Journal
JOURNAL OF ENVIRONMENTAL ENGINEERING
Volume 136, Issue 2, Pages 160-171Publisher
ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)EE.1943-7870.0000121
Keywords
Kriging; Interpolation; Water quality modeling; Salinity; Temperature; Dissolved oxygen; Chesapeake
Funding
- National Science Foundation [0618986]
- Directorate For Engineering
- Div Of Chem, Bioeng, Env, & Transp Sys [0618986, 0854329] Funding Source: National Science Foundation
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [0853765] Funding Source: National Science Foundation
Ask authors/readers for more resources
Spatial interpolation methods are frequently used to estimate values of physical or chemical constituents in locations where they are not measured. Very little research has been conducted, however, to investigate the relative performance of different interpolation methods in surface waters. The study reported here uses archived water quality data from the Chesapeake Bay to compare three spatial interpolation methods: inverse distance weighting, ordinary kriging, and a universal kriging method that incorporates output from a process-based water quality model. Interpolations were performed on salinity, water temperature, and dissolved oxygen snap shots (cruise-based data sets) taken between 1985 and 1994 at 21 different depths for multiple locations in the mainstem Bay, using data compiled by the prototypical Chesapeake Bay Environmental Observatory. The kriging methods generally outperform inverse distance weighting for all parameters and depths. Incorporating output from the water quality model through universal kriging appears to improve some of the interpolations by specifically accounting for some physical and biogeochemical features of the estuary. Such integration of process-based information with statistical interpolation warrants further study.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available