Quantifying Uncertainty in Urban Flooding Analysis Considering Hydro-Climatic Projection and Urban Development Effects

How will the combined impacts of land use change, climate change, and hydrologic modeling influence changes in urban flood frequency and what is the main un- certainty source of the results? Will such changes differ by catchment with different degrees of current and future ur- ban development? We attempt to answer these questions in two catchments with different degrees of urbanization, the Fanno catchment with 84% urban land use and the Johnson catchment with 36% urban land use, both located in the Pa- cific Northwest of the US. Five uncertainty sources - gen- eral circulation model (GCM) structures, future greenhouse gas (GHG) emission scenarios, land use change scenarios, natural variability, and hydrologic model parameters - are considered to compare the relative source of uncertainty in flood frequency projections. Two land use change scenarios, conservation and development, representing possible future land use changes are used for analysis. Results show the highest increase in flood frequency under the combination of medium high GHG emission (A1B) and development sce- narios, and the lowest increase under the combination of low GHG emission (B1) and conservation scenarios. Although the combined impact is more significant to flood frequency change than individual scenarios, it does not linearly increase flood frequency. Changes in flood frequency are more sensi- tive to climate change than land use change in the two catch- ments for 2050s (2040-2069). Shorter term flood frequency change, 2 and 5 year floods, is highly affected by GCM structure, while longer term flood frequency change above 25 year floods is dominated by natural variability. Projected flood frequency changes more significantly in Johnson creek than Fanno creek. This result indicates that, under expected climate change conditions, adaptive urban planning based on the conservation scenario could be more effective in less de- veloped Johnson catchment than in the already developed Fanno catchment.

[1]  Hayley J. Fowler,et al.  Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling , 2007 .

[2]  P. Mote,et al.  Future climate in the Pacific Northwest , 2010 .

[3]  Stefan Hagemann,et al.  Gradient in the climate change signal of European discharge predicted by a multi-model ensemble , 2007 .

[4]  Jay R. Lund,et al.  Climate change, urbanization, and optimal long‐term floodplain protection , 2007 .

[5]  Richard N. Palmer,et al.  Water Resources Implications of Global Warming: A U.S. Regional Perspective , 1999 .

[6]  Keith Beven,et al.  Multi-period and multi-criteria model conditioning to reduce prediction uncertainty in an application of TOPMODEL within the GLUE framework , 2007 .

[7]  Hoshin Vijai Gupta,et al.  Improving robustness of hydrologic parameter estimation by the use of moving block bootstrap resampling , 2010 .

[8]  Guohe Huang,et al.  An Integrated Simulation-Assessment Approach for Evaluating Health Risks of Groundwater Contamination Under Multiple Uncertainties , 2010 .

[9]  Deg-Hyo Bae,et al.  Potential changes in Korean water resources estimated by high-resolution climate simulation , 2008 .

[10]  Soroosh Sorooshian,et al.  Dual state-parameter estimation of hydrological models using ensemble Kalman filter , 2005 .

[11]  Ge Sun,et al.  Streamflow Response to Climate and Landuse Changes in a Coastal Watershed in North Carolina , 2009 .

[12]  Jim W. Hall,et al.  Information gap analysis of flood model uncertainties and regional frequency analysis , 2010 .

[13]  K. Flynn,et al.  User's Manual for Program PeakFQ, Annual Flood-Frequency Analysis Using Bulletin 17B Guidelines , 2006 .

[14]  X. Chen,et al.  Comparison of hydrological impacts of climate change simulated by six hydrological models in the Dongjiang Basin, South China , 2007 .

[15]  C. Prudhomme,et al.  Downscaling of global climate models for flood frequency analysis: where are we now? , 2002 .

[16]  Anthony J. Jakeman,et al.  Assessing the impact of land use change on hydrology by ensemble modelling(LUCHEM) II: ensemble combinations and predictions , 2009 .

[17]  Mary Lynn Baeck,et al.  Field studies of the storm event hydrologic response in an urbanizing watershed , 2005 .

[18]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

[19]  H. Künsch.  The Jackknife and the Bootstrap for General Stationary Observations , 1989 .

[20]  Mohammad Najafi,et al.  Statistical Downscaling of Precipitation Using Machine Learning with Optimal Predictor Selection , 2011 .

[21]  Martyn P. Clark,et al.  Reducing Streamflow Forecast Uncertainty: Application and Qualitative Assessment of the Upper Klamath River Basin, Oregon 1 , 2009 .

[22]  D. Bae,et al.  Hydroclimatological response to dynamically downscaled climate change simulations for Korean basins , 2010 .

[23]  S. Kanae,et al.  Global Hydrological Cycles and World Water Resources , 2006, Science.

[24]  S. Changnon,et al.  Detection of changes in streamflow and floods resulting from climate fluctuations and land use-drainage changes , 1996 .

[25]  D. Higdon,et al.  Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling , 2009 .

[26]  Richard L. Smith,et al.  Quantifying Uncertainty in Projections of Regional Climate Change: A Bayesian Approach to the Analysis of Multimodel Ensembles , 2005 .

[27]  Hamid Moradkhani,et al.  Statistical Comparisons of Watershed-Scale Response to Climate Change in Selected Basins across the United States , 2011 .

[28]  Richard G. Taylor,et al.  Sources of uncertainty in climate change impacts on river discharge and groundwater in a headwater catchment of the Upper Nile Basin, Uganda , 2010 .

[29]  Martyn P. Clark,et al.  One-Way Coupling of an Atmospheric and a Hydrologic Model in Colorado , 2006 .

[30]  T. Wigley,et al.  Natural variability of the climate system and detection of the greenhouse effect , 1990, Nature.

[31]  Lawrence E. Band,et al.  Simulating runoff behavior in an urbanizing watershed , 2000 .

[32]  Kenneth R. Sperber,et al.  ENSO simulation in coupled ocean-atmosphere models: are the current models better? , 2006 .

[33]  Heejun Chang,et al.  Climate Change, Land‐Use Change, and Floods: Toward an Integrated Assessment , 2008 .

[34]  Sarah Praskievicz,et al.  Winter precipitation intensity and ENSO/PDO variability in the Willamette Valley of Oregon , 2009 .

[35]  Soroosh Sorooshian,et al.  General Review of Rainfall-Runoff Modeling: Model Calibration, Data Assimilation, and Uncertainty Analysis , 2009 .

[36]  S. Crooks,et al.  Assessment of land use change in the thames catchment and its effect on the flood regime of the river , 2001 .

[37]  L. Brekke,et al.  A framework for assessing flood frequency based on climate projection information , 2009 .

[38]  Suraje Dessai,et al.  Challenges in using probabilistic climate change information for impact assessments: an example from the water sector , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[39]  David Hulse,et al.  ENVISIONING ALTERNATIVES: USING CITIZEN GUIDANCE TO MAP FUTURE LAND AND WATER USE , 2004 .

[40]  R. Wilby,et al.  A framework for assessing uncertainties in climate change impacts: Low‐flow scenarios for the River Thames, UK , 2006 .

[41]  Martyn P. Clark,et al.  Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models , 2008 .

[42]  S. Uhlenbrook,et al.  Quantifying the impact of land-use changes at the event and seasonal time scale using a process-oriented catchment model , 2004 .

[43]  M. Canty,et al.  Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter , 2011 .

[44]  Nigel W. Arnell,et al.  Relative effects of multi-decadal climatic variability and changes in the mean and variability of climate due to global warming: future streamflows in Britain , 2003 .

[45]  L. Vasiliades,et al.  Climate change effects on drought severity , 2008 .

[46]  M. J. Booij,et al.  Impact of climate change on river flooding assessed with different spatial model resolutions , 2005 .

[47]  Tyler Smith,et al.  Bayesian methods in hydrologic modeling: A study of recent advancements in Markov chain Monte Carlo techniques , 2008 .

[48]  Murugesu Sivapalan,et al.  Transcending limitations of stationarity and the return period: process‐based approach to flood estimation and risk assessment , 2009 .

[49]  R. Stouffer,et al.  Stationarity Is Dead: Whither Water Management? , 2008, Science.

[50]  Jannis Epting,et al.  Integrating field and numerical modeling methods for applied urban karst hydrogeology , 2009 .

[51]  Roberto Ranzi,et al.  Effects on floods of recent afforestation and urbanisation in the Mella River (Italian Alps) , 2002 .

[52]  Witold F. Krajewski,et al.  The effects of aerosols on intense convective precipitation in the northeastern United States , 2009 .

[53]  M. Oppenheimer,et al.  Urbanization, climate change and flood policy in the United States , 2010 .

[54]  Vijay P. Singh,et al.  Analysis of drought severity‐area‐frequency curves using a general circulation model and scenario uncertainty , 2009 .

[55]  Kuolin Hsu,et al.  Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter , 2005 .

[56]  David L. Peterson,et al.  Preparing for climate change: the water, salmon, and forests of the Pacific Northwest , 2003 .

[57]  Heejun Chang,et al.  What is responsible for increasing flood risks? The case of Gangwon Province, Korea , 2009 .

[58]  B. Bates,et al.  Climate change and water. , 2008 .

[59]  Sarah Praskievicz,et al.  A review of hydrological modelling of basin-scale climate change and urban development impacts , 2009 .

[60]  Antonius Laenen,et al.  Precipitation-runoff and streamflow-routing models for the Willamette River basin, Oregon , 1997 .

[61]  Renzo Rosso,et al.  An Integrated Simulation Method for Flash-flood Risk Assessment :2. Effect of Historical Changes in Land Use an Integrated Simulation Method for Flash-flood Risk Assessment: 2. Effects of Changes in Land-use under a Historical Perspective , 2022 .

[62]  J. Tu.  Combined impact of climate and land use changes on streamflow and water quality in eastern Massachusetts, USA , 2009 .

[63]  H. Moradkhani,et al.  Assessing the uncertainties of hydrologic model selection in climate change impact studies , 2011 .

[64]  George H. Leavesley,et al.  USGS Modular Modeling System (MMS) - Precipitation-Runoff Modeling System (PRMS) , 2006 .

[65]  Subimal Ghosh,et al.  Nonparametric methods for modeling GCM and scenario uncertainty in drought assessment , 2007 .

[66]  Vijay P. Singh,et al.  The Precipitation-Runoff Modeling System - PRMS. , 1995 .

[67]  D. T. Snyder,et al.  Hydrology of the Johnson Creek Basin, Oregon , 2009 .

[68]  D. Lettenmaier,et al.  Hydrologic uncertainties in climate change from IPCC AR4 GCM simulations of the Chungju Basin, Korea , 2011 .

[69]  Heejun Chang,et al.  Hydrologic Impacts of Climate Change in the Upper Clackamas River Basin, Oregon, USA , 2007 .

[70]  Paul D. Bates,et al.  The Regional Hydrology of Extreme Floods in an Urbanizing Drainage Basin , 2002 .

[71]  Bengt Carlsson,et al.  Assessing climate change impacts on hydrology from an ensemble of regional climate models, model scales and linking methods – a case study on the Lule River basin , 2007 .

[72]  D. Randall,et al.  Climate models and their evaluation , 2007 .

[73]  Kay,et al.  Comparison of uncertainty sources for climate change impacts : flood frequency in England , 2009 .

[74]  Christel Prudhomme,et al.  Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 2: future climate , 2009 .

[75]  H. Moradkhani,et al.  Snow water equivalent prediction using Bayesian data assimilation methods , 2011 .

[76]  I. Jung,et al.  The temporal and spatial structures of recent and future trends in extreme indices over Korea from a regional climate projection , 2011 .

[77]  Veronica W. Griffis,et al.  Evolution of Flood Frequency Analysis with Bulletin 17 , 2007 .

[78]  T. Huntington.  Evidence for intensification of the global water cycle: Review and synthesis , 2006 .

[79]  M. Figliozzi,et al.  Potential Impacts of Climate Change on Flood-Induced Travel Disruptions: A Case Study of Portland, Oregon, USA , 2010 .

[80]  Heejun Chang,et al.  Spatial and temporal changes in runoff caused by climate change in a complex large river basin in Oregon. , 2010 .

[81]  Hamid Moradkhani,et al.  Uncertainty assessment of climate change impacts for hydrologically distinct river basins , 2012 .

[82]  Witold F. Krajewski,et al.  Extreme hydrometeorological events and the urban environment: Dissecting the 7 July 2004 thunderstorm over the Baltimore MD Metropolitan Region , 2008 .

[83]  Sarah Praskievicz,et al.  Impacts of Climate Change and Urban Development on Water Resources in the Tualatin River Basin, Oregon , 2011 .

[84]  L. Vasiliades,et al.  Evaluation of Climate Change on Drought Impulses in Thessaly , Greece , 2008 .

[85]  E. P. Evans,et al.  Land use, water management and future flood risk. , 2009 .

[86]  Alan F. Hamlet,et al.  Statistical downscaling techniques for global climate model simulations of temperature and precipitation with application to water resources planning studies , 2010 .

[87]  C. M. DeChant,et al.  Radiance data assimilation for operational snow and streamflow forecasting , 2011 .

[88]  Woonsup Choi.  Catchment-Scale Hydrological Response to Climate-Land-Use Combined Scenarios: A Case Study for the Kishwaukee River Basin, Illinois , 2008 .

[89]  B. Bobée,et al.  The gamma family and derived distributions applied in hydrology , 1991 .

[90]  Deg-Hyo Bae,et al.  Long‐term trend of precipitation and runoff in Korean river basins , 2008 .

[91]  P. Reed,et al.  Hydrology and Earth System Sciences Discussions Comparing Sensitivity Analysis Methods to Advance Lumped Watershed Model Identification and Evaluation , 2022 .

[92]  J. M. Shepherd,et al.  A Review of Current Investigations of Urban-Induced Rainfall and Recommendations for the Future , 2005 .

[93]  H. H. Rosenbrock,et al.  An Automatic Method for Finding the Greatest or Least Value of a Function , 1960, Comput. J..

[94]  D. Lettenmaier,et al.  Effects of 20th century warming and climate variability on flood risk in the western U.S. , 2006 .

[95]  Hamid Moradkhani,et al.  Assessment of climate change impact on floodplain and hydrologic ecotones. , 2010 .

[96]  M. Hulme,et al.  Relative impacts of human-induced climate change and natural climate variability , 1999, Nature.

[97]  D. Lettenmaier,et al.  Effects of 20 th century warming and climate variability on flood risk in the western U . S . , 2007 .

[98]  Heejun Chang,et al.  The effects of climate change and urbanization on the runoff of the Rock Creek basin in the Portland metropolitan area, Oregon, USA , 2009 .

[99]  Robert L. Wilby,et al.  Uncertainty in water resource model parameters used for climate change impact assessment , 2005 .

[100]  Woonsup Choi,et al.  Simulating streamflow response to climate scenarios in central Canada using a simple statistical downscaling method , 2009 .

[101]  Armando Brath,et al.  Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty) , 2006 .

[102]  H. Johnson,et al.  Chapter D. Effects of Urbanization on Stream Ecosystems in the Willamette River Basin and Surrounding Area, Oregon and Washington , 2008 .

[103]  K.R. Davey.  Latin Hypercube Sampling and Pattern Search in Magnetic Field Optimization Problems , 2008, IEEE Transactions on Magnetics.