir drawdown scenarios and to evaluate factors controlling the rate, volume, and mechanisms of lateral erosion. Modeled processes included dynamic drawdown of groundwater, sequential slope failures via limit equilibrium analysis, and retrogression considering stress interaction between failing blocks. Field measurements were coupled with Staged, Slow, and Rapid drawdown scenarios. Results highlight the importance of including retrogression as an avenue for lateral erosion, as sequential block failures were found to occur in all scenarios except Slow drawdown. This result indicates that bank stability models without some means of characterizing the evolution of slope failure during drawdown are likely underestimating bank failure rates and volumes. In contrast, dynamic groundwater was not found to be a dominant control for any drawdown scenario. Model results also demonstrate that the drawdown increment is a first-order control on slope instability via the development of drained or undrained conditions. A majority of failures occurred under undrained conditions. To maximize slope stability, using slow drawdown to activate internal friction under drained conditions is essential. The design of the drawdown rate created a tradeoff between the amount of impact created and when the impact is produced. The study also articulated the need for coupling models and field observations for rapidly changing systems.     

Comparison of Machine Learning Models Performance on Simulating Reservoir Outflow: A Case Study of Two Reservoirs in Illinois,U.S.A.

Reservoir outflow is an important variable for understanding hydrological processes and water resource management. Natural streamflow variation, in addition to the streamflow regulation provided by dams and reservoirs, can make streamflow difficult to understand and predict. This makes them a challenge to accurately simulate hydrologic processes at a daily scale. In this study, three Machine Learning (ML) algorithms, Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN), were examined and compared to model reservoir outflow. Past, current, and future hydrologic and meteorological data were used as model inputs, and the outflow of next day was used as prediction. Simulation results demonstrated that all three models can reasonably simulate reservoir outflow. For Carlyle Lake, the coefficient of determination and Nash–Sutcliffe efficiency were each close to one for the three models. The coefficient of determination, relative mean bias, and root mean square error indicated that the SVM performed better than the RF and ANN, but the SVM output displayed a larger relative mean bias than that from RF and ANN. For Lake Shelbyville, the ANN model performed better than RF and SVM when considering the coefficient of determination, Nash–Sutcliffe efficiency, relative mean bias, and root mean square error. The study results demonstrate that the three ML algorithms (RF, SVM, and ANN) are all promising tools for simulating reservoir outflow. Both the accuracy and efficacy of the three ML algorithms are considered to support practitioners in planning reservoir management.