Susan Colarullo

Susan's current areas of expertise include development of GIS tools and applications to automate processing of large numbers of spatially-distributed datasets, prediction of streamflows using surface water models, and use of multivariate and spatial statistical methods for characterizing distributed hydrologic processes.

She is trained in application of semi- and fully-distributed watershed models for predicting surface water flow, design of optimal surface water monitoring networks using first-order second-moment uncertainty analysis, and automated calibration of watershed models using both maximum-likelihood and Bayesian techniques. Susan also has extensive experience in development of GIS applications using ESRI's ArcGIS software and extensions, Arc Macro Language (AML), and ArcObjects, has used the ArcHydro data model extensively, and is trained in the use of HSPF, TOPMODEL, and PRMS watershed models for predicting streamflows that can be used to assess impacts of urbanization. Her deep experience in geostatistical characterization of hydrologic processes and in many aspects of univariate and multivariate probability and statistics, geostatistics, and stochastic hydrology includes stochastic simulation of random processes, spectral and Monte Carlo approaches to solving stochastic partial differential equations governing fluid flow and transport, and indicator methods for incorporating semi-quantitative information and for assessing local uncertainty and spatial connectivity. Susan has programming experience in fortran, R, python, VBA, VB.NET, C#, html, and javascript, and has done limited programming in SAS and S-Plus. She also has experience in the simulation of groundwater flow and solute transport using numerical finite-difference models.

Susan holds bachelor's and master's degrees from the University of Arizona and earned her doctorate from New Mexico Tech.