Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

Perceptions of safety on a shared road: Driving,cycling, or walking near an autonomous vehicle

Introduction: While improved safety is a highly cited potential benefit of autonomous vehicles (AVs), at the same time a frequently cited concern is the new safety challenges that AVs introduce. The literature lacks a rigorous exploration of the safety perceptions of road users who will interact with AVs, including vulnerable road users. Addressing this gap is essential because the successful integration of AVs into transportation systems hinges on an understanding of how all road users will react to their presence. Methods: A stated preference survey of the Phoenix, Arizona, metropolitan statistical area (Phoenix MSA) was conducted in July 2018. A series of ordered probit models was estimated to analyze the survey responses and identify differences between various population groups with respect to the perceived safety of driving, cycling, and walking near AVs. Results: Greater exposure to and awareness of AVs are not uniformly associated with increases in perceived safety. Various attitudinal factors, level of AV automation, and other intrinsic and extrinsic factors are related to safety perceptions of driving, walking, and cycling near AVs. Socioeconomic and demographic characteristics, such as gender, age, income, employment, and automobile usage and ownership, have various relationships with perceived safety. Conclusions: Cycling near an AV was perceived as the least safe activity, followed by walking and then driving near an AV. Both similarities and differences were observed among the factors associated with the perceived safety of different travel alternatives. Practical Applications: Public perception will guide the development and adoption of AVs directly and indirectly. To help maintain control of public perception, transportation planners, decision makers, and other stakeholders should consider more deliberate and targeted messaging to address the concerns of different road users. In addition, more careful pilot testing and more direct attention to vulnerable road users may help avoid a backlash that could delay the rollout of this technology.     

An Experimental Methodology for Monitoring Contaminant Transport Through Geotechnical Centrifuge Models

In this paper, an attempt has been made to highlight an experimental methodology for monitoring contaminant transport through locally available silty soil and commercially available clay in geotechnical centrifuge models, for different compaction states. Use of multiple depth sensors to determine depth distribution of sodium chloride in the soil column has been detailed. The obtained results have been compared with argentometric method. To validate the centrifuge modelling, modelling of models has been used. The test setup developed can simulate contaminant transport mechanisms through the soil mass, which is approximately 10 m deep, over a period of 600 days. R _e and P _e are found to be N times higher in the centrifuge models. These numbers are found to be several orders less than unity. This indicates that laminar flow prevails and the dominating Cl⁻ transport mechanism in centrifuge is diffusion. The study also highlights the fact that the geotechnical centrifuge modelling can be used as a viable alternative to field scale experimentation.     

Combining Logistic Models with Multivariate Methods for the Rapid Biological Assessment of Rivers Using Macroinvertebrates

This work represents an attempt to define a simple method to classify the relative degree of disturbance of sites in lotic systems on the basis of comparison of their faunistic composition with reference sites. Two ecotypes were selected in northern Portugal where benthic invertebrates were sampled in reaches with different levels of contamination. As a first stage, previous Geographic Information System information was used to define reference sites in each ecotype. Afterwards, multivariate techniques and non linear estimation models were combined to assess biological quality. This method allowed us to quantify sites according to increasing levels of contamination, after the probabilities of occurrence of taxa along a gradient of contamination taking into account the reference condition. The results suggest that this method is sensitive to organic pollution, easy to interpret, namely the species tolerance, and could be a good framework to establish regional rankings depending on the ecological impact of river sites.     

运用QSPR预测有机磷农药的色谱保留值

通过计算43种有机磷农药的各种结构参数,运用多元线性回归分析方法比较了适用于有机磷农药色谱保留值的定量关系表达式,建立了有机磷农药结构参数对色谱保留值的QSPR模型.模型分析表明:磷酸酯与硫逐磷酸酯两类有机磷农药的模型非交叉验证相关系数R2分别为0.991和0.998,标准误差SE分别为0.0539和0.2874,交叉验证相关系数Q2分别为0.976和0.990,标准偏差Scv分别为0.086和0.610.在已知磷酸酯与硫逐磷酸酯两类有机磷农药结构参数的情况下,此模型可有助于有机磷农药的色谱分析.     

Determination of Frequency for Remeasuring Ground and Vegetation Cover Factor Needed for Soil Erosion Modeling

Determining a remeasurement frequency of variables over time is required in monitoring environmental systems. This article demonstrates methods based on regression modeling and spatio-temporal variability to determine the time interval to remeasure the ground and vegetation cover factor on permanent plots for monitoring a soil erosion system. The spatio-temporal variability methods include use of historical data to predict semivariograms, modeling average temporal variability, and temporal interpolation by two-step kriging. The results show that for the cover factor, the relative errors of the prediction increase with an increased length of time interval between remeasurements when using the regression and semivariogram models. Given precision or accuracy requirements, appropriate time intervals can be determined. However, the remeasurement frequency also varies depending on the prediction interval time. As an alternative method, the range parameter of a semivariogram model can be used to quantify average temporal variability that approximates the maximum time interval between remeasurements. This method is simpler than regression and semivariogram modeling, but it requires a long-term dataset based on permanent plots. In addition, the temporal interpolation by two-step kriging is also used to determine the time interval. This method is applicable when remeasurements in time are not sufficient. If spatial and temporal remeasurements are sufficient, it can be expanded and applied to design spatial and temporal sampling simultaneously.     

环境-经济系统整合模型的构建研究

环境经济系统整合模型的研究将环境的、经济的、社会的因素整合在可持续发展框架中．模拟、分析经济系统与环境系统之闻的相互作用和反馈关系。本文在分析环境经济系统整合模型构建的背景、理论与方法的基础上．设计了环境经济系统整合模型开发的技术路线．提出了环境经济系统整合模型的主要内容。     

Robustness of Meteorological Droughts in Dynamically Downscaled Climate Simulations

We examine the robustness of a suite of regional climate models (RCMs) in simulating meteorological droughts and associated metrics in present‐day climate (1971‐2003) over the conterminous United States (U.S.). The RCMs that are part of North American Regional Climate Change Assessment Program (NARCCAP) simulations are compared with multiple observations over the climatologically homogeneous regions of the U.S. The seasonal precipitation, climatology, drought attributes, and trends have been assessed. The reanalysis‐based multi‐model median RCM reasonably simulates observed statistical attributes of drought and the regional detail due to topographic forcing. However, models fail to simulate significant drying trend over the Southwest and West. Further, reanalysis‐based NARCCAP runs underestimate the observed drought frequency overall, with the exception of the Southwest; whereas they underestimate persistence in the drought‐affected areas over the Southwest and West‐North Central regions. However, global climate model‐driven NARCCAP ensembles tend to overestimate regional drought frequencies. Models exhibit considerable uncertainties while reproducing meteorological drought statistics, as evidenced by a general lack of agreement in the Hurst exponent, which in turn controls drought persistence. Water resources managers need to be aware of the limitations of current climate models, while regional climate modelers may want to fine‐tune their parameters to address impact‐relevant metrics.     

Impacts of Changes in Precipitation Amount and Distribution on Water Resources Studied Using a Model Rainwater Harvesting System

Water supply reliability is expected to be affected by both precipitation amount and distribution changes under recent and future climate change. We compare historical (1951‐2010) changes in annual‐mean and annual‐maximum daily precipitation in the global set of station observations from Global Historical Climatology Network and climate models from the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP), and develop the study to 2011‐2099 for model projections under high radiative forcing scenario (RCP8.5). We develop a simple rainwater harvesting system (RWHS) model and drive it with observational and modeled precipitation. We study the changes in mean and maximum precipitation along with changes in the reliability of the model RWHS as tools to assess the impact of changes in precipitation amount and distribution on reliability of precipitation‐fed water supplies. Results show faster increase in observed maximum precipitation (10.14% per K global warming) than mean precipitation (7.64% per K), and increased reliability of the model RWHS driven by observed precipitation by an average of 0.2% per decade. The ISI‐MIP models show even faster increase in maximum precipitation compared to mean precipitation. However, they imply decreases in mean reliability, for an average 0.15% per decade. Compared to observations, climate models underestimate the increasing trends in mean and maximum precipitation and show the opposite direction of change in reliability of a model water supply system.