Spatial modelling and prediction on river networks: up model, down model or hybrid?

Preservation of rivers and water resources is crucial in most environmental policies and many efforts are made to assess water quality. Environmental monitoring of large river networks are based on measurement stations. Compared to the total length of river networks, their number is often limited and there is a need to extend environmental variables that are measured locally to the whole river network. The objective of this paper is to propose several relevant geostatistical models for river modeling. These models use river distance and are based on two contrasting assumptions about dependency along a river network. Inference using maximum likelihood, model selection criterion and prediction by kriging are then developed. We illustrate our approach on two variables that differ by their distributional and spatial characteristics: summer water temperature and nitrate concentration. The data come from 141 to 187 monitoring stations in a network on a large river located in the Northeast of France that is more than 5000 km long and includes Meuse and Moselle basins. We first evaluated different spatial models and then gave prediction maps and error variance maps for the whole stream network.

Situational and Driver Characteristics Associated With Deervehicle Collisions in Southeastern Michigan

Deer-vehicle collisions (DVCs) create societal impacts throughout the range of white-tailed deer (Odocoileus virginanus). In Michigan reported DVCs increased by nearly 60% between 1992-2003, with current estimates at more than 65,000 DVCs per year and a mean of $2,300 vehicle damage. To better understand where to direct education and information programs, we used Office of Highway Safety Planning (OHSP) data, 2001-2003, to profile driver characteristics and accident situations of DVCs in Washtenaw, Oakland, and Monroe Counties in Michigan. Each county varies in intensity of land use, human and deer densities, and available deer habitat. Deer density in Washtenaw, Oakland, and Monroe Counties was 49.5, 21.9 and 8.9 per mi2, respectively, and the annual rate of DVCs in these counties was 5.3, 2.6 and 1.8 per 1,000 licensed drivers. Drivers are at particular risk of being involved in DVCs between 6pm- 6am, which includes dawn and dusk commuting hours, and night. Single lane roads and roads with higher posted speed limits provided greater risk to drivers of involvement in a DVC. Middle-aged drivers, particularly males, were at increased risk deer-related collisions. Results from this study will be combined with survey research to determine how best to educate drivers about risk factors that make occurrence of a DVC more likely.