scholarly journals The implications of climate change scenario selection for future streamflow projection in the Upper Colorado River Basin

2012 ◽  
Vol 16 (11) ◽  
pp. 3989-4007 ◽  
Author(s):  
B. L. Harding ◽  
A. W. Wood ◽  
J. R. Prairie

Abstract. The impact of projected 21st century climate conditions on streamflow in the Upper Colorado River Basin was estimated using a multi-model ensemble approach wherein the downscaled outputs of 112 future climate projections from 16 global climate models (GCMs) were used to drive a macroscale hydrology model. By the middle of the century, the impacts on streamflow range, over the entire ensemble, from a decrease of approximately 30% to an increase of approximately the same magnitude. Although prior studies and associated media coverage have focused heavily on the likelihood of a drier future for the Colorado River Basin, approximately 25 to 35% of the ensemble of runs, by 2099 and 2039, respectively, result in no change or increases in streamflow. The broad range of projected impacts is primarily the result of uncertainty in projections of future precipitation, and a relatively small part of the variability of precipitation across the projections can be attributed to the effect of emissions pathways. The simulated evolution of future temperature is strongly influenced by emissions, but temperature has a smaller influence than precipitation on flow. Period change statistics (i.e., the change in flow from one 30-yr period to another) vary as much within a model ensemble as between models and emissions pathways. Even by the end of the current century, the variability across the projections is much greater than changes in the ensemble mean. The relatively large ensemble analysis described herein provides perspective on earlier studies that have used fewer scenarios, and suggests that impact analyses relying on one or a few climate scenarios are unacceptably influenced by the choice of projections.

2012 ◽  
Vol 9 (1) ◽  
pp. 847-894 ◽  
Author(s):  
B. L. Harding ◽  
A. W. Wood ◽  
J. R. Prairie

Abstract. The impact of projected 21st century climate conditions on streamflow in the Upper Colorado River Basin was estimated using a multi-model ensemble approach wherein the downscaled outputs of 112 future climate scenarios from 16 global climate models (GCMs) were used to drive a macroscale hydrology model. By the middle of the century, the impacts on streamflow range, over the entire ensemble, from a decrease of approximately 30% to an increase of approximately the same magnitude. Although prior studies and associated media coverage have focused heavily on the likelihood of a drier future for the Colorado River Basin, approximately one-third of the ensemble of runs result in little change or increases in streamflow. The broad range of projected impacts is primarily the result of uncertainty in projections of future precipitation, and a relatively small part of the variability of precipitation across the projections can be attributed to the effect of emissions scenarios. The simulated evolution of future temperature is strongly influenced by emissions, but temperature has a smaller influence than precipitation on flow. Period change statistics (i.e., the change in flow from one 30-yr period to another) vary as much within a model ensemble as between models and emissions scenarios. Even over the course of the current century, the variability across the projections is much greater than the trend in the ensemble mean. The relatively large ensemble analysis described herein provides perspective on earlier studies that have used fewer scenarios, and suggests that impact analyses relying on one or a few scenarios, as is still common in dynamical downscaling assessments, are unacceptably influenced by choice of projections.


2018 ◽  
Vol 10 (12) ◽  
pp. 2058 ◽  
Author(s):  
Mahyar Aboutalebi ◽  
Alfonso Torres-Rua ◽  
Niel Allen

Accurate spatial and temporal precipitation estimates are important for hydrological studies of irrigation depletion, net irrigation requirement, natural recharge, and hydrological water balances in defined areas. This analysis supports the verification of water savings (reduced depletion) from deficit irrigation of pastures in the Upper Colorado River Basin. The study area has diverse topography with scattered fields and few precipitation gauges that are not representative of the basin. Gridded precipitation products from TRMM-3B42, PRISM, Daymet, and gauge observations were evaluated on two case studies located in Colorado and Wyoming during the 2014–2016 irrigation seasons. First, the resolution at the farm level is discussed. Next, bias occurrence at different time scales (daily to monthly) is evaluated and addressed. Then, the coverage area of the gauge station, along with the impact of the dominant wind direction on the shape of the coverage area, is evaluated. Ultimately, available actual ET maps derived from the METRIC model are used to estimate spatial effective rainfall. The results show that the spatial resolutions of TRMM and PRISM are not adequate at the farm level, while Daymet is a better fit but lacks the adequate latency versus TRMM and PRISM. When compared against local weather station records, all three spatial datasets were found to have a bias that decreases at coarser temporal intervals. However, the performance of Daymet and PRISM at the monthly time step is acceptable, and they can be used for water resource management at the farm level. The adequacy of an existing gauge station for a given farm location depends on the willingness to accept the risk of the bias associated with a non-persistent, non-symmetric gauge coverage area that is highly correlated with the dominant wind direction. Among all goodness of fit statistics considered in the study, the interpretation of the summation of error makes more sense for quantifying the rainfall bias and risk for the user. Finally, based on the USDA-SCS model and actual spatial ET, overall, seasonal effective rainfall tends to be less than 60% of total rainfall for agricultural lands.


2021 ◽  
Vol 21 ◽  
pp. 100206
Author(s):  
Connie A. Woodhouse ◽  
Rebecca M. Smith ◽  
Stephanie A. McAfee ◽  
Gregory T. Pederson ◽  
Gregory J. McCabe ◽  
...  

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