An official website of the United States government
Abstract Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra‐Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter‐model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning.
more »
« less
Using A Physics-informed State-space Model to Assess Future Projection Uncertainty of Regional Climate and Water Supply
A state-space model (SSM) integrating physical parameters is proposed and developed in this work, to describe the increase of global average temperature and the subsequent changes in regional climate and hydrology. This SSM approach aims at providing updated and improved forecasts, based on observations and using Bayesian inference, and at facilitating flexible engineering decision-making schemes. Global climate model simulations are used for informing the distribution of the parameters of the SSM. The case study of the Colorado River Basin serves as a preliminary application of the method, to forecast changes in the upper basin natural flow. The method projects that the post-2000 low flow volume will continue, or become even lower on average, although such projections are subject to large uncertainty. Given the increasing need of climate projections in the design, operation, and management of infrastructure, the SSM approach can serve as a useful tool, informed by historical records, to facilitate engineering applications.
more »
« less
- Award ID(s):
- 1919453
- PAR ID:
- 10456128
- Date Published:
- Journal Name:
- ICASP14 - 14th International Conference on Applications of Statistics and Probability in Civil Engineering
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Assessing the uncertainty associated with projections of climate change impacts on hydrological processes can be challenging due to multiple sources of uncertainties within and between climate and hydrological models. Here we compare the effects of parameter uncertainty in a hydrological model to inter-model spread from climate projections on hydrological projections of urban streamflow in response to climate change. Four hourly climate model outputs from the RCP8.5 scenario were used as inputs to a distributed hydrologic model (SWMM) calibrated using a Bayesian approach to summarize uncertainty intervals for both model parameters and streamflow predictions. Continuous simulation of 100 years of streamflow generated 90 % prediction intervals for selected exceedance probabilities and flood frequencies prediction intervals from single climate models were compared to the inter climate model spread resulting from a single calibration of the SWMM model. There will be an increase in future flows with exceedance probabilities of 0.5 %-50 % and 2-year floods for all climate projections and all 21st century periods, for the modeled Ohio (USA) watershed. Floods with return periods of ≥ 5 years increase relative to the historical from mid-century (2046–2070) for most climate projections and parameter sets. Across the four climate models, the 90th percentile increase in flows and floods ranges from 17-108 % and 11–63 % respectively. Using multiple calibration parameter sets and climate projections helped capture the most likely hydrologic outcomes, as well as upper and lower bounds of future predictions. For this watershed, hydrological model parameter uncertainty was large relative to inter climate model spread, for near term moderate to high flows and for many flood frequencies. The uncertainty quantification and comparison approach developed here may be helpful in decision-making and design of engineering infrastructure in urban watersheds.more » « less
-
Abstract. Global projections for ocean conditions in 2100 predict that the North Pacific will experience some of the largest changes. Coastal processes that drive variability in the region can alter these projected changes but are poorly resolved by global coarse-resolution models. We quantify the degree to which local processes modify biogeochemical changes in the eastern boundary California Current System (CCS) using multi-model regionally downscaled climate projections of multiple climate-associated stressors (temperature, O2, pH, saturation state (Ω), and CO2). The downscaled projections predict changes consistent with the directional change from the global projections for the same emissions scenario. However, the magnitude and spatial variability of projected changes are modified in the downscaled projections for carbon variables. Future changes in pCO2 and surface Ω are amplified, while changes in pH and upper 200 m Ω are dampened relative to the projected change in global models. Surface carbon variable changes are highly correlated to changes in dissolved inorganic carbon (DIC), pCO2 changes over the upper 200 m are correlated to total alkalinity (TA), and changes at the bottom are correlated to DIC and nutrient changes. The correlations in these latter two regions suggest that future changes in carbon variables are influenced by nutrient cycling, changes in benthic–pelagic coupling, and TA resolved by the downscaled projections. Within the CCS, differences in global and downscaled climate stressors are spatially variable, and the northern CCS experiences the most intense modification. These projected changes are consistent with the continued reduction in source water oxygen; increase in source water nutrients; and, combined with solubility-driven changes, altered future upwelled source waters in the CCS. The results presented here suggest that projections that resolve coastal processes are necessary for adequate representation of the magnitude of projected change in carbon stressors in the CCS.more » « less
-
Endorheic drainage basins, those inland basins not connected directly to ocean, are essential for hydrological modeling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. Within many hydrological model frameworks, river basins are defined by digital river networks through their flow direction and connectivity datasets. Here we present an improvement to gridded flow direction data and its derivatives produced from upscaled global 5 and 15 arc minute MERIT networks. We explicitly label endorheic and exorheic drainage basins and alter the delineation of endorheic basins by merging small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion of those basins since most of the merged catchments were inside other larger endorheic areas. We developed and present here the endorheic basin delineation method. This method performs an analysis of the contributing river and basin geometry relative to the location of the flow end point (i.e. potential endorheic lake), proximity of the latter to the drainage basin boundary and the elevation difference between the basin's lowest point and potential spillover location at the basin boundary. The new digital river network was validated using the University of New Hampshire Water Balance Model by comparing the water balance of endorheic inland depressions with modeled accumulation of water in their inland lakes based on the observed historical climate drivers used by WBM.more » « less
-
Abstract Accurate groundwater representation in land surface models (LSMs) is vital for water and energy cycle studies, water resource assessments, and climate projections. Yet, many LSMs do not consider key processes including lateral groundwater flow and aquifer pumping, especially at the global scale. This study simulates these processes using an enhanced version of the Community Land Model (CLM5) and evaluates their roles at three spatial resolutions (0.5°, 0.25°, 0.1°). Results show that lateral flow strongly modulates water table depth and capillary rise at all resolutions. The magnitude of mean lateral flow increases from 25 mm/year at 0.5° to 36 mm/year at 0.25°, and 52 mm/year at 0.1° resolution, with pumping inducing lateral flow even at 0.5° (∼50 km), a typical grid size in global LSMs. Further, lateral flow alters runoff in regions with high recharge and shallow water table (e.g., eastern North America and Amazon basin), and soil moisture and ET in regions with comparatively low recharge and deeper water table (e.g., western North America, central Asia, and Australia) through enhanced capillary rise. Runoff alteration by lateral flow increases substantially with resolution, from a maximum of 15 mm/month at 0.5° to 20 mm/month and 25 mm/month at 0.25° and 0.1°, respectively; the impact of resolution on soil moisture and ET is less pronounced. While the model does not fully capture deeper water tables—warranting further enhancements—it provides valuable insights on how lateral groundwater flow impacts land surface processes, highlighting the importance of lateral groundwater flow and pumping in global LSMs.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
