Modeling managed flows in the Sacramento/San Joaquin watershed, California, under scenarios of future change for CASCaDE2

Abstract

Projections of managed flows from the Sacramento River/San Joaquin River watershed, California, into the San Francisco Bay and Sacramento-San Joaquin Delta under scenarios of future climate change are needed for evaluations of potential impacts on water supply and estuarine ecosystems. A new, multiple-model approach for achieving this is described. First, downscaled global climate model outputs are used to drive an existing Variable Infiltration Capacity/Variable Infiltration Capacity Routing (VIC/RVIC) model of Sacramento/San Joaquin hydrology, resulting in projections of daily, unimpaired flows (flows unaffected by management infrastructure such as reservoirs, diversions, exports, and so on) throughout the watershed. A management model, Computational Assessments of Scenarios of Change for the Delta Ecosystem phase 2 (CASCaDE2) modified CalSim (C2-CalSim), uses these projections as inputs and produces monthly estimates of reservoir and other infrastructure operations and resulting downstream managed flows. A historical resampling algorithm, CASCaDE2 resampling algorithm (CRESPI), also uses the projected daily unimpaired flows, along with historical managed flows, to estimate the daily variability in managed flows (flows that have been altered by management infrastructure and actions) throughout the watershed. The monthly and daily managed-flow estimates are combined in a way that preserves the multi-decadal variability and century-scale trends produced by the C2-CalSim model and the day-today variability produced by the CRESPI algorithm. The performance of the new modeling approach is evaluated at major inflows to the Bay-Delta estuary using multiple metrics and found to be satisfactory for the purposes of future scenario evaluation.

Responses of Unimpaired Flows, Storage, and Managed Flows to Scenarios of Climate Change in the San Francisco Bay‐Delta Watershed

“…Finer‐scale measures such as intra‐annual flow timing and extreme flow frequency (Figures d–e) capture the observed variability reasonably well, though a tendency to underestimate peak flows is again evident in the latter. Performance metrics for more detailed and site‐specific parameters than those discussed here are presented in Knowles and Cronkite‐Ratcliff ().…”

“…The C2‐CalSim model, the CRESPI algorithm, and the CRESPI scaling procedure are discussed more below. Complete details of this modeling approach are presented in Knowles and Cronkite‐Ratcliff ().…”

“…CalSim 2 has been applied in other climate‐change studies (Anderson et al, ; Brekke et al, , ; Dracup et al, ; Vicuna et al, ). While there are valid criticisms of the model (e.g., Ferreira et al, ), the performance metrics of the modeling approach used in this study (see section 3.1 and Knowles & Cronkite‐Ratcliff, ) were deemed sufficient for the present application. Key limitations and associated caveats are discussed in sections 2.7 and 4.…”

The Future of Sediment Transport and Streamflow Under a Changing Climate and the Implications for Long‐Term Resilience of the San Francisco Bay‐Delta

“…Secondly, to calculate management operations, these unimpaired flows were routed through a modified CalSim model (C2‐CalSim; Knowles & Cronkite‐Ratcliff, 2018), producing monthly managed flows for each of the dam boundary conditions. Finally, to produce the necessary daily flows for HSPF, a machine learning algorithm called CRESPI (Cascade RESamPlIng; Knowles & Cronkite‐Ratcliff, 2018) was implemented using flow outputs from the RVIC and C2‐CalSim to produce daily managed flow estimates that were scaled to match multidecadal variability represented in the C2‐CalSim outputs. A detailed explanation of each model and associated methodology can be found in Knowles and Cronkite‐Ratcliff (2018).…”

“…Daily streamflow boundary conditions below each dam ( Figure 1) for the historical HSPF model run were compiled and input directly to the model (Stern et al, 2016). To develop future time series of outflow for each reservoir site, a combination of models was applied to simulate future managed flows that reflected the influences of reservoir operational rules, diversions, and groundwater pumping (Knowles & Cronkite-Ratcliff, 2018). This process was three-fold.…”