Modelling Replicated Weed Growth Data using Spatially-varying Growth Curves

Weed growth in agricultural fields constitutes a major deterrent to the growth of crops, often resulting in low productivity and huge losses for the farmers. Therefore, proper understanding of patterns in weed growth is vital to agricultural research. Recent advances in Geographical Information Systems (GIS) now allow geocoding of agricultural data, which enable more sophisticated spatial analysis. Our current application concerns the development of statistical models for conducting spatial analysis of growth patterns in weeds. Our data comes from an experiment conducted in Waseca, Minnesota, that recorded growth of the weed Setariaspp. We capture the spatial variation in Setaria spp. growth using spatially-varying growth curves. An added challenge is that these designs are spatially replicated, with each plot being a lattice of sub-plots. Therefore, spatial variation may exist at different resolutions – a macro level variation between the plots and micro level variation between the sub-plots nested within each plot. We develop a Bayesian hierarchical framework for this setting. Flexible classes of models result which are fitted using simulation-based methods.     

A RATING-CURVE METHOD FOR HYDRODYNAMIC SIMULATIONS IN CONTAMINANT TRANSPORT MODELING1

ABSTRACT: Accurate prediction of hydrodynamics is of great importance to modeling contaminant transport and water quality in a river. Flow conditions are needed in estimating potential exposure contamination levels and the recovery time for a no-action alternative in contaminated sediments remediation. Considering highly meandering characteristics of the Buffalo River, New York, a three-dimensional hydrodynamic model was selected to route upstream flows through the 8-km river section with limited existing information based on the model's fully predictive capability and process-oriented feature. The model was employed to simulate changes in water depth and flow velocity with space and time in response to variation in flow rate and/or water surface elevation at boundaries for given bottom morphometry and initial conditions. Flow conditions of the river reach where historical flow data are not available were computed. A rating-curve approach was developed to meet continuous and event contaminant modeling needs. Rating curves (depth-discharge and velocity-discharge relationships) were constructed at selected stations from the 3-D hydrodynamic simulations of individual flow events. The curves were obtained as steady solutions to an unsteady problem. The rating-curve approach serves to link flow information provided by the hydrodynamic model to a contaminant transport model. With the approach, the linking problem resulting from incompatible model dimensions and grid sizes can be solved. The curves will be used to simulate sediment movement and to predict contaminant fate and transport in the river.     

Development of an Overall Index of Pollution for Surface Water Based on a General Classification Scheme in Indian Context

Various National and International Agencies involved in water quality assessment and pollution control have defined water quality criteria for different uses of water considering different indicator parameters. Classification schemes for water quality criteria/standards developed by these agencies differ inaddition to terminologies used such as Action level, Guide level etc. in defining the concentration values in these classes. In the present article a general classification scheme viz. Excellent,Acceptable, Slightly Polluted, Polluted and Heavily Polluted water is proposed for surface water quality assessment. The concentration ranges in these classes are defined in Indianscenario considering Indian Standards and CPCB criteria. Standardsby the European Community (EC), WHO etc. and the reported factsabout the pollution effects of important water quality indicatorparameters on the surrounding were also taken into account. Themathematical equations to transform the actual concentrationvalues into pollution indices are formulated and correspondingvalue function curves are plotted. Based on the individual indexvalues, an `Overall Index of Pollution' (OIP) is estimated. Theapplication of OIP is demonstrated at a few sampling stations onriver Yamuna based on observed water quality data. The general classification scheme along with concentrationranges defined in these classes will be of immense use fordetermining the surface water quality status with reference tospecific individual parameter, and the OIP for assessing theoverall water quality status in Indian context.     

Socio-demographic and experience factors affecting drivers’ runoff risk along horizontal curves of two-lane rural highway

Introduction: An improper driving strategy is one of the causative factors for a high probability of runoff and overturning crashes along the horizontal curves of two-lane highways. The socio-demographic and driving experience factors of a driver do influence driving strategy. Hence, this paper explored the effect of these factors on the driver’s runoff risk along the horizontal curves. Method: The driving performance data of 48 drivers along 52 horizontal curves was recorded in a fixed-base driving simulator. The driving performance index was estimated from the weighted lateral acceleration profile of each driver along a horizontal curve. It was clustered and compared with the actual runoff events observed during the experiment. It yielded high, moderate, and low-risk clusters. Using cross-tabulation, each risk cluster was compared with the socio-demographic and experience factors. Further, generalized mixed logistic regression models were developed to predict the high-risk and high to moderate risk events. Results: The age and experience of drivers are the influencing factors for runoff crash. The high-risk event percentage for mid-age drivers decreases with an increase in driving experience. For younger drivers, it increases initially but decreases afterwards. The generalized mixed logistic regression models identified young drivers with mid and high experience and mid-age drivers with low-experience as the high-risk groups. Conclusions: The proposed index parameter is effective in identifying the risk associated with horizontal curves. Driver training program focusing on the horizontal curve negotiation skills and graduated driver licensing could help the high-risk groups. Practical applications: The proposed index parameter can evaluate driving behavior at the horizontal curves. Driving behavior of high-risk groups could be considered in highway geometric design. Motor-vehicle agencies, advanced driver assistance systems manufacturers, and insurance agencies can use proposed index parameter to identify the high-risk drivers for their perusal.     

Characteristics of Carbon Emission in China and Analysis on Its Cause

From the history of human economic development, it is known that there is a close relationship between economic development and environment quality. Thus, in this study a factor decomposition model of carbon emission in China is built and the contributions that economic scale, industrial structure, and carbon emission intensity make to carbon emission quantitatively from 1990 to 2005 are analyzed, in other words—scale effect, structural effect, and technical effect—using the decomposition method of average distribution cushion which is based on the environmental Kuznets curves model is studied. The result suggests that the average of the effect changes of carbon emission in China is 19.55%, the effects brought by economic scale, industrial structure, and carbon emission intensity are 15.76%, −0.86%, and 4.65%, respectively. In general, the relation between carbon emission and China's economy was more like an “N” curve; Economy scale is a primary drive factor and has incremental effect to carbon emission. Since otherness of different industry is getting bigger, the industrial restructure has certain decremental effect to carbon emission, but the restrictive function is not obvious, the industrial structure still need to be further optimized; the technical effect is positive and its volatility is large. From the perspective of reducing carbon emission, the current technology has not played to its advantages. This study will promote the understanding of the theory about the relationship between carbon emission and economy development and provide reference value by all means to the adjustment of industrial development.     

Experimental Zn(II) retention in a sandy loam soil by very small columns

The use of column experiments, usually performed to better approximate field conditions, may provide information that is not available from batch experiments. In such experiments heavy metals are often adsorbed until saturation followed by desorption experiments. When the affinity of the metal to soil is high, the retention factor (R) could be greater than thousands and the duration of experiments can become impractically long. In order to use reasonable laboratory time, the flow rate should be increased or the column size decreased. The increase in flow rate produces undesirable kinetic and dispersion effects, so we used very small soil columns (pore volume = 0.31–0.70 ml) and relatively high flow rates (0.03–0.12 ml min⁻¹) in studies of Zn(II) adsorption and retention in soils. Conservative tracer flow column experiments under saturation conditions were carried out to determine flow parameters for different flow rates. Column pore volume (V_p), Peclet numbers (Pe) and longitudinal dispersion coefficients (D_L) were determined from breakthrough curves. The effect of type of electrolyte and ionic strength on the Zn(II) retention onto soil was determined. The influence of flow rate and bed height on the retention coefficient and on the mass transfer zone was also studied. The effect of different influent Zn(II) concentrations on the R values obtained was analyzed. Freundlich parameters from column experiments were compared with batch ones. The leaching efficiency of different electrolytes, salts of weak organic acids and EDTA was also studied.     

Defining Acceptable Levels for Ecological Indicators: An Approach for Considering Social Values

Ecological indicators can facilitate an adaptive management approach, but only if acceptable levels for those indicators have been defined so that the data collected can be interpreted. Because acceptable levels are an expression of the desired state of the ecosystem, the process of establishing acceptable levels should incorporate not just ecological understanding but also societal values. The goal of this research was to explore an approach for defining acceptable levels of ecological indicators that explicitly considers social perspectives and values. We used a set of eight indicators that were related to issues of concern in the Lake Champlain Basin. Our approach was based on normative theory. Using a stakeholder survey, we measured respondent normative evaluations of varying levels of our indicators. Aggregated social norm curves were used to determine the level at which indicator values shifted from acceptable to unacceptable conditions. For seven of the eight indicators, clear preferences were interpretable from these norm curves. For example, closures of public beaches because of bacterial contamination and days of intense algae bloom went from acceptable to unacceptable at 7–10 days in a summer season. Survey respondents also indicated that the number of fish caught from Lake Champlain that could be safely consumed each month was unacceptably low and the number of streams draining into the lake that were impaired by storm water was unacceptably high. If indicators that translate ecological conditions into social consequences are carefully selected, we believe the normative approach has considerable merit for defining acceptable levels of valued ecological system components.     

环境库兹涅茨曲线的虚幻性及其对可持续发展的现实影响

生态环境质量真的能够随着经济发展而改善吗？“先污染、后治理”真的是普遍的发展规律吗？既有的理论一般认为．随着经济的发展．生态环境的质量在经过一个时期的恶化之后，将在一定的发展阶段出现好转．其变化过程呈“倒U曲线”状态．这就是环境Kuznets曲线。作者认为这是一个貌似真实的虚幻．生态环境随着经济发展而好转只可能是局部的、而不可能是整体性的．经济发展与生态维护的双赢目标也同样是难以企及的，经济发展与生态维护只能是基于各种利益关系的权衡。文章还对中国长期推行的几种宏观经济政策的生态环境影响进行了分析，并提出了经济利益与生态利益相权衡的现实主张。     

Methodology for Developing Flood Rule Curves Conditioned on El Niño‐Southern Oscillation Classification1

Lee, Se‐Yeun, Alan F. Hamlet, Carolyn J. Fitzgerald, and Stephen J. Burges, 2011. Methodology for Developing Flood Rule Curves Conditioned on El Niño‐Southern Oscillation Classification. Journal of the American Water Resources Association (JAWRA) 47(1):81‐92. DOI: 10.1111/j.1752‐1688.2010.00490.x Abstract: Regional climate varies on interannual and decadal time scales that in turn affect annual streamflows, flood risks, and reservoir storage deficits in mid‐summer. However, these variable elements of the climate system are generally not included in water resources operating policies that attempt to preserve a balance between flood risk and other water resources system objectives. A methodology for incorporating El Niño‐Southern Oscillation (ENSO) information in designing flood control curves is investigated. An optimization‐simulation procedure is used to develop a set of ENSO‐conditioned flood control rule curves that relate streamflow forecasts to flood control evacuation requirements. ENSO‐conditioned simulated flood risk and storage deficits under current operating policy are used to calibrate a unique objective function for each ENSO classification. Using a case study for the Columbia River Basin, we demonstrate that ENSO‐conditioned flood control curves constructed using the optimization‐simulation procedure consistently reduce storage deficits at a number of interrelated projects without increasing flood risk. For the Columbia Basin, the overall improvements in reservoir operations are relatively modest, and (in isolation) might not motivate a restructuring of flood control operations. However, the technique is widely applicable to a wide range of water resources systems and/or different climate indices.