Publications of the Center

Journal articles, reports, and products

Journal Articles

The Center for Hydrologic Innovations builds on the efforts of our faculty, researchers, and graduate students since 2020 in the support of our programs, solution spaces, and tools. The following organization of our peer-reviewed journal articles is based on science and engineering topics with contributions from all of our labs.

Urban Land-Atmosphere Interactions

Kindler, M., Vivoni, E.R., Perez-Ruiz, E.R., and Wang, Z. 2022. Water Conservation Potential of Modified Turf Grass Irrigation in Urban Parks of Phoenix, ArizonaEcohydrology. 15(3): eco.2339.

Vivoni, E.R., Kindler, M., Wang, Z., and Perez-Ruiz, E.R. 2020. Abiotic Mechanisms Drive Enhanced Evaporative Losses under Urban Oasis Conditions. Geophysical Research Letters. 47: e2020GL090123.

Perez-Ruiz, E.R., Vivoni, E.R., and Templeton, N.P. 2020. Urban Land Cover Type Determines the Sensitivity of Carbon Dioxide Fluxes to Precipitation in Phoenix, ArizonaPLOS One. 15(2): e0228537.

Precipitation Characteristics and Changes

Ansh Srivastava, N., and Mascaro, G. 2023. Improving the Utility of Weather Radar for the Spatial Frequency Analysis of Extreme Precipitation. Journal of Hydrology. 624: 129902. 624: 129902.

Mascaro, G., Papalexiou, S., and Wright, D. 2023. Advancing Characterization and Modeling of Space-Time Correlation Structure and Marginal Distribution of Short-Duration Precipitation. Advances in Water Resources. 177: 104451.

Huang, J., Fatichi, S., Mascaro, G., Manoli, G., and Peleg, N. 2022. Intensification of Sub-daily Rainfall Extremes in a Low-rise Urban AreaUrban Climate. 42: 101124.

Farris, S., Deidda, R., Viola, F., and Mascaro, G. 2021. On the Role of Serial Correlation and Field Significance in Detecting Changes in Extreme Precipitation FrequencyWater Resources Research. 57: e2021WR030172.

Mascaro, G. 2020. Comparison of Local, Regional, and Scaling Models for Rainfall Intensity-Duration-Frequency AnalysisJournal of Applied Meteorology and Climatology. 59(9): 1519-1536.

Hydrological Processes in Natural Ecosystems

Keller, Z.T., Vivoni, E.R., Kimsal, C.R., Robles-Morua, A., and Perez-Ruiz, E.R. 2023. Hillslope to Channel Hydrologic Connectivity in a Dryland Ecosystem. Ecosphere. 14(11): e4707.  

Vivoni, E.R., Perez-Ruiz, E.R., Scott, R.L., Naito, A.T., Archer, S.R., Biederman, J.A., and Templeton, N.P. 2022. A Micrometeorological Flux Perspective on Brush Management in a Shrub-encroached Sonoran Desert GrasslandAgricultural and Forest Meteorology. 313: 108763.

Perez-Ruiz, E.R., Vivoni, E.R., and Sala, O.E. 2022. Seasonal Carryover of Water and Effects on Carbon Dynamics in a Dryland EcosystemEcosphere. 13(7): e4189.

Vivoni, E.R., Perez-Ruiz, E.R., Keller, Z.T., Escoto, E.A., Templeton, R.C., Templeton, N.P., Anderson, C.A., Schreiner-McGraw, A.P., Mendez-Barroso, L.A., Robles-Morua, A., Scott, R.L., Archer, S.R., and Peters, D.P.C. 2021. Long-term Research Catchments to Investigate Shrub Encroachment in the Sonoran and Chihuahuan Deserts: Santa Rita and Jornada Experimental RangesHydrological Processes. 35: e14031. 

Groundwater Changes and Sustainability

Liu, P-W., Famiglietti, J.S., Purdy, A.J., Adams, K.H., McEvoy, A.L., Reager, J.T., Bindlish, R., Wiese, D.N., David, C.H., and Rodell., M. 2022. Groundwater Depletion in California’s Central Valley Accelerates During Megadrought. Nature Communications. 13: 7825.

Adams, K.H., Reager, J.T., Rosen, P., Wiese, D.N., Farr, T.G., Rao, S., Haines, B.J., Argus, D.F., Liu, Z., Smith, R., Famiglietti, J.S., and Rodell, M. 2022. Remote Sensing of Groundwater: Current Capabilities and Future Directions. Water Resources Research. 58(10): e2022WR032219.

Surface Water Detection and Characterization

Wang, Z., and Vivoni, E.R. 2022. Detecting Streamflow in Dryland Rivers using CubeSatsGeophysical Research Letters. 49(15): e2022GL098729.

Wang, Z., and Vivoni, E.R. 2022. Mapping Flash Flood Hazards in Arid Regions using CubeSatsRemote Sensing. 14(17): 4218.

Agricultural and Watershed Management

Wei, S., Xu, T., Niu, G-Y., and Zeng, R. 2022. Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High PlainsRemote Sensing. 14(3): 3004.

Sridharan, V.K., Kumar, S., and Kumar, S.M. 2022. Can Remote Sensing Fill the United States’ Monitoring Gap for Watershed Management? Water. 14(3): 1985.

Sadri, S., Famiglietti, J.S., Pan, M., Beck, H., Berg, A., and Wood, E.F. 2022. FarmCan: Developing a Physical, Statistical, and Machine Learning Model to Forecast Crop Water Deficit at Farm Scales. Hydrology and Earth System Sciences. 6(20): 5373-5390.

Infrastructure and Hydrologic Extremes

Shrestha, A., Mascaro, G. and Garcia, M. 2022. Effects of Stormwater Infrastructure Data Completeness and Model Resolution on Urban Flood ModelingJournal of Hydrology. 607: 127498.

Garcia, M., Yu, D., Park, S., Iravanloo, B. M., Bahambari, P. Y., and Sivapalan, M. 2022. Weathering Water Extremes and Cognitive Biases in a Changing ClimateWater Security. 15: 100110.

Underwood, B.S., Mascaro, G., Chester, M.V., Fraser, A., Lopez-Cantu, T., and Samaras, C. 2020. Past and Present Design Practices and Uncertainty in Climate Projections are Challenges for Designing Infrastructure to Future Conditions. Journal of Infrastructure Systems. 26(3): 04020026.

Urban Monitoring and Green Infrastructure

Shrestha, A., and Garcia, M. 2023. Influence of Precipitation Uncertainty and Land Use Change on the Optimal Catchment Scale Green Infrastructure ConfigurationJournal of Sustainable Water and the Built Environment. 9(2): 04023001.

Lara-Valencia, F., Garcia, M., Norman, L.M., Morales, A.A., and Castellanos-Rubio, E.E. 2022. Integrating Urban Planning and Water Management through Green Infrastructure in the United States-Mexico BorderFrontiers in Water. 4: 782922.

Helmrich, A.M., Ruddell, B.L., Chester, M., Bessem, K., Chohan, N., Doerry, E., Eppinger, J., Garcia, M., Goodall, J.L., Lowry, C., and Zahura, F. 2021. Opportunities for Crowdsourcing in Urban Flood Monitoring. Environmental Modelling and Software. 143: 105124.

Infrastructure Operations, Planning and Policy

Longyang, Q. and Zeng, R. 2023. A Hierarchical Temporal Scale Framework for Data-Driven Reservoir Release ModelingWater Resources Research. 59(6): e2022WR033922.

Garcia, M., and Islam S. 2021. Water Stress & Water Salience: Implications for Water Supply PlanningHydrological Sciences Journal. 66(6): 919-934.

Chester, M., Underwood, S., Allenby, B., Garcia, M., Samaras, C., Markolf, S., Sanders, K., Preston, B., and Miller, T. 2021. Infrastructure Resilience to Navigate Increasingly Uncertain and Complex Conditions in the AnthropoceneNature Urban Sustainability. 1: 4.

Garcia, M., Ridolfi, E., and di Baldassarre, G. 2020. The Interplay between Reservoir Storage and Operating Rules under Evolving ConditionsJournal of Hydrology. 590: 125270.

Colorado River Basin Modeling with Stakeholders

Whitney, K.M., Vivoni, E.R., and White, D.D. 2023. Enhancing the Accessibility and Interactions of Regional Hydrologic Projections for Water Managers. Environmental Modelling and Software. 167: 105763.

Whitney, K.M., Vivoni, E.R., Wang, Z., White, D.D., Quay, R., Mahmoud, M.I., and Templeton, N.P. 2023. A Stakeholder Engaged Approach to Anticipating Forest Disturbance Impacts in the Colorado River Basin under Climate ChangeJournal of Water Resources Planning and Management. 149(7): 04023020.

Whitney, K.M., Vivoni, E.R., Bohn, T.J., Mascaro, G., Wang, Z., Xiao, M., Mahmoud, M.I., Cullom, C., and White, D.D. 2023. Spatial Attribution of Declining Colorado River Streamflow under Future WarmingJournal of Hydrology. 617(C): 129125.

Xiao, M., Mascaro, G., Wang, Z., Whitney, K.M., and Vivoni, E.R. 2022. On the Value of Satellite Remote Sensing to Reduce Uncertainties in Regional Simulations of the Colorado RiverHydrology and Earth System Sciences. 26(21): 5627-5646.

Erlingis, J.M., Rodell, M., Peters-Lidard, C.D., Li, B., Kumar, S.V., Famiglietti, J.S., Granger, S.L., Liu, P-W. and Mocko, D.M. 2021. A High-resolution Land Data Assimilation System Optimized for the Western United States. Journal of the American Water Resources Association. 57(5): 692-710.

Hydrologic Modeling and Assessments in Arizona

Guan, X., and Mascaro, G. 2023. Impacts of Climate Change on the Food-Water Nexus in central Arizona. Agricultural and Forest Meteorology. 333: 109413.

Mascaro, G., Hussein, A., Dugger, A., and Gochis, D.J. 2023. Process-based Calibration of WRF-Hydro in a Mountainous Basin in Southwestern U.S. Journal of the American Water Resources Association. 59(1): 49-70.

Wang, Z., and Vivoni, E.R. 2022. Individualized and Combined Effects of Future Urban Growth and Climate Change on Irrigation Water Use in Central ArizonaJournal of the American Water Resources Association. 58(3): 370-387.

Hjelmstad, A., Shrestha, A., Garcia, M., and Mascaro, G. 2021. Propagation of Radar Rainfall Uncertainties into Urban Pluvial Flood Modeling during the North American MonsoonHydrological Sciences Journal. 66(15): 2232-2248.

Wang, Z., Vivoni, E.R., Bohn, T.J., and Wang, Z-H. 2021. A Multiyear Assessment of Irrigation Cooling Capacity in Agricultural and Urban Settings of Central ArizonaJournal of the American Water Resources Association. 57(5): 771-788.

Machine and Deep Learning Modeling

Tyson, C., Longyang, Q., Neilson, B.T., Zeng, R., and Xu, T. 2023. Effects of Meteorological Forcing Uncertainty on High-resolution Snow Modeling and Streamflow Prediction in a Mountainous Karst Watershed. Journal of Hydrology. 619: 129304.

Xu, T., Longyang, Q., Tyson, C., Zeng, R. and Neilson, B.T., 2022. Hybrid Physically Based and Deep Learning Modeling of a Snow Dominated, Mountainous, Karst WatershedWater Resources Research. 58(3): e2021WR030993.

Razavi, S., Hannah, D.M., Elshorbagy, A., Kumar, S., Marshall, L., Solomatine, D.P., Dezfuli, A., Sadegh, M., and Famiglietti, J.S. 2022. Coevolution of Machine Learning and Process-based Modelling to Revolutionize Earth and Environmental Sciences: A Perspective. Hydrological Processes. 36(6): e14596.

Xu, T. and Liang, F., 2021. Machine Learning for Hydrologic Sciences: An Introductory OverviewWiley Interdisciplinary Reviews: Water. 8(5): e1533.

Surrogate Modeling of Hydrologic Systems

Li, P., Xu, T., Wei, S., and Wang, Z-H. 2022. Multi-objective Optimization of Urban Environmental System Design using Machine Learning. Computers, Environment and Urban Systems. 94: 101796.

Ivanov, V.Y., Dwelle, M.C., Xu, D., Sargsyan, K., Wright, D., Katopodes, N., Kim, J., Tran, V.N., Warnock, A., Fatichi, S., Burlando, P., Caporali, E., Restrepo, P., Sanders, B., Chaney, M., Nunes, A.M.B., Nardi, F., Vivoni, E.R., Istanbulluoglu, E., Bisht, G., and Bras, R.L. 2021. Breaking Down the Computational Barriers to Real-Time Urban Flood ForecastingGeophysical Research Letters. 48(20): e2021GL093585.