Construction of a historical Water Pollution Index for the Mersey Basin

The Mersey Basin has been significantly polluted for over 200 years. However, there is a lack of quantitative historical water quality data as effective water quality monitoring and data recording only began 30-40 years ago. This paper assesses water pollution in the Mersey Basin using a Water Pollution Index constructed from social and economic data. Methodology, output and the difficulties involved with validation are discussed. With the limited data input available the index approximately reproduces historical water quality. The paper illustrates how historical studies of environmental water quality may provide valuable identification of factors responsible for pollution and a marker set for contemporary and future water quality issues in the context of the past. This is an issue of growing research interest.

Linking urban water balance and energy balance models to analyse urban design options

Using a water balance modelling framework, this paper analyses the effects of urban design on the water balance, with a focus on evapotranspiration and storm water. First, two quite different urban water balance models are compared: Aquacycle which has been calibrated for a suburban catchment in Canberra, Australia, and the single-source urban evapotranspiration-interception scheme (SUES), an energy-based approach with a biophysically advanced representation of interception and evapotranspiration. A fair agreement between the two modelled estimates of evapotranspiration was significantly improved by allowing the vegetation cover (leaf area index, LAI) to vary seasonally, demonstrating the potential of SUES to quantify the links between water sensitive urban design and microclimates and the advantage of comparing the two modelling approaches. The comparison also revealed where improvements to SUES are needed, chiefly through improved estimates of vegetation cover dynamics as input to SUES, and more rigorous parameterization of the surface resistance equations using local-scale suburban flux measurements. Second, Aquacycle is used to identify the impact of an array of water sensitive urban design features on the water balance terms. This analysis confirms the potential to passively control urban microclimate by suburban design features that maximize evapotranspiration, such as vegetated roofs. The subsequent effects on daily maximum air temperatures are estimated using an atmospheric boundary layer budget. Potential energy savings of about 2% in summer cooling are estimated from this analysis. This is a clear ‘return on investment’ of using water to maintain urban greenspace, whether as parks distributed throughout an urban area or individual gardens or vegetated roofs.

The surface urban energy and water balance scheme (SUEWS): evaluation in Los Angeles and Vancouver

An urban energy and water balance model is presented which uses a small number of commonly measured meteorological variables and information about the surface cover. Rates of evaporation-interception for a single layer with multiple surface types (paved, buildings, coniferous trees and/or shrubs, deciduous trees and/or shrubs, irrigated grass, non-irrigated grass and water) are calculated. Below each surface type, except water, there is a single soil layer. At each time step the moisture state of each surface is calculated. Horizontal water movements at the surface and in the soil are incorporated. Particular attention is given to the surface conductance used to model evaporation and its parameters. The model is tested against direct flux measurements carried out over a number of years in Vancouver, Canada and Los Angeles, USA. At all measurement sites the model is able to simulate the net all-wave radiation and turbulent sensible and latent heat well (RMSE = 25–47 W m−2, 30–64 and 20–56 W m−2, respectively). The model reproduces the diurnal cycle of the turbulent fluxes but typically underestimates latent heat flux and overestimates sensible heat flux in the day time. The model tracks measured surface wetness and simulates the variations in soil moisture content. It is able to respond correctly to short-term events as well as annual changes. The largest uncertainty relates to the determination of surface conductance. The model has the potential be used for multiple applications; for example, to predict effects of regulation on urban water use, landscaping and planning scenarios, or to assess climate mitigation strategies.

Flood detection in urban areas using TerraSAR-X

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X Synthetic Aperture Radar (SAR) data to detect flooded regions in urban areas is described. The study uses a TerraSAR-X image of a 1 in 150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SAR End-To-End simulator (SETES) was used in conjunction with airborne scanning laser altimetry (LiDAR) data to estimate regions of the image in which water would not be visible due to shadow or layover caused by buildings and taller vegetation. A semi-automatic algorithm for the detection of floodwater in urban areas is described, together with its validation using the aerial photographs. 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. The algorithm is aimed at producing urban flood extents with which to calibrate and validate urban flood inundation models, and these findings indicate that TerraSAR-X is capable of providing useful data for this purpose.

Detection of flood extent in urban areas using high resolution TerraSAR-X data

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

"Ever-growing Amman", Jordan: Urban expansion, social polarisation and contemporary urban planning issues

Amman the primate capital city of the Hashemite Kingdom of Jordan currently has a population in excess of 2 million, but in 1924 it consisted of little more than a collection of dwellings and some 2000-3000 inhabitants. The present paper sets out to document and explain the phenomenal expansion of "ever-growing Amman". The physical geography of the urban region and the early growth of the city are considered at the outset and this leads directly to consideration of the highly polarised social structuring that characterises contemporary Amman. In doing this, original data derived from the recent Greater Amman Municipality's Geographical Information System are presented. In this respect, the essential modernity of the city is exemplified. The employment and industrial bases of the city and a range of pressing contemporary issues are then considered, including transport and congestion, the provision of urban water under conditions of water stress and privatisation, and urban and regional development planning for the city. The paper concludes by emphasizing the growing regional and international geopolitical salience of the city of Amman at the start of the 21st century. (C) 2008 Elsevier Ltd. All rights reserved.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively.

Estimating regional benefits of reducing targeted pollutants: An application to agricultural effects on water quality and the value of recreational fishing

The general focus of this paper is the regional estimation of marginal benefits of targeted water pollution abatement to instream uses. Benefit estimates are derived from actual consumer choices of recreational fishing activities and the implied expenditures for various levels of water quality. The methodology is applied to measuring the benefits accruing to recreational anglers in Indiana from the abatement of pollutants that are by-products of agricultural crop production.

Determinants of pollution: what do we really know?

The recent literature proposes many variables as significant determinants of pollution. This paper gives an overview of this literature and asks which of these factors have an empirically robust impact on water and air pollution. We apply Extreme Bound Analysis (EBA) on a panel of up to 120 countries covering the period 1960–2001. We find supportive evidence of the existence of the environmental Kuznets curve for water pollution. Furthermore, mainly variables capturing the economic structure of a country affect air and water pollution.

Hydrological controls on soil redox dynamics in a peat-based, restored wetland

Increasing areas of altered wetland are being restored by re-flooding the soil. Evidence in the literature indicates that this practice can induce the redox-mediated release of soil nutrients, thereby increasing the risk of diffuse water pollution. However, for the sake of improving wedand management decisions, there is a need for more detailed studies of the underlying relationship between the hydrological and redox dynamics that explain this risk; this is particularly the case in agricultural peatlands that are commonly targeted for the creation of lowland wet grassland. A 12-month field study was conducted to evaluate the relationship between hydrological fluctuations and soil redox potential (Eh) in a nutrient-rich peat field (32 g N kg(-1) and 1100 mg P kg(-1) in the surface 0-30 cm soil) that had been restored as lowland wet grassland from intensive arable production. Field tensiometers were installed at the 30-, 60- and 90-cm soil depths, and Pt electrodes at the 10-, 30-, 60- and 90-cm depths, for daily logging of soil water tension and Eh, respectively. The values for soil water tension displayed a strong negative relationship (P < 0.001) with monthly dip well observations of water table height. Calculations of soil water potential from the logged tension values were used, therefore, to provide a detailed profile of field water level and, together with precipitation data, explained some of the variation in Eh. For example, during the summer, alternating periods of aerobism (Eh > 330 mV) in the surface, 0-10 cm layer of peat coincided with intense precipitation events. Redox potential throughout the 30-100 cm profile also fluctuated seasonally; indeed, at all depths Eh displayed a strong, negative relationship (P < 0.001) with water table height over the 12-month study period. However, Eh throughout the 30-100 cm profile remained relatively low (< 230 mV), indicating permanently reduced conditions that are associated with denitrification and reductive dissolution of Fe-bound P. The implications of these processes in the N- and P-rich peat for wetland plant diversity and water quality are discussed. (c) 2006 Elsevier B.V. All rights reserved.

An application of life-cycle assessment for environmental planning and management: the potential environmental and human health impacts of growing genetically-modified herbicide-tolerant sugar beet

Life-Cycle Assessment (LCA) was used to assess the potential environmental and human health impacts of growing genetically-modified (GM), herbicide-tolerant sugar beet in the UK and Germany compared with conventional sugar beet varieties. The GM variety results in lower potential environmental impacts on global warming, airborne nutrification, ecotoxicity (of soil and water) and watercourse enrichment, and lower potential human health impacts in terms of production of toxic particulates, summer smog, carcinogens and ozone depletion. Although the overall contribution of GM sugar beet to reducing harmful emissions to the environment would be relatively small, the potential for GM crops to reduce pollution from agriculture, including diffuse water pollution, is highlighted.

The use of life-cycle assessment to evaluate the environmental impacts of growing genetically modified, nitrogen use-efficient canola

Agriculture, particularly intensive crop production, makes a significant contribution to environmental pollution. A variety of canola (Brassica napus) has been genetically modified to enhance nitrogen use efficiency, effectively reducing the amount of fertilizer required for crop production. A partial life-cycle assessment adapted to crop production was used to assess the potential environmental impacts of growing genetically modified, nitrogen use-efficient (GMNUE) canola in North Dakota and Minnesota compared with a conventionally bred control variety. The analysis took into account the entire production system used to produce 1 tonne of canola. This comprised raw material extraction, processing and transportation, as well as all agricultural field operations. All emissions associated with the production of 1 tonne of canola were listed, aggregated and weighted in order to calculate the level of environmental impact. The findings show that there are a range of potential environmental benefits associated with growing GMNUE canola. These include reduced impacts on global warming, freshwater ecotoxicity, eutrophication and acidification. Given the large areas of canola grown in North America and, in particular, Canada, as well as the wide acceptance of genetically modified varieties in this area, there is the potential for GMNUE canola to reduce pollution from agriculture, with the largest reductions predicted to be in greenhouse gases and diffuse water pollution.