Quantifying sources of climate uncertainty to inform risk analysis for climate change decision-making

Quantitative estimates of future climate change and its various impacts are often based on complex climate models which incorporate a number of physical processes. As these models continue to become more sophisticated, it is commonly assumed that the latest generation of climate models will provide us with better estimates of climate change. Here, we quantify the uncertainty in future climate change projections using two multi-model ensembles of climate model simulations and divide it into different components: internal, scenario and model. The contributions of these sources of uncertainty changes as a function of variable, temporal and spatial scale and especially lead time in the future. In the new models, uncertainty intervals for each of the components have increased. For temperature, importance of scenario uncertainty is the largest over low latitudes and increases nonlinearly after the mid-century. It has a small importance for precipitation simulations on all time scales, which hampers estimating the effect which any mitigation efforts might have. In line with current state-of-the-art adaptation approaches, we argue that despite these uncertainties climate models can provide useful information to support adaptation decision-making. Moreover, adaptation decisions should not be postponed in the hope that future improved scientific understanding will result in more accurate predictions of future climate change. Such simulations might not become available. On the contrary, while planning adaptation initiatives, a rational framework for decision-making under uncertainty should be employed. We suggest that there is an urgent need for continued development and use of improved risk analysis methods for climate change adaptation.     

Use of observed hydroclimatic trends to constrain projections of snowmelt season runoff in the Rio Grande headwaters

A method is developed for choosing 21st Century streamflow projections among widely varying results from a large ensemble of climate model-driven simulations. We quantify observed trends in climate–streamflow relationships in the Rio Grande headwaters, which has experienced warming temperature and declining snowpack since the mid-20th Century. Prominent trends in the snowmelt runoff season are used to assess corresponding statistics in downscaled global climate model projections. We define “Observationally Consistent (OC)” simulations as those that reproduce historical changes to linear statistics of diminished snowpack–streamflow coupling in the headwaters and an associated increase in the contribution of spring season (post-peak snowpack) precipitation to streamflow. Only a modest fraction of the ensemble of simulations meets these consistency metrics. The subset of OC simulations projects significant decreases in headwaters flow, whereas the simulations that poorly replicate historical trends exhibit a much wider range of projected changes. These results bolster confidence in model-based projections of declining runoff in the Rio Grande headwaters in the snowmelt runoff season and offer an example of a methodology for evaluating model-based projections in basins with similar hydroclimates that have experienced pronounced climate changes in the recent historical record.     

SOCIOECONOMIC IMPACTS OF CLIMATE CHANGE ON U.S. WATER SUPPLIES1

ABSTRACT: A greenhouse warming would have major effects on water supplies and demands. A framework for examining the socioeconomic impacts associated with changes in the long-term availability of water is developed and applied to the hydrologic implications of the Canadian and British Hadley2 general circulation models (GCMs) for the 18 water resource regions in the conterminous United States. The climate projections of these two GCMs have very different implications for future water supplies and costs. The Canadian model suggests most of the nation would be much drier in the year 2030. Under the least-cost management scenario the drier climate could add nearly $105 billion to the estimated costs of balancing supplies and demands relative to the costs without climate change. Measures to protect instream flows and irrigation could result in significantly higher costs. In contrast, projections based on the Hadley model suggest water supplies would increase throughout much of the nation, reducing the costs of balancing water supplies with demands relative to the no-climate-change case.     

Climate Change and Floodplain Delineation in Two Southern Quebec River Basins1

Laforce, Serge, Marie‐Claude Simard, Robert Leconte, and François Brissette, 2011. Climate Change and Floodplain Delineation in Two Southern Quebec River Basins. Journal of the American Water Resources Association (JAWRA) 47(4):785‐799. DOI: 10.1111/j.1752‐1688.2011.00560.x Abstract: A methodology is presented for mapping the flooded extent of rivers under projected climate change. The methodology follows a top‐down modeling approach, where future climate projections generated by global climate models (GCMs) are downscaled to the watershed scale and used as input to hydrological and hydrodynamic models for predicting future river flows and associated open water levels. A range of possible future climate responses are taken into account, allowing quantification of flood‐mapping uncertainties resulting from GCM structure and greenhouse gas emission scenarios (GHGES). Probabilistic projections of future flood zones are developed by assuming that all GCMs and GHGES be equally weighted. The proposed methodology was applied to two river basins located in southern Quebec, Canada, for the time horizons 2020 and 2080. Twenty‐ and hundred‐year floods were computed and corresponding flood maps have been produced. Results indicate that there is a general trend toward an increased spring peak discharge for the Châteauguay River Basin and a decrease for the du Nord River Basin at the 2020 horizon. A less obvious trend was observed for the 2080 horizon, some GCM‐GHGES producing an increase in spring peak flows, whereas others would result in a less severe spring flood. These uncertainties in flood flows have cascaded into uncertainties in the corresponding flooded extent and represented as probabilistic flood maps.     

POTENTIAL EFFECTS OF CLIMATE CHANGE ON GROUND WATER IN LANSING,MICHIGAN1

ABSTRACT: Computer simulations involving general circulation models, a hydrologic modeling system, and a ground water flow model indicate potential impacts of selected climate change projections on ground water levels in the Lansing, Michigan, area. General circulation models developed by the Canadian Climate Centre and the Hadley Centre generated meteorology estimates for 1961 through 1990 (as a reference condition) and for the 20 years centered on 2030 (as a changed climate condition). Using these meteorology estimates, the Great Lakes Environmental Research Laboratory's hydrologic modeling system produced corresponding period streamflow simulations. Ground water recharge was estimated from the streamflow simulations and from variables derived from the general circulation models. The U.S. Geological Survey developed a numerical ground water flow model of the Saginaw and glacial aquifers in the Tri‐County region surrounding Lansing, Michigan. Model simulations, using the ground water recharge estimates, indicate changes in ground water levels. Within the Lansing area, simulated ground water levels in the Saginaw aquifer declined under the Canadian predictions and increased under the Hadley.     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

Impacts of Changes in Precipitation Amount and Distribution on Water Resources Studied Using a Model Rainwater Harvesting System

Water supply reliability is expected to be affected by both precipitation amount and distribution changes under recent and future climate change. We compare historical (1951‐2010) changes in annual‐mean and annual‐maximum daily precipitation in the global set of station observations from Global Historical Climatology Network and climate models from the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP), and develop the study to 2011‐2099 for model projections under high radiative forcing scenario (RCP8.5). We develop a simple rainwater harvesting system (RWHS) model and drive it with observational and modeled precipitation. We study the changes in mean and maximum precipitation along with changes in the reliability of the model RWHS as tools to assess the impact of changes in precipitation amount and distribution on reliability of precipitation‐fed water supplies. Results show faster increase in observed maximum precipitation (10.14% per K global warming) than mean precipitation (7.64% per K), and increased reliability of the model RWHS driven by observed precipitation by an average of 0.2% per decade. The ISI‐MIP models show even faster increase in maximum precipitation compared to mean precipitation. However, they imply decreases in mean reliability, for an average 0.15% per decade. Compared to observations, climate models underestimate the increasing trends in mean and maximum precipitation and show the opposite direction of change in reliability of a model water supply system.     

Incorporating Climate Change Into Water Resources Planning in England and Wales1

Arnell, Nigel W., 2011. Incorporating Climate Change Into Water Resources Planning in England and Wales. Journal of the American Water Resources Association (JAWRA) 47(3):541‐549. DOI: 10.1111/j.1752‐1688.2011.00548.x Abstract: Public water supplies in England and Wales are provided by around 25 private‐sector companies, regulated by an economic regulator (Ofwat) and environmental regulator (Environment Agency). As part of the regulatory process, companies are required periodically to review their investment needs to maintain safe and secure supplies, and this involves an assessment of the future balance between water supply and demand. The water industry and regulators have developed an agreed set of procedures for this assessment. Climate change has been incorporated into these procedures since the late 1990s, although has been included increasingly seriously over time and it has been an effective legal requirement to consider climate change since the 2003 Water Act. In the most recent assessment in 2009, companies were required explicitly to plan for a defined amount of climate change, taking into account climate change uncertainty. A “medium” climate change scenario was defined, together with “wet” and “dry” extremes, based on scenarios developed from a number of climate models. The water industry and its regulators are now gearing up to exploit the new UKCP09 probabilistic climate change projections – but these pose significant practical and conceptual challenges. This paper outlines how the procedures for incorporating climate change information into water resources planning have evolved, and explores the issues currently facing the industry in adapting to climate change.     

Will Evolving Climate Conditions Increase the Risk of Floods of the Large U.S.‐Canada Transboundary Richelieu River Basin?

In spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past.     

Governing green stormwater infrastructure: the Philadelphia experience

Many cities throughout the world are adopting green infrastructure techniques to reduce stormwater and sewer overflows into waterways, which is particularly problematic for places experiencing more frequent and severe rain events. Governance of green stormwater implementation is proving to be as important as the techniques themselves. Building on the climate and sustainability governance literature, we argue that effective governance requires planning across city departments, experimentation and a strategy for organisational learning. We employ a case study of Philadelphia, the first city in the United States to attempt an entirely green approach to meeting federal regulations to examine issues of governance that emerged and how they were addressed. The case study draws on interviews with fourteen public and private sector actors involved in implementation, a site visit to observe the installations and to discuss the approach with a key planner, and grey literature. We find that silos can be broken down and that if open communications and a willingness to change practices are present, obstacles cited in the literature can be overcome. The key implication is that the three elements of governance need to be built into the green infrastructure planning process. While the analysis focuses on a US city, the departments involved and the governance needs of green stormwater infrastructure are similar in cities in much of the world.     

Climate change adaptation and livestock activity choices in Kenya: An economic analysis

This paper examines the impact of climate change on the decision of farmers to engage or not to engage in livestock activities and also on the choice of different livestock species in Kenya. To this end, cross‐sectional household level data supplemented by long‐term averages of climate data are used. The probit model is employed to derive the response of the probability of engaging in livestock activities to climate change. Probit and multivariate probit methods are employed to model the choice of different livestock species. Atmosphere–ocean global circulation models are used to project the impact of different climate scenarios on the probability of engaging in livestock activities and also of adopting different livestock species according to variations in climate. The results suggest that farmers adapt livestock management decisions to climate change. At low levels of temperature increase, the probability of engaging in livestock activities falls, but at higher levels of climate change, the probability rises. The results further show that as it gets hotter, farmers change their livestock choices from dairy cattle and sheep to beef cattle and goats.     

Climate Change Impacts and Uncertainties on Spring Flooding of Lake Champlain and the Richelieu River

The source of the Richelieu River is Lake Champlain, located between the states of New York, Vermont, and Québec. In 2011, the lake and the Richelieu River reached historical flood levels, raising questions about the influence of climate change on the watershed. The objectives of this work are to model the hydrology of the watershed, construct a reservoir model for the lake and to analyze flooding trends using climate simulations. The basin was modeled using the HSAMI lumped conceptual model from Hydro‐Québec with a semi‐distributed approach in order to estimate the inflows into Lake Champlain. The discharge at the Richelieu River was computed by using a mass balance equation between the inputs and outputs of Lake Champlain. Future trends were estimated over the 2041‐2070 and 2071‐2100 periods using a large number of outputs from general circulation models and regional climate models downscaled with constant scaling and daily translation methods. While there is a certain amount of uncertainty as to future trends, there is a decreasing tendency in the magnitude of the mean spring flood. A flood frequency analysis showed most climate projections indicate the severity of most extreme spring floods may be reduced over the two future periods although results are subject to a much larger uncertainty than for the mean spring flood. On the other hand, results indicate summer‐fall extreme events such as caused by hurricane Irene in August 2011 may become more frequent in the future.     

Projected Changes in Discharge in an Agricultural Watershed in Iowa

Our improved capability to adapt to the future changes in discharge is linked to our capability to predict the magnitude or at least the direction of these changes. For the agricultural United States Midwest, too much or too little water has severe socioeconomic impacts. Here, we focus on the Raccoon River at Van Meter, Iowa, and use a statistical approach to examine projected changes in discharge. We build on statistical models using rainfall and harvested corn and soybean acreage to explain the observed discharge variability. We then use projections of these two predictors to examine the projected discharge response. Results are based on seven global climate models part of the Coupled Model Intercomparison Project Phase 5 and two representative concentration pathways (RCPs 4.5 and 8.5). There is not a strong signal of change in the discharge projections under the RCP 4.5. However, the results for the RCP 8.5 point to a stronger changing signal related to larger projected increases in rainfall, resulting in increased trends, in particular, in the upper part of the discharge distribution (i.e., 60th percentile and above). Examination of two hypothetical agricultural scenarios indicates that these increasing trends could be alleviated by decreasing the extent of the agricultural production. We also discuss how the methodology presented in this study represents a viable approach to move forward with the concept of return period for engineering design and management in a nonstationary world.     

Climate Change Impacts on Local Flood Risks in the U.S. Northeast: A Case Study on the Connecticut and Merrimack River Basins

This study investigates the potential impacts of climate change on future flows in the main stem of the Connecticut and Merrimack rivers within Massachusetts. The study applies two common climate projections based on (Representative Concentration Pathways), RCP 4.5 and RCP 8.5 and downscaled gridded climate projections from 14 global climate models (GCMs) to estimate the 100‐year, 24‐h extreme precipitation events for two future time‐periods: near‐term (2021–2060) and far‐term (2060–2099). 100‐year 24‐h precipitation events at near‐ and far‐term are compared to GCM‐driven historical extreme precipitation events during a base period (1960–1999) and results for RCP 8.5 scenario show average increases between 25%–50% during the near‐term compared to the base period and increases of over 50% during the far‐term. Streamflow conditions are generated with a distributed hydrological model where downscaled climate projections are used as inputs. For the near‐term, the medians of the GCMs using the RCP 4.5 and RCP 8.5 suggest 2.9%–8.1% increases in the 100‐year, 24‐h flow event in the Connecticut and an increase of 9.9%–13.7% in the Merrimack River. For the far‐term, the medians of the GCMs using the RCP 4.5 and RCP 8.5 suggest a 9.0%–14.1% increase in the Connecticut and 15.8%–20.6% for the Merrimack River. Ultimately, the results presented here can be used as a guidance for the long‐term management of infrastructures on the Connecticut and Merrimack River floodplains.     

A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1

Abstract: Water resources planning and management efficacy is subject to capturing inherent uncertainties stemming from climatic and hydrological inputs and models. Streamflow forecasts, critical in reservoir operation and water allocation decision making, fundamentally contain uncertainties arising from assumed initial conditions, model structure, and modeled processes. Accounting for these propagating uncertainties remains a formidable challenge. Recent enhancements in climate forecasting skill and hydrological modeling serve as an impetus for further pursuing models and model combinations capable of delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The framework presented here proposes integration and offline coupling of global climate models (GCMs), multiple regional climate models, and numerous water balance models to improve streamflow forecasting through generation of ensemble forecasts. For demonstration purposes, the framework is imposed on the Jaguaribe basin in northeastern Brazil for a hindcast of 1974‐1996 monthly streamflow. The ECHAM 4.5 and the NCEP/MRF9 GCMs and regional models, including dynamical and statistical models, are integrated with the ABCD and Soil Moisture Accounting Procedure water balance models. Precipitation hindcasts from the GCMs are downscaled via the regional models and fed into the water balance models, producing streamflow hindcasts. Multi‐model ensemble combination techniques include pooling, linear regression weighting, and a kernel density estimator to evaluate streamflow hindcasts; the latter technique exhibits superior skill compared with any single coupled model ensemble hindcast.     

Place influences in framing and understanding climate change adaptation challenges

The climate change literature emphasises the importance of geographical understanding for guiding adaptation, in which “place” perspectives are particularly significant. After “scale”, the term “place” within the climate change adaptation literature is most often implicitly used in reference to a delineated and localised region, such as place-based risk assessment or place-based adaptation planning. Here, we use a case study of the Australian island-state of Tasmania to demonstrate the importance and particularity of place in the formation of climate change adaptation issues, problem definition and framing, and the dynamics of knowledge and praxis development across a range of research and industry sectors. We describe the significance of the place Tasmania with regard to its geographical location; its portrayal as an island place; and its cultural meaning and relations. Through a synthesis of climate change adaptation research, policy literature and engagement with researchers and stakeholders, we identify three emergent thematic place characterisations of Tasmania. We find that these characterisations have contributed directly or indirectly to the: initiation and extent of research and practical activities; the framing of adaptation issues and perspectives on potential adaptation responses in different sectors including the marine biodiversity and resources sector, small business and human health sectors. Exposing these influences is essential for focusing future adaptation activities, including research, planning, investment and practice, in Tasmania and other locations where place is a central issue.     

Climate change adaptation in the urban planning and design research: missing links and research agenda

This paper investigates the extent and the nature of how the urban planning literature has addressed climate change adaptation. It presents a longitudinal study of 157 peer-reviewed articles published from 2000 to 2013 in the leading urban planning and design journals whose selection considered earlier empirical studies that ranked them these journals. The findings reveal that the years 2006–07 represent a turning point, after which climate change studies appear more prominently and consistently in the urban planning and design literature; however, the majority of these studies address climate change mitigation rather than adaptation. Most adaptation studies deal with governance, social learning, and vulnerability assessments, while paying little attention to physical planning and urban design interventions. This paper identifies four gaps that pertain to the lack of interdisciplinary linkages, the absence of knowledge transfer, the presence of scale conflict, and the dearth of participatory research methods. It then advocates for the advancement of participatory and collaborative action research to meet the multifaceted challenges of climate change.     

Robust Prioritization of Climate Change Adaptation Strategies Using the VIKOR Method with Objective Weights

This study proposes a robust prioritization framework for climate change adaptation strategies under uncertain climate change scenarios, using the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, a multi‐criteria decision‐making approach, together with the Shannon entropy‐based weights. The VIKOR method allows us to find a compromise solution between two decision strategies of maximizing group utility and minimizing individual regret, and the Shannon entropy is used to determine objective weights among multiple climate change scenarios. The proposed methodology was applied to the problem of selecting locations of subwatersheds for reusing treated wastewater (TWW) in a Korean urban watershed. Selected based on the sustainability concept, hydro‐environmental and socioeconomic indicators were used to evaluate the sustainability of TWW reuse under multiple climate change scenarios, using the hydrologic simulation model results and statistical data. Finally, sustainability scores under multiple scenarios were aggregated using the VIKOR together with the Shannon entropy‐based weights for the robust prioritization of adaptation strategies. According to the different levels of regret aversion or affinity, our results for water quality showed different sets of adaptation strategies as the best options, suggesting that our framework would help stakeholders seeking the robust options considering both the utility and regret.     

Exploring the autonomous adaptation strategies to climate change and climate variability in selected villages in the rural northern savannah zone of Ghana

Evidence abounds attesting to changes in the global climate. In Ghana, climate change and climate variability have brought several exposure-sensitivities on different people and at different times. Due to the multiplicity of climate change and climate variability effects, adaptation strategies invariably could be influenced by several factors. This paper assesses the adoption of adaptation strategies in the rural northern savannah zone of Ghana as a result of climate change and variability. Using two villages each from Savelugu Nanton, West Mamprusi and Kassena Nankana East Districts, which are slightly different as case studies, the paper unearthed panoply of varied adaptation strategies in each of them including intensification of irrigation; integration of livestock production; changes in tillage practices; fertiliser application on farms; shift from agriculture to non-farm jobs; seasonal migration and purchase of drought insurance for maize. The results indicate that the relativity in adoption and utilisation of the different adaptive strategies are interlinked with geographical, social, economic, institutional and political factors and processes in the villages. The findings drum home the essentiality of location-specific planned adaptation strategies for climate change through a bottom-up approach, in order to ensure their effectiveness and sustainability.     

Contrasting Lumped and Distributed Hydrology Models for Estimating Climate Change Impacts on California Watersheds1

Maurer, Edwin P., Levi D. Brekke, and Tom Pruitt, 2010. Contrasting Lumped and Distributed Hydrology Models for Estimating Climate Change Impacts on California Watersheds. Journal of the American Water Resources Association (JAWRA) 46(5):1024–1035. DOI: 10.1111/j.1752-1688.2010.00473.x Abstract: We compare the projected changes to streamflows for three Sierra Nevada rivers using statistically downscaled output from 22 global climate projections. The downscaled meteorological data are used to drive two hydrology models: the Sacramento Soil Moisture Accounting model and the variable infiltration capacity model. These two models differ in their spatial resolution, computational time step, and degree and objective of calibration, thus producing significantly different simulations of current and future streamflow. However, the projected percentage changes in monthly streamflows through mid-21st Century generally did not differ, with the exceptions of streamflow during low flow months, and extreme low flows. These findings suggest that for physically based hydrology models applied to snow-dominated basins in Mediterranean climate regimes like the Sierra Nevada, California, model formulation, resolution, and calibration are secondary factors for estimating projected changes in extreme flows (seasonal or daily). For low flows, hydrology model selection and calibration can be significant factors in assessing impacts of projected climate change.