Journal ArticleDOI
A comprehensive assessment of water storage dynamics and hydroclimatic extremes in the Chao Phraya River Basin during 2002–2020
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TLDR
In this paper, the water storage dynamics and extremes in the basin during 2002-2020 were quantified, for the first time, using GRACE (Follow-On) based terrestrial water storage anomaly (TWSA) with the help of a novel artificial neural network-based model for the data gap filling.About:
This article is published in Journal of Hydrology.The article was published on 2021-12-01. It has received 42 citations till now. The article focuses on the topics: Water storage & Drainage basin.read more
Citations
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Journal ArticleDOI
Spatial Downscaling of GRACE Data Based on XGBoost Model for Improved Understanding of Hydrological Droughts in the Indus Basin Irrigation System (IBIS)
Shoaib Ali,Behnam Khorrami,Muhammad Jehanzaib,Aqil Tariq,Mohammad Ajmal,Arfan Arshad,Muhammad Shafeeque,Adil Dilawar,Iqra Basit,Liangliang Zhang,Sam Sadri,Muhammad Ahmad Niaz,A.H.M. Nasimul Jamil,Shahid Nawaz Khan +13 more
TL;DR: In this article , the authors employed machine learning models such as Extreme Gradient Boosting (XGBoost) and Artificial Neural Network (ANN) to downscale GRACE TWSA from 1° to 0.25°.
Journal ArticleDOI
Multidecadal Land Water and Groundwater Drought Evaluation in Peninsular India
Abhishek,Tsuyoshi Kinouchi +1 more
TL;DR: In this article , the authors used the GRACE gravity data, PCR-GLOBWB model outputs and in situ data to quantify the deficits based on land water storage (LWS) and groundwater storage (GWS) in Peninsular India for 35 years from January 1980 to December 2014.
Journal ArticleDOI
Annual runoff coefficient variation in a changing environment: a global perspective
TL;DR: In this article , the authors combine observation-based runoff and precipitation datasets to quantify basin-averaged RC changes in 433 major global river basins during the period 1985-2014.
Journal ArticleDOI
Leveraging machine learning methods to quantify 50 years of dwindling groundwater in India.
TL;DR: In this article , the state-wise past (2000-2020) and future (2030-2050) assessment of dwindling groundwater in India utilizing in-situ groundwater levels (GWL) from 54,112 wells, remote sensing products, and hydrological simulations was provided.
Journal ArticleDOI
A framework for quantifying climate-informed heavy rainfall change: Implications for adaptation strategies.
TL;DR: In this article , a conditional artificial neural network (CANN) model is employed for temporal disaggregation to obtain the monthly maximum of 1 hourly rainfall in the future periods and subsequently, a zero-inflated generalized extreme value function (ZIGEV) is applied for extreme value analysis (EVA) to obtain rainfall intensity with different return periods.
References
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The ERA5 global reanalysis
Hans Hersbach,Bill Bell,Paul Berrisford,Shoji Hirahara,András Horányi,Joaquín Muñoz-Sabater,Julien Nicolas,Carole Peubey,Raluca Radu,Dinand Schepers,Adrian Simmons,Cornel Soci,Saleh Abdalla,Xavier Abellan,Gianpaolo Balsamo,Peter Bechtold,Gionata Biavati,Jean Bidlot,Massimo Bonavita,Giovanna de Chiara,Per Dahlgren,Dick Dee,Michail Diamantakis,Rossana Dragani,Johannes Flemming,Richard G. Forbes,Manuel Fuentes,Alan J. Geer,Leo Haimberger,Sean Healy,Robin J. Hogan,Elías Hólm,Marta Janisková,Sarah Keeley,Patrick Laloyaux,Philippe Lopez,Cristina Lupu,Gabor Radnoti,Patricia de Rosnay,Iryna Rozum,Freja Vamborg,Sebastien Villaume,Jean-Noël Thépaut +42 more
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The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)
Ronald Gelaro,Will McCarty,Max J. Suarez,Max J. Suarez,Ricardo Todling,Andrea Molod,Lawrence L. Takacs,Cynthia A. Randles,Cynthia A. Randles,Anton Darmenov,Michael G. Bosilovich,Rolf H. Reichle,Krzysztof Wargan,Lawrence Coy,Richard I. Cullather,Richard I. Cullather,Clara S. Draper,Clara S. Draper,Santha Akella,V. Buchard,V. Buchard,Austin Conaty,Arlindo da Silva,Wei Gu,Gi-Kong Kim,Randal D. Koster,Robert A. Lucchesi,Dagmar Merkova,J. E. Nielsen,Gary Partyka,Steven Pawson,William M. Putman,Michele M. Rienecker,Siegfried D. Schubert,Meta Sienkiewicz,Bin Zhao,Bin Zhao +36 more
TL;DR: An overview of the MERRA-2 system and various performance metrics is provided, including the assimilation of aerosol observations, several improvements to the representation of the stratosphere including ozone, and improved representations of cryospheric processes.
Journal ArticleDOI
The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.
Chris Funk,Pete Peterson,Martin Landsfeld,Diego Pedreros,James P. Verdin,Shraddhanand Shukla,Gregory Husak,James Rowland,Laura Harrison,Andrew Hoell,Joel Michaelsen +10 more
TL;DR: The Variable Infiltration Capacity model, a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights, is presented and it is shown that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.
Journal ArticleDOI
GLEAM v3: satellite-based land evaporation and root-zone soil moisture
Brecht Martens,Diego G. Miralles,Diego G. Miralles,Hans Lievens,Hans Lievens,Robin van der Schalie,Richard de Jeu,Diego Fernández-Prieto,Hylke E. Beck,Wouter Dorigo,Wouter Dorigo,Niko E. C. Verhoest +11 more
TL;DR: The Global Land Evaporation Amsterdam Model (GLEAM) as discussed by the authors is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data.