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Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty assessment accounting for prior understanding and what is learned through model development and data assimilation. Model construction and data assimilation are time consuming and prone to errors, which motivates a repeatable workflow where revisions resulting from new interpretations or discovery of errors can be addressed and the analyses repeated efficiently and rigorously. In this work, motivated by the real world application of delineating risk-based (probabilistic) sources of water to supply wells in a humid temperate climate, a scripted workflow was generated for groundwater model construction, data assimilation, particle-tracking and post-processing. The workflow leverages existing datasets describing hydrogeology, hydrography, water use, recharge, and lateral boundaries. These specific data are available in the United States but the tools can be applied to similar datasets worldwide. The workflow builds the model, performs ensemble-based history matching, and uses a posterior Monte Carlo approach to provide probabilistic capture zones describing source water to wells in a risk-based framework. The water managers can then select areas of varying levels of protection based on their tolerance for risk of potential wrongness of the underlying models. All the tools in this workflow are open-source and free, which facilitates testing of this repeatable and transparent approach to other environmental problems.

Transport of nutrients to lakes can occur via surface-water inflow, atmospheric deposition, groundwater (GW) inflow and benthic processes. Identifying and quantifying within-lake nutrient sources and recycling processes is challenging. Prior studies in hypereutrophic Upper Klamath Lake, Oregon, USA, indicated that ~60% of the early summer phosphorus (P) load to the lake was internal and hypothesized to be lakebed sediment release. Dynamic nutrient transport processes were examined to better characterize the nutrient sources. One-dimensional heat transport models calibrated to observed lakebed temperatures and a cross-sectional GW flow model provided estimates of GW-inflow rates that were greatest in spring and decreased through summer. One-dimensional solute transport models calibrated to observed lakebed pore-water dissolved silica (Si) and dissolved phosphate-phosphorus (DP) concentrations indicated that nutrients were transported from the lakebed by advection, diffusion, and enhanced mixing by benthic organisms and waves, and that DP removal occurred near the lakebed interface. Estimated water, Si, DP and total-phosphorus (TP) budgets indicated that GW contributed 21% of lake water inflow and at least 26, 20 and 16% of total Si, DP and TP inflow, respectively, when conservatively assuming background GW nutrient concentrations. However, lakebed GW (LGW) is enriched in nutrients during flow through lakebed sediment and the estimated GW contribution increased to 29 (33), 49 (67) and 43% (61%) of total Si, DP and TP inflow, respectively, if 20% (50%) of GW inflow to the lake was assumed to have LGW concentrations. Net nutrient inflow to the lake was greatest in spring and coincident with the annual diatom bloom. Inflowing dissolved nutrients appear to be assimilated by diatoms during the spring and become available for the summer Aphanizomenon flos-aquae bloom when the diatoms senesce. Thus, nutrient-enriched GW inflow and nutrient recycling by successive algal blooms must be considered when evaluating internal nutrient loading to lakes.