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Many water planning and operation decisions are affected by climate uncertainty. Given concerns about the effects of uncertainty on the outcomes of long‐term decisions, many water planners seek adaptation alternatives that are robust given a wide range of possible climate futures. However, there is no standardized paradigm for quantifying robustnes...
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Citations
... Stormwater systems designed for a 100-year storm may no longer provide adequate protection if the frequency and intensity of such events increase [7]. New standards should incorporate the latest climate normals and provide guidance on designing infrastructure that can perform in a range of climate scenarios due to large uncertainties in current projections [8]. These standards would help urban water systems adapt to changing conditions, making them fail less (but not necessarily never) and recover faster, thus increasing resilience. ...
Urban water systems are increasingly vulnerable to climate change. Traditional planning, often based on past conditions, fails to address these new challenges. We suggest policy options for integrating climate scenarios into urban water planning, which will enhance the resilience of drinking water, wastewater, and stormwater systems. The policy options are (1) requiring climate scenario analysis in planning processes, (2) developing climate-resilient infrastructure standards, (3) promoting low-impact development and nature-based solutions, (4) creating regional planning bodies, (5) educating professionals for climate-responsive planning, and (6) securing funding for climate adaptation. We discuss our experience in the state of Utah, USA, and summarize case studies in Copenhagen, New York, and Melbourne. The policy options align with Sustainable Development Goals and offer a roadmap for building adaptable, sustainable urban water systems.
... The uncertainty in future precipitation and temperature for each period and dataset is sometimes modelled using a bivariate normal distribution (Moody and Brown 2013;Whateley et al. 2014). In the case presented here, a normal distribution is a poor fit for both precipitation and temperature changes. ...
... Evaluation of portfolios of investment options typically requires implementing new infrastructure, water rights, and altered or optimized system operations within the system model (e.g., Whateley et al. 2014;Borgomeo et al. 2018;Brown et al. 2020). A new stress test experiment must be carried out for each portfolio for which performance metrics Y and associated robustness CRI is evaluated. ...
Water resources managers face decisions related to building new infrastructure to increase water system resilience to climate and demand changes. To inform this adaptation planning process, current decision-making methods commonly use scenario approaches to estimate the benefit of adaptation options. While effective, these new analyses require communication of complicated findings to often nontechnical audiences. This paper introduces a pragmatic approach that uses the results from a bottom-up assessment of vulnerability of the water system with future climate projection-based probabilities of climate change to select a single planning scenario that encapsulates the decision-makers’ chosen level of robustness for their system. Contrary to typical implementation of option analysis under deep climate uncertainty, the proposed pragmatic approach does not require the analyst to evaluate each portfolio of adaptation options against all possible states of the world, significantly reducing the required computational costs and communication challenges. It also aligns with the planning scenario approach used in practice by water utilities. The modeling framework is illustrated for the regional water system operated by the San Francisco Public Utilities Commission (California, United States) for which changes in average temperature, precipitation and urban demand are considered.
... Affected by climate characteristics on watershed and regional scales, uncertainties are introduced at every step in this top-down approach. Even the stress testing (or sensitivity-based) technique, which is independent from GCM results, can be affected by the uncertainties in hydrological model structures and parameters [3][4][5][6]. ...
Understanding hydrological nonstationarity under climate change is important for runoff prediction and it enables more robust decisions. Regarding the multiple structural hypotheses, this study aims to identify and interpret hydrological structural nonstationarity using the Bayesian Model Averaging (BMA) method by (i) constructing a nonstationary model through the Bayesian weighted averaging of two lumped conceptual rainfall–runoff (RR) models (the Xinanjiang and GR4J model) with time-varying weights; and (ii) detecting the temporal variation in the optimized Bayesian weights under climate change conditions. By combining the BMA method with period partition and time sliding windows, the efficacy of adopting time-varying model structures is investigated over three basins located in the U.S. and Australia. The results show that (i) the nonstationary ensemble-averaged model with time-varying weights surpasses both individual models and the ensemble-averaged model with time-invariant weights, improving NSE[Q] from 0.04 to 0.15; (ii) the optimized weights of Xinanjiang model increase and that of GR4J declines with larger precipitation, and vice versa; (iii) the change in the optimized weights is proportional to that of precipitation under monotonic climate change, as otherwise the mechanism changes significantly. Overall, it is recommended to adopt nonstationary structures in hydrological modeling.
... (13)-(15), and as such, the robustness metrics are calculated from each 1 , 2 , and 3 . To account for both the magnitude and frequency of violations, the robustness metrics are formulated as the combination of (1) the average normalized magnitude of violations (Abokifa et al., 2020) and (2) the percent of Stage II solutions that incur a violation (Whateley et al., 2014;Moody and Brown, 2013). For each Stage I solution, the final demand, quality, and sustainability metrics are calculated as: ...
... The robustness index (RI) is a generalized metric for quantifying robustness under climate change uncertainty that can be used to compare alternative adaptation strategies, and this concept can be extended to other sources of uncertainty associated with CBA studies to provide insight into the level of project performance under uncertainty (Whateley et al., 2014). Mathematically, the RI is the integral of the binary performance function, ⋀ (d,X), divided by the integral of the (climate) uncertainty space considered, resulting in a fraction between zero, or never meeting the criteria, and one, or acceptable performance over the entire range considered (Moody and Brown, 2013). ...
... where, d is the decision, and X is a vector of (climate) uncertainty variables representing a future state A particular advantage of the robustness index is that it does not rely strongly on assumptions about the future, rather it is defined in a decision-focused and scenario neutral manner and provides sufficient flexibility to update information as the project progresses (Moody and Brown, 2013;Whateley et al., 2014). Alternative project designs that have a similar pointestimate ERR but different robustness to climate change can also be compared using the robustness index, and improvement in projects when additional robustness measures are implemented to guard against project failure under climate uncertainty can be examined. ...
... It can subvert the assumptions upon which the system was historically built and operated, due to changes in the probabilistic behavior of hydrologic variables that were previously assumed to be stationary. This may lead to the need for new approaches to be developed, in order to mitigate the risk, for example [2][3][4][5]; i.e., the systems that were designed according to the stationary assumption, in which the future statistical characteristics are equivalent to the historical data, are subject to vulnerable performance [6,7]. This provides the impetus to examine alternatives (or adaptations) to improve the system performance under climate variations, and to provide the best use of existing infrastructure, since the cost of upgrading to cope with the climate variations is high [6,8,9]. ...
... The use of GCM scenarios restricts decision-making capabilities, since these models can only simulate limited, discrete cases of climate variability, which results in judgments that are fraught with uncertainty. Therefore, evaluating the risks and examining the exact degree of undesirable system performances is less useful [5,7,12,13]. Furthermore, general circulation models are spatially coarse, in order to capture the high-intensity precipitation that occurs at fine spatial scales, which leads to difficult selection in the case of an adaptation strategy [14]. ...
... The change in precipitation is from a decrease of 25 percent to an increase of 5 percent, and the temperature increase is from 0.5 degrees to 2.5 degrees Celsius higher. Whateley et al. [7] examined all of the GCM outputs for CMIP3 and CMIP5 in the Connecticut River Basin in the United States for the period 2025 to 2075, and compared them to the baseline period, which spanned the years 1950 to 1999. The change in precipitation was from −5 percent to 10 percent, and the temperature increase was from +1.5 degrees Celsius to +3.5 degrees Celsius. ...
The planning and management of water resources are being impacted by climate change, and are in need of comprehensive adaptation strategies to respond to future projections. The goal of this study is to support those strategies with a new decision-making paradigm that employs a probabilistic-nonstationary hydroclimatic scenario to examine the long-term system resilience for multiple dam objectives. The modified approach to examine resilience was applied, and uses a bottom-up approach with a modified resilience concept to achieve the long-term operation targets. The approach integrates Global Circulation Models (GCMs) with a statistical weather generator (SWG) to produce a range of future scenarios. Then, the system response is evaluated against those scenarios. The study utilizes a pre-developed SWG to synthesize different trajectories by altering three weather variables: the precipitation amount, temperature mean, and wind-speed magnitude. The proposed has four staged phases: (1) identification of the future climate exposure using different GCMs; (2) future water supply estimation for scenarios using hydrological models; (3) future water demand estimation for scenarios of all system stakeholders; and (4) evaluation of system performance resilience for the dam operational purposes. The Diyala River Basin in Iraq was selected as a case study, to apply the suggested paradigm. The analysis of the GCM outputs revealed that the rainfall mean varies between −37% and +31%; temperature mean varies between +0.4 °C and 5.1 °C; and the mean wind speed varies between −22% and 11%. Based on these ranges, the future climate trajectories were simulated. According to the examination of the system’s response to those weather changes, the precipitation is the most effective parameter, followed by the temperature change, and lastly the wind speed. Furthermore, the findings show that the existing system operating rules are reliable in terms of flood protection but vulnerable in terms of drought management. The analysis of system resilience to manage the drought was found to be 0.74 for the future trajectories, while it was 0.91 for flood protection. This indicates that project managers should prioritize the drought and water scarcity management, due to climate change impact and upstream country development. The study also shows that the suggested resilience paradigm is capable of measuring the negative effects of climate change and able to provide long-term adaptation guidance for water resources management.
... On the other hand, the bottom-up approach is characterized by (1) being a decisioncentered approach (because it is designed to identify thresholds, relevant objectives, and alternative local responses to cope with change-related threats), (2) considering social vulnerability and resilience as a starting point, and (3) moving from the local to the global scale. In this regard, there are several interpretations of the bottom-up approach: while some authors use this term in relation to the exploration of local knowledge through participative methodologies (Harrison et al 2013;Bhave et al. 2014), others refer to scenario-free, robustness-based planning (Brown et al. 2012;Whateley et al. 2014;Shortridge and Zaitchik 2018;Ray et al. 2019). The latter deals with the challenges that model uncertainty poses for future infrastructure planning by integrating the identification of scenarios associated to system failure and their likelihood into robust decision-making frameworks. ...
Climate change is challenging the conventional approaches for water systems planning. Two main approaches are commonly implemented in the design of climate change adaptation plans: impact-oriented top-down approaches and vulnerability-oriented bottom-up approaches. In order to overcome the shortcomings of both approaches and take advantage of their strengths, we propose an integrative methodology to define adaptation strategies at basin scale, identifying and combining potential changes in water demand and water supply infrastructure along with climate variability and change. The impact of climate change on future local water availability is assessed applying a top-down approach. Local knowledge is used through a participatory bottom-up approach to foresee future scenarios of evolution of the agricultural sector and agricultural water demand, and to identify locally relevant adaptation strategies. A hydroeconomic model integrates the information from both approaches to identify a socially acceptable and cost-effective program of measures for each climate scenario. This method was applied to the Jucar basin, a highly regulated basin with a tight equilibrium between water resources and demands. The results show an important variability of climate change impacts across the basin, with main inflow reductions in the headwaters. The stakeholders prioritized the adaptation options of change to drip irrigation , use of non-conventional resources, and changes in water governance. The results obtained from the hydroeconomic model show that the portfolio of selected adaptation measures could significantly reduce the system's average annual deficit and cost.
... The former of these processes is common to approaches adopted for other infrastructure networks and involves a convolution of spatial functions that represent the hydrometeorological hazard (drought, flood, cyclone) at a range of different timescales, with a probabilistic representation of the resistance of the water infrastructure system network to yield a probability distribution over a set of asset failures and consequential disruptions of supply to water users (Laucelli & Giustolisi, 2015;Pant et al., 2018;Thacker et al., 2018). Analysis of drought risk, involves hydrological modeling and mass balance calculations (supply vs. demand) in order to estimate the frequency and duration of water shortage for given numbers of water users (Borgomeo et al., 2014;Ghile et al., 2014;Taner et al., 2019;Whateley et al., 2014). ...
Water utilities' supply systems are vulnerable to several climate‐related hazards, including droughts, floods and cyclones. Here we propose a generally applicable framework for conducting multi‐hazard risk assessments of water supply systems and use it to quantify the impact of present and future climate extremes on the national water supply network in Jamaica. The proposed framework involves stress‐testing a model of the system with a large set of spatially coherent drought, cyclone and pluvial and fluvial flood events to calculate the number of water users whose supplies would be disrupted during an event, that is, the Customer disruption days (CDD). We estimate the total multi‐hazard annual expected disruption to be approximately 5 days per year per utility customer under present conditions. This is increased by a factor of between 2 and 2.5 when end‐of‐century climate scenarios are propagated through the model. Our analysis shows that more high probability drought events lead to greater CDD compared with asset damage events. However, extreme asset damage events, despite manifesting over shorter timescales (days) compared to drought events (months), can lead to more widespread CDD. This quantified risk framework would allow utility managers to compare the risk of both asset damage‐ and water shortage‐induced disruptions via a common, decision‐relevant metric. However, applications to other utilities would require tailored hazard modeling approaches. The proposed risk assessment is intended to inform prioritization of infrastructure investments, ranging from asset protection to drought mitigation projects, with the goal of enhancing water supply resilience in the face of a changing climate.
... An acceptable water management activity can be related to the satisfaction of profitable, safe, and ecological requirements. The thresholds mostly used in the literature are system performance indices, such as, the RRV (Reliability, Resilience, and Vulnerability) metrics and the robustness index (see applications of water supply reliability and robustness Whateley et al., 2014;. Giuliani and Castelletti (2016) argued that different definitions of the system performance indices could lead to different decision-making consequences. ...
Study region
The Aure Valley in the French Pyrenees.
Study focus
This study applies a bottom-up framework for assessing water management vulnerability in terms of hydropower production, environmental regulations, and reservoir storage management by integrating the sensitivity, the management metrics with the participation of stakeholders, and the exposure of the water system. The hydrological model GR6J-CEMANEIGE is implemented to simulate the management metrics in the study region. The sensitivity of management metrics to climate change is investigated by comparing simulation results under current climate conditions and under perturbed climate series. Results are demonstrated with response surfaces, which are overlaid with the predefined thresholds of management metrics. The thresholds help identifying climate conditions that are critical for water management. Plausible climate change pathways are displayed on the response surfaces to assess the probability of critical conditions.
New hydrological insights for the region
Results show that annual hydropower production is mostly vulnerable to future drier conditions. Environmental metrics are sensitive to both precipitation and temperature changes while the current policy render the low-flow management less susceptible to risks. Reservoir storage management is found to be extremely sensitive to temperature increase that induces an earlier snowmelt. Although downstream water use is less vulnerable to climate change even under a high greenhouse gases emissions scenario, more intense water competition among stakeholders could be foreseen. Corresponding adaptation actions are proposed to reduce the vulnerability.
... Some, instead, have thus adopted a less time-consuming sensitivity-based approach, using existing climate change projections to calculate uniform seasonal or annual climatic changes over a region. This approach allows investigating a wider spectrum of simple climate change scenarios against which updated climate projections can be compared (Aygün et al., 2021;Aygün et al., 2020b;López-Moreno et al., 2013;Prudhomme et al., 2010;Rasouli et al., 2015;Rasouli et al., 2022;Wetterhall et al., 2011;Whateley et al., 2014). ...
Hydrological conditions in cold regions have been shown to be sensitive to climate change. However, a detailed understanding of how regional climate and basin landscape conditions independently influence the current hydrology and its climate sensitivity is currently lacking. This study, therefore, compares the climate sensitivity of the hydrology of two basins with contrasted landscape and meteorological characteristics typical of eastern Canada: a forested boreal climate basin (Montmorency) versus an agricultural hemiboreal basin (Acadie). The physically based Cold Regions Hydrological Modelling (CRHM) platform was used to simulate the current and future hydrological processes. Both basin landscape and regional climate drove differences in hydrological sensitivities to climate change. Projected peak SWE were highly sensitive to warming, particularly for milder baseline climate conditions and moderately influenced by differences in landscape conditions. Landscape conditions mediated a wide range of differing hydrological processes and streamflow responses to climate change. The effective precipitation was more sensitive to warming in the forested basin than in the agricultural one, due to reductions in forest canopy interception losses with warming. Under current conditions, precipitation and discharge were found to be more synchronized in the greater relief and slopes of the forested basin, whereas under climate change, they are more synchronized in the agricultural basin due to reduced infiltration and storage capacities. Flow through and over agricultural soils translated the increase in water availability under a warmer and wetter climate into higher peak discharges, whereas the porous forest soils dampened the response of peak discharge to increased available water. These findings help diagnose the mechanisms controlling hydrological response to climate change in cold regions forested and agricultural basins.
