Naoki Mizukami

NSF National Center for Atmospheric Research

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Martyn Clark

University of Calgary

Andrew J. Newman

NSF National Center for Atmospheric Research

E. D. Gutmann

NSF National Center for Atmospheric Research

Bart Nijssen

University of Washington

Andrew W. Wood

NSF National Center for Atmospheric Research

J. R. Arnold

United States Department of Agriculture

L. D. Brekke

United States Bureau of Reclamation

Pablo A. Mendoza

University of Chile

Shervan Gharari

University of Saskatchewan

Michael Smith

NOAA National Weather Service

Cooperative Institutions

NSF National Center for Atmospheric Research

NOAA National Weather Service

University of Washington

United States Geological Survey

Research Applications (United States)

University of Arizona

University of Saskatchewan

National Oceanic and Atmospheric Administration

University of Colorado Boulder

John Wiley & Sons (United States)

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Climate change impacts on flood risk and asset damages within mapped 100-year floodplains of the contiguous United States

Natural hazards and earth system sciences (2017)

Cameron Wobus E. D. Gutmann Russell Jones Matthew Rissing Naoki Mizukami

Abstract. A growing body of work suggests that the extreme weather events that drive inland flooding are likely to increase in frequency and magnitude in a warming climate, thus potentially increasing flood damages in the future. We use hydrologic projections based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) to estimate changes in the frequency of modeled 1 % annual exceedance probability (1 % AEP, or 100-year) flood events at 57 116 stream reaches across the contiguous United States (CONUS). We link these flood projections to a database of assets within mapped flood hazard zones to model changes in inland flooding damages throughout the CONUS over the remainder of the 21st century. Our model generates early 21st century flood damages that reasonably approximate the range of historical observations and trajectories of future damages that vary substantially depending on the greenhouse gas (GHG) emissions pathway. The difference in modeled flood damages between higher and lower emissions pathways approaches USD 4 billion per year by 2100 (in undiscounted 2014 dollars), suggesting that aggressive GHG emissions reductions could generate significant monetary benefits over the long term in terms of reduced flood damages. Although the downscaled hydrologic data we used have been applied to flood impacts studies elsewhere, this research expands on earlier work to quantify changes in flood risk by linking future flood exposure to assets and damages on a national scale. Our approach relies on a series of simplifications that could ultimately affect damage estimates (e.g., use of statistical downscaling, reliance on a nationwide hydrologic model, and linking damage estimates only to 1 % AEP floods). Although future work is needed to test the sensitivity of our results to these methodological choices, our results indicate that monetary damages from inland flooding could be significantly reduced through substantial GHG mitigation.

Representative Concentration Pathways

10.5194/nhess-17-2199-2017

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Citations (65)

Representation of spatial and temporal variability in large-domain hydrological models: case study for a mesoscale pre-Alpine basin

Hydrology and earth system sciences (2016)

Lieke Melsen Adriaan J. Teuling P.J.J.F. Torfs Massimiliano Zappa Naoki Mizukami

Abstract. The transfer of parameter sets over different temporal and spatial resolutions is common practice in many large-domain hydrological modelling studies. The degree to which parameters are transferable across temporal and spatial resolutions is an indicator of how well spatial and temporal variability is represented in the models. A large degree of transferability may well indicate a poor representation of such variability in the employed models. To investigate parameter transferability over resolution in time and space we have set up a study in which the Variable Infiltration Capacity (VIC) model for the Thur basin in Switzerland was run with four different spatial resolutions (1 km × 1 km, 5 km × 5 km, 10 km × 10 km, lumped) and evaluated for three relevant temporal resolutions (hour, day, month), both applied with uniform and distributed forcing. The model was run 3150 times using the Hierarchical Latin Hypercube Sample and the best 1 % of the runs was selected as behavioural. The overlap in behavioural sets for different spatial and temporal resolutions was used as an indicator of parameter transferability. A key result from this study is that the overlap in parameter sets for different spatial resolutions was much larger than for different temporal resolutions, also when the forcing was applied in a distributed fashion. This result suggests that it is easier to transfer parameters across different spatial resolutions than across different temporal resolutions. However, the result also indicates a substantial underestimation in the spatial variability represented in the hydrological simulations, suggesting that the high spatial transferability may occur because the current generation of large-domain models has an inadequate representation of spatial variability and hydrologic connectivity. The results presented in this paper provide a strong motivation to further investigate and substantially improve the representation of spatial and temporal variability in large-domain hydrological models.

Transferability

Temporal resolution

Forcing (mathematics)

Temporal scales

Representation

10.5194/hess-20-2207-2016

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Citations (103)

Diagnostic Evaluation of Large‐Domain Hydrologic Models Calibrated Across the Contiguous United States

Journal of Geophysical Research Atmospheres (2019)

Oldřich Rakovec Naoki Mizukami Rohini Kumar Andrew J. Newman Stephan Thober

Abstract This study presents diagnostic evaluation of two large‐domain hydrologic models: the mesoscale Hydrologic Model (mHM) and the Variable Infiltration Capacity (VIC) over the contiguous United States (CONUS). These models have been calibrated using the Multiscale Parameter Regionalization scheme in a joint, multibasin approach using 492 medium‐sized basins across the CONUS yielding spatially distributed model parameter sets. The mHM simulations are used as a performance benchmark to examine performance deficiencies in the VIC model. We find that after calibration to streamflow, VIC generally overestimates the magnitude and temporal variability of evapotranspiration (ET) as compared to mHM as well as the FLUXNET observation‐based ET product, resulting in underestimation of the mean and variability of runoff. We perform a controlled calibration experiment to investigate the effect of varying number of transfer function parameters in mHM and to enable a fair comparison between both models (14 and 48 for mHM vs. 14 for VIC). Results of this experiment show similar behavior of mHM with 14 and 48 parameters. Furthermore, we diagnose the internal functioning of the VIC model by looking at the relationship of the evaporative fraction versus the degree of soil saturation and compare it with that of the mHM model, which has a different model structure, a prescribed nonlinear relationship between these variables and exhibits better model skill than VIC. Despite these limitations, the VIC‐based CONUS‐wide calibration constrained against streamflow exhibits better ET skill as compared to two preexisting independent VIC studies.

10.1029/2019jd030767

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Citations (102)

Estimate of SWE distribution in Colorado Rive Basin using unsupervised classiflcation of SSM/I data

Naoki Mizukami

Estimates of snow water equivalent (SWE) distribution in mountainous areas are needed for water resources management, such as forecasting stream runofi during spring time. Among various types of remote sensing sensors, a passive microwave sensor is only one that has capability of extracting snow volume information. However, the current algorithm equation signiflcantly underestimates the SWE in complex terrains. One of the unsupervised classiflcations, ISODATA, was tested with microwave data from SSM/I for SWE distribution estimates in the complex terrains during snow accumulation and melting periods. Using ISODATA technique, the upper Colorado River Basin was partitioned into 5, 10 and 20 classes based on statistical similarity of following image parameters BTD between 19GHz H and 37 GHz H and individual Brightness temperatures (19GHz V, 22GHz H, 37GHz V, 85GHz H, and 85GHz V) for two difierent winter time. Remaining research efiort would be toward the reconflgurations of input image parameters into the ISODATA. This would include implementations of vegetation classiflcation data, and terrain information.

Multispectral pattern recognition

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Mapping (dis)agreement in hydrologic projections

Hydrology and earth system sciences (2018)

Lieke Melsen Nans Addor Naoki Mizukami Andrew J. Newman P.J.J.F. Torfs

Abstract. Hydrologic projections are of vital socio-economic importance. However, they are also prone to uncertainty. In order to establish a meaningful range of storylines to support water managers in decision making, we need to reveal the relevant sources of uncertainty. Here, we systematically and extensively investigate uncertainty in hydrologic projections for 605 basins throughout the contiguous US. We show that in the majority of the basins, the sign of change in average annual runoff and discharge timing for the period 2070–2100 compared to 1985–2008 differs among combinations of climate models, hydrologic models, and parameters. Mapping the results revealed that different sources of uncertainty dominate in different regions. Hydrologic model induced uncertainty in the sign of change in mean runoff was related to snow processes and aridity, whereas uncertainty in both mean runoff and discharge timing induced by the climate models was related to disagreement among the models regarding the change in precipitation. Overall, disagreement on the sign of change was more widespread for the mean runoff than for the discharge timing. The results demonstrate the need to define a wide range of quantitative hydrologic storylines, including parameter, hydrologic model, and climate model forcing uncertainty, to support water resource planning.

Hydrological modelling

Forcing (mathematics)

10.5194/hess-22-1775-2018

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Citations (79)

Towards scale-independent land-surface flux estimates in Noah-MP

HAL (Le Centre pour la Communication Scientifique Directe) (2017)

Stephan Thober Naoki Mizukami Luis Samaniego Sabine Attinger Martyn Clark

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Gridded Ensemble Precipitation and Temperature Estimates for the Contiguous United States

Journal of Hydrometeorology (2015)

Andrew J. Newman Martyn Clark J. Craig Bart Nijssen Andrew W. Wood

Abstract Gridded precipitation and temperature products are inherently uncertain because of myriad factors, including interpolation from a sparse observation network, measurement representativeness, and measurement errors. Generally uncertainty is not explicitly accounted for in gridded products of precipitation or temperature; if it is represented, it is often included in an ad hoc manner. A lack of quantitative uncertainty estimates for hydrometeorological forcing fields limits the application of advanced data assimilation systems and other tools in land surface and hydrologic modeling. This study develops a gridded, observation-based ensemble of precipitation and temperature at a daily increment for the period 1980–2012 for the conterminous United States, northern Mexico, and southern Canada. This allows for the estimation of precipitation and temperature uncertainty in hydrologic modeling and data assimilation through the use of the ensemble variance. Statistical verification of the ensemble indicates that it has generally good reliability and discrimination of events of various magnitudes but has a slight wet bias for high threshold events (>50 mm). The ensemble mean is similar to other widely used hydrometeorological datasets but with some important differences. The ensemble product produces a more realistic occurrence of precipitation statistics (wet day fraction), which impacts the empirical derivation of other fields used in land surface and hydrologic modeling. In terms of applications, skill in simulations of streamflow in 671 headwater basins is similar to other coarse-resolution datasets. This is the first version, and future work will address temporal correlation of precipitation anomalies, inclusion of other data streams, and examination of topographic lapse rate choices.

Hydrometeorology

Proxy (statistics)

Forcing (mathematics)

Hydrological modelling

10.1175/jhm-d-15-0026.1

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Citations (174)

Effects of different regional climate model resolution and forcing scales on projected hydrologic changes

Journal of Hydrology (2016)

Pablo A. Mendoza Naoki Mizukami Kyoko Ikeda Martyn Clark E. D. Gutmann

Forcing (mathematics)

Water balance

Hydrological modelling

10.1016/j.jhydrol.2016.08.010

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Citations (49)

Hydrologic Implications of Different Large-Scale Meteorological Model Forcing Datasets in Mountainous Regions

Journal of Hydrometeorology (2013)

Naoki Mizukami Martyn Clark A. G. Slater L. D. Brekke Marketa M. Elsner

Abstract Process-based hydrologic models require extensive meteorological forcing data, including data on precipitation, temperature, shortwave and longwave radiation, humidity, surface pressure, and wind speed. Observations of precipitation and temperature are more common than other variables; consequently, radiation, humidity, pressure, and wind speed often must be either estimated using empirical relationships with precipitation and temperature or obtained from numerical weather prediction models. This study examines two climate forcing datasets using different methods to estimate radiative energy fluxes and humidity and investigates the effects of the choice of forcing data on hydrologic simulations over the mountainous upper Colorado River basin (293 472 km2). Comparisons of model simulations forced by two climate datasets illustrate that the methods used to estimate shortwave radiation impact hydrologic states and fluxes, particularly at high elevation (e.g., ~20% difference in runoff above 3000-m elevation), substantially altering the timing of snowmelt and runoff (~20 days difference) and the partitioning of precipitation between evapotranspiration and runoff. The different forcing datasets also exhibit differences in hydrologic sensitivity to interannual temperature at high elevation. The results suggest that the choice of forcing dataset is an important consideration when conducting climate impact assessments and the subsequent applications of these assessments for water resources planning and management.

Shortwave radiation

Forcing (mathematics)

Snowmelt

Shortwave

Longwave

Elevation (ballistics)

Hydrological modelling

10.1175/jhm-d-13-036.1

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Citations (65)

Towards spatial and temporal snow distribution estimates over the mountain region of the western United States

PhDT (2011)

Naoki Mizukami

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