Abstract
Fundamental differences in the nature of climate and hydrologic models make coupling of future climate projections to models of watershed hydrology challenging. This study uses the NCAR Weather Research and Forecast model (WRF) to dynamically downscale climate simulations over the Saginaw Bay Watershed, MI and prepare the results for input into semi-distributed hydrologic models. One realization of the bias-corrected NCAR CESM1 model's RCP 8.5 climate scenario is dynamically downscaled at a spatial resolution of 3 km by 3 km for the end of the twenty-first century and validated based on a downscaled run for the end of the twentieth century in comparison to ASOS and NWS COOP stations. Bias-correction is conducted using Quantile Mapping to correct daily maximum and minimum temperature, precipitation, and relative humidity for use in future hydrologic model experiments. In the Saginaw Bay Watershed the end of the twenty-first century is projected to see maximum and minimum average daily temperatures warming by 5.7 and 6.3°C respectively. Precipitation characteristics over the watershed show an increase in mean annual precipitation (average of +14.3 mm over the watershed), mainly due to increases in precipitation intensity (average of +0.3 mm per precipitation day) despite a decrease in frequency of −10.7 days per year. The projected changes have substantial implications for watershed processes including flood prediction, erosion, mobilization of non-point source and legacy contaminants, and evapotranspirative demand, among others. We present these results in the context of usefulness of the downscaled and bias corrected data for semi-distributed hydrologic modeling.
Highlights
Climate change has the potential to substantially alter the abundance, availability, distribution, fluxes, and quality of water in the Great Lakes region (Hayhoe et al, 2010; D’Orgeville et al, 2014; Byun and Hamlet, 2018; Wang et al, 2018; Byun et al, 2019; Mahdiyan et al, 2021)
Weather Research and Forecast model (WRF) grid cells near the bay experience precipitation more frequently (∼210 days/year compared to ∼176 days/year; Figure 6A), but at a lower intensity (3.69 mm/rain day compared to 5.14 mm/rain day; Figure 7A), resulting in lower total amounts of precipitation than inland (∼739 mm compared to 995.4 mm; Figure 5A)
Temperatures will increase substantially, with the largest changes occurring at the extremes (10th percentile maximum and 90th percentile minimum), meaning that it is likely that the Saginaw Bay Watershed (SBW) will see simultaneously more frost-free days in the winters and more exceptionally hot days in the summer months
Summary
Climate change has the potential to substantially alter the abundance, availability, distribution, fluxes, and quality of water in the Great Lakes region (Hayhoe et al, 2010; D’Orgeville et al, 2014; Byun and Hamlet, 2018; Wang et al, 2018; Byun et al, 2019; Mahdiyan et al, 2021). This study presents a unique approach to addressing some of the challenges posed by the existing methodologies for preparation of future climate projections for coupling with hydrologic SDHMs. One realization of a GCM’s projections of future climate are dynamically downscaled with a highfidelity weather model, to retain the physical processes occurring within the atmosphere at subsequently smaller spatial and temporal resolutions. They found that the deviation among the models in the end-of-twenty-first century RCP 8.5 scenario runs resulted in an average temperature and precipitation uncertainty of 1.29◦C and 0.20 mm day−1 For both WRF model runs the daily variables retained for future input into SDHMs are: maximum temperature (◦C); minimum temperature (◦C); total liquid precipitation (mm); average relative humidity (%); and average daily wind speed (m/s) computed for each grid cell in the SBW domain. This is useful for distributions that require different corrections for the tails of the distributions compared to the means of the distributions, as the tails represent flood and drought conditions that can have important devastating impacts on hydrologic systems
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