Uncertainty assessment in watershed‐scale water quality modeling and management: 1. Framework and application of generalized likelihood uncertainty estimation (GLUE) approach

摘要: [1] Watershed-scale water quality models involve substantial uncertainty in model output because of sparse observations and other sources uncertainty. Assessing the is very important for those who use to support management decision making. Systematic analysis these has rarely been done remains a major challenge. This study aimed (1) develop framework characterize all their interactions management-oriented watershed modeling, (2) apply generalized likelihood estimation (GLUE) approach quantifying simulation complex models, (3) investigate influence subjective choices (especially measure) GLUE analysis, as well availability observational data, on outcome analysis. A two-stage was first established basis assessment probabilistic decision-making. (watershed risk (WARMF)) implemented using data from Santa Clara River Watershed southern California. typical catchment constructed which series experiments conducted. The results show that can be with affordable computational cost, yielding insights into behavior. However, highly depend made by modeler data. importance considering concerns also demonstrated. Overall, this establishes guidance modeling. have suggested future efforts we could make GLUE-based led development new method, will introduced companion paper. Eventually, should assist generation models.