Identification and quantification of the hydrological impacts of imperviousness in urban catchments: a review

Urbanisation produces numerous changes in the natural environments it replaces. The impacts include habitat fragmentation and changes to both the quality and quantity of the stormwater runoff, and result in changes to hydrological systems. This review integrates research in relatively diverse areas to examine how the impacts of urban imperviousness on hydrological systems can be quantified and modelled. It examines the nature of reported impacts of urbanisation on hydrological systems over four decades, including the effects of changes in imperviousness within catchments, and some inconsistencies in studies of the impacts of urbanisation. The distribution of imperviousness within urban areas is important in understanding the impacts of urbanisation and quantification requires detailed characterisation of urban areas. As a result most mapping of urban areas uses remote sensing techniques and this review examines a range of techniques using medium and high resolution imagery, including spectral unmixing. The third section examines the ways in which scientists and hydrological and environmental engineers model and quantify water flows in urban areas, the nature of hydrological models and methods for their calibration. The final section examines additional factors which influence the impact of impervious surfaces and some uncertainties that exist in current knowledge.     

Managing the impact of climate change on the hydrology of the Gallocanta Basin,NE-Spain

The Gallocanta Basin represents an environment highly sensitive to climate change. Over the past 60 years, the Laguna de Gallocanta, an ephemeral lake situated in the closed Gallocanta basin, experienced a sequence of wet and dry phases. The lake and its surrounding wetlands are one of only a few bird sanctuaries left in NE-Spain for grey cranes on their annual migration from Scandinavia to northern Africa. Understanding the impact of climate change on basin hydrology is therefore of utmost importance for the appropriate management of the bird sanctuary. Changes in lake level are only weakly linked to annual rainfall, with reaction times between hours and months after rainfall. Both the total amount of rainfall over the reaction period, as well as individual extreme events, affect lake level. In this study the characteristics and frequencies of daily, event, monthly and bi-monthly rainfall over the past 60 years were analysed. The results revealed a clear link between increased frequencies of high magnitude rainfall and phases of water filling in the Laguna de Gallocanta. In the middle of the 20th century, the absolute amount of rainfall appears to have been more important for lake level, while more recently the frequency of high magnitude rainfall has emerged as the dominant variable.     

煤巷掘进过程中粉尘浓度影响因素分析

为了掌握煤巷掘进过程中粉尘浓度变化的影响因素,根据气固两相流理论,针对矿井掘进工作面的特点,采用计算流体力学的离散相模型（DPM）考察了掘进巷道风速、风筒直径、风筒出风口到掘进工作面距离以及风筒的悬挂高度对粉尘浓度变化的影响。结果发现：当掘进巷道风速为0.25-4 m/s时,提高巷道内的通风风速,可以降低巷道内的粉尘浓度,缩短呼吸性粉尘浓度达到稳定的时间,减小工作面粉尘的危害;有利于通风除尘的风筒相关参数为风筒直径0.4-0.6 m、风筒出风口到掘进工作面距离6-7 m、风筒悬挂高度2.0-2.2 m。     

Incorporating low-resolution historic species location data decreases performance of distribution models

Developing robust species distribution models is important as model outputs are increasingly being incorporated into conservation policy and management decisions. A largely overlooked component of model assessment and refinement is whether to include historic species occurrence data in distribution models to increase the data sample size. Data of different temporal provenance often differ in spatial accuracy and precision. We test the effect of inclusion of historic coarse-resolution occurrence data on distribution model outputs for 187 species of birds in Australian tropical savannas. Models using only recent (after 1990), fine-resolution data had significantly higher model performance scores measured with area under the receiver operating characteristic curve (AUC) than models incorporating both fine- and coarse-resolution data. The drop in AUC score is positively correlated with the total area predicted to be suitable for the species (R² = 0.163-0.187, depending on the environmental predictors in the model), as coarser data generally leads to greater predicted areas. The remaining unexplained variation is likely to be due to the covariate errors resulting from resolution mismatch between species records and environmental predictors. We conclude that decisions regarding data use in species distribution models must be conscious of the variation in predictions that mixed-scale datasets might cause.     

Evolving Expectations of Dam Removal Outcomes: Downstream Geomorphic Effects Following Removal of a Small,Gravel‐Filled Dam1

Kibler, Kelly, Desiree Tullos, and Mathias Kondolf, 2011. Evolving Expectations of Dam Removal Outcomes: Downstream Geomorphic Effects Following Removal of a Small, Gravel‐Filled Dam. Journal of the American Water Resources Association (JAWRA) 1‐16. DOI: 10.1111/j.1752‐1688.2011.00523.x Abstract: Dam removal is a promising river restoration technique, particularly for the vast number of rivers impounded by small dams that no longer fulfill their intended function. As the decommissioning of small dams becomes increasingly commonplace in the future, it is essential that decisions regarding how and when to remove these structures are informed by appropriate conceptual ideas outlining potential outcomes. To refine predictions, it is necessary to utilize information from ongoing dam removal monitoring to evolve predictive tools, including conceptual models. Following removal of the Brownsville Dam from the Calapooia River, Oregon, aquatic habitats directly below the dam became more heterogeneous over the short term, whereas changes further downstream were virtually undetectable. One year after dam removal, substrates of bars and riffles within 400 m downstream of the dam coarsened and a dominance of gravel and cobble sediments replaced previously hardpan substrate. New bars formed and existing bars grew such that bar area and volume increased substantially, and a pool‐riffle structure formed where plane‐bed glide formations had previously dominated. As the Brownsville Dam stored coarse rather than fine sediments, outcomes following removal differ from results of many prior dam removal studies. Therefore, we propose a refined conceptual model describing downstream geomorphic processes following small dam removal when upstream fill is dominated by coarse sediments.     

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States1

Moore, Richard B., Craig M. Johnston, Richard A. Smith, and Bryan Milstead, 2011. Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States. Journal of the American Water Resources Association (JAWRA) 47(5):965‐990. DOI: 10.1111/j.1752‐1688.2011.00582.x Abstract: This study investigates nutrient sources and transport to receiving waters, in order to provide spatially detailed information to aid water‐resources managers concerned with eutrophication and nutrient management strategies. SPAtially Referenced Regressions On Watershed attributes (SPARROW) nutrient models were developed for the Northeastern and Mid‐Atlantic (NE US) regions of the United States to represent source conditions for the year 2002. The model developed to examine the source and delivery of nitrogen to the estuaries of nine large rivers along the NE US Seaboard indicated that agricultural sources contribute the largest percentage (37%) of the total nitrogen load delivered to the estuaries. Point sources account for 28% while atmospheric deposition accounts for 20%. A second SPARROW model was used to examine the sources and delivery of phosphorus to lakes and reservoirs throughout the NE US. The greatest attenuation of phosphorus occurred in lakes that were large relative to the size of their watershed. Model results show that, within the NE US, aquatic decay of nutrients is quite limited on an annual basis and that we especially cannot rely on natural attenuation to remove nutrients within the larger rivers nor within lakes with large watersheds relative to the size of the lake.     

CS2在TiO2表面的多相光化学反应研究

本文运用原位漫反射红外光谱(DRIFTS)、GC、XPS等手段研究了CS2在大气半导体颗粒TiO2表面的多相光化学反应.结果表明在模拟太阳光照射下,低浓度的CS2(8.1 mg·m(-3))在TiO2:表面发生多相光化学反应,生成气态产物cos、H2S、SO2,进而在颗粒物表面生成硫酸盐.在氧气体积浓度为21%,氙灯照...     

Estimating influence of stocking regimes on livestock grazing distributions

Livestock often concentrate grazing in particular regions of landscapes while partly or wholly avoiding other regions. Dispersing livestock from the heavily grazed regions is a central challenge in grazing land management. Position data gathered from GPS-collared livestock hold potential for increasing knowledge of factors driving livestock aggregation patterns, but advances in gathering the data have outpaced advancements in analyzing and learning from it. We fit a hierarchical seemingly unrelated regression (SUR) model to explore how season of stocking and the location where cattle entered a pasture influenced grazing distributions. Stocking alternated between summer on one side of the pasture one year and fall on another side of the pasture the next year for 18 years. Waypoints were recorded on cattle for 50 d each year. We focused our analysis on the pasture's 10 most heavily grazed 4-ha units, because these units were the most prone to negative grazing impacts. Though grazing of the study units was always disproportionately heavy, it was much heavier with the summer than fall stocking regime: Bayesian confidence intervals indicate summer grazing of study units was approximately double the average fall grazing value. This is our core result, and it illustrates the strong effect stocking season or date or both can have on grazing distributions. We fit three additional models to explore the relative importance of stocking season versus location. According to this analysis, stocking season played a role, but stocking location was the main driver. Ostensibly minor factors (e.g. stocking location) can greatly influence livestock distributions.     

Predicting modes of spatial change from state-and-transition models

State-and-transition models (STMs) can represent many different types of landscape change, from simple gradient-driven transitions to complex, (pseudo-) random patterns. While previous applications of STMs have focused on individual states and transitions, this study addresses broader-scale modes of spatial change based on the entire network of states and transitions. STMs are treated as mathematical graphs, and several metrics from algebraic graph theory are applied—spectral radius, algebraic connectivity, and the S-metric. These indicate, respectively, the amplification of environmental change by state transitions, the relative rate of propagation of state changes through the landscape, and the degree of system structural constraints on the spatial propagation of state transitions. The analysis is illustrated by application to the Gualalupe/San Antonio River delta, Texas, with soil types as representations of system states. Concepts of change in deltaic environments are typically based on successional patterns in response to forcings such as sea level change or river inflows. However, results indicate more complex modes of change associated with amplification of changes in system states, relatively rapid spatial propagation of state transitions, and some structural constraints within the system. The implications are that complex, spatially variable state transitions are likely, constrained by local (within-delta) environmental gradients and initial conditions. As in most applications, the STM used in this study is a representation of observed state transitions. While the usual predictive application of STMs is identification of local state changes associated with, e.g., management strategies, the methods presented here show how STMs can be used at a broader scale to identify landscape scale modes of spatial change.