Lista de obras -

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions.

artículo científico publicado en 2016

Benchmarking of a Physically Based Hydrologic Model

article by Andrew J. Newman et al published August 2017 in Journal of Hydrometeorology

Caravan - A global community dataset for large-sample hydrology

conference paper presented et EGU2023

Deep learning rainfall–runoff predictions of extreme events

scientific article published in 2022

Flood forecasting with machine learning models in an operational framework

scientific article published in 2022

Global prediction of extreme floods in ungauged watersheds

artículo científico publicado en 2024

Hybrid forecasting: using statistics and machine learning to integrate predictions from dynamical models

In Defense of Metrics: Metrics Sufficiently Encode Typical Human Preferences Regarding Hydrological Model Performance

Information Theory for Model Diagnostics: Structural Error is Indicated by Trade‐Off Between Functional and Predictive Performance

scientific article published in 2019

Model representation of the coupling between evapotranspiration and soil water content at different depths

artículo científico publicado en 2020

NeuralHydrology — A Python library for Deep Learning research in hydrology

Nonparametric triple collocation

artículo científico publicado en 2017

Peeking Inside Hydrologists' Minds: Comparing Human Judgment and Quantitative Metrics of Hydrographs

conference paper presented at EGU23

Performance Metrics, Error Modeling, and Uncertainty Quantification

article by Yudong Tian et al published February 2016 in Monthly Weather Review

Quantifying Process Connectivity With Transfer Entropy in Hydrologic Models

artículo científico publicado en 2019

Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks

Ten simple rules to cultivate transdisciplinary collaboration in data science

artículo científico publicado en 2021

The Efficiency of Data Assimilation

scientific article published on 17 July 2018

The Impact of Vertical Measurement Depth on the Information Content of Soil Moisture for Latent Heat Flux Estimation

artículo científico publicado en 2016

The persistence of errors: How evaluating models over data partitions relates to a global evaluation

conference paper presented et EGU2023

The plumbing of land surface models: is poor performance a result of methodology or data quality?

artículo científico publicado en 2016

Towards flood warnings everywhere - data-driven rainfall-runoff modeling at global scale

conference paper presented et EGU2023

Lista de obras de

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions.

Benchmarking of a Physically Based Hydrologic Model

Caravan - A global community dataset for large-sample hydrology

Deep learning rainfall–runoff predictions of extreme events

Flood forecasting with machine learning models in an operational framework

Global prediction of extreme floods in ungauged watersheds

Hybrid forecasting: using statistics and machine learning to integrate predictions from dynamical models

In Defense of Metrics: Metrics Sufficiently Encode Typical Human Preferences Regarding Hydrological Model Performance

Information Theory for Model Diagnostics: Structural Error is Indicated by Trade‐Off Between Functional and Predictive Performance

Model representation of the coupling between evapotranspiration and soil water content at different depths

NeuralHydrology — A Python library for Deep Learning research in hydrology

Nonparametric triple collocation

Peeking Inside Hydrologists' Minds: Comparing Human Judgment and Quantitative Metrics of Hydrographs

Performance Metrics, Error Modeling, and Uncertainty Quantification

Quantifying Process Connectivity With Transfer Entropy in Hydrologic Models

Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks

Ten simple rules to cultivate transdisciplinary collaboration in data science

The Efficiency of Data Assimilation

The Impact of Vertical Measurement Depth on the Information Content of Soil Moisture for Latent Heat Flux Estimation

The persistence of errors: How evaluating models over data partitions relates to a global evaluation

The plumbing of land surface models: is poor performance a result of methodology or data quality?

Towards flood warnings everywhere - data-driven rainfall-runoff modeling at global scale