These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

142 related articles for article (PubMed ID: 32611129)

  • 21. Applicability of a nationwide flood forecasting system for Typhoon Hagibis 2019.
    Ma W; Ishitsuka Y; Takeshima A; Hibino K; Yamazaki D; Yamamoto K; Kachi M; Oki R; Oki T; Yoshimura K
    Sci Rep; 2021 May; 11(1):10213. PubMed ID: 33986352
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.
    Liu Y; Xi DG; Li ZL; Ji W
    PLoS One; 2015; 10(10):e0140044. PubMed ID: 26447470
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping.
    Shafizadeh-Moghadam H; Valavi R; Shahabi H; Chapi K; Shirzadi A
    J Environ Manage; 2018 Jul; 217():1-11. PubMed ID: 29579536
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A real-time hourly water index for flood risk monitoring: Pilot studies in Brisbane, Australia, and Dobong Observatory, South Korea.
    Deo RC; Byun HR; Kim GB; Adamowski JF
    Environ Monit Assess; 2018 Jul; 190(8):450. PubMed ID: 29974256
    [TBL] [Abstract][Full Text] [Related]  

  • 25. A robust stochastic approach in correcting the TRMM precipitation product and simulating flood features.
    Asadollah SBHS; Sharafati A; Neshat A; Hemmati N
    Environ Monit Assess; 2022 Apr; 194(5):364. PubMed ID: 35426083
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Incorporation of Satellite Precipitation Uncertainty in a Landslide Hazard Nowcasting System.
    Hartke SH; Wright DB; Kirschbaum DB; Stanley TA; Li Z
    J Hydrometeorol; 2020 Aug; 21(8):1741-1759. PubMed ID: 34054350
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Interconnected hydrologic extreme drivers and impacts depicted by remote sensing data assimilation.
    Lahmers TM; Kumar SV; Locke KA; Wang S; Getirana A; Wrzesien ML; Liu PW; Ahmad SK
    Sci Rep; 2023 Feb; 13(1):3411. PubMed ID: 36854885
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Deep learning models to predict flood events in fast-flowing watersheds.
    Luppichini M; Barsanti M; Giannecchini R; Bini M
    Sci Total Environ; 2022 Mar; 813():151885. PubMed ID: 34826469
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Added value of online satellite data transmission for flood forecasting: warning systems in medium-size catchments.
    Ruch C; Stadler H
    Water Sci Technol; 2009; 59(1):23-9. PubMed ID: 19151482
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Changes in toxicity and Ah receptor agonist activity of suspended particulate matter during flood events at the rivers Neckar and Rhine - a mass balance approach using in vitro methods and chemical analysis.
    Wölz J; Engwall M; Maletz S; Olsman Takner H; van Bavel B; Kammann U; Klempt M; Weber R; Braunbeck T; Hollert H
    Environ Sci Pollut Res Int; 2008 Oct; 15(7):536-53. PubMed ID: 18936997
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Satellite-based Flood Modeling Using TRMM-based Rainfall Products.
    Harris A; Rahman S; Hossain F; Yarborough L; Bagtzoglou AC; Easson G
    Sensors (Basel); 2007 Dec; 7(12):3416-3427. PubMed ID: 28903302
    [TBL] [Abstract][Full Text] [Related]  

  • 32. DroughtCast: A Machine Learning Forecast of the United States Drought Monitor.
    Brust C; Kimball JS; Maneta MP; Jencso K; Reichle RH
    Front Big Data; 2021; 4():773478. PubMed ID: 34993467
    [TBL] [Abstract][Full Text] [Related]  

  • 33. A complex network approach to study the extreme precipitation patterns in a river basin.
    Agarwal A; Guntu RK; Banerjee A; Gadhawe MA; Marwan N
    Chaos; 2022 Jan; 32(1):013113. PubMed ID: 35105108
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Research on classified real-time flood forecasting framework based on K-means cluster and rough set.
    Xu W; Peng Y
    Water Sci Technol; 2015; 71(10):1507-15. PubMed ID: 26442493
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Cyber surveillance for flood disasters.
    Lo SW; Wu JH; Lin FP; Hsu CH
    Sensors (Basel); 2015 Jan; 15(2):2369-87. PubMed ID: 25621609
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Flood hazard mapping using geospatial techniques and satellite images-a case study of coastal district of Tamil Nadu.
    Thirumurugan P; Krishnaveni M
    Environ Monit Assess; 2019 Feb; 191(3):193. PubMed ID: 30810867
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Predictions of extreme precipitation and sea-level rise under climate change.
    Senior CA; Jones RG; Lowe JA; Durman CF; Hudson D
    Philos Trans A Math Phys Eng Sci; 2002 Jul; 360(1796):1301-11. PubMed ID: 12804251
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Future climate scenarios and rainfall--runoff modelling in the Upper Gallego catchment (Spain).
    Bürger CM; Kolditz O; Fowler HJ; Blenkinsop S
    Environ Pollut; 2007 Aug; 148(3):842-54. PubMed ID: 17428594
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Combining Geostatistics and Remote Sensing Data to Improve Spatiotemporal Analysis of Precipitation.
    Varouchakis EA; Kamińska-Chuchmała A; Kowalik G; Spanoudaki K; Graña M
    Sensors (Basel); 2021 Apr; 21(9):. PubMed ID: 33946422
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Rainfall time series disaggregation in mountainous regions using hybrid wavelet-artificial intelligence methods.
    Nourani V; Farboudfam N
    Environ Res; 2019 Jan; 168():306-318. PubMed ID: 30366282
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.