Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

土地利用/覆盖变化对长江上游非点源污染影响研究

在国内外相关研究的基础上,利用输出系数模型,结合RS和GIS技术,对长江上游的非点源污染负荷进行了空间模拟和负荷估算.模拟结果表明,在不考虑流域损失的前提下,由于土地利用造成的非点源污染负荷TN总量从20世纪70年代的123万t下降至2000年的116万t,基本呈逐年减少的趋势,由土地利用造成的TP的变化趋势与TN基本相同,从70年代的3.7万t下降到2000年的3.5万t左右.就省份、土地利用类型和水系而言,四川省、种植用地和草地以及金沙江水系和嘉陵江水系对长江上游的非点源污染贡献较大.在非点源污染负荷强度上,重庆市和嘉陵江水系单位面积负荷最高,是今后应重点治理的地区.结果表明,该模型可以对长江上游这样的超大尺度空间的非点源污染进行较好的空间模拟.     

Characteristics of sewage sludge and distribution of heavy metal in plants with amendment of sewage sludge

In order to better understand land application of sewage sludge, the characterization of heavy metals and organic pollutants were investigated in three different sewage sludges in Shanghai City, China. It was found that the total concentrations of Cd in all of sewage sludge and total concentrations of Zn in Jinshan sewage sludge, as well as those ofZn, Cu, and Ni in Taopu sludge are higher than Chinese regulation limit of pollutants for sludge to be used in agriculture. Leachability of rig in all of studied samples and that of Cd in Taopu sewage sludge exceed the limit values of waste solid extraction standard in China legislation. Based on the characteristics for three kinds of sewage sludge, a pot experiment was conducted to investigate the effect of soil amended with Quyang sewage sludge on the accumulation of heavy metalo.by Begonia semperfloreas-hybr; Ophiopogon japonicas （L.F.） Ker-Gaw; Loropetalum chindense-var, rubrum; Dendranthema morifolium; Viola tricolor; A ntirrhinum majas; Buxas radicans Sieb; Viburnum macrocephalum; Osmanthas fragrans Lour; Cinnamomum camphora siebold and Ligustrum lucidum ait. Results showed that 8 species of plant survived in the amended soil, and moreover they flourished as well as those cultivated in the control soil. The heavy metal concentration in plants varied with species, As, Pb, Cd and Cr concentration being the highest in the four herbaceous species studied, particularly in the roots of D. morifolium. These plants, however, did not show accumulator of As, Pb, Cd and Cr. The highest concentration of Ni and Hg was found in the roots ofD. morifolium, followed by the leaves ofB. semperflorens-hybr. Levels of Zn and Cu were much higher in D. morifolium than in the other plant species. D. morifolium accumulated Ni, Hg, Cu and Zn, which may contribute to the decrease of heavy metal contents in the amended soil. Treatment with sewage sludge did not significantly affect the uptake of heavy metals by the L. chindense-var, rubrum, however, it significantly affected the uptake of heavy metals by D. morifolium.     

Fatal pedestrian crashes on interstates and other freeways in the United States

Introduction: More than 800 pedestrians die annually in crashes on interstates and other freeways in the United States, but few studies have examined their characteristics. Method: Data from the Fatality Analysis Reporting System on pedestrians fatally injured during 2015–2017 were analyzed. Chi-square tests compared characteristics of pedestrians killed on interstates and other freeways with those that died on other roads, and across crash types among freeway deaths. Land use characteristics of locations where pedestrians were killed while crossing freeways in a large state (California) were identified using Google Earth. Results: A larger proportion of pedestrians killed on freeways died on dark and unlit roads (48% vs. 32%), were male (78% vs. 68%), or were ages 20–44 (55% vs. 32%) compared with pedestrians killed on other roads. Crossing (42%) was the most common crash type among pedestrian deaths on freeways, followed by disabled-vehicle-related crashes (18%). Pedestrians who died while crossing more often had blood alcohol concentrations ≥ 0.08 g/dL (40%) than those in disabled-vehicle-related (22%) or other crashes (34%). Deaths in crossing crashes were more likely than other freeway deaths to occur on urban roads (81%), at speed limits ≤50 mph (13%), or between 18:00 and 23:59 (49%), and 58% of crossing crashes analyzed for land use were located between residential and other (e.g., commercial, recreational) uses. Over a third (37%) of deaths in disabled-vehicle-related crashes occurred at speed limits ≥70 mph. Conclusions: A surprising proportion of pedestrian deaths occur on controlled-access roads not designed for walking. Countermeasures for these crashes need to be implemented to see meaningful reductions in pedestrian fatalities overall. Practical applications: Improving roadway and vehicle lighting, requiring reflective warning devices for marking disabled vehicles, constructing pedestrian overpasses and underpasses in areas frequently crossed, and promoting alternative means of traveling between residential and commercial areas could help.     

农地整治权属调整中农户认知对行为响应的作用机制--基于改进TPB及多群组SEM

农地整治权属调整是实现农业规模化和现代化的重要手段,而农户有效参与是推动权属调整的内在动力,研究农地整治权属调整中农户认知对其行为响应的作用机制,有助于高效引导农户参与权属调整,并为制定农地整治权属调整的政策提供科学依据。基于改进计划行为理论和湖北省11个县(市、区)1044份农户抽样调查数据,采用多群组结构方程模型探究了农地整治权属调整中不同类型农户认知对其行为响应的作用机制。结果表明:农地整治权属调整中农户行为逻辑符合改进计划行为理论,农户的行为态度、主观规范、知觉行为控制交互影响行为意愿,进而转换为行为响应,政府支持在行为意愿和行为响应之间起到部分中介作用。总体上,农户行为响应是"自发性""诱发性"和"约束性"三重行动逻辑的结合,且"自发性"占主导地位。多群组结构方程估计结果表明,纯农型与兼业Ⅰ型农户的行为响应受到"自发性""诱发性"和"约束性"三重影响,兼业Ⅱ型农户受到"自发性"和"诱发性"双重影响,非农型农户仅受到"诱发性"单一影响。因此,为引导农户积极参与农地整治权属调整,应该分别针对各类农户相应地提高其参与的"自发性"和"诱发性",降低"约束性",充分发挥农村社会经济组织的作用,将四种不同类型农户的利益需求统筹考虑,降低权属调整过程中利益协调难度。     

基于复式记账的土地资源资产核算与报表编制研究

借鉴会计学复式记账核算的优点,在国际资源核算体系的基础上,根据我国自然资源资产核算需求,提出土地资源资产核算的复式记账体系和报表编制框架。研究认为,基于复式记账的土地资源资产核算和报表编制要以“摸清家底、反映自然资源负债、提供土地资源审计和绩效考核信息”为目标,明确区、县级自然资源局为土地资源资产受托管理和进行土地资源资产核算与报表编制的核算单位。在界定土地资源资产、负债和权益相关概念的基础上,提出土地资源资产属性变化的核算内容和每次土地资源资产实物量变化必须遵循占补平衡的基本原则,进行过程核算。以YC县土地资源资产变化为例,对土地资源资产变化进行了基于复式记账的土地资源资产核算与报表编制实证研究,确定核算的事项类型和特征及其借贷核算流程,编制出土地资源资产负债表,并同时进行实物量核算和价值量核算的报表编制,结果表明:YC县土地资源资产实物量1485 km^2,2018年末价值量5639874.22万元、经济权益5271874.22万元、生态权益367991.6万元,土地资源负债8.40万元,通过土地资源资产用途调整,土地资源资产价值量增加21319.42万元,但在调整过程中,形成了土地资源负债0.07 km^2(8.4万元),在以后土地整治中需要增加园地。     

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.     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

Can we gain precision by sampling with probabilities proportional to size in surveying recent landscape changes in the Netherlands?

Seventy-two squares of 100 ha were selected by stratified random sampling with probabilities proportional to size (pps) to survey landscape changes in the period 1996–2003. The area of the plots times the urbanization pressure was used as a size measure. The central question of this study is whether the sampling with probabilities proportional to size leads to gain in precision compared to equal probability sampling. On average 1.03 isolated buildings per 100 ha have been built, while 0.90 buildings per 100 ha have been removed, leading to a net change of 0.13 building per 100 ha. The area with unspoiled natural relief has been reduced by 2.3 ha per 100 ha, and the length of linear relicts by 137 m per 100 ha. On average 74 m of linear green elements have been planted per 100 ha, while 106 m have been removed, leading to a net change of −31 m per 100 ha. For the state variables ‘unspoiled natural relief', ‘ linear relicts', ‘removed linear green elements', and ‘new – removed linear green elements' there is a gain in precision due to the pps-sampling. For the remaining state variables there is no gain or even a loss of precision (`new buildings', ‘removed buildings', ‘new – removed buildings', ‘new linear green elements'). Therefore, if many state variables must be monitored or when interest is not only in the change but also in the current totals, we recommend to keep things simple, and to select plots with equal probability.