Impact of Warming on Outflows from Selected Upper Watersheds in California
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1 Impact of Warming on Outflows from Selected Upper Watersheds in California Guobiao Huang (CA DWR), Tariq Kadir (CA DWR) and Francis Chung (CA DWR) California Water and Environmental Modeling Forum Pacific Grove (Asilomar), California February 28 March 2, 2011
2 Background Stationarity assumption in current planning models has been undermined by climate change (Milly and others 2008). In California specially true for snow-dominant watersheds of the Sierra-Nevada. Historical observed hydrology may contain effect of historical warming; simulated (stationary) hydrology may be more appropriate as input to planning models. Several previous studies have shown regional scale, qualitatively similar conclusions (e.g. Miller et al. 2003; Young et al. 2009). Detailed distributed models at the watershed scale are still needed to get better quantitative results.
3 Location Map of Selected Watersheds 1. Sacramento River -Lake Shasta 2. Feather River Lake Oroville 3. Yuba River above Smartville 4. American River Folsom Lake 5. Tuolumne River- Lake McClure 6. Merced River La Grande Dam
4 Elevations for the six watersheds (meters above sea level) Watershed Min Max mean Std. Deviation Shasta Feather Yuba American Tuolumne Merced Based on 30m DEM elevation data
5 Impact on unimpaired outflows from the six watersheds Upper Feather Basin: Both PRMS (precipitation-runoff modeling system) and SWAT (soil water assesment tool) models Detrending on temperature data T+1 o C to T+4 o C sensitivity and 12 GCMs projections Others watersheds: SWAT model only T+1 o C to T+4 o C sensitivity
6 Observed changes in Upper Feather River based on detrended simulations Variables Tmax Tmin Detrended Baseline Historical Relative Change ~+0.5 C ~+1.5 C April 1 SWE % Annual natural flow 602 mm 605 mm 0.4% Center of mass March 23 March 14-9 days Snow as % of total Precip April to July Runoff as % of total flow 42% 36% -6% 42% 38% -4%
7 April to July Runoff
8 Effect of climate warming Sensitivity to uniform warming (results on later slides with SWAT results) 12 GCM projections: consistent warming trend in annual mean air temperature ranging from +0.6 to +2.3 C for the time horizon while the relative changes in annual precipitation range from 10.7% to +9.3%.
9 Impact of GCM warming on April to July Runoff Dry season snowmelt runoff
10 Impact of GCM warming on April to July Runoff
11 Upper Feather River Basin Model performance (PRMS vs. SWAT) Lake Oroville Monthly Daily R 2 R 2 PRMS SWAT Note: Based on observed and simulated natural streamflow above Lake Oroville
12 Upper Feather River Water budget (PRMS vs. SWAT) Lake Oroville PRMS SWAT Period of Simulation Precipitation (mm) WY Snow (mm) % of snow in total Precip Streamflow (mm)
13 PRMS and SWAT (Model feature) Feature PRMS SWAT Period of simulation Snow model Energy balance, quasi-two-layer Temperature index Min spatial unit for water balance Hydrologic Response Unit (324) Time step Daily Daily Subwatershed (64)
14 SWAT models Observed warming trend in the watersheds Scatter plots (observed vs. modeled) with R 2, N-S Sensitivity to temperature change
15 Observed Warming trend
16 SWAT Model calibration performance (Monthly observed and simulated flow)
17 Sample of Sensitivity to warming with SWAT models Annual mean streamflow is not sensitive to warming Watershed T+1 o C T+2 o C T+3 o C T+4 o C Shasta 0.24% 0.10% 0.96% 2.07% Feather SWAT 0.10% 0.04% 0.29% 0.97% Feather PRMS* 1.3% 2.1% 1.7% 0.4% Yuba 0.7% 1.2% 1.5% 1.8% Merced 0.7% 1.4% 1.8% 2.2% Note: PRMS model is run with detrended baseline (WY ); all SWAT models:
18 Sample of Sensitivity to warming with SWAT models April-July Runoff sharply decreases with warming
19 Monthly streamflow
20 Summary and Further Work Impact of climate warming on unimpaired outflows from six Upper Watersheds in California were studied with distributed hydrologic models (PRMS and SWAT). Simulation results show that annual streamflow is insensitive to warming BUT timing of flow and seasonal runoff are very sensitive to warming. The SWAT models may be improved with further calibration with daily flow data. Detrending of SWAT forcing data may explain observed changes in hydrology of the watersheds. Use of simulated streamflow data as input to CalSim or CalLite water planning models for further water resources impact studies.
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