Francisco Munoz-Arriola

Francisco Munoz-Arriola

  • Contact Information
  • My Story
  • Publications
  • Background
  • Interests
  • Advising
  • Courses Taught

Contact Information

TitleHydroinformatics and Integrated Hydroclimatologist
Faculty RankAssociate Professor
Address620 South Hardin Hall
3310 Holdrege Street
Lincoln NE
68583–0997
Phone
  • office: 402-472-0850
E-mailfmunoz@unl.edu
VitaeDownload file

 

My Story

I am an Associate Professor in Hydroinformatics and Integrated Hydroclimate in the School of Natural Resources and the Department of Biological Systems Engineering. My academic and professional experiences encompass sub-seasonal to seasonal diagnostics and prognostics of extreme hydrometeorological and climate events, and their effects on infrastructure (i.e., water resources, agriculture, and ecosystem services).

In the natural and built environment, for example, water quality and quantity are components of a complex system regulated or exacerbated by extreme hydrometeorological and climate events (EHCEs), fluctuating markets, technological developments, social behaviors, and evolving policies and decision making. Thus, the (re)design and management of resilient water infrastructure in a non-stationary world demands a better understanding of the underlying principles that enable water to maintain their core functions across geospatial attributions and management scales.

Research

My research program operates at the intersection of science and engineering. In particular, the study of climate-resilient water, agriculture, and ecosystem services and their operationalization. I study infrastructure as an engineered complex system that can be an integrated food-energy-water-ecosystem services (FEWES) system, a driver of coupled natural-human systems (CNH) across scales, or a combination of environmental variables and genetic markers.

My research group combines field, proximal, and remote sensing products to advance the applications and theories of climate-resilient systems through the use of geospatial and predictive data analytics, or physical models. Such data analytics and syntheses are built-in architectures of software and theories of ecological resilience designed to operationalize adaptive water management in a changing climate.

The complexity and nature of such research endeavors entail forming groups and teamwork across disciplines (ecologists, computer scientists, and geologists), geographies (working infrastructure issues in more than 20 countries), and sectors (public, private, and social). My collaborations also involve international institutions such as the Delft Institute for Water Education (IHE), the Universidad Autónoma de Baja California-Mexicali, the Universidade do Sao Paulo, and the Indian Institutes of Technology (Roorkee, Mumbai, and Gandhinagar) to mention some of them.

Teaching

As in the operationalization of basic and applied research on climate-resilient infrastructure, teaching, and training the next generation of engineers, scientists, and entrepreneurs also undergo a paradigm shift. I integrate foundational concepts and process understanding with on-hand activities and outreach training involving data science, the conceptualization of non-stationarity, and the science of attribution in the classroom. These educational efforts are intertwined with experiences on equity, diversity and inclusion, ethics, teamwork, and environmental responsibility. I teach and co-teach disciplinary and interdisciplinary courses in soil and water resources engineering, hydroclimatology, complexity science, and attribution science and decision-making in socio-(agro)ecological systems.

Service

My service to the profession and the University includes activities that foster diversity, inclusion and equity at the University and College of Engineering levels. These experiences have led me to advocate for and contribute to design programs to recruit, mentor, and retain students and faculty from minority and underrepresented groups in STEM areas. Additionally, I am a member of the American Meteorological Society Water Resources Committee (WRC). The WRC has been working on weather and climate issues relevant to water resources operations, data science, and standards for a non-stationary world.

Selected Publications

Amaranto1, A., F. Pianosi, D. Solomatine, G. Corzo-Perez, and F. Munoz-Arriola (2020). Sensitivity Analysis of Hydroclimatic Controls of Data-driven Groundwater Forecast in Irrigated Croplands. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2020.124957Online
Garret Williams4, Parisa Sarzaeim1, and Francisco Muñoz-Arriola (2020). Simplification of Complex Environmental Variations on Maize-Phenotype Predictability. 2020 ASABE Annual International Meeting, Paper No. 1291. DOI: https://doi.org/10.13031/aim.201291Online
Kumar, M., F. Munoz-Arriola, H. Furumai, and T Chaminda (2020) RESILIENCE, RESPONSE, AND RISK IN WATER SYSTEMS: SHIFTS IN NATURAL FORCINGS AND MANAGEMENT PARADIGMS. Springer Transactions in Civil and Environmental Engineering. ISBN#978-981-15-4667-9: 395pp.
Luciano Alves de Oliveira2, Bryan L Woodbury, Jarbas Honorio de Miranda, and Francisco Munoz-Arriola (2020). Geospatial upscaling of atrazine’s transport using electromagnetic induction across point to field scale. 2020 ASABE Annual International Meeting, Paper No. 884. DOI: https://doi.org/10.13031/aim.202001165. Online
Rico, D.A.1, Carrick Detweiler, and Francisco Muñoz-Arriola (2020). Power-over-Tether UAS Leveraged for Nearly-Indefinite Meteorological Data Acquisition. 2020 ASABE Annual International Meeting, Paper No. 1345. DOI: https://doi.org/10.13031/aim.202001345. Online
Sarzaeim, P1., D. Jarquin, and F. Muñoz-Arriola (2020). Analytics for climate-uncertainty estimation and propagation in maize-phenotype predictions. 2020 ASABE Annual International Meeting, Paper No. 1165. DOI: https://doi.org/10.13031/aim.20884Online
Amaranto1, A., F. Munoz-Arriola, G. Corzo-Perez, and D. Solomatine (2019). A Spatially enhanced data-driven multi-model to improve semi-seasonal groundwater forecasts in the High Plains aquifer, USA. Water Resources Research. DOI:10.1029/2018WR024301.Online
Amaranto1, A., F. Munoz-Arriola, G. Corzo-Perez, and D. Solomatine (2019). A Spatially enhanced data-driven multi-model to improve semi-seasonal groundwater forecasts in the High Plains aquifer, USA. Water Resources Research. DOI:10.1029/2018WR024301.Online
Ashish Kumar1, RAAJ Ramsankaran3, Luca Brocca, Francisco Munoz-Arriola (2019). A Machine learning approach for improving near-real-time satellite-based rainfall estimates by integrating soil moisture. Remote Sensing. doi:10.3390/rs11192221.Online
Isaak Arslan4, Jake Field4, Cale Harms4, Hallie Hohbein4, Miracle Modey4, B. Ramamurthy, D. Benet. Y-C Chen, and F. Munoz-Arriola (2019). NEO-SAT: An information support system for flood-disaster management.
Khan1, M., F. Munoz-Arriola, R. Shaik3, and P. Greer1 (2019). Spatial heterogeneity of temporal shifts in extreme precipitation across India. Journal of Climate Change. DOI: 10.3233/JCC190003.Online
Shaik R., F. Munoz-Arriola, D. A. Rico, and S. L. Bartelt-Hunt (2019). Modelling Water Temperature’s Sensitivity to Atmospheric Warming and River Flow. In Environmental Biotechnology: for sustainable future (Eds. R. B. Sobti, N. Arora, and R. Kothari) ISBN 978-981-10-7283-3.
Amaranto1, A., F. Munoz-Arriola, G. Meyer, D. Solomatine, and G. Corzo (2018). Semi-seasonal Predictability of Water-table Changes Using Machine Learning Methods in Response to Integrated Hydroclimatic and Management Controls. Journal of Hydroinformatics. doi: 10.2166/hydro.2018.002.Online
Cantú-Guerrero1, J., Craven, J., A. Amaranto1, G. Corzo-Perez, F. Munoz-Arriola (2018). Prototype of Software Platform to Forecast Semiseasonal Well-Level Responses to Climate and Irrigation Scheduling in the High Plains.
Herrera-Leon1, L. A., M. Khan1, G. Lopez-Morteo3, and F. Munoz-Arriola (2018). Unified-access mechanisms for Weather, Climate, Water data with geospatial constrains and resolutions.
Lawrence-Dill, C.J., Patrick Schnable, Nathan Springer, and: Natalia de Leon, Jode Edwards, David Ertl, Shawn Kaeppler, Nick Lauter, John McKay, Francisco Munoz-Arriola, Seth Murray, Duke Pauli, Nathalia Penna Cruzato, Colby Ratcliff, James Schnable, Kevin Silverstein, Edgar P. Spalding, Addie Thompson, Ruth Wagner, Jason Wallace, Justin Walley, and Jianming Yu (2018). White paper: High Throughput, Field-Based Phenotyping Technologies for the Genomes to Fields (G2F) Initiative. 2018 NIFA FACT Workshop. January 28-30, 2018, 8 pp.
Ou2, G., F. Munoz-Arriola, D. Uden2, D. Martin and C. Allen (2018). Climate change implications for irrigation and groundwater in the Republican River Basin, USA. Climatic Change. https://doi.org/10.1007/s10584-018-2278-z.Online
Rudnick, D.R., T. Lo, J. Singh1, R. Werle, F. Muñoz-Arriola, T.M. Shaver, C.A. Burr, and T.J. Dorr (2018). Reply to comments on "Performance assessment of factory and field calibrations for electromagnetic sensors in a loam soil". 203:272-276. DOI:10.1016/j.agwat.2018.02.036. Online
Singh1, J., T. Lo, D.R. Rudnick, T.J. Dorr, C.A. Burr, R. Werle, T.M. Shaver, and F. Muñoz-Arriola (2018). Performance Assessment of Factory and Field Calibrations for Electromagnetic Sensors in a Loam Soil. Agricultural Water Management.196: 87-98.
Uden, D., Allen, C., Munoz-Arriola, F., Ou, G., Shank, N. (2018). A Framework for Tracing Social–Ecological Trajectories and Traps in Intensive Agricultural Landscapes. Sustainability, 10, 1646.
Uden, D., Allen, C., Munoz-Arriola, F., Ou, G., Shank, N. (2018). A Framework for Tracing Social–Ecological Trajectories and Traps in Intensive Agricultural Landscapes. Sustainability, 10, 1646.
Das, A., F. Munoz-Arriola, S. Singh, and M. Kumar3 (2017). Nutrient Dynamics of Brahmaputra (Tropical River) during Monsoon Period. Desalinization and Water Treatment.doi:10.5004/dwt.2017.20788.Online
Shekhar, S., J. Colleti, F. Munoz-Arriola, L. Ramaswamy, C. Krinz, L. Varshney, D. Richardson (2017). Intelligent Infrastructure for Smart Agriculture: An Integrated Food, Energy and Water System. eprint arXiv:1705.01993. 2017arXiv170501993S. A Computing Community Consortium (CCC) white paper, 8 pp.
Avery, W., Finkenbiner, C., Franz, T., Wang, T., Nguy-Robertson, A., Munoz-Arriola, F., Suyker, A., Arkebauer, T. 2016. Incorporation of globally available datasets into the cosmic-ray neutron probe method for estimating field scale soil water content. HyOnline
Livneh, B., T. Bohn, D. Pierce, F. Munoz-Arriola, B. Nijssen, R. Vose, D. Cayan, L. Brekke (2015): A spatially comprehensive, hydrometeorological data set for Mexico, the U.S., and southern Canada 1950-2013. Nature - Scientific Data, doi:10.1038/sdata.2015.42.Online
Frans, C, Istanbulluoglu, E., M. Vimal, F. Munoz-Arriola y D. P. Lettenmaier (2013). On runoff trends in the Upper Mississippi River Basin: influences of climate and land use. Geophysical Research Letters. 40, doi:10.1002 /grl.50262, 2013.Online
Wilder, M., G. Garfin, P.Ganster, H. Eakin, P. Romero-Lankao, F. Lara-Valencia, A. Cortez-Lara, S. Mumme, C. Neri, and F. Munoz-Arriola (2013). Impacts of Future Climate Change in the Southwest on Border Communities. In: National Climate Assessment Southwest.
Tang, Q., E. Vivoni, F. Munoz-Arriola, and D. P. Lettenmaier (2012). Predictability of evapotranspiration patterns using remotely-sensed vegetation dynamics during the North American monsoon. Journal of Hydrometeorology, 13(1), 103-121.
Preisler, H. K., A. L. Westerling, K. M. Gebert, F. Munoz-Arriola, and T. P. Holmes (2011). Spatially Explicit Forecasts of Large Fire Probability and Suppression Costs for California Federal and State Lands. International Journal of Wildland Fire, 20(4), 508-517.
Sheffield, J, E. Wood and F. Munoz-Arriola (2010). Long-term regional estimates of evapotranspiration for Mexico based on downscaled ISCCP data. Journal of Hydrometeorology, 11(2), 253-275.
Hohbein, H., A. Zhang, Z. Trautman, D. Brecic, and J. Carter. P. Sarzaeim, D. Jarquin, and F. Munoz-Arriola. Prototype of the GEnetics by ENvironment (GEEN): A Phenotype Predictive System.
Pandey, V., P. K. Srivastava, R. K. Mall, F. Munoz-Arriola, D. Han (Accepted). Multi-Satellite Precipitation Products for Meteorological Drought Assessment and Forecasting in Bundelkhand region of Central India. Geocarto Internacional

Background

Education

DegreeMajorInstitutionYear Awarded
Research AssociateScripps Institution of OceanographyUniversity of California, San Diego2012
Research AssociateLand Surface Hydrology ResearchUniversity of Washington2010
Doctorate of PhilosophyCivil and Environmental Engineering,Duke University2007
Master of ScienceOceanographyUniversidad Autónoma de Baja California1997
Bachelor of ScienceOceanographyUniversidad Autónoma de Baja California1994

 

Affiliations

 

Awards

TitleAwarded byYear Awarded
FellowUniversity of Nebraska Public Policy Center2019
Annual Recognition Teaching AwardUNL, College of Engineering2019
Annual Recognition Research AwardUNL, College of Engineering2018
FellowNational Science Foundation-Enabling the Next Generation of Hazards and Disasters Researchers Fellow2016
FellowNational Science Foundation-Interdisciplinary Methods (for Disaster Research)2016
FellowNational Science Foundation-Interdisciplinary Methods (for Disaster Research)2015
Parent’s Recognition AwardUNL Teaching Council and Parents Association2015
FellowNational Science Foundation-Enabling the Next Generation of Hazards and Disasters Researchers Fellow2015
FellowAmerica Meteorological Society/National Science Foundation-Summer Policy Colloquium2014
FellowDougherty Water for Food Global Institute2014
FellowConsejo Nacional de Ciencia y Tecnologia – Sistema Nacional de Investigadores (México)2014
Adviser/ConsultantWorld Meteorological Organization2010

Areas of Interest/Expertise

  • Data science
  • Integrated hydrology (water quality, quantity, and ecosystem resilience)
  • Surface water and groundwater conjunctive use, interactions, and integration
  • Coupled natural-human systems
  • Complex systems
  • Predictability of hydrometeorological and climate extremes
  • Climate-resilient infrastructure
  • Phenotype predictability
  • Teaching Interests:
  • Predictability of Hydrometeorological and Climate Extremes
  • Complex Systems Modeling
  • Attribution Science and Decision Making
  • Design and Management of Resilient Water Infrastructure

Advising

Graduate Programs

Master of Applied Science

Master of Science in Natural Resource Sciences
including specializations in

  • Climate Assessment and Impacts
  • Hydrological Sciences

Doctorate of Philosophy in Natural Resource Sciences
including specializations in

  • Climate Assessment and Impacts
  • Hydrological Sciences

Courses Taught

Course NumberCourse TitleFall Even YearsFall Odd YearsSpring Even YearsSpring Odd YearsSummer SessionCross Listing
NRES 479/879HydroclimatologyBSEN/METR 479/879; WATS 479
NRES 898Complexity Science in FEWS SystemsXBSEN 892
NRES 898Attribution Science and Decision MakingXBSEN 892
NRES 898Hydraulic Systems in EuropeXBSEN 892