Cara Christine Tobin | EPFL Graph Search

CARA C. TOBIN, PE

Civil Engineer

EDUCATION

PhD in Environmental Engineering, Swiss Federal Institute of Technology, Fulbright Fellowship

01/2007-present

Master's in Civil and Environmental Engineering, Stanford University, National Science Foundation (NSF) Fellowship Recipient

06/2001

Bachelor's in Civil and Environmental Engineering, Georgia Institute of Technology, National Science Foundation Undergraduate Research Fellow

06/1999

PROFESSIONAL SUMMARY

Swiss Federal Institute of Technology, Department of Environmental Engineering, Lausanne, Switzerland, MINERVE2011

· Research on Predicting floods and managing hydropower in the Swiss Alps. Project includes improving knowledge of hydrological processes and conducting uncertainty analysis.

10/2007 - present

Asian Development Bank: World Bank, Baku, Azerbaijan

· Environmental engineering specialist in charge of reviewing environmental aspects of water supply and wastewater discharge designs. Environmental Assessments Performed and managed the local environmental, social and resettlement specialists.

02/2009 - 07/2009

Asian Development Bank / World Bank, Yerevan, Armenia

· Environmental engineering specialist for the assessment of water supply designs. Performed Environmental Assessments and Resettlement due diligence.

01/2008 - 04/2008

Temple University, Department of Civil Engineering, Philadelphia, USA

· Adjunct Professor for Environmental Engineering,

Introduction to the Environment and Environmental Engineering

10/2005-06/2006

CH2M HILL, Environmental Engineering Consultancy, Philadelphia, USA

· Project leader for river discharge ammonia toxicity study

· Engineer in charge of over $ 100,000 in WWTP design upgrades

10/2004-06/2006

MWH Ltd., Environmental Engineering Consultancy, Christchurch, NZ and Brisbane, AU

Leader hydraulic engineer for major components of a $ 150 million wastewater and desalination project

· Head shape for a dozen water and groundwater projects

02/2003-09/2004

Kennedy / Jenks Consultants, Civil Engineering Consultancy, San Francisco, USA

· Environmental engineer in charge of Drinking Water Source Assessments and water quality sampling programs

08/2001-01/2003

Stanford Environmental Fluid Mechanics Lab, USA

· Developer of a 3D computer model simulating turbulent mixing at lateral boundaries due to steepening and breaking of internal waves

08/2000-06/2001

Georgia Instititute of Technology, Civil Engineering Labs, USA

· Analyzed influence of copper sorption rates on particle flocculation kinetics

Developed turbulence · PIV experiments in hydraulic flume

06/1998-06/2000

AFFILIATIONS and SPECIALIZATIONS

. Fluent en Anglais et Français, proficient in Spanish

· Professional Civil Engineer (PE072050), ASCE, AGU, Fulbright Alumnus

· Experienced with ArcGIS, Matlab, R Statistical Analysis, MapInfo, MODFLOW, H2OMap, AutoCAD, Idrisi, Unix / Lenox, Fortran, NetCDF, Visual Basic

Improving the degree-day method for sub-daily melt simulations with physically-based diurnal variations

Guillermo Barrenetxea Kobas, Ludovico Nicotina, Marc Parlange, Andrea Rinaldo, Bettina Schaefli, Silvia Simoni, Cara Christine Tobin

This paper proposes a new extension of the classical degree-day snowmelt model applicable to hourly simulations for regions with limited data and adaptable to a broad range of spatially-explicit hydrological models. The snowmelt schemes have been tested with a point measurement dataset at the Cotton Creek Experimental Watershed (CCEW) in British Columbia, Canada and with a detailed dataset available from the Dranse de Ferret catchment, an extensive ly monitor ed catchment in the Swiss Alps. The snowmelt model performance is quantified with the use of a spatially-explicit model of the hydrologic response. Comparative analyses are presented with the widely-known, grid-based method proposed by Hock which combines a local, temperature-index approach with potential radiation. The results suggest that a simple diurnal cycle of the degree-day melt parameter based on minimum and maximum temperature s is competitive with the Hock approach for sub-daily melt simulations. Advantages of the new extension of the classical degree-da y method over other temperature-index methods include its use of physically-based, diurnal variations and its abil ity to be adapted to data-constrained hydrological models which are lumped in some nature.

Elsevier2013

Improving Alpine Flood Prediction through Hydrological Process Characterization and Uncertainty Analysis

Cara Christine Tobin

Among the many challenges of Alpine flood prediction is describing complex, meteo-hydrological processes in a simplified, robust manner that can be easily integrated into operational forecasting. In this dissertation, improved methods to characterize these processes are developed and integrated into the hydrological modeling component of an operational flood forecasting system used in the Swiss Alps. Detailed studies are conducted to improve hydrological model inputs, processes and outputs. Improvements, detailed in four chapters of this thesis, address the overarching goal of this work – the reduction of flood forecasting uncertainty. The accuracy of flood predictions in Alpine areas is contingent upon adequate interpolation of meteorological forcings, which has significant impacts on discharge volumes and flood peaks. This thesis demonstrates an improvement in the interpolation of temperature and precipitation inputs using a robust variogram which considers anisotropy and using a geostatistical interpolation method to distribute inputs in space and time. Results show that using elevation as the external drift factor better describes orographically-induced precipitation and temperature gradients. Also, the consideration of anisotropy is integral in detailing spatial patterns of precipitation induced by storm advection. Hydrological flood forecasting in mountainous areas also requires accurate partitioning between rain and snowfall to properly estimate the extent of runoff contributing areas. Partitioning is improved in this work by using a new method to integrate Limited Area Model output. Unlike standard hydrological procedures in inferring snowfall limit estimates based on dry, ground temperature measurements, Limited Area Model output considers the vertical, humid, atmospheric structure in its snowfall limit calculations. In effect, this method provides good estimates of runoff contributing areas in the spring as evidenced by validation on discharge measurements and satellite images of snow coverage. Accurately describing snowmelt processes on a sub-daily scale is also of critical importance in Alpine flood forecasting. However, the complex topography of the study region has limited observations available for validation. This thesis presents the development of a new physically-based snowmelt method applicable to regions with limited data. This method uses only daily minimum and maximum temperatures to mimic the effects of radiation. A comparative analysis of snowmelt methods is validated with snow lysimeter data and with a unique, distributed meteorological dataset collected by a wireless weather station network. Results demonstrate that the new method is competitive with more complex snowmelt methods as shown by accurately reproducing diurnal snowmelt cycles. Conveying limits of certainty on flood prediction outputs to users is critical because of epistemic and aleatory errors inherent to environmental modeling. Due to the presence of these errors, the GLUE methodology and multi-criteria performance ideas have been adapted with a fit-for-purpose uncertainty estimation technique in the final part of this thesis. With this method, hydrological model parameters are constrained based on hydrograph behavior, with a particular focus on flood peak response. A key component of the technique is a visualization tool which shows acceptable ensembles of discharge with respect to individual and combined criteria. By integrating the aforementioned input and process improvements into the hydrological model, calibration achieves model outputs that capture observed river discharge. Also, the uncertainty associated with hydrological modeling output error is reduced. Findings of this thesis are applicable to operational flood forecasting in general and have proven utility in improving hydrological model predictions in mountainous regions. Due to the novelty of the developments in terms of new methods or the use of tools and data sources previously unexploited in flood forecasting, further testing of the improvements is recommended. Future research in quantifying the chain of uncertainty produced by combining probabilistic forecast inputs with the hydrological output ensembles is also critical when the improved flood forecasting model becomes fully operational.

EPFL2012

Snowfall Limit Forecasts and Hydrological Modeling

Andrea Rinaldo, Bettina Schaefli, Cara Christine Tobin

Hydrological flood forecasting in mountainous areas requires accurate partitioning between rain and snowfall to properly estimate the extent of runoff contributing areas. Here a method to make use of snowfall limit information-a standard output of limited-area models (LAMs)-for catchment-scale hydrological modeling is proposed. LAMs consider the vertical, humid, atmospheric structure in their snowfall limit calculations. The proposed approach is thus more physically based than inferring snowfall limit estimates based on (dry) ground temperature measurements, which is the standard procedure in most hydrological models. The presented case study uses forecast reanalyses from the Consortium for Small-Scale Modeling (COSMO) limited-area model as input for discharge simulation in a topographically complex catchment in the Swiss Alps. Results suggest that the use of COSMO snowfall limits during spring snowmelt periods can provide more accurate runoff simulations than routine procedures, with practical implications for operational hydrology in Alpine regions.

Amer Meteorological Soc2012

Improving Alpine Flood Prediction through Hydrological Process Characterization and Uncertainty Analysis

Cara Christine Tobin

EPFL2012