Diego Avesani

About Diego Avesani

Diego Avesani, With an exceptional h-index of 14 and a recent h-index of 13 (since 2020), a distinguished researcher at Università degli Studi di Trento, specializes in the field of Hydrology, Water Resources Management, Hight Performace Computing, Applied mathematics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region

Can neural networks outperform quantile mapping for post-processing seasonal weather forecast variables over the Alpine region?

A WENO SPH scheme with improved transport velocity and consistent divergence operator

Seasonal Weather Forecast Biases Dependence on Static and Dynamic Environmental Variables in the Alpine Region

Hydrological model calibration in high streamflow extremes climate change studies

Analysis and attribution of the hydrological coherence of gridded precipitation and temperature datasets in the Italian Alpine Region

Time-wise analysis of satellite gravity data and hydrological modeling of a the Po watershed basin and the Alpine divide

Elevation Dependence of Seasonal Precipitation Forecast Biases in the Alpine Region

Diego Avesani Information

University

Position

___

Citations(all)

406

Citations(since 2020)

361

Cited By

107

hIndex(all)

14

hIndex(since 2020)

13

i10Index(all)

16

i10Index(since 2020)

16

Email

University Profile Page

Google Scholar

Diego Avesani Skills & Research Interests

Hydrology

Water Resources Management

Hight Performace Computing

Applied mathematics

Top articles of Diego Avesani

Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region

Journal of Hydrology: Regional Studies

2024/4/1

Can neural networks outperform quantile mapping for post-processing seasonal weather forecast variables over the Alpine region?

2024/3/7

A WENO SPH scheme with improved transport velocity and consistent divergence operator

Computational Particle Mechanics

2023/11/15

Seasonal Weather Forecast Biases Dependence on Static and Dynamic Environmental Variables in the Alpine Region

2023/2/22

Hydrological model calibration in high streamflow extremes climate change studies

EGU General Assembly Conference Abstracts

2023/5

Analysis and attribution of the hydrological coherence of gridded precipitation and temperature datasets in the Italian Alpine Region

EGU General Assembly Conference Abstracts

2023/5

Time-wise analysis of satellite gravity data and hydrological modeling of a the Po watershed basin and the Alpine divide

2023

Elevation Dependence of Seasonal Precipitation Forecast Biases in the Alpine Region

AGU Fall Meeting Abstracts

2022/12

Analysis of high streamflow extremes in climate change studies: How do we calibrate hydrological models?

Hydrology and Earth System Sciences

2022/7/25

On the accurate representation of hydropower systems in large-scale hydrological models

EGU General Assembly Conference Abstracts

2022/5

The role of innovative econometric models in short-term hydropower optimization

EGU General Assembly Conference Abstracts

2022/5

Diego Avesani
Diego Avesani

H-Index: 5

Bruno Majone
Bruno Majone

H-Index: 22

Short-term hydropower optimization driven by innovative time-adapting econometric model

Applied Energy

2022/3/15

HYPERSTREAMHS: UN MODELLO IDROLOGICO CONTINUO BASATO SU UN APPROCCIO MPI-DUAL-LAYER PER UNA MODELLAZIONE A GRANDE SCALA DELLE INFRASTRUTTURE IDRAULICHE

2022

Short term optimization of hydropower production: toward an innovative hydro-econometric modelling framework

2022

Detailed simulation of storage hydropower systems in large Alpine watersheds

Journal of Hydrology

2021/12/1

Towards a high order convergent ALE-SPH scheme with efficient WENO spatial reconstruction

Water

2021/9/4

An alternative SPH formulation: ADER-WENO-SPH

Computer Methods in Applied Mechanics and Engineering

2021/8/15

Diego Avesani
Diego Avesani

H-Index: 5

Renato Vacondio
Renato Vacondio

H-Index: 18

A dual-layer MPI continuous large-scale hydrological model including Human Systems

Environmental Modelling & Software

2021/5/1

Reducing hydrological modelling uncertainty by using MODIS snow cover data and a topography-based distribution function snowmelt model

Journal of Hydrology

2021/8/1

Coping with the Presence of Hydropower Systems in Hydrological Modeling: Development of a Dual-Layer MPI Framework

2021

See List of Professors in Diego Avesani University(Università degli Studi di Trento)