Estimation of Catchment Nutrient Loads in New Zealand Using Monthly Water Quality Monitoring Data

Causes of variation between loads estimated using alternative calculation methods and their repeatability were investigated using 20 years of daily flow and monthly concentration samples for 77 rivers in New Zealand. Loads of dissolved and total nitrogen and phosphorus were calculated using the Ratio, L5, and L7 methods. Estimates of loads and their precision associated with short‐term records of 5, 10, and 15 years were simulated by subsampling. The representativeness of the short‐term loads was quantified as the standard deviation of the 20 realizations. The L7 method generally produced more realistic loads with the highest precision and representativeness. Differences between load estimates were shown to be associated with poor agreement between the data and the underlying model. The best method was shown to depend on the match between the model and functional and distributional characteristics of the data, rather than on the contaminant. Short‐term load estimates poorly represented the long‐term load estimate, and deviations frequently exceeded estimated imprecision. The results highlight there is no single preferred load calculation method, the inadvisability of “unsupervised” load estimation and the importance of inspecting concentration‐flow, unit load‐flow plots and regression residuals. Regulatory authorities should be aware that the precision of loads estimated from monthly data are likely to be “optimistic” with respect to the actual repeatability of load estimates.     

Modeling Summer Month Hydrological Drought Probabilities in the United States Using Antecedent Flow Conditions

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5‐11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best‐performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid‐Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.     

Effects of Urbanization on Flow Duration and Stream Flashiness: A Case Study of Puget Sound Streams,Western Washington,USA

The overall influence of urbanization on how flows of different frequency might change over time, while important in hydrologic design, remains imprecisely known. In this study, we investigate the effects of urbanization on flow duration curves (FDCs) and flow variability through a case study of eight watersheds that underwent different amounts of growth, in the Puget Sound region in Western Washington State, United States. We computed annual FDCs from flow records spanning 1960‐2010 and, after accounting for the effects of precipitation, we conducted statistical trend analyses on flow metrics to quantify how key FDC percentiles changed with time in response to urbanization. In the urban watersheds, the entire FDC tended to increase in magnitude of flow, especially the 95th‐99th percentile of the daily mean flow series, which increased by an average of 43%. Stream flashiness in urban watersheds was found to increase by an average of 70%. The increases in FDC magnitude and flashiness in urbanizing watersheds are most likely a result of increasing watershed imperviousness and altered hydrologic routing. Rural watersheds were found to have decreasing FDC magnitude over the same time period, which is possibly due to anthropogenic extractions of groundwater, and increasing stream flashiness, which is likely a result of reductions in base flow and increasing precipitation intensity and variability.     

Drivers of future streamflow changes in watersheds across the Northeastern United States

Accurate projections of streamflow, which have implications for flooding, water resources, hydropower, and ecosystems, are critical to climate change adaptation and require an understanding of streamflow sensitivity to climate drivers. The northeastern United States has experienced a dramatic increase in extreme precipitation over the past 25 years; however, the effects of these changes, as well as changes in other drivers of streamflow, remain unclear. Here, we use a random forest model forced with a regional climate model to examine historical and future streamflow dynamics of four watersheds across the Northeast. We find that streamflow in the cold season (November–May) is primarily driven by 3-day rainfall and antecedent wetness (Antecedent Precipitation Index) in three rainfall-dominant watersheds, and 30-day rainfall, antecedent wetness, and 30-day snowmelt in the fourth, more snowmelt-dominated watershed. In the warm season (June–October), streamflow is driven by antecedent wetness and rainfall in all watersheds. By the end of the century (2070–2099), cold season streamflow depends on the importance placed on snow in the machine learning model, with changes ranging from −7% (with snow) to +40% (without snow) in a single watershed. Simulated future warm season streamflow increases in two watersheds (56% and 193%) due to increased precipitation and antecedent soil wetness, but decreases in the other two watersheds (−6% and −27%) due to reduced precipitation.     

加速度均方根地震动统计研究

根据美国加州等地的强震记录,采用回归分析方法研究了加速度记录水平、竖向分量的峰值加速度(PGA)和一定时间窗内加速度均方根(SRSTM S)的衰减规律。所采用的加速度记录共795组(两水平向与一竖向)2 385条。对作为地震危险性分析的主要参数PGA的衰减规律与SRSTM S的衰减规律作了详细的研究,结果表明,SRSTM S的离散性明显的小于PGA,因此建议将SRSTM S的衰减关系应用于地震动强度的危险性分析。     

Reconstructed Streamflows for the Headwaters of the Wind River,Wyoming, United States1

Abstract: Tree rings offer a means to extend observational records of streamflow by hundreds of years, but dendrohydrological techniques are not regularly applied to small tributary and headwaters gages. Here we explore the potential for extending three such gage records on small streams in the Wind River drainage of central Wyoming, United States. Using core samples taken from Douglas fir (Pseudotsuga menziesii), piñon pine (Pinus edulis), and limber pine (Pinus flexilis) at 38 sites, we were able to reconstruct streamflows for the headwaters of the Wind River back to 1672 AD or earlier. The streamflow reconstructions for Bull Lake Creek above Bull Lake; the Little Popo Agie River near Lander, Wyoming; and Wind River near Dubois, Wyoming explained between 40% and 64% of the observed variance, and these extended records performed well in a variety of statistical verification tests. The full reconstructions show pronounced inter‐annual variability in streamflow, and these proxy records also point to the prevalence of severe, sustained droughts in this region. These reconstructions indicate that the 20th Century was relatively wet compared to previous centuries, and actual gage records may capture only a limited subset of potential natural variability in this area. Further analyses reveal how tree‐ring based reconstructions for small tributary and headwaters gages can be strongly influenced by the length and quality of calibration records, but this work also demonstrates how the use of a spatially extensive network of tree‐ring sites can improve the quality of these types of reconstructions.     

Finding Common Ground: How Advocacy Coalitions Succeed in Protecting Environmental Flows1

Abstract: This paper reviews several recent case studies in which states or countries have strengthened their protection of environmental flows to explore the key policy, stakeholder, and scientific elements that contributed to these advances in water management. A conceptual framework is developed to describe the actions of interest groups and individuals, how environmental flow issues get onto the formal agenda of decision makers, the events and conditions which precipitate this attention, the role of science and scientific uncertainty, and how interactions and dialog among individuals and groups with different interests lead to changes in state and national statutes. In general, the review found that changing policies is a result of actions of informed groups of interested parties using science and information to inform both the public and decision makers about the need for action and about the specific action needed. In almost all cases, environmental flow issues make it onto the formal agenda of institutions through one or more precipitating events, often legal challenges that call into question the existing legal framework for water management. Significantly, in almost all cases the engagement between advocacy coalitions with different and often opposing views results in reframing the issues to provide a common approach or solution upon which the competing coalitions can agree.     

Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408. Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.     

Daily Updating of Operational Statistical Seasonal Water Supply Forecasts for the western U.S.1

Abstract: Official seasonal water supply outlooks for the western United States are typically produced once per month from January through June. The Natural Resources Conservation Service has developed a new outlook product that allows the automated production and delivery of this type of forecast year‐round and with a daily update frequency. Daily snow water equivalent and water year‐to‐date precipitation data from multiple SNOTEL stations are combined using a statistical forecasting technique (“Z‐Score Regression”) to predict seasonal streamflow volume. The skill of these forecasts vs. lead‐time is comparable to the official published outlooks. The new product matches the intra‐monthly trends in the official forecasts until the target period is partly in the past, when the official forecasts begin to use information about observed streamflows to date. Geographically, the patterns of skill also match the official outlooks, with highest skill in Idaho and southern Colorado and lowest skill in the Colorado Front Range, eastern New Mexico, and eastern Montana. The direct and frequent delivery of objective guidance to users is a significant new development in the operational hydrologic seasonal forecasting community.     

长江流域年平均气温的时空变化特征

利用长江流域146个气象站点1960~2005年的逐年气温资料,选用EOF和REOF方法识别长江流域年平均气温空间变化特征,并对长江流域年平均气温变化敏感区域进行时间演变分析和突变检测。研究表明:长江流域年平均气温主要有2种空间振荡型（即全流域气温变化趋向一致型和流域内气温变化存在东西向差异型）,3个变化敏感区域（长江流域中下游地区、长江流域南部和金沙江流域）。3个变化敏感区域的年平均气温都在20世纪90年代明显升高,且均在90年代后期呈突变增加,其中金沙江流域升温趋势最为明显,气候倾向率为0.20℃/10a。全流域1991~2005年年平均气温距平空间分布表明,自1991年以来全流域都为升温趋势,其中长江流域中下游地区和金沙江流域是升温幅度最大的地区。