Simulated Impacts of Three Decadal Climate Variability Phenomena on Water Yields in the Missouri River Basin1

Mehta, Vikram M., Norman J. Rosenberg, and Katherin Mendoza, 2011. Simulated Impacts of Three Decadal Climate Variability Phenomena on Water Yields in the Missouri River Basin. Journal of the American Water Resources Association (JAWRA) 47(1):126‐135. DOI: 10.1111/j.1752‐1688.2010.00496.x Abstract: The Missouri River Basin (MRB) is the largest river basin in the United States (U.S.), and is one of the most important crop and livestock‐producing regions in the world. In a previous study of associations between decadal climate variability (DCV) phenomena and hydro‐meteorological (HM) variability in the MRB, it was found that positive and negative phases of the Pacific Decadal Oscillation (PDO), the tropical Atlantic sea‐surface temperature gradient variability (TAG), and the west Pacific warm pool (WPWP) temperature variability were significantly associated with decadal variability in precipitation and 2‐meter air temperature in the MRB, with combinations of various phases of these DCV phenomena associated with drought, flood, or neutral HM conditions. Here, we report on a methodology developed and applied to assess whether the aforementioned DCVs directly affect the hydrology of the MRB. The Hydrologic Unit Model of the U.S. (HUMUS) was used to simulate water yields in response to realistic values of the PDO, TAG, and WPWP at 75 widely distributed, eight‐digit hydrologic unit areas within the MRB. HUMUS driven by HM anomalies in both the positive and negative phases of the PDO and TAG resulted in major impacts on water yields, as much as ±20% of average water yield in some locations. Impacts of the WPWP were smaller. The combined and cumulative effects of these DCV phenomena on the MRB HM and water availability can be dramatic with important consequences for the MRB.     

垫江县次级河流环境现状分析

垫江县次级河流部分水质指标不容乐观,以种植污染、养殖污染和生活污染为代表的农村面源污染日渐成为垫江河流污染的主要因素。改变垫江河流水质现状,必须尽量减少化肥农药施用,改变传统养殖模式,完善农村垃圾收运系统,加快建设农村废水治理设施。     

An Assessment of U.S. Stream Compensatory Mitigation Policy: Necessary Changes to Protect Ecosystem Functions and Services

Compensatory mitigation of impacted streams and wetlands has increased over the past two decades, with the associated industry spending over US$2.9 billion in aquatic restoration annually. Despite these expenditures, evaluations by the National Research Council and U.S. Government Accountability Office have provided evidence that compensatory mitigation practices are failing to protect aquatic resource functions and services, and vague federal policy and inadequate evaluation of compensatory mitigation projects are to blame. To address these weaknesses, an update to federal regulations on compensatory mitigation was released in 2008. Additionally, the 2012 Reissuance of Nationwide Permits, some of which affects compensatory stream mitigation, was recently published. Current policy, as reflected in these documents, still uses nonspecific language to direct compensatory stream mitigation leaving most implementation decisions to the local U.S. Army Corps of Engineers district. The majority of federal mitigation policy has focused on wetland compensation, with other aquatic resources receiving less attention (e.g., streams). In this article, weaknesses of current policy are discussed, as are suggested policy changes to minimize the loss of stream ecosystem functions and services. Compensatory mitigation policy should clearly define key terms, incorporate adaptive management procedures, and provide guidelines for determining mitigation costs and compensation ratio requirements.     

Ecosystem health assessment of urban rivers and lakes-Case study of "the six lakes" in Beijing,China

The assessment of the ecosystem health of urban rivers and lakes is the scientific basis for their management and ecological restoration. This study developed a three-level indicator system for its assessment. The results indicated that: Zhonghai and Nanhai are in the state of transition from unhealthy to critical state and all the other lakes are in unhealthy states. Water environmental quality, structure and function of the aquatic ecosystem, and the structure of waterfront areas were the constraints. Nanhai was ranked as poor and the others were all ranked as very poor. However, the ecological environment of Zhonghai and Nanhai were better than the others, the sums of the degree of membership to the healthy state and critical state were all close to 0.6. and the restorations of these lakes were moderate. The sums of the degree of membership to the healthy state and critical state of the other lakes were under 0.3, as it was difficult to restore these lakes. Some suggestions on scientific management and ecological restoration of the six lakes were proposed: ①To control non-point pollution and to improve the water quality of six lakes and the water entering into these lakes; ②To improve the hydrological conditions of six lakes; ③To rehabilitate the aquatic ecosystem and waterfront areas. __________ Translated from Acta Ecologica Sinica, 2005, 25(11): 3019–3027[译自: 生态学报]     

罗源湾海水中粪大肠菌群的来源及空间分布

2002年1月到2005年12月通过多种方式对罗源湾海水中的FCB(粪大肠菌群)数量、来源及空间分布进行了调查.结果表明:湾内主要水域FCB的数量在<0.02～≥24 /mL之间,入海河流、沿岸居民的生活和农业生产活动以及海上网箱养殖是罗源湾海水中FCB的主要来源,其中湾内主要的入海河流FCB超标严重,入海河流是罗源湾内FCB污染的最主要来源.罗源湾内 FCB空间分布与盐度呈负相关(R2=0.84),空间分布表现为,西高东低、内腹海区高于湾口,近岸海区高于湾中央海区,表层高于底层,网箱养殖区高于非网箱养殖区,松山垦区由于受到河流入海的影响成为罗源湾内污染最严重的海区.     

河流恶臭生成机理及控制措施探讨

在对河流恶臭的生成机理及其形成过程进行分析和研究的基础上,提出了利用物理、化学和生物等工程措施进行河流恶臭污染治理的对策。     

廊坊市河流水质污染特征分析

根据廊坊市2001年～2008年地表水环境质量监测数据,论述了廊坊河流水质状况及其污染特征,指出廊坊河流水质为劣Ⅴ类,河流水质污染较重,基本属有机污染类型;河流水污染恶化趋势基本得到遏制,水体总体污染有所减轻。在此基础上,分析河流污染的原因,并提出改善河流污染的对策与措施。     

太湖流域典型河流沉积物的反硝化作用

用15N同位素配对法对太湖流域江苏和上海境内主要河流沉积物的反硝化作用及其影响因素进行研究.结果表明,河流沉积物反硝化作用具有显著空间差异.25℃时,河流总反硝化速率Dtot在0～4.03mmol.m-.2d-1之间;10℃时,Dtot在0～2.27mmol.m-.2d-1之间,平均值分别为0.79mmol.m-.2d-1和0.26mmol.m-.2d-1.相关性分析显示,沉积物的反硝化作用与沉积物氮含量和实验过程中的耗氧速率(SOD)呈显著相关关系(p<0.01).以总反硝化速率大小为依据将沉积物分成4组后的相关分析表明,反硝化速率与原位上覆水中的NO3--N含量之间亦存在显著的相关关系(p<0.05),预示着反硝化作用对水体氮负荷起到的氮汇作用.     

Streamflow Hydrology Estimate Using Machine Learning (SHEM)

Continuity and accuracy of near real‐time streamflow gauge (streamgage) data are critical for flood forecasting, assessing imminent risk, and implementing flood mitigation activities. Without these data, decision makers and first responders are limited in their ability to effectively allocate resources, implement evacuations to save lives, and reduce property losses. The Streamflow Hydrology Estimate using Machine Learning (SHEM) is a new predictive model for providing accurate and timely proxy streamflow data for inoperative streamgages. SHEM relies on machine learning (“training”) to process and interpret large volumes (“big data”) of historic complex hydrologic information. Continually updated with real‐time streamflow data, the model constructs a virtual dataset index of correlations and groups (clusters) of relationship correlations between selected streamgages in a watershed and under differing flow conditions. Using these datasets, SHEM interpolates estimated discharge and time data for any indexed streamgage that stops transmitting data. These estimates are continuously tested, scored, and revised using multiple regression analysis processes and methodologies. The SHEM model was tested in Idaho and Washington in four diverse watersheds, and the model's estimates were then compared to the actual recorded data for the same time period. Results from all watersheds revealed a high correlation, validating both the degree of accuracy and reliability of the model.     

Statistical Models to Predict and Assess Spatial and Temporal Low‐Flow Variability in New England Rivers and Streams

In the northern hemisphere, summer low flows are a key attribute defining both quantity and quality of aquatic habitat. I developed one set of models for New England streams/rivers predicting July/August median flows averaged across 1985–2015 as a function of weather, slope, % imperviousness, watershed storage, glacial geology, and soils. These models performed better than most United States Geological Survey models for summer flows developed at a statewide scale. I developed a second set of models predicting interannual differences in summer flows as a function of differences in air temperature, precipitation, the North Atlantic Oscillation (NAO) index, and lagged NAO. Use of difference equations eliminated the need for transformations and accounted for serial autocorrelations at lag 1. The models were used in sequence to estimate time series for monthly low flows and for two derived flow metrics (tenth percentile [Q10] and minimum 3‐in‐5 year average flows). The first metric is commonly used in assessing risk to low‐flow conditions over time, while the second has been correlated with increased probability of localized extinctions for brook trout. The flow metrics showed increasing trends across most of New England for 1985–2015. However, application of summer flow models with average and extreme climate projections to the Taunton River, Massachusetts, a sensitive watershed undergoing rapid development, projected that low‐flow metrics will decrease over the next 50 years.