Dr. Ricardo Mantilla, Ph.D. P.Eng.

Biography

I joined the faculty of the Civil Engineering Department at the University of Manitoba as an Associate Professor in July 2021 moving from the University of Iowa in the US where I was an Assistant Professor in the Department of Civil and Environmental Engineering. I obtained my PhD degree in Civil Engineering at the University of Colorado in 2007 under the supervision of Prof. Vijay K Gupta, and my master's and bachelor's degree in Civil Engineering at Universidad Nacional de Colombia in Medellin under the supervision of professors Oscar Mesa and German Poveda. My research focus has been the role of self-similarity in river network topology, and in hydraulic geometric variables, in shaping the magnitude, duration, and frequency of floods in space and time. My theoretical developments led to the development of a statewide flood forecasting system (IFC-FFS) for the state of Iowa (US). The statewide implementation of the distributed model requires that the equations describing water movement in the landscape be solved using High-Performance Computing (HPC) resources. Some of the results from the model are made available to the public through the Iowa Flood Information System (IFIS) web platform. I am currently using theoretical insights and computational modeling to predict how climatic and anthropogenic changes to the landscape will alter flood and drought regimes for different climatic regions in the world.

Research

Area

Water resources.

Expertise

Hydrology, Flood Forecasting, Flood Frequency Estimation, River Networks, Nonlinear Dynamical Systems.

Research description

My research is on Surface Hydrology. I continue to expand the work that I started in my PhD dissertation on the Physical Basis of Statistical Self-Similarity in Peak Flows for Random Self-Similar Networks, which was supervised by my former advisor Prof. Vijay Gupta. Through this work, I investigated the two basic physical components that explain the power-law exponents observed in the relationship between Peak Flows and Basin Area at the single storm scale. These two components are River Network Topology and Network Hydraulic Geometry. I am one of the architects of HidroSig, a GIS developed by the Water Resources Department at the Universidad Nacional de Colombia. I am now working on a more specialized version of the software that we call the Hillslope-Link Model (HLM) model. This new application is designed specifically to predict flows in River Networks. I am currently working on the development of Hydrologic Observatories to test the predictions of the Theory of Floods. These predictions include power laws in event-scale peak flows and connections of characteristics of the flood frequency distribution to changing climatic conditions.

Graduate Student Opportunities

I am often looking for highly motivated, bright, enthusiastic students to join our research group. If you have excellent communication skills, a passion for water resources engineering, the ability to show initiative and problem solve, as well as a love of the outdoors (including during winter!) or laboratory environment you may want to consider emailing an application.

Selected Publications

Jadidoleslam, N., Hornbuckle, B.K., Krajewski, W.F., Mantilla, R., Cosh, M.H.,
Analyzing Effects of Crops on SMAP Satellite-Based Soil Moisture Using a Rainfall–
Runoff Model in the US Corn Belt, IEEE Journal of Selected Topics in Applied Earth
Observations and Remote Sensing, 15, 2022

Perez, G., Gomez-Velez, J.D., Mantilla, R, Wright, D.B., Li, Z, The Effect of Storm
Direction on Flood Frequency Analysis, Geophysical Research Letters, 48, 9, 2021

Velásquez, N., Mantilla, R., Krajewski, W.F., Fonley, M., Quintero, F., Improving
Hillslope Link Model Performance from Non-Linear Representation of Natural and
Artificially Drained Subsurface Flows, Hydrology, 8, 4, 2021

Fonley, M.R., Qiu, K., Velásquez, N., Haut, N.K., Mantilla, R., Development and
Evaluation of an ODE Representation of 3D Subsurface Tile Drainage Flow Using the
HLM Flood Forecasting System, Water Resources Research, 57, 3, 2021

Jadidoleslam, N., Mantilla, R., Krajewski, W.F., Data assimilation of satellite-based soil
moisture into a distributed hydrological model for streamflow predictions, Hydrology,
8,1, 2021

Krajewski, Witold F; Ghimire, Ganesh R; Demir, Ibrahim; Mantilla, R; Real-time
streamflow forecasting: AI vs. Hydrologic insights, Journal of Hydrology X, 13, 2021

Quintero, F., W.F. Krajewski, B. Seo, R. Mantilla, Improvement and evaluation of the
Iowa Flood Center Hillslope Link Model (HLM) by calibration-free approach, Journal of
Hydrology, Volume 584, 2020

Jadidoleslam, N., Goska R, Mantilla R, Krajewski, W.F., Hydrovise: A non-proprietary
open-source software for hydrologic model and data visualization and evaluation,
Environmental Modelling & Software, Volume 134, 2020

Bressan F., Mantilla R., Schilling K. E., Palmer J. A. & Weber L., Hydrologic-hydraulic
modeling of sediment transport along the main stem of a watershed: role of tributaries
and channel geometry, Hydrological Sciences Journal, 65:2, 183-199, 2020

Velasquez, N., Mantilla, R. Limits of Predictability of a Global Self-Similar Routing
Model in a Local Self-Similar Environment. Atmosphere, 11, 791, 2020

Jadidoleslam N., Mantilla R., Krajewski W.F, Goska R., Investigating the role of
antecedent SMAP satellite soil moisture, radar rainfall and MODIS vegetation on runoff
production in an agricultural region, Journal of Hydrology, Volume 579, 2019.

Perez, G., Mantilla, R., Krajewski, W.F., & Quintero, F., Examining Observed Rainfall,
Soil Moisture, and River Network Variabilities on Peak Flow Scaling of Rainfall-Runoff
Events with Implications on Regionalization of Peak Flow Quantiles. Water Resources
Research, 55(12), 10707–10726, 2019

Jadidoleslam, N., Mantilla, R., Krajewski, W.F., Cosh, M. H. Data-driven stochastic
model for basin and sub-grid variability of SMAP satellite soil moisture. Journal of
Hydrology, 576, 85-97, 2019.

Perez, G., Mantilla, R., Krajewski, W.F., & Wright, D. B. Using physically based
synthetic peak flows to assess local and regional flood frequency analysis methods.
Water Resources Research, 55. 2019.

Fonley, M.; Mantilla, R.; Curtu, R. Doing Hydrology Backwards—Analytic Solution
Connecting Streamflow Oscillations at the Basin Outlet to Average Evaporation on a
Hillslope. Hydrology 6, 85, 2019.

Perez, G., Mantilla, R., & Krajewski, W.F., Estimation of Historical-Annual and
Historical-Monthly Scale-Invariant Flow Duration Curves with Implementation for
Iowa, Journal of Hydrologic Engineering, volume 23, issue 12, 2018.

Perez, G., Mantilla, R., & Krajewski, W.F. The influence of spatial variability of width
functions on regional peak flow regressions, Water Resources Research, 54, 2018.

Quintero, F., Mantilla, R., Anderson, C., Claman, D., Krajewski, W.F. (2019). Assessment
of changes in flood frequency due to the effects of climate change: implications for
engineering design. Hydrology, 5(19), 2018.