{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T21:03:05Z","timestamp":1780779785440,"version":"3.54.1"},"reference-count":81,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2020,12,15]],"date-time":"2020-12-15T00:00:00Z","timestamp":1607990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Extreme rainfall can be a catastrophic trigger for natural disaster events at urban scales. However, there remains large uncertainties as to how satellite precipitation can identify these triggers at a city scale. The objective of this study is to evaluate the potential of satellite-based rainfall estimates to monitor natural disaster triggers in urban areas. Rainfall estimates from the Global Precipitation Measurement (GPM) mission are evaluated over the city of Rio de Janeiro, Brazil, where urban floods and landslides occur periodically as a result of extreme rainfall events. Two rainfall products derived from the Integrated Multi-satellite Retrievals for GPM (IMERG), the IMERG Early and IMERG Final products, are integrated into the Noah Multi-Parameterization (Noah-MP) land surface model in order to simulate the spatial and temporal dynamics of two key hydrometeorological disaster triggers across the city over the wet seasons during 2001\u20132019. Here, total runoff (TR) and rootzone soil moisture (RZSM) are considered as flood and landslide triggers, respectively. Ground-based observations at 33 pluviometric stations are interpolated, and the resulting rainfall fields are used in an in-situ precipitation-based simulation, considered as the reference for evaluating the IMERG-driven simulations. The evaluation is performed during the wet seasons (November-April), when average rainfall over the city is 4.4 mm\/day. Results show that IMERG products show low spatial variability at the city scale, generally overestimate rainfall rates by 12\u201335%, and impacts on TR and RZSM vary spatially mostly as a function of land cover and soil types. Results based on statistical and categorical metrics show that IMERG skill in detecting extreme events is moderate, with IMERG Final performing slightly better for most metrics. By analyzing two recent storms, we observe that IMERG detects mostly hourly extreme events, but underestimates rainfall rates, resulting in underestimated TR and RZSM. An evaluation of normalized time series using percentiles shows that both satellite products have significantly improved skill in detecting extreme events when compared to the evaluation using absolute values, indicating that IMERG precipitation could be potentially used as a predictor for natural disasters in urban areas.<\/jats:p>","DOI":"10.3390\/rs12244095","type":"journal-article","created":{"date-parts":[[2020,12,15]],"date-time":"2020-12-15T21:11:02Z","timestamp":1608066662000},"page":"4095","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9635-7220","authenticated-orcid":false,"given":"Augusto","family":"Getirana","sequence":"first","affiliation":[{"name":"Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA"},{"name":"Science Applications International Corporation, Greenbelt, MD 20771, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dalia","family":"Kirschbaum","sequence":"additional","affiliation":[{"name":"Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9576-5257","authenticated-orcid":false,"given":"Felipe","family":"Mandarino","sequence":"additional","affiliation":[{"name":"Instituto Pereira Passos, Rio de Janeiro 22221-070, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2259-5848","authenticated-orcid":false,"given":"Marta","family":"Ottoni","sequence":"additional","affiliation":[{"name":"Geological Survey of Brazil, Rio de Janeiro 22290-240, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sana","family":"Khan","sequence":"additional","affiliation":[{"name":"Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA"},{"name":"Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristi","family":"Arsenault","sequence":"additional","affiliation":[{"name":"Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA"},{"name":"Science Applications International Corporation, Greenbelt, MD 20771, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1023\/A:1007024703844","article-title":"Megacities and natural disasters: A comparative analysis","volume":"49","author":"Mitchell","year":"1999","journal-title":"GeoJournal"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1080\/09640568.2018.1547693","article-title":"A review of structural approach to flood management in coastal megacities of developing nations: Current research and future directions","volume":"63","author":"Ogie","year":"2020","journal-title":"J. Environ. Plan. Manag."},{"key":"ref_3","unstructured":"ELLA (2017). Urban Disaster Risk Management in Latin American Cities, Evidence and Lessons from Latin America."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"29","DOI":"10.2495\/SAFE130041","article-title":"Flood risk assessment and management: A case study in Rio de Janeiro","volume":"134","author":"Miguez","year":"2013","journal-title":"WIT Trans. Built Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1177\/095624789200400208","article-title":"Landslides in the squatter settlements of Caracas; towards a better understanding of causative factors","volume":"4","author":"Diaz","year":"1992","journal-title":"Environ. Urban."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Haigh, M., and Rawat, J.S. (2011). Landslide causes: Human impacts on a Himalayan landslide swarm. Belgeo, 201\u2013220.","DOI":"10.4000\/belgeo.6311"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1007\/s10346-019-01167-x","article-title":"The cost of rapid and haphazard urbanization: Lessons learned from the Freetown landslide disaster","volume":"16","author":"Cui","year":"2019","journal-title":"Landslides"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"20006","DOI":"10.3390\/s150820006","article-title":"Visual Sensing for Urban Flood Monitoring","volume":"15","author":"Lo","year":"2015","journal-title":"Sensors"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Garcia, F.C.C., Retamar, A.E., and Javier, J.C. (2015, January 1\u20134). A real time urban flood monitoring system for metro Manila. Proceedings of the TENCON 2015\u20142015 IEEE Region 10 Conference, Macao, China.","DOI":"10.1109\/TENCON.2015.7372990"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Hsu, S.-Y., Chen, T.-B., Du, W.-C., Wu, J.-H., and Chen, S.-C. (2019). Integrate Weather Radar and Monitoring Devices for Urban Flooding Surveillance. Sensors, 19.","DOI":"10.3390\/s19040825"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.cageo.2017.11.008","article-title":"Hyper-resolution monitoring of urban flooding with social media and crowdsourcing data","volume":"111","author":"Wang","year":"2018","journal-title":"Comput. Geosci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.envres.2015.02.028","article-title":"Urban flood risk warning under rapid urbanization","volume":"139","author":"Chen","year":"2015","journal-title":"Environ. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2106","DOI":"10.2166\/wst.2010.382","article-title":"Real-time forecasting urban drainage models: Full or simplified networks?","volume":"62","author":"Ferreira","year":"2010","journal-title":"Water Sci. Technol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4015","DOI":"10.5194\/hess-17-4015-2013","article-title":"Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data","volume":"17","author":"Ozdemir","year":"2013","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1002\/hyp.9515","article-title":"An automated routing methodology to enable direct rainfall in high resolution shallow water models","volume":"27","author":"Sampson","year":"2013","journal-title":"Hydrol. Process."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"209","DOI":"10.5194\/hess-19-209-2015","article-title":"Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: Data set characteristics and assessment of regional variability in hydrologic model performance","volume":"19","author":"Newman","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Miguez, M.G., Battemarco, B.P., De Sousa, M.M., Rezende, O.M., Ver\u00f3l, A.P., and Gusmaroli, G. (2017). Urban Flood Simulation Using MODCEL\u2014An Alternative Quasi-2D Conceptual Model. Water, 9.","DOI":"10.3390\/w9060445"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Varlas, G., Anagnostou, M.N., Spyrou, C., Papadopoulos, A., Kalogiros, J., Mentzafou, A., Michaelides, S., Baltas, E., Karymbalis, E., and Katsafados, P. (2018). A Multi-Platform Hydrometeorological Analysis of the Flash Flood Event of 15 November 2017 in Attica, Greece. Remote Sens., 11.","DOI":"10.3390\/rs11010045"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2536","DOI":"10.1016\/j.rse.2011.04.039","article-title":"The accuracy of sequential aerial photography and SAR data for observing urban flood dynamics, a case study of the UK summer 2007 floods","volume":"115","author":"Schumann","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.3390\/w7041437","article-title":"Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier\u2014A Case of Yuyao, China","volume":"7","author":"Feng","year":"2015","journal-title":"Water"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1111\/j.1753-318X.2011.01093.x","article-title":"Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 floods in Tewkesbury, UK","volume":"4","author":"Neal","year":"2011","journal-title":"J. Flood Risk Manag."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"853","DOI":"10.5194\/nhess-15-853-2015","article-title":"Technical Note: An operational landslide early warning system at regional scale based on space\u2013time-variable rainfall thresholds","volume":"15","author":"Segoni","year":"2015","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"817","DOI":"10.5194\/nhess-17-817-2017","article-title":"Adapting the EDuMaP method to test the performance of the Norwegian early warning system for weather-induced landslides","volume":"17","author":"Piciullo","year":"2017","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Rosi, A., Canavesi, V., Segoni, S., Dias Nery, T., Catani, F., and Casagli, N. (2019). Landslides in the Mountain Region of Rio de Janeiro: A Proposal for the Semi-Automated Definition of Multiple Rainfall Thresholds. Geosciences, 9.","DOI":"10.3390\/geosciences9050203"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.1007\/s10346-018-0966-4","article-title":"A review of the recent literature on rainfall thresholds for landslide occurrence","volume":"15","author":"Segoni","year":"2018","journal-title":"Landslides"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"102973","DOI":"10.1016\/j.earscirev.2019.102973","article-title":"Geographical landslide early warning systems","volume":"200","author":"Guzzetti","year":"2020","journal-title":"Earth-Science Rev."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1002\/2017EF000715","article-title":"Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness","volume":"6","author":"Kirschbaum","year":"2018","journal-title":"Earth\u2019s Futur."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_29","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_30","doi-asserted-by":"crossref","first-page":"1679","DOI":"10.1175\/BAMS-D-15-00306.1","article-title":"The Global Precipitation Measurement (GPM) Mission for Science and Society","volume":"98","author":"Petersen","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1175\/BAMS-D-15-00296.1","article-title":"NASA\u2019s Remotely Sensed Precipitation: A Reservoir for Applications Users","volume":"98","author":"Kirschbaum","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"8646","DOI":"10.1029\/2018JD028584","article-title":"Investigating the Potential of Using Satellite-Based Precipitation Radars as Reference for Evaluating Multisatellite Merged Products","volume":"123","author":"Khan","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1002\/qj.3313","article-title":"The Global Precipitation Measurement (GPM) mission\u2019s scientific achievements and societal contributions: Reviewing four years of advanced rain and snow observations","volume":"144","author":"Kirschbaum","year":"2018","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.atmosres.2016.12.007","article-title":"Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42 over Far-East Asia","volume":"187","author":"Kim","year":"2017","journal-title":"Atmos. Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1080\/01431161.2016.1268735","article-title":"Comprehensive evaluation of 3-hourly TRMM and half-hourly GPM-IMERG satellite precipitation products","volume":"38","author":"Saghafian","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3543","DOI":"10.5194\/hess-21-3543-2017","article-title":"Hydrological modeling of the Peruvian-Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset","volume":"21","author":"Zubieta","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1865","DOI":"10.1175\/2009BAMS2786.1","article-title":"The AMMA land surface model intercomparison project (ALMIP)","volume":"90","author":"Boone","year":"2009","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.jhydrol.2011.04.037","article-title":"Assessment of different precipitation datasets and their impacts on the water balance of the Negro River basin","volume":"404","author":"Getirana","year":"2011","journal-title":"J. Hydrol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1694","DOI":"10.1002\/2017JD027606","article-title":"To What Extent is the Day 1 GPM IMERG Satellite Precipitation Estimate Improved as Compared to TRMM TMPA-RT?","volume":"123","author":"Gebregiorgis","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1016\/j.jhydrol.2016.01.029","article-title":"A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region","volume":"556","author":"Prakash","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Rozante, J., Vila, D., Barboza Chiquetto, J., Fernandes, A., and Souza Alvim, D. (2018). Evaluation of TRMM\/GPM Blended Daily Products over Brazil. Remote Sens., 10.","DOI":"10.3390\/rs10060882"},{"key":"ref_42","unstructured":"Huffman, G., Bolvin, D.T., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C., Nelkin, E.J., and Xie, P. (2015). NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) Prepared for: Global Precipitation Measurement (GPM) National Aeronautics and Space Administration (NASA), Algorithm Theoretical Basis Document Version 4.5."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Tan, M., and Duan, Z. (2017). Assessment of GPM and TRMM Precipitation Products over Singapore. Remote Sens., 9.","DOI":"10.3390\/rs9070720"},{"key":"ref_44","unstructured":"(2020, June 29). Floodlist Brazil\u201410 Dead After Torrential Rain in Rio de Janeiro. Available online: http:\/\/floodlist.com\/america\/brazil-rio-floods-april-2019."},{"key":"ref_45","unstructured":"(2020, June 29). Floodlist Brazil\u2014Deadly Floods and Landslides in Rio de Janeiro After 90 mm of Rain in 1 Hour. Available online: http:\/\/floodlist.com\/america\/brazil-rio-de-janeiro-flood-storm-february-2019."},{"key":"ref_46","unstructured":"Fonseca, P., and Gaier, R.V. (2020, June 29). Powerful, \u201cAbnormal\u201d Rains Lash Rio de Janeiro, at Least Six Dead. Available online: https:\/\/www.reuters.com\/article\/us-brazil-weather\/powerful-abnormal-rains-lash-rio-de-janeiro-at-least-six-dead-idUSKCN1RL20U."},{"key":"ref_47","unstructured":"Jeantet, D. (2020, June 29). Heavy Rains Cause Deadly Floods in Rio de Janeiro. Available online: https:\/\/www.pbs.org\/newshour\/world\/heavy-rains-cause-deadly-floods-in-rio-de-janeiro."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1402","DOI":"10.1016\/j.envsoft.2005.07.004","article-title":"Land information system: An interoperable framework for high resolution land surface modeling","volume":"21","author":"Kumar","year":"2006","journal-title":"Environ. Model. Softw."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3605","DOI":"10.5194\/gmd-11-3605-2018","article-title":"The Land surface Data Toolkit (LDT v7.2)\u2014A data fusion environment for land data assimilation systems","volume":"11","author":"Arsenault","year":"2018","journal-title":"Geosci. Model Dev."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Yang, Z.-L., Niu, G.-Y., Mitchell, K.E., Chen, F., Ek, M.B., Barlage, M., Longuevergne, L., Manning, K., Niyogi, D., and Tewari, M. (2011). The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins. J. Geophys. Res. Atmos., 116.","DOI":"10.1029\/2010JD015140"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2010JD015139","article-title":"The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements","volume":"116","author":"Niu","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Ek, M.B., Mitchell, K.E., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G., and Tarpley, J.D. (2003). Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res. Atmos., 108.","DOI":"10.1029\/2002JD003296"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Ball, J.T., Woodrow, I.E., and Berry, J.A. (1987). A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions. Progress in Photosynthesis Research, Springer.","DOI":"10.1007\/978-94-017-0519-6_48"},{"key":"ref_54","first-page":"D07103","article-title":"Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data","volume":"112","author":"Niu","year":"2007","journal-title":"J. Geophys. Res."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1029\/2018MS001422","article-title":"Updates to the Noah Land Surface Model in WRF-CMAQ to Improve Simulated Meteorology, Air Quality, and Deposition","volume":"11","author":"Campbell","year":"2019","journal-title":"J. Adv. Model. Earth Syst."},{"key":"ref_56","unstructured":"Schueler, T.R., and Holland, H.K. (2000). The Compaction of Urban Soils. The Practice of Watershed Protection, Center for Watershed Protection."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"6215","DOI":"10.1029\/1998JD200090","article-title":"Mapping global land surface albedo from NOAA AVHRR","volume":"104","author":"Csiszar","year":"1999","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"7251","DOI":"10.1029\/95JD02165","article-title":"Modeling of land surface evaporation by four schemes and comparison with FIFE observations","volume":"101","author":"Chen","year":"1996","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_59","first-page":"163","article-title":"Basic laws of turbulent mixing in the surface layer of the atmosphere","volume":"24","author":"Monin","year":"1954","journal-title":"Tr. Akad. Nauk. SSSR Geophiz. Inst."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1175\/JHM538.1","article-title":"Effects of Frozen Soil on Snowmelt Runoff and Soil Water Storage at a Continental Scale","volume":"7","author":"Niu","year":"2006","journal-title":"J. Hydrometeorol."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Niu, G.-Y., and Yang, Z.-L. (2004). Effects of vegetation canopy processes on snow surface energy and mass balances. J. Geophys. Res. Atmos., 109.","DOI":"10.1029\/2004JD004884"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2002JD003118","DOI":"10.1029\/2002JD003118","article-title":"Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project","volume":"108","author":"Cosgrove","year":"2003","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Shepard, D. (1968, January 27\u201329). A two-dimensional interpolation function for irregularly-spaced data. Proceedings of the 1968 23rd ACM national conference, Las Vegas, NV, USA.","DOI":"10.1145\/800186.810616"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1919","DOI":"10.5194\/nhess-18-1919-2018","article-title":"Application of a physically based model to forecast shallow landslides at a regional scale","volume":"18","author":"Salvatici","year":"2018","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1923","DOI":"10.2307\/1941547","article-title":"Mission to Planet Earth: The Ecological Perspective","volume":"72","author":"Wickland","year":"1991","journal-title":"Ecology"},{"key":"ref_66","unstructured":"Lumbreras, J.F., and Gomes, J.B.V. (2004). Atualiza\u00e7\u00e3o do Levantamento Semidetalhado de Solos do Munic\u00edpio do Rio de Janeiro, RJ. Mapeamento Pedol\u00f3gico e Interpreta\u00e7\u00f5es \u00dateis ao Planejamento Ambiental do Munic\u00edpio do Rio de Janeiro, Embrapa Solos."},{"key":"ref_67","unstructured":"Soil Survey Staff (2014). Keys to Soil Taxonomy."},{"key":"ref_68","unstructured":"(2017). Soil Science Division Staff Soil Survey Manual, USDA Handbook 18."},{"key":"ref_69","unstructured":"Embrapa (2004). Mapeamento Pedol\u00f3gico e Interpreta\u00e7\u00f5es \u00dateis ao Planejamento Ambiental do Munic\u00edpio do Rio de Janeiro, Embrapa."},{"key":"ref_70","unstructured":"(2020, November 17). GEORIO Rio de Janeiro City Landslide Susceptibility Map. Available online: https:\/\/www.data.rio\/app\/suscetibilidade-a-deslizamentos."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1002\/2016JD025418","article-title":"Ground validation of GPM IMERG and TRMM 3B42V7 rainfall products over southern Tibetan Plateau based on a high-density rain gauge network","volume":"122","author":"Xu","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Jiang, Q., Li, W., Wen, J., Qiu, C., Sun, W., Fang, Q., Xu, M., and Tan, J. (2018). Accuracy Evaluation of Two High-Resolution Satellite-Based Rainfall Products: TRMM 3B42V7 and CMORPH in Shanghai. Water, 10.","DOI":"10.3390\/w10010040"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Arsenault, K.R., Shukla, S., Hazra, A., Getirana, A., McNally, A., Kumar, S.V., Koster, R.D., Peters-Lidard, C.D., Zaitchik, B.F., and Badr, H. (2020). The NASA hydrological forecast system for food and water security applications. Bull. Am. Meteorol. Soc.","DOI":"10.1175\/BAMS-D-18-0264.1"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1175\/JHM-D-19-0096.1","article-title":"GRACE Improves Seasonal Groundwater Forecast Initialization over the United States","volume":"21","author":"Getirana","year":"2020","journal-title":"J. Hydrometeorol."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Li, B., Rodell, M., Kumar, S., Beaudoing, H.K., Getirana, A., Zaitchik, B.F., Goncalves, L.G., Cossetin, C., Bhanja, S., and Mukherjee, A. (2019). Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges. Water Resour. Res., 1\u201323.","DOI":"10.1029\/2018WR024618"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1175\/1520-0477-83.8.1181","article-title":"THE DROUGHT MONITOR","volume":"83","author":"Svoboda","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1175\/2010WAF2222325.1","article-title":"Combining TRMM and Surface Observations of Precipitation: Technique and Validation over South America","volume":"25","author":"Rozante","year":"2010","journal-title":"Weather Forecast."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"2387","DOI":"10.1002\/2018JD028377","article-title":"Evaluation of the WRF-Urban Modeling System Coupled to Noah and Noah-MP Land Surface Models Over a Semiarid Urban Environment","volume":"123","author":"Salamanca","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1002\/wrcr.20067","article-title":"Large-scale hydrologic and hydrodynamic modeling of the Amazon River basin","volume":"49","author":"Paiva","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"3416","DOI":"10.3390\/s7123416","article-title":"Satellite-based Flood Modeling Using TRMM-based Rainfall Products","volume":"7","author":"Harris","year":"2007","journal-title":"Sensors"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Schumann, G.J., Bates, P.D., Apel, H., and Aronica, G.T. (2018). Rainfall Information for Global Flood Modeling. Global Flood Hazard: Applications in Modeling, Mapping, and Forecasting, American Geophysical Union.","DOI":"10.1002\/9781119217886"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/24\/4095\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:45:26Z","timestamp":1760179526000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/24\/4095"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,15]]},"references-count":81,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["rs12244095"],"URL":"https:\/\/doi.org\/10.3390\/rs12244095","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,15]]}}}