{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T03:27:45Z","timestamp":1762918065429,"version":"build-2065373602"},"reference-count":62,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1545874"],"award-info":[{"award-number":["1545874"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A new generation of precipitation measurement products has emerged, and their performances have gained much attention from the scientific community, such as the Multi-Radar Multi-Sensor system (MRMS) from the National Severe Storm Laboratory (NSSL) and the Global Precipitation Measurement Mission (GPM) from the National Aeronautics and Space Administration (NASA). This study statistically evaluated the MRMS and GPM products and investigated their cascading hydrological response in August of 2017, when Hurricane Harvey brought historical and record-breaking precipitation to the Gulf Coast (&gt;1500 mm), causing 107 fatalities along with about USD 125 billion worth of damage. Rain-gauge observations from Harris County Flood Control District (HCFCD) and stream-gauge measurements by the United States Geological Survey (USGS) were used as ground truths to evaluate MRMS, GPM and National Centers for Environmental Prediction (NCEP) gauge-only data by using statistical metrics and hydrological simulations using the Ensemble Framework for Flash Flooding Forecast (EF5) model. The results indicate that remote sensing technologies can accurately detect and estimate the unprecedented precipitation event with their near-real-time products, and all precipitation products produced good hydrological simulations, where the Nash\u2013Sutcliff model efficiency coefficients (NSCE) were close to 0.9 for both the MRMS and GPM products. With the timeliness and seamless coverage of MRMS and GPM, the study also demonstrated the capability and efficiency of the EF5 framework for flash flood modeling over the United States and potentially additional international domains.<\/jats:p>","DOI":"10.3390\/rs12030445","type":"journal-article","created":{"date-parts":[[2020,2,5]],"date-time":"2020-02-05T03:18:48Z","timestamp":1580872728000},"page":"445","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Can Remote Sensing Technologies Capture the Extreme Precipitation Event and Its Cascading Hydrological Response? A Case Study of Hurricane Harvey Using EF5 Modeling Framework"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2135-1670","authenticated-orcid":false,"given":"Mengye","family":"Chen","sequence":"first","affiliation":[{"name":"Hydrometeorology and Remote Sensing Laboratory, School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2883-1482","authenticated-orcid":false,"given":"Soumaya","family":"Nabih","sequence":"additional","affiliation":[{"name":"Hydrometeorology and Remote Sensing Laboratory, School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73109, USA"},{"name":"Department of Georesources and Environment, Sidi Mohamed Ben Abdellah University, Fez 32000, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noah S.","family":"Brauer","sequence":"additional","affiliation":[{"name":"Advanced Radar Research Center, School of Meteorology, University of Oklahoma, Norman, OK 73109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8641-2433","authenticated-orcid":false,"given":"Shang","family":"Gao","sequence":"additional","affiliation":[{"name":"Hydrometeorology and Remote Sensing Laboratory, School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan J.","family":"Gourley","sequence":"additional","affiliation":[{"name":"NOAA National Severe Storm Laboratory, Norman, OK 73109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4303-7500","authenticated-orcid":false,"given":"Zhen","family":"Hong","sequence":"additional","affiliation":[{"name":"Hydrometeorology and Remote Sensing Laboratory, School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Randall L.","family":"Kolar","sequence":"additional","affiliation":[{"name":"Hydrometeorology and Remote Sensing Laboratory, School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Hong","sequence":"additional","affiliation":[{"name":"Hydrometeorology and Remote Sensing Laboratory, School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,1]]},"reference":[{"key":"ref_1","unstructured":"Smith, K., and Ward, R. (1998). Floods: Physical Processes and Human Impact, John Wiley. Available online: http:\/\/agris.fao.org\/agris-search\/search.do?recordID=GB1997043473."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1023\/B:NHAZ.0000024895.48463.eb","article-title":"Use of systematic, palaeoflood and historical data for the improvement of flood risk estimation. Review of scientific methods","volume":"31","author":"Benito","year":"2004","journal-title":"Nat. Hazards"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1007\/s11069-006-9065-2","article-title":"Major flood disasters in Europe: 1950\u20132005","volume":"42","author":"Barredo","year":"2007","journal-title":"Nat. Hazards"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1175\/2007JAMC1611.1","article-title":"Flood fatalities in the United States","volume":"47","author":"Ashley","year":"2008","journal-title":"J. Appl. Meteorol. Clim."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1175\/JHM-D-14-0048.1","article-title":"Hydrometeorological Analysis and Remote Sensing of Extremes: Was the July 2012 Beijing Flood Event Detectable and Predictable by Global Satellite Observing and Global Weather Modeling Systems?","volume":"16","author":"Zhang","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1038\/s41586-018-0676-z","article-title":"Urbanization exacerbated the rainfall and flooding caused by hurricane Harvey in Houston","volume":"563","author":"Zhang","year":"2018","journal-title":"Nat."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1007\/s11069-019-03794-y","article-title":"Modeling the effect of urbanization on flood risk in Ayamama Watershed, Istanbul, Turkey, using the MIKE 21 FM model","volume":"99","author":"Nigussie","year":"2019","journal-title":"Nat. Hazards"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s11069-010-9537-2","article-title":"A digitized global flood inventory (1998\u20132008): compilation and preliminary results","volume":"55","author":"Adhikari","year":"2010","journal-title":"Nat. Hazards"},{"key":"ref_9","unstructured":"Eric, B.S., and Zelinsky, D.A. (2018). National Hurricane Center Tropical Cyclone Report Hurricane Harvey, National Hurricane Center."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"019501","DOI":"10.1088\/1748-9326\/aaa343","article-title":"Corrigendum: Attribution of extreme rainfall from Hurricane Harvey, August 2017 (2017 Environ. Res. Lett. 12 124009)","volume":"13","author":"Sebastian","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_11","unstructured":"Murphy, J.D. (2020, January 30). Service Assessment August\u2013September 2017 Hurricane Harvey, Available online: https:\/\/www.weather.gov\/media\/publications\/assessments\/harvey6-18.pdf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.envsoft.2017.01.006","article-title":"Flood inundation modelling: A review of methods, recent advances and uncertainty analysis","volume":"90","author":"Teng","year":"2017","journal-title":"Environ. Model. Softw."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1365","DOI":"10.1002\/hyp.6092","article-title":"An application of a flood risk analysis system for impact analysis of a flood control plan in a river basin","volume":"20","author":"Dutta","year":"2006","journal-title":"Hydrol. Process."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"53","DOI":"10.5194\/nhess-13-53-2013","article-title":"Multi-variate flood damage assessment: a tree-based data-mining approach","volume":"13","author":"Merz","year":"2013","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1175\/BAMS-D-15-00247.1","article-title":"The FLASH Project: Improving the Tools for Flash Flood Monitoring and Prediction across the United States","volume":"98","author":"Gourley","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1016\/j.advwatres.2009.05.008","article-title":"Two-dimensional, high-resolution modeling of urban dam-break flooding: A case study of Baldwin Hills, California","volume":"32","author":"Gallegos","year":"2009","journal-title":"Adv. Water Resour."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.jhydrol.2013.09.033","article-title":"Storage-based approaches to build floodplain inundation modelling capability in river system models for water resources planning and accounting","volume":"504","author":"Dutta","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/S0022-1694(00)00159-1","article-title":"Modelling suspended sediment deposition on a fluvial floodplain using a two-dimensional dynamic finite element model","volume":"229","author":"Hardy","year":"2000","journal-title":"J. Hydrol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/0022-1694(86)90114-9","article-title":"An introduction to the European Hydrological System\u2014Systeme Hydrologique European, \u201cSHE\u201d, 1: History and philosophy of a physically-based, distributed modeling system","volume":"87","author":"Abbott","year":"1986","journal-title":"J. Hydrol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"948","DOI":"10.1016\/j.envint.2005.05.005","article-title":"The effect of floods on the transport of suspended sediments and contaminants: A case study from the estuary of the Dese River (Venice Lagoon, Italy)","volume":"31","author":"Zonta","year":"2005","journal-title":"Environ. Int."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.advwatres.2013.06.010","article-title":"Hydrological data assimilation with the Ensemble Square-Root-Filter: Use of streamflow observations to update model states for real-time flash flood forecasting","volume":"59","author":"Chen","year":"2013","journal-title":"Adv. Water Resour."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s11069-004-4537-8","article-title":"Flood Forecasting and Warning at the River Basin and at the European Scale","volume":"36","author":"Werner","year":"2005","journal-title":"Nat. Hazards"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1175\/JHM574.1","article-title":"Evaluation of PERSIANN-CCS Rainfall Measurement Using the NAME Event Rain Gauge Network","volume":"8","author":"Hong","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.jhydrol.2007.01.030","article-title":"Hydrologic response to climatic variability in a Great Lakes Watershed: A case study with the SWAT model","volume":"337","author":"Wu","year":"2007","journal-title":"J. Hydrol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1693","DOI":"10.1002\/2015MS000510","article-title":"Fully coupled atmosphere-hydrology simulations for the central Mediterranean: Impact of enhanced hydrological parameterization for short and long time scales","volume":"7","author":"Senatore","year":"2015","journal-title":"J. Adv. Model. Earth Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2049","DOI":"10.1007\/s11069-014-1412-0","article-title":"Usage of the WRF\/DHSVM model chain for simulation of extreme floods in mountainous areas: A pilot study for the Uzh River Basin in the Ukrainian Carpathians","volume":"75","author":"Kocalets","year":"2015","journal-title":"Nat. Hazards"},{"key":"ref_27","unstructured":"McAllister, M., Gochis, D., Bariage, M.J., Dugger, A.L., FitzGerald, K., Karsten, L., and McCreight, J.L. (2018). The community of WRF-Hydro Modeling system Version 5 melding with the National Water Model: Enhancements and education. Proceedings of the AGU Fall Meeting 2018, AGU."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1007\/s11069-018-3462-1","article-title":"An integrated 1D\u20132D hydraulic modeling approach to assess the sensitivity of a coastal region to compound flooding hazard under climate change","volume":"98","author":"Pasquier","year":"2019","journal-title":"Nat. Hazards"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1080\/02626667.2010.543087","article-title":"The coupled routing and excess storage (CREST) distributed hydrological model","volume":"56","author":"Wang","year":"2011","journal-title":"Hydrol. Sci. J."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1697","DOI":"10.1175\/BAMS-D-15-00130.1","article-title":"Hydrological Modeling and Capacity Building in the Republic of Namibia","volume":"98","author":"Clark","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1029\/2005WR004398","article-title":"Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response","volume":"42","author":"Hong","year":"2006","journal-title":"Water Resour. Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.jhydrol.2013.07.023","article-title":"Multi-scale evaluation of high-resolution multi-sensor blended global precipitation products over the Yangtze River","volume":"500","author":"Li","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1519","DOI":"10.1175\/1520-0450(1999)038<1519:RRGCUO>2.0.CO;2","article-title":"Radar\u2013Rain Gauge Comparisons under Observational Uncertainties","volume":"38","author":"Ciach","year":"1999","journal-title":"J. Appl. Meteorol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1029\/2006WR005739","article-title":"A first approach to global runoff simulation using satellite rainfall estimation","volume":"43","author":"Hong","year":"2007","journal-title":"Water Resour. Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1029\/2007JD009214","article-title":"Rainfall and sampling uncertainties: A rain gauge perspective","volume":"113","author":"Villarini","year":"2008","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1175\/JHM-D-15-0059.1","article-title":"Statistical and Hydrological Comparisons between TRMM and GPM Level-3 Products over a Midlatitude Basin: Is Day-1 IMERG a Good Successor for TMPA 3B42V7?","volume":"17","author":"Tang","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/S0022-1694(98)00140-1","article-title":"Real-time estimation of rainfall fields using rain gage data under fractional coverage conditions","volume":"208","author":"Seo","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1175\/1525-7541(2001)002<0036:GPAODD>2.0.CO;2","article-title":"Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations","volume":"2","author":"Huffman","year":"2001","journal-title":"J. Hydrometeorol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1175\/2010JTECHA1488.1","article-title":"A New Dual-Polarization Radar Rainfall Algorithm: Application in Colorado Precipitation Events","volume":"28","author":"Cifelli","year":"2011","journal-title":"J. Atmospheric Ocean. Technol."},{"key":"ref_40","unstructured":"Hong, Y., and Gourley, J.J. (2014). Radar Hydrology: Principles, Models, and Applications, CRC Press. Available online: https:\/\/content.taylorfrancis.com\/books\/download?dac=C2011-0-18942-9&isbn=9781466514621&format=googlePreviewPdf."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1175\/BAMS-D-14-00174.1","article-title":"Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation: Initial Operating Capabilities","volume":"97","author":"Zhang","year":"2016","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Chang, N.-B., and Hong, Y. (2012). Multiscale Hydrologic Remote Sensing: Perspectives and Applications, CRC Press. Available online: https:\/\/www.taylorfrancis.com\/books\/e\/9780429109300.","DOI":"10.1201\/b11279"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1175\/BAMS-D-13-00164.1","article-title":"The Global Precipitation Measurement Mission","volume":"95","author":"Hou","year":"2014","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_44","unstructured":"Huffman, G.J., Bolvin, D.T., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C., Nelkin, E.J., Sorooshain, S., Tan, J., and Xie, P. (2012). Developing the Integrated Multi-Satellite Retrievals for GPM (IMERG). Proceedings of the EGU General Assembly, EGU."},{"key":"ref_45","unstructured":"Huffman, G.J., Bolvin, D.T., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C., Nelkin, E.J., Sorooshian, S., Tan, J., and Xie, P. (2019). Algorithm Theoretical Basis Document (ATBD) Version 06 NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG)."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1007\/s11069-018-3202-6","article-title":"Investigating the impacts of typhoon-induced floods on the agriculture in the central region of Vietnam by using hydrological models and satellite data","volume":"92","author":"Pham","year":"2018","journal-title":"Nat. Hazards"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1007\/s11069-018-3426-5","article-title":"On the rainfall asymmetry and distribution in tropical cyclones over Bay of Bengal using TMPA and GPM rainfall products","volume":"94","author":"Thakur","year":"2018","journal-title":"Nat. Hazards"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.atmosres.2019.03.004","article-title":"Extreme rainfall from Hurricane Harvey (2017): Empirical intercomparisons of WRF simulations and polarimetric radar fields","volume":"223","author":"Yang","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Omaranian, E., Sharif, H.O., and Tavakoly, A.A. (2018). How well can Global Precipitation Measurement (GPM) capture hurricanes? Case study: Hurricane Harvey. Remote. Sens., 10.","DOI":"10.3390\/rs10071150"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1175\/JHM-D-18-0197.1","article-title":"Effective Cloud Detection and Segmentation Using a Gradient-Based Algorithm for Satellite Imagery: Application to Improve PERSIANN-CCS","volume":"20","author":"Hayatbini","year":"2019","journal-title":"J. Hydrometeorol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"05019005","DOI":"10.1061\/(ASCE)HE.1943-5584.0001768","article-title":"Hurricane Harvey Highlights: Need to Assess the Adequacy of Probable Maximum Precipitation Estimation Methods","volume":"24","author":"Kao","year":"2019","journal-title":"J. Hydrol. Eng."},{"key":"ref_52","unstructured":"Huffman, G.J., Bolvin, D.T., Nelkin, E.J., Jackson, T., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C., Sorooshian, S., and Xie, P. (2020, January 30). Early Results for Version 06 IMERG, Available online: https:\/\/ntrs.nasa.gov\/search.jsp?R=20190029175."},{"key":"ref_53","unstructured":"Blake, E.S., and Zelinsky, D.A. (2020, January 30). Tropical Cyclone Report Hurricane Harvey, Available online: https:\/\/www.nhc.noaa.gov\/data\/tcr\/AL092017_Harvey.pdf."},{"key":"ref_54","unstructured":"Kats, S. (2020, January 30). NCEP\/EMC U.S. Gage Only Hourly Precipitation Data Version 1.0. UCAR\/NCAR - Earth Observing Laboratory. Available online: https:\/\/data.eol.ucar.edu\/dataset\/21.004."},{"key":"ref_55","unstructured":"Huffman, G., Bolvin, D., Braithwaite, D., Hsu, K., Joyce, R., and Xie, P. (2020, January 31). Integrated Multi-satellitE Retrievals for GPM (IMERG), Vers. 4.4. NASA\u2019s Precipitation Processing Center, Available online: https:\/\/docserver.gesdisc.eosdis.nasa.gov\/public\/project\/GPM\/IMERG_doc.06.pdf."},{"key":"ref_56","unstructured":"Huffman, G.J., Bolvin, D.T., Nelkin, E.J., Stocker, E.F., and Tan, J. (2020, January 30). V06 IMERG Release Notes 2019, Available online: https:\/\/pmm.nasa.gov\/sites\/default\/files\/document_files\/IMERG_V06_release_notes_190503.pdf."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2155","DOI":"10.1098\/rstb.2005.1754","article-title":"Climate science and famine early warning","volume":"360","author":"Verdin","year":"2005","journal-title":"Philos. Trans. R. Soc. B Boil. Sci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1016\/j.jhydrol.2016.06.011","article-title":"Estimating a-priori kinematic wave model parameters based on regionalization for flash flood forecasting in the Conterminous United States","volume":"541","author":"Vergara","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_59","unstructured":"Chow, V.T., Maidment, D.R., and Mays, L.W. (1988). Applied Hydrology, McGraw-Hill."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1007\/s00477-008-0274-y","article-title":"Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?","volume":"23","author":"Vrugt","year":"2009","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"05015019","DOI":"10.1061\/(ASCE)HE.1943-5584.0001282","article-title":"New Multisite Cascading Calibration Approach for Hydrological Models: Case Study in the Red River Basin Using the VIC Model","volume":"21","author":"Xue","year":"2016","journal-title":"J. Hydrol. Eng."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"32","DOI":"10.3390\/w6010032","article-title":"Evaluation of Version-7 TRMM multi-satellite precipitation Analysis product during the Beijing extreme heavy rainfall event of","volume":"6","author":"Huang","year":"2014","journal-title":"Water"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/3\/445\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T08:53:39Z","timestamp":1760172819000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/3\/445"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,1]]},"references-count":62,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["rs12030445"],"URL":"https:\/\/doi.org\/10.3390\/rs12030445","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2020,2,1]]}}}