Assessing market and non-market costs of freshwater flooding due to climate change in the community of Fredericton, Eastern Canada

There is a general consensus that climate change will increase the frequency and severity of freshwater flooding in many parts of the world. Communities prone to such flooding have struggled to understand the manner in which this will affect them (in both economic and social terms) and the appropriate way to adapt. In this study, we conduct a case-study investigation into the costs of freshwater flooding due to climate change along the Saint John River in Fredericton, NB, Canada. We develop a four-step framework that combines extreme event analysis, downscaled general circulation models, hydrologic analysis, and the contingent valuation method. Using this framework, together with primary data on a 2005 flooding event, we estimate market and non-market annual average flood damage under a number of climate and population scenarios. We find that non-market costs can represent up to 50% of total household costs of flooding events, and 23–42% of the total costs of flooding due to climate change, depending on the different climate and population scenarios considered. Incorporating such costs into flood adaptation planning may substantially increase support for active adaptation activities, especially in ‘worst case’ climate scenarios.     

Wind erosion of blanket peat during a short period of surface desiccation (North Pennines,Northern England)

Strong winds are a characteristic feature of UK upland areas. Despite this, understanding of aeolian processes in upland environments of the UK is limited. This paper presents direct measurements and observations of blanket peat erosion by wind action during a two week period of desiccation in the North Pennines, Northern England. A circular configuration of mass flux sediment samplers was used to collect peat eroded by wind action from 16 cardinal compass directions. Meteorological conditions (wind speed, wind direction, precipitation and temperature) were recorded by an automatic weather station set up adjacent to the site. Surface desiccation led to peat crust erosion and dust deflation. During short (≤1 hour) periods of precipitation, wind‐driven rainfall also caused erosion. Typically, dust flux rates were up to two orders of magnitude lower than recorded during periods of sustained wet weather. Measurements demonstrate the hitherto unreported rapid switch in process regime between wind‐driven rainfall and dry blow deflation in blanket peat environments. Dry blow processes of blanket peat erosion may become more important in UK upland areas if climate change promotes more frequent surface desiccation. Copyright © 2006 John Wiley & Sons, Ltd.     

Significance of geomorphological and subsurface drainage controls on failures of peat‐covered hillslopes triggered by extreme rainfall

On 19 September 2003, 40 landslides of 140–18 000 m³ volume occurred within 2·5 km² on the slopes of Dooncarton Mountain (Republic of Ireland) during a storm that may have exceeded 90 mm within 90 minutes. The landslides were investigated to determine the reasons for such a high density of slope failures. All of the landslides were surveyed within four months, and nine of them were investigated in detail. The six largest landslides, all peat failures, accounted for 57% of the more than 100 000 m³ of material displaced during the event. A consistent sequence of superficial materials was found on the failed hillslopes, including an extensive iron pan at the base of a buried soil horizon 0·3 m below the base of the peat. Morphologically, almost all of the landslides occurred on steep planar slopes or around sharp convexities, with the latter failures developing retrogressively upslope. The only significant relationship found from analysis of 371 subsurface pipes and 142 seepage cracks (defined here as contiguous fissures conducting concentrated subsurface flow) across all the failures was that the thinner the peat cover, the deeper the pipes and seepage cracks occurred below the base of peat. It is concluded that most of the landslides were probably caused by a combination of excess water pressures in the buried soil horizon and the thinner overburden of peat or peaty soil associated with the steeper slope segments. Pipes and seepage cracks formed on the iron pan probably existed prior to the failure event and may have contributed to the high water pressures as rainwater inputs exceeded their discharge capacities. One large peat slide was probably triggered by excess water pressures developed within and between artificial tine cuts. The properties of the blanket peat were generally of little consequence in the occurrence of the landslides, but relict desiccation cracks and other structural weaknesses through the peat mass were probably highly significant. Although several aspects of the peat failures correspond to previously published examples, the context of these failures in terms of the topography and upland catena is distinctive. Copyright © 2007 John Wiley & Sons, Ltd.     

Assessing the hydrological and geomorphic behaviour of a landscape evolution model within a limits-of-acceptability uncertainty analysis framework

Landscape evolution models (LEMs) have the capability to characterize key aspects of geomorphological and hydrological processes. However, their usefulness is hindered by model equifinality and paucity of available calibration data. Estimating uncertainty in the parameter space and resultant model predictions is rarely achieved as this is computationally intensive and the uncertainties inherent in the observed data are large. Therefore, a limits-of-acceptability (LoA) uncertainty analysis approach was adopted in this study to assess the value of uncertain hydrological and geomorphic data. These were used to constrain simulations of catchment responses and to explore the parameter uncertainty in model predictions. We applied this approach to the River Derwent and Cocker catchments in the UK using a LEM CAESAR-Lisflood. Results show that the model was generally able to produce behavioural simulations within the uncertainty limits of the streamflow. Reliability metrics ranged from 24.4% to 41.2% and captured the high-magnitude low-frequency sediment events. Since different sets of behavioural simulations were found across different parts of the catchment, evaluating LEM performance, in quantifying and assessing both at-a-point behaviour and spatial catchment response, remains a challenge. Our results show that evaluating LEMs within uncertainty analyses framework while taking into account the varying quality of different observations constrains behavioural simulations and parameter distributions and is a step towards a full-ensemble uncertainty evaluation of such models. We believe that this approach will have benefits for reflecting uncertainties in flooding events where channel morphological changes are occurring and various diverse (and yet often sparse) data have been collected over such events.     

Transboundary impacts on regional ground water modeling in Texas

Recent legislation required regional grassroots water resources planning across the entire state of Texas. The Texas Water Development Board (TWDB), the state's primary water resource planning agency, divided the state into 16 planning regions. Each planning group developed plans to manage both ground water and surface water sources and to meet future demands of various combinations of domestic, agricultural, municipal, and industrial water consumers. This presentation describes the challenges in developing a ground water model for the Llano Estacado Regional Water Planning Group (LERWPG), whose region includes 21 counties in the Southern High Plains of Texas. While surface water is supplied to several cities in this region, the vast majority of the regional water use comes from the High Plains aquifer system, often locally referred to as the Ogallala Aquifer. Over 95% of the ground water demand is for irrigated agriculture. The LERWPG had to predict the impact of future TWDB-projected water demands, as provided by the TWDB, on the aquifer for the period 2000 to 2050. If detrimental impacts were noted, alternative management strategies must be proposed. While much effort was spent on evaluating the current status of the ground water reserves, an appropriate numerical model of the aquifer system was necessary to demonstrate future impacts of the predicted withdrawals as well as the effects of the alternative strategies. The modeling effort was completed in the summer of 2000. This presentation concentrates on the political, scientific, and nontechnical issues in this planning process that complicated the modeling effort. Uncertainties in data, most significantly in distribution and intensity of recharge and withdrawals, significantly impacted the calibration and predictive modeling efforts. Four predictive scenarios, including baseline projections, recurrence of the drought of record, precipitation enhancement, and reduced irrigation demand, were simulated to identify counties at risk of low final ground water storage volume or low levels of satisfied demand by 2050.     

Does geographic location impact the survival differential between screen- and interval-detected breast cancers?

Although mammography screening programs aim to diagnose breast cancer at an early stage, not all tumours are detected during the regular screening examination. This study examines the influence of various characteristics, including geographical residence, on the survival between screen- and interval-detected breast cancers among participants of a public population-based breast screening program in Queensland, Australia. The investigation was performed using the linked population-based datasets from BreastScreen Queensland and the Queensland Cancer Registry for the period of 1997–2008 for women aged 40–89 years at diagnosis. A Bayesian spatial relative survival modelling approach that accommodates rare outcomes in small geographic regions was adopted, with the use of Markov chain Monte Carlo computation, to evaluate the relative excess risk of breast cancer. In the multivariate Bayesian spatial model, higher relative excess risk of mortality was observed in interval-detected cancer (RER = 1.59, 95 % credible interval = [1.33, 1.89]) compared to screen-detected cancer. Higher cancer survival among the study cohort was also observed among younger women (40–59 years), those of non-Indigenous ethnicity, with localised (stage I) tumour stage as well as those not in the work force. There was no independent association with marital status. Moreover, there was no substantive evidence of either measured geographical or latent random spatial inequalities in survival among screening participants across Queensland, meaning the higher survival for screen-detected breast cancer patients compared to interval-detected women was consistent across the state. These results provide suggestive evidence supporting the effectiveness of the BreastScreen Queensland screening program in reaching socio-economically disadvantaged women as well as those living in rural and remote areas of the state, but also highlights the need for any interval cancer awareness programs to be geographically widespread.     

Time–space continuity of daily maps of fractional snow cover and albedo from MODIS

Using reflectance values from the seven MODIS “land” bands with 250 or 500 m resolution, along with a corresponding cloud product, we estimate the fraction of each 500 m pixel that snow covers, along with the albedo of that snow. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry. Rather than make users interpolate and filter these patchy daily maps without completely understanding the retrieval algorithm and instrument properties, we use the daily time series to improve the estimate of the measured snow properties for a particular day. We use a combination of noise filtering, snow/cloud discrimination, and interpolation and smoothing to produce our best estimate of the daily snow cover and albedo. We consider two modes: one is the “predictive” mode, whereby we estimate the snow-covered area and albedo on that day using only the data up to that day; the other is the “retrospective” mode, whereby we reconstruct the history of the snow properties for a previous period.