Details

Autor(en) / Beteiligte

• Razavi, Saman
• Tolson, Bryan A.
• Burn, Donald H.

Titel

Review of surrogate modeling in water resources

Ist Teil von

• Water resources research, 2012-07, Vol.48 (7), p.np-n/a

Ort / Verlag

Washington: Blackwell Publishing Ltd

Erscheinungsjahr

2012

Link zum Volltext

Quelle

Wiley Online Library

Beschreibungen/Notizen

• Surrogate modeling, also called metamodeling, has evolved and been extensively used over the past decades. A wide variety of methods and tools have been introduced for surrogate modeling aiming to develop and utilize computationally more efficient surrogates of high‐fidelity models mostly in optimization frameworks. This paper reviews, analyzes, and categorizes research efforts on surrogate modeling and applications with an emphasis on the research accomplished in the water resources field. The review analyzes 48 references on surrogate modeling arising from water resources and also screens out more than 100 references from the broader research community. Two broad families of surrogates namely response surface surrogates, which are statistical or empirical data‐driven models emulating the high‐fidelity model responses, and lower‐fidelity physically based surrogates, which are simplified models of the original system, are detailed in this paper. Taxonomies on surrogate modeling frameworks, practical details, advances, challenges, and limitations are outlined. Important observations and some guidance for surrogate modeling decisions are provided along with a list of important future research directions that would benefit the common sampling and search (optimization) analyses found in water resources. Key Points Categorize different surrogate‐enabled analysis frameworks and their components Summarize current surrogate modeling efforts and suggest future directions Outline case study features that influence surrogate model selection or design