Weighting Nitrogen and Phosphorus Pixel Pollutant Loads to Represent Runoff and Buffering Likelihoods

Watershed models often estimate annual nitrogen (N) or phosphorus (P) pollutant loads in rural areas with export coefficient (EC) (kg/ha/yr) values based on land cover, and in urban areas as the product of spatially uniform event mean concentration (EMC) (mg/L) values and runoff volume. Actual N and P nonpoint source (NPS) pollutant loading has more spatial complexity due to watershed variation in runoff likelihood and buffering likelihood along surface and subsurface pathways, which can be represented in a contributing area dispersal area (CADA) NPS model. This research develops a CADA NPS model to simulate how watershed properties of elevation, land cover, and soils upslope and downslope of each watershed pixel influence nutrient loading. The model uses both surface and subsurface runoff indices (RI), and surface and subsurface buffer indices (BI), to quantify the runoff and buffering likelihood for each watershed pixel, and generate maps of weighted EC and EMC values that identify NPS pollutant loading hotspots. The research illustrates how CADA NPS model maps and pixel loading values are sensitive to the spatial resolution and accuracy of elevation and land cover data, and model predictions can represent the lower and upper bounds of NPS loading. The model provides managers with a tool to rapidly visualize, rank, and investigate likely areas of high nutrient export.     

Intensive land use in the Swedish mountains between AD 800 and 1200 led to deforestation and ecosystem transformation with long-lasting effects

Anthropogenic deforestation has shaped ecosystems worldwide. In subarctic ecosystems, primarily inhabited by native peoples, deforestation is generally considered to be mainly associated with the industrial period. Here we examined mechanisms underlying deforestation a thousand years ago in a high-mountain valley with settlement artifacts located in subarctic Scandinavia. Using the Heureka Forestry Decision Support System, we modeled pre-settlement conditions and effects of tree cutting on forest cover. To examine lack of regeneration and present nutrient status, we analyzed soil nitrogen. We found that tree cutting could have deforested the valley within some hundred years. Overexploitation left the soil depleted beyond the capacity of re-establishment of trees. We suggest that pre-historical deforestation has occurred also in subarctic ecosystems and that ecosystem boundaries were especially vulnerable to this process. This study improves our understanding of mechanisms behind human-induced ecosystem transformations and tree-line changes, and of the concept of wilderness in the Scandinavian mountain range.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0634-z) contains supplementary material, which is available to authorized users.     

Phytoremediation of Atrazine by Poplar Trees: Toxicity,Uptake, and Transformation

Toxicity, uptake, and transformation of atrazine [2-chloro-4-(ethylamino)-6-(isopropylamino)-s-triazine] by three species of poplar tree were assessed. Poplar cuttings were grown in sealed flasks with hydrophonic solutions and exposed to various concentrations of atrazine for a period of two weeks. Toxicity effects were evaluated by monitoring transpiration and measuring poplar cutting mass. Exposure to higher atrazine concentrations resulted in decrease of biomass and transpiration accompanied by leaf chlorosis and abscission. However, poplar cuttings exposed to lower concentrations of atrazine grew well and transpired at a constant rate during experiment periods. Poplar cuttings could take up, hydrolyze, and dealkylate atrazine to less toxic metabolites. Metabolism of atrazine occurred in roots, stems, and leaves and became more complete with increased residence time in tissue. These results suggest that phytoremediation is a viable approach to removing atrazine from contaminated water and should be considered for other contaminants.     

Physically Based,Hydrologic Model Results Based on Three Precipitation Products1

Abstract: The main objective of the study is to examine the accuracy of and differences among simulated streamflows driven by rainfall estimates from a network of 22 rain gauges spread over a 2,170 km² watershed, NEXRAD Stage III radar data, and Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite data. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA), a physically based, distributed parameter, grid‐structured, hydrologic model, was used to simulate the June‐2002 flooding event in the Upper Guadalupe River watershed in south central Texas. There were significant differences between the rainfall fields estimated by the three types of measurement technologies. These differences resulted in even larger differences in the simulated hydrologic response of the watershed. In general, simulations driven by radar rainfall yielded better results than those driven by satellite or rain‐gauge estimates. This study also presents an overview of effects of land cover changes on runoff and stream discharge. The results demonstrate that, for major rainfall events similar to the 2002 event, the effect of urbanization on the watershed in the past two decades would not have made any significant effect on the hydrologic response. The effect of urbanization on the hydrologic response increases as the size of the rainfall event decreases.     

A Simple Process‐Based Snowmelt Routine to Model Spatially Distributed Snow Depth and Snowmelt in the SWAT Model1

Abstract: We present a method to integrate a process‐based (PB) snowmelt model that requires only daily temperature and elevation information into the Soil and Water Assessment Tool (SWAT) model. The model predicts the spatiotemporal snowpack distribution without adding additional complexity, and in fact reduces the number of calibrated parameters. To demonstrate the utility of the PB model, we calibrate the PB and temperature‐index (TI) SWAT models to optimize agreement with stream discharge on a 46‐km² watershed in northwestern Idaho, United States, for 10 individual years and use the calibrated parameters for the year with the best agreement to run the model for 15 remaining years. Stream discharge predictions by the PB and TI model were similar, although the PB model simulated snowmelt more accurately than the TI model for the remaining 15‐year period. Spatial snow distributions predicted by the PB model better matched observations from LandSat imagery and a SNOTEL station. Results for this watershed show that including PB snowmelt in watershed models is feasible, and calibration of TI‐based watershed models against discharge can incorrectly predict snow cover.     

Short-Run Allocation of Emissions Allowances and Long-Term Goals for Climate Policy

We summarize the latest results on the rapid changes that are occurring to Arctic sea ice thickness and extent, the reasons for them, and the methods being used to monitor the changing ice thickness. Arctic sea ice extent had been shrinking at a relatively modest rate of 3–4% per decade (annually averaged) but after 1996 this speeded up to 10% per decade and in summer 2007 there was a massive collapse of ice extent to a new record minimum of only 4.1 million km². Thickness has been falling at a more rapid rate (43% in the 25 years from the early 1970s to late 1990s) with a specially rapid loss of mass from pressure ridges. The summer 2007 event may have arisen from an interaction between the long-term retreat and more rapid thinning rates. We review thickness monitoring techniques that show the greatest promise on different spatial and temporal scales, and for different purposes. We show results from some recent work from submarines, and speculate that the trends towards retreat and thinning will inevitably lead to an eventual loss of all ice in summer, which can be described as a ‘tipping point’ in that the former situation, of an Arctic covered with mainly multi-year ice, cannot be retrieved.     

基于modis数据鲁甸6.5级地震不同烈度区地震前后植被变化研究

为了研究鲁甸6.5级地震不同烈度区地震前后植被的变化,以鲁甸地震完整烈度为研究区,以MODIS产品中的MOD13Q1数据为数据源,通过数据预处理获得2004-2018年不同烈度区年均NDVI时间序列,并用像元二分模型计算得到地震前后的植被覆盖度,从NDVI动态变化、植被覆盖度空间分布特征、植被覆盖度动态变化、植被损毁像...     

1980~2010年江苏沿海城市土地利用变化及其与环境因子关系分析——以东台市为例

2009年江苏省沿海开发规划上升为国家战略,了解江苏沿海城市过去土地利用变化轨迹以及驱动因子是未来江苏省沿海城市土地利用规划的重要基础性工作。基于5期TM30 m×30 m RS遥感影像和GIS技术,分析东台市1980~2010年土地利用结构与变化轨迹,并通过典型对应分析(CCA)分析其与环境因子之间的关系。结果表明,东台市1980~2010年主要土地利用类型为耕地(2029.02 km²)、建设用地(155.31 km²)、草地(60.41 km²)和水域(56.56 km²)。近30年土地利用变化量占总面积的16.98%,其中耕地、草地和建设用地变化量最大。土地利用变化最主要轨迹为耕地转建设用地,主要位于市区及周边地区,其次为草地转耕地,主要位于海岸带地区。东台市土地利用变化热点区域分别为市中心和海岸带,二者相距较远,相对独立。CCA分析显示城镇、交通和斑块形状复杂程度等是影响沿海城市土地利用变化的重要因子,海岸线作为沿海城市主要特征,随着海岸滩涂围垦开发,到海岸距离也是沿海城市土地利用变化的重要影响因子。因此,在沿海城市土地利用规划中需要重点考虑城镇布局、交通等基础设施分布、斑块的形状等因子,通过海岸带土地利用方式转变来加强市区与海岸带之间联系,促进社会经济转变,进一步保护海岸生态环境,提高海岸开发综合效益,引导土地利用走向可持续发展道路。     

嘉陵江流域植被覆盖时空变化特征

归一化植被指数(Normal Difference Vegetation Index,NDVI)能够反映植被的繁茂程度,可用来揭示环境的演化,并且能在全球变化研究中起到“指示器”的作用。目前利用NDVI研究植被变化多集中于陕西、甘肃、新疆等地区,对嘉陵江流域的植被变化趋势及其影响因素研究很少。利用线性相关分析方法分析GIMMS NDVI数据,借助于地理信息系统软件,分析嘉陵江流域植被覆盖的时空变化规律。研究结果如下：（1）嘉陵江流域在1982～2006年植被覆盖呈微弱上升趋势,与我国其它地区一致,但增长速率大小不一样;（2）嘉陵江流域植被覆盖明显优于黄土高原、西北地区,存在明显的空间差异,南部地区小于北部地区;（3）植被变化也存在空间差异,南部地区多呈增加趋势,而北部地区多呈减少趋势;（4）嘉陵江流域植被覆盖及其变化与气候变化和人类活动均有密切关系。基于分析,发现嘉陵江流域在人类活动和气候变化的双重影响下,环境向有利的方向发展。     

Receptor modeling for source apportionment of polycyclic aromatic hydrocarbons in urban atmosphere

This study reports source apportionment of polycyclic aromatic hydrocarbons (PAHs) in particulate depositions on vegetation foliages near highway in the urban environment of Lucknow city (India) using the principal components analysis/absolute principal components scores (PCA/APCS) receptor modeling approach. The multivariate method enables identification of major PAHs sources along with their quantitative contributions with respect to individual PAH. The PCA identified three major sources of PAHs viz. combustion, vehicular emissions, and diesel based activities. The PCA/APCS receptor modeling approach revealed that the combustion sources (natural gas, wood, coal/coke, biomass) contributed 19–97% of various PAHs, vehicular emissions 0–70%, diesel based sources 0–81% and other miscellaneous sources 0–20% of different PAHs. The contributions of major pyrolytic and petrogenic sources to the total PAHs were 56 and 42%, respectively. Further, the combustion related sources contribute major fraction of the carcinogenic PAHs in the study area. High correlation coefficient (R ² > 0.75 for most PAHs) between the measured and predicted concentrations of PAHs suggests for the applicability of the PCA/APCS receptor modeling approach for estimation of source contribution to the PAHs in particulates.