Vulnerability‐based frameworks are increasingly used to better understand water system performance under climate change. This work advances the use of stochastic weather generators for climate vulnerability assessments that simulate weather based on patterns of regional atmospheric flow (i.e., weather regimes) conditioned on global‐scale climate features. The model is semiparametric by design and includes (1) a nonhomogeneous Markov chain for weather regime simulation; (2) block bootstrapping and a Gaussian copula for multivariate, multisite weather simulation; and (3) modules to impose thermodynamic and dynamical climate change, including Clausius‐Clapeyron precipitation scaling, elevation‐dependent warming, and shifting dynamics of the El Niño–Southern Oscillation (ENSO). In this way, the model can be used to evaluate climate impacts on water systems based on hypotheses of dynamic and thermodynamic climate change. The model is developed and tested for cold‐season climate in the Tuolumne River Basin in California but is broadly applicable across the western United States. Results show that eight weather regimes exert strong influences over local climate in the Tuolumne Basin. Model simulations adequately preserve many of the historical statistics for precipitation and temperature across sites, including the mean, variance, skew, and extreme values. Annual precipitation and temperature are somewhat underdispersed, and precipitation spell statistics are negatively biased by 1‐2 days. For simulations of future climate, the model can generate a range of Clausius‐Clapeyron scaling relationships and modes of elevation‐dependent warming. Model simulations also suggest a muted response of Tuolumne climate to changes in ENSO variability.
Climate vulnerability assessments have become a common feature of water resources systems planning studies (Arnell, 2011;Plummer et al., 2012; US Bureau of Reclamation, 2012;Weaver et al., 2013). These assessments generally require ensemble simulations of future climate scenarios that are passed through a combination of hydrologic models and water resources systems models to measure the vulnerability of the water system to properties of future climate. Once these vulnerabilities are identified, additional simulation or optimization experiments are used to determine how well different adaptation actions mitigate these vulnerabilities (
<p>Nature-based features (NNBFs) have emerged over the past two decades as tools to leverage natural processes that provide a range of functions from flood reduction to pollutant removal. Despite their growing popularity, a notable gap remains between our understanding of internal NNBF processes and our ability to design NNBFs for specific objectives (e.g., x% reduction of peak storm flow, x% nitrogen reduction) by leveraging such processes. NNBF benefits are, as a result, difficult to quantify, making them a riskier investment compared to tried-and-true grey infrastructure alternatives. This knowledge gap must be filled if we want to design effective and sustainable NNBFs that are viewed on equal footing with grey infrastructure. This presentation will discuss the development of a non-tidal constructed wetland model for the purpose of evaluating design suitability across a range of performance metrics. This model, written in MATLAB, couples hydrologic, hydraulic, and water quality modules. It also allows the user to adjust the constructed wetland configuration (i.e., shape, area, grid cell water depths, vegetation placement, etc.) to maximize specific performance objectives including flood control, wildlife habitat, and water quality. Current efforts are also underway to build upon this design model concept to (1) expand to tidal wetland environments like salt marshes, (2) incorporate vegetation growth/death and morphologic processes, and (3) to incorporate future uncertainty into the design process to support the development of robust and sustainable NNBFs across a range of potential futures and landscape contexts. The overall aim of this work is to develop a framework that allows engineers and policy-makers to evaluate NNBF performance on level footing with grey infrastructure alternatives.</p>
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