Designing a Dynamic Data-Driven Application System for Estimating Real-Time Load of Dissolved Organic Carbon in a River

摘要

Understanding the dynamics of naturally occurring dissolved organic carbon (DOC) in a river is central to estimating surface water quality, aquatic carbon cycling, and global climate change. Currently, determination of DOC in surface water is primarily accomplished by manually collecting samples for laboratory analysis, which requires at least 24 h. In other words, no effort has been devoted to monitoring realtime variations of DOC in a river due to the lack of suitable and/or cost-effective wireless sensors. However, when considering human health, carbon footprints, effects of urbanization, industry, and agriculture on water supply, timely DOC information may be critical. We have developed here a new paradigm of a dynamic data-driven application system (DDDAS) for estimating the real-time load of DOC into a river. This DDDAS was validated with field measurements prior to its applications. Results show that the real-time load of DOC in the river varied over a range from -13,143 to 29,248 kg/ h at the selected site. The negative loads occurred because of the back flow in the estuarine reach of the river. The cumulative load of DOC in the river for the selected site at the end of the simulation (178 h) was about 1.2 tons. Our results support the utility of the DDDAS developed in this study for estimating the real-time variation of DOC in a river ecosystem.