Water under a Changing and Uncertain Climate: Lessons from Climate Model Ensembles*

Abstract

Climate change and rapidly rising global water demand are expected to place unprecedented pressures on already strained water resource systems. Successfully planning for these future changes requires a sound scientific understanding of the timing, location, and magnitude of climate change impacts on water needs and availability-not only average trends but also interannual variability and quantified uncertainties. In recent years, two types of large-ensemble runs of climate projections have become available: those from groups of more than 20 different climate models and those from repeated runs of several individual models. These provide the basis for novel probabilistic evaluation of both projected climate change and the resulting effects on water resources. Using a broad range of available ensembles, this research explores the spatial and temporal patterns of high confidence as well as uncertainty in projected river runoff, irrigation water requirements, basin storage yield, and cost estimates of adapting regional water systems to maintain historical supply. Projections of river runoff show robust between-ensemble agreement in regional drying (e.g., southern Africa and southern Europe) and wetting trends (e.g., northeastern United States). By integrating runoff over space and time, the economic effects of adapting supply systems to 2050 water availability show still broader trend agreement across ensembles. That agreement, obtained across such a wide range of multiple-member climate model ensembles in some locations, suggests a high degree of confidence in direction of change in water availability and provides clearer signals for longer-term investment decisions in water infrastructure.

Climate model uncertainty in impact assessments for agriculture: A multi‐ensemble case study on maize in sub‐Saharan Africa

“…The two CMIP5 ensembles included 23 projections for the Representative Concentration Pathway (RCP) 4.5 scenario (a mid‐range emissions scenario) and 20 projections for RCP8.5 (high emissions scenario). The names of the specific CMIP3 and CMIP5 models used in this study are presented in Tables S1 and S2, Supporting Information [also presented in Boehlert et al ., ]. GCM projections were regridded from their native resolution to the common 2° × 2° resolution as described by Boehlert [].…”

“…Our work extends the multi‐ensemble approach of Boehlert et al . [] to the problem of climate change impacts on maize production in sub‐Saharan Africa (SSA).…”

“…Such comparisons have practical relevance in the development of appropriate adaptation and mitigation strategies: they separate the sources of uncertainty that are theoretically reducible (model and scenario uncertainty) from those that largely are not (internal variability) [Hawkins and Sutton, 2009]. Boehlert et al [2015] used multiple within-and between-model GCM ensembles to assess the impact of climate model uncertainties on projected changes in runoff, crop water requirements, and adaptation costs out to 2090. Our work extends the multi-ensemble approach of Boehlert et al [2015] to the problem of climate change impacts on maize production in sub-Saharan Africa (SSA).…”

Climate Change Impacts on US Water Quality Using Two Models: HAWQS and US Basins

“…Also, as in all climate change impact studies, we are limited by the spatial scale and uncertainty of the GCMs. Climate-related uncertainties were also not fully addressed here, in part by using a subset of the CMIP-5 models, but also by not including uncertainties related to initial conditions (addressing the chaos in the system), as in [37]. In addition, over the last several decades, large improvements have been made in agricultural and urban water conservation, agricultural soil conservation, farming technologies, urban stormwater and wastewater treatment, and protection of critical natural areas.…”

“…For each of the basins, the priorities of the various water users are assumed to be in the following order: (1) minimum flows driven by environmental and trans-boundary concerns; (2) M&I water demands (including mining and thermal cooling); (3) irrigation demands; and (4) hydropower production. More detail on the calibration and verification of US Basins can be found in [37].…”