Bridging groundwater models and decision support with a Bayesian network
Fienen, Michael N.
Masterson, John P.
Plant, Nathaniel G.
Gutierrez, Benjamin T.
Thieler, E. Robert
MetadataShow full item record
Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.
Author Posting. © American Geophysical Union, 2013. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Water Resources Research 49 (2013): 6459–6473, doi:10.1002/wrcr.20496.
Showing items related by title, author, creator and subject.
Characterizing the natural system : toward sustained, integrated coastal ocean acidification observing networks to facilitate resource management and decision support Alin, Simone R.; Brainard, Russell E.; Price, Nichole N.; Newton, Jan A.; Cohen, Anne L.; Peterson, William T.; De Carlo, Eric H.; Shadwick, Elizabeth H.; Noakes, Scott; Bednarsek, Nina (The Oceanography Society, 2015-06)Coastal ocean ecosystems have always served human populations—they provide food security, livelihoods, coastal protection, and defense. Ocean acidification is a global threat to these ecosystem services, particularly when ...
A decision support tool for response to global change in marine systems : the IMBER-ADApT Framework Bundy, Alida; Chuenpagdee, Ratana; Cooley, Sarah R.; Defeo, Omar; Glaeser, Bernhard; Guillotreau, Patrice; Isaacs, Moenieba; Mitsutaku, Makino; Perry, R. Ian (2014-05)Global change is occurring now, often with consequences far beyond those anticipated. Although there is a wide range of assessment approaches available to address specific aspects of global change, there is currently no ...
Decision-support for the economic analysis of trade-offs in coastal and marine spatial planning (CMSP) for the US northeast shelf large marine ecosystem Hoagland, Porter; Jin, Di (2011-09-20)Coastal and marine spatial planning (CMSP) is a process for improving the management of coastal and marine resources in order to promote their sustainable development. Sustainability necessitates that decisions be made ...