ClimateChange Assessment Guide.pdf - University of Waterloo

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E-38Guide for Assessment of Hydrological Effects of Climate Change in Ontariothan all other climates except the current climate, demonstrating the wide variance in temperatures comparedwith the change field climates. When the SDSM temperatures are compared directly with the change fieldclimates created using the same GCMs that were used to generate the predictors, it is apparent that theSDSM climates display more extreme results.• Annual precipitation is higher for all future climates, compared with the current climate, in all scenarios except# 30. The range of annual change is from -6.3% to +13.6%. The SDSM climates have marginally more wetdays, exceeding the current climate annual average by 1 and 3 days on 176 days. The average droughtlength is expected to decrease from 13 days to 9 and 10 days with the future SDSM climates.• Only three future climates display higher total annual solar radiation compared with the current climate. In allcases the differences are small ranging, in relative terms, from -3% to +2%.• Average annual wind speeds are lower in three scenarios compared with the current climate. In generalfuture climates have higher winds in the winter months and lower winds in the summer months. Overalldifferences in average annual wind speeds are small ranging from -0.2% to +0.8% compared with the currentclimate.• Potential evapotranspiration (PET) is a direct function of air temperature and solar radiation in the methodused (Jensen and Haise, 1963). While all future climates are expected to yield higher temperatures, mosthave lower solar radiation. Therefore in several cases the dependant variables (i.e., temperature and solarradiation) will have opposite effects on PET. In all cases the net change is to higher PET, thus, thetemperature influence is dominant. Annual scenario PET differences range from +8% to +20%, comparedwith the current climate. Relative differences are much higher in the winter months ranging up to increases of+265% compared with maximum increases in summer months of +24%. Absolute differences are largest inthe summer months.
Appendix E E-39Subwatershed 19 Case Study To determine impacts to streamflow and water budget parameters, the Subwatershed 19 HSP-F streamflowgeneration model was run using each of the developed future climates discussed in the previous section. The climatechange scenarios included: nine GCM scenarios selected using the Percentile Method; two SDSM scenarios and theircorresponding GCM scenarios; as well as the baseline (i.e., current condition) scenario. Simulated streamflow andwater budget parameters (i.e., precipitation, runoff, recharge, and ET) from each climate change scenario were outputfrom HSP-F at the daily time step.To determine climate change impacts to the groundwater flow system, the Subwatershed 19 MODFLOW groundwatermodel was run using a monthly stress period. For each month, the simulated mean monthly recharge rates from theHSP-F model for each climate change scenario were input in the MODFLOW groundwater model. The MODFLOWmodel was run with seven time steps per month, with simulated groundwater discharge output for each month. Allsimulated data were compiled in a relational database for analysis.Streamflow regimes are a function of climate, geology, vegetation, topography, land use and hydraulic infrastructure(e.g. dams). In this assessment, only the climate was varied; all other factors were not modified from the currentconditions. This was done to isolate impacts due to climate change.For the purposes of this case study, the climate change impact assessment was completed at the subwatershedscale; however, investigation of impacts at smaller spatial scales (e.g., hydrologic response units) is also possible.The impacts of climate change on the hydrology of Subwatershed 19 was assessed by comparing streamflow andgroundwater discharge under current (1961-1990) and future (2041-2070) climate conditions. This comparisonrequired the summary of current and future flow regimes into a variety of metrics (e.g., average monthly streamflow,average monthly recharge), which are presented in the following sections.Simulation results for the Percentile Method climates are examined separately from the SDSM climates because thePercentile Method climates have been selected and grouped for their statistical significance. Results from this groupshould be evaluated in terms of the distribution of outcomes. This distribution cannot be influenced by the SDSMclimates. The SDSM climates are examined specifically for the degree of climate variability they reflect and its effecton hydrology, rather than their influence on mean conditions. SDSM climates are generally compared with the GCMbased change field climates that correspond to the GCM scenario run used to generate the required predictors. To determine changes in streamflow, it is necessary to summarize long-term hydrographs into statistical metrics. Thisis required due to the difficulty associated with detecting changes in long-term (30-year) hydrographs by directcomparison alone. Examples of such statistical metrics are: mean annual and monthly flow, median monthly flow,maximum daily streamflow, and low flows statistics, such as the 7Q 20 streamflow (the 7 day low flow over a 20 yearperiod). These are discussed in Section 6.6.2 and Table 6.8 of the Guide.Annual streamflow reflects the total volume of streamflow generated within a particular year for a subwatershed, andis generally representative of precipitation, net of evapotranspiration. Changes in mean annual streamflow arereflective of larger scale impacts due to climate change, namely changes in precipitation or temperature. Simulatedannual streamflow, predicted by the HSP-F model for the baseline climate (1961-1990) and for the nine GCM-basedfuture climate scenarios (2041-2070) are included in Figure 6-1. Mean annual streamflow for the entire study period,both with current climate and the full range of future climates, is also shown on the figure. Over the 30 year period,the nine future climate scenarios predict a change in mean annual streamflow ranging from +16% to –11%. On anindividual basis, there are more future scenarios that predict an increase in mean annual streamflow than a decrease.
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