Lessons learned from the 2013 Calgary flood: Assessing risk of drinking water well contamination

A devastating flood occurred in southern Alberta on June 19, 2013, from greater than normal snowfalls in the Rocky Mountains and excess precipitation during the early spring that left soils saturated and unable to absorb any additional precipitation. This flood was Canada's most costly natural disaster, with five to six billion Canadian dollars in damages. The first objective of this study was to determine if the flood caused an increase in private drinking water well contamination in the Calgary Health Zone by comparing contamination rates to previous years. The second objective was to determine which environmental factors were associated with contamination during this flood event. Test results of total coliforms (TC) and Escherichia coli (EC) of private water wells were used to determine contamination. A geographically weighted Poisson regression analysis suggested that TC contamination was not associated with this flood. The EC contamination is positively associated with floodways, flood fringe, farms, and negatively associated with intermittent water (sloughs). These results suggest that for the 2013 flood, individual well characteristics are more important than surrounding geographic features. Thus, it is recommended that homeowners who live in a high-risk area ensure their wells are properly maintained to reduce risk of water well contamination.     

Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices

By incorporating temporal effects into the geographically weighted regression (GWR) model, an extended GWR model, geographically and temporally weighted regression (GTWR), has been developed to deal with both spatial and temporal nonstationarity simultaneously in real estate market data. Unlike the standard GWR model, GTWR integrates both temporal and spatial information in the weighting matrices to capture spatial and temporal heterogeneity. The GTWR design embodies a local weighting scheme wherein GWR and temporally weighted regression (TWR) become special cases of GTWR. In order to test its improved performance, GTWR was compared with global ordinary least squares, TWR, and GWR in terms of goodness-of-fit and other statistical measures using a case study of residential housing sales in the city of Calgary, Canada, from 2002 to 2004. The results showed that there were substantial benefits in modeling both spatial and temporal nonstationarity simultaneously. In the test sample, the TWR, GWR, and GTWR models, respectively, reduced absolute errors by 3.5%, 31.5%, and 46.4% relative to a global ordinary least squares model. More impressively, the GTWR model demonstrated a better goodness-of-fit (0.9282) than the TWR model (0.7794) and the GWR model (0.8897). McNamara's test supported the hypothesis that the improvements made by GTWR over the TWR and GWR models are statistically significant for the sample data.     

Sustainable development and urban policy: hijacking the term in Calgary

Sustainable development is not an easy term to conceptualize, despite its recent popularity, because it has been defined in a variety of different ways. Some fundamental published statements on sustainable development from the Brundtland Report and from Haughton and Hunter's recent book on Sustainable Cities are interrelated in the search for a more cohensive and integrated framework of principles that summarize the concept and which can be applied to cities. These principles are used as a background to evaluate the 1995 plans for Sustainable Suburbs in the City of Calgary, a city of over three quarters of a million population. It is shown that Calgary's proposals may have many merits but they will hardly radically change the current low density development or provide much sustainability. This conclusion comes from the fact that many of the fundamental features of sustainability are not incorporated in the recommended set of ideas, which seem more like an environmental update of Garden City and Neighbourhood Unit Design principles.     

ON THE FREQUENCY OF PRECIPITATION-DAYS IN CALGARY,CANADA

Results of analyses of 86 years of precipitation records for Calgary, Canada, showed that there were three periods of above normal precipitation and three periods of precipitation significantly below normal. This pattern gave the precipitation climate a quasi-periodic appearance. The average number of precipitation-days was 134 per annum. The reduction in the frequency of precipitation-days in dry years was not as significant as the equivalent reduction in precipitation amounts. A significant upward trend in the frequency of precipitation-days, which correlated with a similar trend in cloud cover, was not repeated in precipitation amounts. The upward trend in both cloud cover and precipitation-day frequency is believed to be related to urban growth and the corresponding heat island. This enhancement is more pronounced in the fall and winter months than in the spring and summer.