Development and use of spatial interpolation methods to analyze trends in Chesapeake Bay seasonal hypoxia and stratification

Hypoxia is a critical water quality concern for living resources in Chesapeake Bay and other water bodies worldwide. Causes of hypoxia in Chesapeake Bay are related to both biogeochemical and physical processes, with nutrient loadings and stratification being two commonly cited factors. Within this context, unanswered questions remain about the relationship of oxygen conditions to changes in nutrient loads.;The motivation for this research was to evaluate long-term trends in hypoxic volume (the volume of water with low oxygen) principally by developing improved access and workflows for considering bay data and by creating and applying improved tools for spatial interpolation. The approach was two-fold: (1) develop and test alternative spatial interpolation techniques for water quality data as needed to compute hypoxic volume; and (2) use these methods to investigate hypotheses about hypoxia trends and changes in bay stratification.;The interpolation methods developed in this work included kriging-based methods that (1) incorporate process-based model output, (2) account for vertical anisotropy in the bay, and (3) use alternative measures of similarity (rather than Euclidean distance) – i.e., “water distance” (the distance between points over water) and “travel time” (the time for water to flow between locations). These interpolation methods were used to examine the long-term trends in hypoxic volume, and results were compared to stratification and nutrient-load trends.;A major new finding was that there are clear intra-summer differences in the long-term trends of hypoxic volume in Chesapeake Bay. In particular, there has been an increase in early summer hypoxic volume in recent decades and a slight decrease in late summer hypoxia. The increase in early summer hypoxia correlates with an increase in early summer bay stratification strength and the decrease in late summer hypoxia correlates with trends of decreasing total nitrogen loading to the bay. More generally, the research showed that inclusion of more location-and process-specific information into water quality interpolations can improve interpolation performance in shallow waters, lateral transects, and areas with complex flow. Overall, this research revealed important trends in Chesapeake Bay water quality and resulted in new tools for data analysis in physically dynamic and complex water bodies.