Using river distances in the space/time estimation of dissolved oxygen along two impaired river networks in New Jersey.
Understanding surface water quality is a critical step towards protecting human health and ecological stability. Because of resource deficiencies and the large number of river miles needing assessment, there is a need for a methodology that can accurately depict river water quality where data do not exist. The objective of this research is to implement a methodology that incorporates a river metric into the space/time analysis of dissolved oxygen data for two impaired river basins. An efficient algorithm is developed to calculate river distances within the BMElib statistical package for space/time geostatistics. We find that using a river distance in a space/time context leads to an appreciable 10% reduction in the overall estimation error, and results in maps of DO that are more realistic than those obtained using a Euclidean distance. As a result river distance is used in the subsequent non-attainment assessment of DO for two impaired river basins in New Jersey.
Money
Eric
E
University of North Carolina, Department of Environmental Sciences & Engineering, Chapel Hill, NC 27599-7431, USA. emoney@email.unc.edu
Carter
Gail P
GP
Serre
Marc L
ML
D000465:Algorithms; D008962:Models, Theoretical; D009515:New Jersey; D010100:Oxygen / Q000032:analysis*; D045483:Rivers
D010100:Oxygen