Global BROOK90 R Package: An Automatic Framework to Simulate the Water Balance at Any Location
暂无分享,去创建一个
[1] Steffen Fritz,et al. Copernicus Global Land Service: Land Cover 100m: version 3 Globe 2015-2019: Validation Report , 2020 .
[2] F. Brissette,et al. Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America , 2020 .
[3] Nandin-Erdene Tsendbazar,et al. Copernicus Global Land Cover Layers - Collection 2 , 2020, Remote. Sens..
[4] B. Arheimer,et al. Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation , 2020 .
[5] J. Bhate,et al. Comparison of Reanalysis Data Sets to Comprehend the Evolution of Tropical Cyclones Over North Indian Ocean , 2020, Earth and Space Science.
[6] P. Salamon,et al. GloFAS-ERA5 operational global river discharge reanalysis 1979–present , 2020, Earth System Science Data.
[7] Peter Berg,et al. Evaluation of precipitation datasets against local observations in southwestern Iran , 2020, International Journal of Climatology.
[8] N. Verhoest,et al. Evaluating the surface energy partitioning in ERA5 , 2020 .
[9] Decision Support Methods for Assessing Flood Risk and Vulnerability , 2020, Advances in Environmental Engineering and Green Technologies.
[10] Ismail Elhassnaoui,et al. Hydrologic Modeling Using SWAT , 2020 .
[11] Cyrus Samimi,et al. Evaluation needs and temporal performance differences of gridded precipitation products in peripheral mountain regions , 2019, Scientific Reports.
[12] Ehsan Sharifi,et al. Performance of the State-Of-The-Art Gridded Precipitation Products over Mountainous Terrain: A Regional Study over Austria , 2019, Remote. Sens..
[13] F. Doblas-Reyes,et al. What global reanalysis best represents near‐surface winds? , 2019, Quarterly Journal of the Royal Meteorological Society.
[14] E. Sudicky,et al. Evaluation of variability among different precipitation products in the Northern Great Plains , 2019, Journal of Hydrology: Regional Studies.
[15] V. L. Mulder,et al. The effect of disaggregating soil data for estimating soil hydrological parameters at different scales , 2019, Geoderma.
[16] A. Teucher. Look Up Time Zones of Point Coordinates [R package lutz version 0.3.1] , 2019 .
[17] V. Jetten,et al. Sensitivity of flood dynamics to different soil information sources in urbanized areas , 2019, Journal of Hydrology.
[18] Abdou Khouakhi,et al. Using R in hydrology: a review of recent developments and future directions , 2019, Hydrology and Earth System Sciences.
[19] Yongjiu Dai,et al. A review of the global soil property maps for Earth system models , 2019, SOIL.
[20] C. Allen,et al. A Validation of ERA5 Reanalysis Data in the Southern Antarctic Peninsula—Ellsworth Land Region, and Its Implications for Ice Core Studies , 2019, Geosciences.
[21] Abdou Khouakhi,et al. Using R in hydrology: a review of recent developments and future directions , 2019, Hydrology and Earth System Sciences.
[22] F. Brissette,et al. Evaluation of the ERA 5 reanalysis as a potential reference dataset for hydrological modeling over North-America , 2019 .
[23] S. Fritz,et al. Developing and applying a multi-purpose land cover validation dataset for Africa , 2018, Remote Sensing of Environment.
[24] S. Uhlenbrook,et al. Improved Process Representation in the Simulation of the Hydrology of a Meso-Scale Semi-Arid Catchment , 2018, Water.
[25] P. de Rosnay,et al. ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better? , 2018, Hydrology and Earth System Sciences.
[26] N. Hanan,et al. HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling , 2018, Scientific Data.
[27] Guillaume Thirel,et al. Continuous state-space representation of a bucket-type rainfall-runoff model: a case study with the GR4 model using state-space GR4 (version 1.0) , 2018 .
[28] Ana M. Gracia-Amillo,et al. Evaluation of global horizontal irradiance estimates from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based data , 2018 .
[29] Fang Zhao,et al. Human impact parameterizations in global hydrological models improve estimates of monthly discharges and hydrological extremes: a multi-model validation study , 2018 .
[30] A. Gessler,et al. Responses of the structure and function of the understory plant communities to precipitation reduction across forest ecosystems in Germany , 2017, Annals of Forest Science.
[31] Bin Zhao,et al. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). , 2017, Journal of climate.
[32] Marvin N. Wright,et al. SoilGrids250m: Global gridded soil information based on machine learning , 2017, PloS one.
[33] U. Vilhar. Comparison of drought stress indices in beech forests: a modelling study , 2016 .
[34] Tim R. McVicar,et al. Global‐scale regionalization of hydrologic model parameters , 2016 .
[35] Beck Hylke,et al. Global-scale regionalization of hydrologic model parameters , 2016 .
[36] A. D. Roo,et al. Global evaluation of runoff from ten state-of-the-art hydrological models , 2016 .
[37] Roger Bivand,et al. Bindings for the Geospatial Data Abstraction Library , 2015 .
[38] Robert J. Hijmans,et al. Geographic Data Analysis and Modeling , 2015 .
[39] Colin W. Rundel,et al. Interface to Geometry Engine - Open Source (GEOS) , 2015 .
[40] H. Wickham. Simple, Consistent Wrappers for Common String Operations , 2015 .
[41] Aditya Sood,et al. Global hydrological models: a review , 2015 .
[42] J. Křeček,et al. Comparing the impacts of mature spruce forests and grasslands on snow melt, water resource recharge, and run-off in the northern boreal environment , 2015, International Soil and Water Conservation Research.
[43] Y. Ban,et al. China: Open access to Earth land-cover map , 2014, Nature.
[44] Keith Loague,et al. Hydrologic‐response simulations for the North Fork of Caspar Creek: second‐growth, clear‐cut, new‐growth, and cumulative watershed effect scenarios , 2014 .
[45] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[46] G. Chi. Applied Spatial Data Analysis with R , 2015 .
[47] L. Alfieri,et al. GloFAS – global ensemble streamflow forecasting and flood early warning , 2012 .
[48] R. Koster,et al. Assessment and Enhancement of MERRA Land Surface Hydrology Estimates , 2011 .
[49] M. Ek,et al. Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water , 2011 .
[50] Hadley Wickham,et al. Dates and Times Made Easy with lubridate , 2011 .
[51] Hadley Wickham,et al. The Split-Apply-Combine Strategy for Data Analysis , 2011 .
[52] Yayoi Harada,et al. The Japanese 55-year Reanalysis "JRA-55": An Interim Report , 2011 .
[53] Uang,et al. The NCEP Climate Forecast System Reanalysis , 2010 .
[54] Hoshin Vijai Gupta,et al. Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling , 2009 .
[55] B. Hurk,et al. A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System , 2009 .
[56] Keith W. Oleson,et al. Simulation of Global Land Surface Conditions from 1948 to 2004. Part I: Forcing Data and Evaluations , 2006 .
[57] B. Rudolf,et al. World Map of the Köppen-Geiger climate classification updated , 2006 .
[58] A. Belward,et al. GLC2000: a new approach to global land cover mapping from Earth observation data , 2005 .
[59] R. B. Jackson,et al. A global analysis of root distributions for terrestrial biomes , 1996, Oecologia.
[60] L. O. Safford. Effect of fertilization on biomass and nutrient content of fine roots in a beech-birch-maple stand , 1974, Plant and Soil.
[61] Balázs M. Fekete,et al. Sensitivity of Annual Evaporation to Soil and Root Properties in Two Models of Contrasting Complexity , 2003 .
[62] P. Döll,et al. A global hydrological model for deriving water availability indicators: model tuning and validation , 2003 .
[63] Wolfgang Grabs,et al. High‐resolution fields of global runoff combining observed river discharge and simulated water balances , 2002 .
[64] Keith W. Oleson,et al. Landscapes as patches of plant functional types: An integrating concept for climate and ecosystem models , 2002 .
[65] C. Körner,et al. Leaf Diffusive Conductances in the Major Vegetation Types of the Globe , 1995 .
[66] P. Bougeault,et al. Cloud-Ensemble Relations Based on the Gamma Probability Distribution for the Higher-Order Models of the Planetary Boundary Layer , 1982 .
[67] D. Malcolm,et al. The Plant Root and Its Environment. , 1975 .
[68] L. O. Safford,et al. Biomass of Fine Roots in a White Spruce Plantation , 1972 .
[69] J. Nash,et al. River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .