{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T16:07:01Z","timestamp":1783008421636,"version":"3.54.5"},"reference-count":51,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,5,7]],"date-time":"2023-05-07T00:00:00Z","timestamp":1683417600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["522031511"],"award-info":[{"award-number":["522031511"]}]},{"name":"National Natural Science Foundation of China","award":["51879067"],"award-info":[{"award-number":["51879067"]}]},{"name":"National Natural Science Foundation of China","award":["52009028"],"award-info":[{"award-number":["52009028"]}]},{"name":"National Natural Science Foundation of China","award":["B220202029"],"award-info":[{"award-number":["B220202029"]}]},{"name":"National Natural Science Foundation of China","award":["B220204014"],"award-info":[{"award-number":["B220204014"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["522031511"],"award-info":[{"award-number":["522031511"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["51879067"],"award-info":[{"award-number":["51879067"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["52009028"],"award-info":[{"award-number":["52009028"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["B220202029"],"award-info":[{"award-number":["B220202029"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["B220204014"],"award-info":[{"award-number":["B220204014"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rainfall-triggered flood and landslide hazards pose significant threats to human lives and infrastructure worldwide. This study aims to evaluate the applicability of three satellite rainfall data sets\u2014namely, CMORPH, GPM, and TRMM\u2014for the prediction of flood and landslide hazards using a coupled hydrological-slope stability model. The spatial distribution of annual rainfall from the three satellite data sets was similar to that of gauge rainfall, with an increasing trend from the north to the south of Shaanxi Province. The average annual rainfall of CMORPH was the lowest, while that of TRMM was the highest. The modeled discharges forcing by satellite rainfall generally matched the observed discharges at four hydrological stations for the period 2010\u20132012, with average correlation coefficients of 0.51, 0.61, and 0.57 for the CMORPH, GPM, and TRMM rainfall, respectively. The exceedance probabilities of modeled discharges for the three satellite rainfall data sets were close to those of the observations, particularly when the discharges were low. Moreover, the landslide prediction results demonstrated that the three satellite rainfall data sets could simulate the spatial distribution of landslide events well; these simulations were consistent with the information in the landslide inventory map. Furthermore, when compared to the classical Intensity-Duration (ID) rainfall threshold method, the physically based slope stability model presented higher global accuracy under all three satellite rainfall data sets. The global accuracy of GPM rainfall was the highest among the three data sets (0.973 for GPM vs. 0.951 for CMORPH and 0.965 for TRMM), indicating that GPM rainfall provides the highest quality compared to CMORPH and TRMM rainfall. These findings provide a crucial basis for the application of satellite rainfall data in the context of flood and landslide prediction.<\/jats:p>","DOI":"10.3390\/rs15092457","type":"journal-article","created":{"date-parts":[[2023,5,8]],"date-time":"2023-05-08T02:03:31Z","timestamp":1683511411000},"page":"2457","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Investigating the Feasibility of Using Satellite Rainfall for the Integrated Prediction of Flood and Landslide Hazards over Shaanxi Province in Northwest China"],"prefix":"10.3390","volume":"15","author":[{"given":"Sheng","family":"Wang","sequence":"first","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China"},{"name":"Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210024, China"},{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5288-9372","authenticated-orcid":false,"given":"Ke","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China"},{"name":"Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210024, China"},{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210024, China"},{"name":"China Meteorological Administration Hydro-Meteorology Key Laboratory, Nanjing 210024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lijun","family":"Chao","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China"},{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210024, China"},{"name":"China Meteorological Administration Hydro-Meteorology Key Laboratory, Nanjing 210024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoding","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China"},{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Xia","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China"},{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuntang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China"},{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.envsoft.2016.08.009","article-title":"Development of time-variant landslide-prediction software considering three-dimensional subsurface unsaturated flow","volume":"85","author":"An","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.jseaes.2017.08.031","article-title":"Evolution of a giant debris flow in the transitional mountainous region between the Tibetan Plateau and the Qinling Mountain range, Western China: Constraints from broadband seismic records","volume":"148","author":"Huang","year":"2017","journal-title":"J. Asian Earth Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.neucom.2013.10.044","article-title":"Deformation prediction of landslide based on functional network","volume":"149","author":"Chen","year":"2015","journal-title":"Neurocomputing"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"93","DOI":"10.5194\/nhess-19-93-2019","article-title":"Characteristics and influencing factors of rainfall-induced landslide and debris flow hazards in Shaanxi Province, China","volume":"19","author":"Zhang","year":"2019","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_5","unstructured":"Burnash, R.J., Ferral, R.L., and McGuire, R.A. (1973). A Generalized Streamflow Simulation System: Conceptual Modeling for Digital Computers."},{"key":"ref_6","unstructured":"Crawford, N.H., and Linsley, R.K. (1966). Digital Simulation in Hydrology\u2019Stanford Watershed Model 4, Stanford University. Technical Report."},{"key":"ref_7","unstructured":"Sugawara, M., Watanabe, I., Ozaki, E., and Katsugama, Y. (1984). Tank Model with Snow Component, Science and Technolgoy. Research Notes of the National Research Center for Disaster Prevention No. 65."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1080\/02626667909491834","article-title":"A physically based, variable contributing area model of basin hydrology\/Un mod\u00e8le \u00e0 base physique de zone d\u2019appel variable de l\u2019hydrologie du bassin versant","volume":"24","author":"BEVEN","year":"1979","journal-title":"Hydrol. Sci. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2559","DOI":"10.1029\/97WR02186","article-title":"A generalized power function for the subsurface transmissivity profile in TOPMODEL","volume":"33","author":"Duan","year":"1997","journal-title":"Water Resour. Res."},{"key":"ref_10","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 Europeen, \u201cSHE\u201d, 1: History and philosophy of a physically-based, distributed modelling system","volume":"87","author":"Abbott","year":"1986","journal-title":"J. Hydrol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e2079","DOI":"10.1002\/met.2079","article-title":"Hydrometeorological analysis of a flash flood event in an ungauged Mediterranean watershed under an operational forecasting and monitoring context","volume":"29","author":"Giannaros","year":"2022","journal-title":"Meteorol. Appl."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Quenum, G.M.L.D., Arnault, J., Klutse, N.A.B., Zhang, Z., Kunstmann, H., and Oguntunde, P.G. (2022). Potential of the coupled WRF\/WRF-hydro modeling system for flood forecasting in the Ou\u00e9m\u00e9 River (West Africa). Water, 14.","DOI":"10.3390\/w14081192"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1144\/GSL.QJEG.1997.030.P4.02","article-title":"Geology for engineers: The geological model, prediction and performance","volume":"30","author":"Fookes","year":"1997","journal-title":"Q. J. Eng. Geol. Hydrogeol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1007\/s002679910020","article-title":"Comparing Landslide Maps: A Case Study in the Upper Tiber River Basin, Central Italy","volume":"25","author":"Guzzetti","year":"2000","journal-title":"Environ. Manag."},{"key":"ref_15","unstructured":"Griffiths, J.S. (2002). Mapping in Engineering Geology, Geological Society of London."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1007\/s000240050017","article-title":"Applying probability determination to refine landslide-triggering rainfall thresholds using an empirical \u201cAntecedent Daily Rainfall Model\u201d","volume":"157","author":"Glade","year":"2000","journal-title":"Pure Appl. Geophys."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10346-007-0112-1","article-title":"The rainfall intensity\u2013duration control of shallow landslides and debris flows: An update","volume":"5","author":"Guzzetti","year":"2008","journal-title":"Landslides"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"31","DOI":"10.5194\/nhess-18-31-2018","article-title":"Hydrological perspectives on precipitation intensity-duration thresholds for a landslide initiation: Proposing hydro-meteorological thresholds","volume":"18","author":"Bogaard","year":"2018","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.5194\/nhess-8-1149-2008","article-title":"A model for triggering mechanisms of shallow landslides","volume":"8","author":"Montrasio","year":"2008","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1007\/s10346-010-0219-7","article-title":"Prototyping an experimental early warning system for rainfall-induced landslides in Indonesia using satellite remote sensing and geospatial datasets","volume":"7","author":"Liao","year":"2010","journal-title":"Landslides"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"5035","DOI":"10.5194\/hess-20-5035-2016","article-title":"iCRESTRIGRS: A coupled modeling system for cascading flood\u2013landslide disaster forecasting","volume":"20","author":"Zhang","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"104607","DOI":"10.1016\/j.envsoft.2019.104607","article-title":"Physically-based landslide prediction over a large region: Scaling low-resolution hydrological model results for high-resolution slope stability assessment","volume":"124","author":"Wang","year":"2020","journal-title":"Environ. Model. Softw."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.jhydrol.2016.10.016","article-title":"Development of a coupled hydrological-geotechnical framework for rainfall-induced landslides prediction","volume":"543","author":"He","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.jhydrol.2003.10.005","article-title":"Systematic correction of precipitation gauge observations using analyzed meteorological variables","volume":"290","author":"Michelson","year":"2004","journal-title":"J. Hydrol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2009WR008328","article-title":"Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors","volume":"46","author":"Renard","year":"2010","journal-title":"Water Resour. Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1933","DOI":"10.1175\/JHM-D-13-040.1","article-title":"Correction of radar QPE errors associated with low and partially observed brightband layers","volume":"14","author":"Qi","year":"2013","journal-title":"J. Hydrometeorol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1175\/1520-0450(1997)036<1176:PEFRSI>2.0.CO;2","article-title":"Precipitation estimation from remotely sensed information using artificial neural networks","volume":"36","author":"Hsu","year":"1997","journal-title":"J. Appl. Meteorol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Alahacoon, N., Matheswaran, K., Pani, P., and Amarnath, G. (2018). A decadal historical satellite data and rainfall trend analysis (2001\u20132016) for flood hazard mapping in Sri Lanka. Remote Sens., 10.","DOI":"10.3390\/rs10030448"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1758","DOI":"10.3390\/rs70201758","article-title":"Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique","volume":"7","author":"Patricio","year":"2015","journal-title":"Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Adane, G.B., Hirpa, B.A., Lim, C.-H., and Lee, W.-K. (2021). Evaluation and comparison of satellite-derived estimates of rainfall in the diverse climate and terrain of central and northeastern Ethiopia. Remote Sens., 13.","DOI":"10.3390\/rs13071275"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1175\/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2","article-title":"The tropical rainfall measuring mission (TRMM) sensor package","volume":"15","author":"Kummerow","year":"1998","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_32","first-page":"1","article-title":"The global satellite mapping of precipitation (GSMaP) project","volume":"2004","author":"Ushio","year":"2003","journal-title":"Aqua AMSR-E"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1175\/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2","article-title":"CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution","volume":"5","author":"Joyce","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_34","first-page":"1","article-title":"NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG)","volume":"4","author":"Huffman","year":"2015","journal-title":"Algorithm Theor. Basis Doc. ATBD Version"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"D06012","DOI":"10.1029\/2004JD005301","article-title":"Improved representation of diurnal variability of rainfall retrieved from the Tropical Rainfall Measurement Mission microwave imager adjusted Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) system","volume":"110","author":"Hong","year":"2005","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1175\/1520-0493(1978)106<1153:REFGSI>2.0.CO;2","article-title":"Rain estimation from geosynchronous satellite imagery\u2014Visible and infrared studies","volume":"106","author":"Griffith","year":"1978","journal-title":"Mon. Weather Rev."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.atmosres.2019.03.001","article-title":"Evaluation of the TRMM 3B42 and GPM IMERG products for extreme precipitation analysis over China","volume":"223","author":"Fang","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Yu, L., Leng, G., Python, A., and Peng, J. (2021). A comprehensive evaluation of latest GPM IMERG V06 early, late and final precipitation products across China. Remote Sens., 13.","DOI":"10.3390\/rs13061208"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"D02114","DOI":"10.1029\/2009JD012097","article-title":"Performance of high-resolution satellite precipitation products over China","volume":"115","author":"Shen","year":"2010","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Getirana, A., Kirschbaum, D., Mandarino, F., Ottoni, M., Khan, S., and Arsenault, K. (2020). Potential of GPM IMERG precipitation estimates to monitor natural disaster triggers in urban areas: The case of Rio de Janeiro, Brazil. Remote Sens., 12.","DOI":"10.3390\/rs12244095"},{"key":"ref_41","unstructured":"Krige, D.G. (1951). A Statistical Approach to Some Mine Valuation and Allied Problems on the Witwatersrand: By DG Krige, University of the Witwatersrand."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1175\/BAMS-85-3-381","article-title":"The global land data assimilation system","volume":"85","author":"Rodell","year":"2004","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1029\/2008EO100001","article-title":"New global hydrography derived from spaceborne elevation data","volume":"89","author":"Lehner","year":"2008","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_44","unstructured":"Wieder, W., Boehnert, J., Bonan, G., and Langseth, M. (2014, September 15). Regridded Harmonized World Soil Database v1. 2. ORNL DAAC, Available online: https:\/\/daac.ornl.gov\/SOILS\/guides\/HWSD.html."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.isprsjprs.2014.09.002","article-title":"Global land cover mapping at 30 m resolution: A POK-based operational approach","volume":"103","author":"Chen","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_46","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_47","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1007\/s11431-008-6009-y","article-title":"Effects of raster resolution on landslide susceptibility mapping: A case study of Shenzhen","volume":"51","author":"Tian","year":"2008","journal-title":"Sci. China Ser. E Technol. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"101542","DOI":"10.1016\/j.gsf.2023.101542","article-title":"Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China","volume":"14","author":"Guo","year":"2023","journal-title":"Geosci. Front."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3119","DOI":"10.1007\/s10346-021-01689-3","article-title":"Can global rainfall estimates (satellite and reanalysis) aid landslide hindcasting?","volume":"18","author":"Ozturk","year":"2021","journal-title":"Landslides"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.jhydrol.2018.01.042","article-title":"Geographically weighted regression based methods for merging satellite and gauge precipitation","volume":"558","author":"Chao","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1016\/j.jhydrol.2017.11.050","article-title":"Comprehensive evaluation of ensemble multi-satellite precipitation dataset using the dynamic bayesian model averaging scheme over the Tibetan Plateau","volume":"556","author":"Ma","year":"2018","journal-title":"J. Hydrol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/9\/2457\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:30:52Z","timestamp":1760124652000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/9\/2457"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,7]]},"references-count":51,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2023,5]]}},"alternative-id":["rs15092457"],"URL":"https:\/\/doi.org\/10.3390\/rs15092457","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,7]]}}}