Modeling Variability and Trends in Pesticide Concentrations in Streams1

Abstract: A parametric regression model was developed for assessing the variability and long‐term trends in pesticide concentrations in streams. The dependent variable is the logarithm of pesticide concentration and the explanatory variables are a seasonal wave, which represents the seasonal variability of concentration in response to seasonal application rates; a streamflow anomaly, which is the deviation of concurrent daily streamflow from average conditions for the previous 30 days; and a trend, which represents long‐term (inter‐annual) changes in concentration. Application of the model to selected herbicides and insecticides in four diverse streams indicated the model is robust with respect to pesticide type, stream location, and the degree of censoring (proportion of nondetections). An automatic model fitting and selection procedure for the seasonal wave and trend components was found to perform well for the datasets analyzed. Artificial censoring scenarios were used in a Monte Carlo simulation analysis to show that the fitted trends were unbiased and the approximate p‐values were accurate for as few as 10 uncensored concentrations during a three‐year period, assuming a sampling frequency of 15 samples per year. Trend estimates for the full model were compared with a model without the streamflow anomaly and a model in which the seasonality was modeled using standard trigonometric functions, rather than seasonal application rates. Exclusion of the streamflow anomaly resulted in substantial increases in the mean‐squared error and decreases in power for detecting trends. Incorrectly modeling the seasonal structure of the concentration data resulted in substantial estimation bias and moderate increases in mean‐squared error and decreases in power.     

Nutrient and Sediment Production,Watershed Characteristics,and Land Use in the Tahoe Basin,California‐Nevada1

Abstract: In efforts to control the degradation of water quality in Lake Tahoe, public agencies have monitored surface water discharge and concentrations of nitrogen, phosphorus, and suspended sediment in two separate sampling programs. The first program focuses on 20 watersheds varying in size from 162 to 14,000 ha, with continuous stream gaging and periodic sampling; the second focuses on small urbanized catchments, with automated sampling during runoff events. Using data from both programs, we addressed the questions (1) what are the fluxes and concentrations of nitrogen and phosphorus entering the lake from surface runoff; (2) how do the fluxes and concentrations vary in space and time; and (3) how are they related to land use and watershed characteristics? To answer these questions, we calculated discharge‐weighted average concentrations and annual fluxes and used multiple regression to relate those variable to a suite of GIS‐derived explanatory variables. The final selected regression models explain 47‐62% of the variance in constituent concentrations in the stormwater monitoring catchments, and 45‐72% of the variance in mean annual yields in the larger watersheds. The results emphasize the importance of impervious surface and residential density as factors in water quality degradation, and well‐developed soil as a factor in water quality maintenance.     

基于下垫面年地表温差的武汉市PM_(10)空间分布的估计

城市可吸入颗粒物(PM_(10))某一时刻或短期的空间分布,主要受气象条件控制,而一年或多年平均分布则主要取决于排放源。这些排放源与城市交通道路、工业区、城市建成区和开发区等的下垫面分布密切相关,而年地表温差可以综合反映下垫面的这些特性,所以可以利用这种相关关系,建立模型来估计年平均PM_(10)的空间分布。以武汉市为例,首先利用Landsat 8热红外遥感数据反演出2013年和2014年夏天和冬天的地表温度,计算出地表温差值;然后,根据影响随距离衰减的地学原理,利用反距离加权法(IDW),得到任意像元处年地表温差加权值,并与地面实测的2013年和2014年PM_(10)年均值做一元线性回归,通过精度对比寻找到最佳年地表温差加权值,并得到空间分布估计模型,其拟合优度R2达到0.655和0.752;最后利用该模型得到武汉市2013年和2014年PM_(10)年均值空间分布图。结果表明,武汉PM_(10)年均值浓度高值区主要集中于主城区,郊区部分人口相对集中的区域PM_(10)也较高,低值区分布在郊区乡镇、偏远山区以及有大型水体的地方。由于新方法充分考虑了下垫面的影响,与克里金内插相比,更能精细地刻画和反映PM_(10)的分布特征和规律,而且简单有效,有一定的应用价值。     

Parcelization in rural agricultural and forested landscapes in Wisconsin, 1972–2007: evaluating multiple dimensions of human decision-making over time

Many land-use change studies have relied on geographical explanatory factors. Unfortunately, they are but a single perspective in the multidimensional process of human decision-making. This project was designed to model the social, economic, geographic, and regulatory factors at the most appropriate unit of analysis, the landowner. By examining parcelization, a window is opened into the antecedent event of land-use change. A logistic regression model determined the likelihood a tax parcel would split in three time periods between 1953 and 2007. Geographic variables showed expected relationships to a parcelization event, while economic and regulatory variables illustrated some unexpected relationships. Social variables demonstrated scale issues that challenged their efficacy. A temporal analysis showed that historic parcelization was explained more robustly than more contemporary parcelization. The results could indicate that contemporary parcelization is driven by new and more complex factors not yet represented in similar models.     

长三角城市群建设用地扩张地区差异的驱动因素解释——基于回归方程的Shapley值分解方法

工业化、城镇化所带来的建设用地过度扩张已成为土地资源领域研究的热点问题。利用基于半对数回归方程的Shapley值分解方法考察了2006~2015年长三角城市群26个城市建设用地扩张的驱动因素及其对地区差异的贡献率。研究表明:(1)耕地保留量、产业结构调整、建设用地利用效率、生态压力等因素对建设用地扩张具有负向驱动作用,经济发展速度、人口城镇化速度、政府财政赤字、政府政策执行力等因素对建设用地扩张具有正向驱动作用,但耕地保有量、生态压力两个因素对建设用地扩张影响不显著;(2)政府财政赤字、建设用地利用效率、政府政策执行力等3个因素对建设用地扩张地区差异的贡献率最大。为此,应从资源约束、生态压力、促进产业结构调整、实施土地供给侧结构性改革、提高土地效率等多方面入手以破解建设用地过度扩张的困局。     

长三角城市群各业用地价格的空间分布格局及影响因素

运用空间自相关及地理加权回归方法,揭示长三角城市群各业用地价格的空间分布及关联特征,并分析其影响因素的空间异质性,丰富和发展城市群地价空间分布规律的理论研究。研究结果表明:工业用地价格普遍偏低,商住地价价格较高,符合城市间土地级差收益规律,但商住倒挂现象明显;在空间分布上,工业地价从浙东南向苏北呈梯度递减,在空间上呈现显著空间正相关,表现为低值空间集聚;居住地价在空间上呈现出较强的空间正相关,具体表现为一、二线城市为高值集聚,商服地价不存在空间自相关性;人均可支配收入、公共财政支出对长三角城市群工业地价的影响空间差异显著,城市等级、国内生产总值和人均可支配收入对居住地价的影响空间差异明显,商服地价主要受到社会消费品总额、每万人公共汽车数量和公共财政支出影响。     

改性白菜叶渣对重金属Zn2＋吸附性能

为了研究白菜叶渣对锌离子的吸附作用,采用静态吸附的方法,以酸碱处理后的废弃白菜渣为原材料,获得加人量（X1）、浓度（X2）、时间（X3）、pH（X4）和温度（X5）各单因素对Zn2＋的最佳吸附点,再通过二次回归正交旋转组合设计对白菜渣吸附Zn2＋的条件进行优化,并讨论了吸附过程中吸附等温线与动力曲线的相关特征。结果表明,当加入量0．2g、浓度2mg／L、吸附时间5h、pH为4以及温度20％时,吸附达到最大95．08％,验证所测最大吸附率93．89％,与预测值基本相符。对比实验说明白菜渣对Zn2吸附效果要优于活性炭。25℃和35℃时的等温线的拟合结果表明,白菜渣对Zn2＋是物理化学共同吸附的复杂过程。     

多元回归和BP人工神经网络模型对混合厌氧消化产气量的预测研究

在中温且控制pH值条件下,对脂肪类单基质和城市污水厂剩余污泥进行混合厌氧消化试验。基于多元回归原理和BP人工神经网络原理,对其建立产气量预测模型。由实验数据计算得出:两个阶段多元回归模型的预测平均准确率分别为75.69%和79.29%;BP神经网络模型的预测平均准确率为79.05%。通过对比两种模型的预测结果可知,两种模型都有较高的预测准确率,但BP模型的预测准确率更高,更适用于混合厌氧消化产气量预测。     

基于土壤重金属污染评价的数学模型

本文采用离散插值、多元非线性回归分析、有限差分法等方法,建立了一种针对土壤中重金属污染程度评价的数学模型,模型包含重金属污染的主要原因、重金属污染源的查证。采用指数函数和多项式拟合建立其数学空间理论模型,结合实际物理扩散方式,得到污染物的传播特征模型;再通过离散插值得到污染物浓度峰值的仿真点位置坐标,进而利用多元非线性回归的方法,对仿真点附近区域内的采集数据实现拟合,定位各个污染源。     

Prediction of primary energy demand in China based on AGAEDE optimal model

In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the model(both linear and quadratic) are optimized by AGA using factors,such as GDP,population,urbanization rate,and RD inputs together with energy consumption structure,that affect demand.Since the spurious regression phenomenon occurs for a wide range of time series analysis in econometrics,we also discuss this problem for the current artificial intelligence model.The simulation results show that the proposed model is more accurate and reliable compared with other existing methods and the China's energy demand will be 5.23 billion TCE in 2020 according to the average results of the AGAEDE optimal model.Further discussion illustrates that there will be great pressure for China to fulfill the planned goal of controlling energy demand set in the National Energy Demand Project(2014—2020).