Innovation

Explore our latest innovations

Constant innovation at hydroclimat

By combining advanced environmental impact models with high-resolution climate projections, Hydroclimat give its customers and partners the critical insight they need on climate risks and extreme events.

This valuable data-driven information is used as such to support investment strategies and to design and plan sustainable territorial plans. Reliable and relevant data-driven information is essential for effective operation and decision making at all levels.

The importance of that makes doing continuous research necessary to constantly improve the quality and reliability of the climate, water, and flood data that we provide.

Our internal expertise and the issues that we consider to be decisive on water resources and flooding are pushing us towards innovative efforts in very high spatial resolution numerical hydroclimatology. We cross our technical cutting-edge skills in hydrology, hydraulics, and climate change with artificial intelligence to give our customers efficient solutions allowing informed decision-making on climate risks, long-term water resource planning, and future flood risks.

From the numerous and complex climate change data, as a result, we offer an intelligible and robust vision of the expected climate change impacts at the local scale.

Flooding in Spain

Innovation created by hydroclimat

POP-Risk system

Building on our experience in North America, we combine our expertise in climate change, water resources and flood with technical cutting-edge skills in numerical modeling to develop POP-Risk. Above all, our « Tech For Good » POP-Risk is designed to answer one of the major challenges of the 21st century: Adaptation to Climate Change.

The POP-Risk innovation is a multi-risk modelling system for climate, water resources and flooding, incorporating a chain of impact models for assessing the impacts of climate change.

This innovation has been partially funded by the Government as part of the France Relance programme.

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Logo_France_Relance_vert

We create innovative numerical technology-based solutions that contribute to sustainable development. Most importantly, Hydroclimat makes towards building confidence in climate change risk assessment. Our M3E© proprietary technology is the cornerstone in POP-Risk. M3E© is a disruptive technology qualified as DeepTech by BPI France (French Tech Emergence grant). Indeed, M3E© is at the crossroads of the state-of-the-art research in:

#1

Data science, big data, and AI

#2

Numerical simulation, multi-model, statistical processing, and ensemble systems

#3

Climate science, hydrology, hydraulic, and climate change

#4

Exposure, risk, and vulnerability to climate change

rain-falling-on-the-ground-hydroclimat

Our implication

Our implication in several applied research projects

Industrial Ph.D. Thesis

“Extreme Value Analysis for Hydroclimatology”

Industrial Ph.D. Thesis

“Using satellite remote sensing to better predict and manage floods”

CNRS Post-doctoral researcher project

“Flood forecasting and new technologies”

Industrial Ph.D. Thesis

“Resilience of agriculture to climate change through the development of an operational agronomic decision support tool”

Our scientific publications

We regularly publish research papers

A semi-parametric distribution stitch based on the Berk-Jones test for French daily precipitation bias correction

2025
Ear, P., Di Bernardino, E., Laloë, T. et al.

Optimizing Spatial Discretization According to Input Data in the Soil and Water Assessment Tool: A Case Study in a Coastal Mediterranean Watershed

2025
Puche, M., Troin, M., Fox, D., Royer-Gaspard, P.

Improving multi-model ensemble streamflow forecasts by combining lumped, distributed and deep learning hydrological models

2025
Armstrong, W., Arsenault, R., Martel, J. L., Troin, M., Dion, P., et al. (2025).

Benefits of upstream data for downstream streamflow forecasting: data assimilation in a semi-distributed flood forecasting model

2024
Royer-Gaspard, P., Bourgin, F., Perrin, C., Andréassian, V., De Lavenne, A., Thirel, G., & Tilmant, F.

Evaluation of Five Reanalysis Products over France: Implications for Agro-Climatic Studies.

2024
Er-Rondi, M., Troin, M., Coly, S., Buisson, E., Serlet, L., Azzaoui, N

Comparing a long short-term memory (LSTM) neural network with a physically-based hydrological model for streamflow forecasting over a Canadian catchment

2023
Sabzipour, B., Arsenault, R., Troin, M., Martel, J.-L., Brissette, F., Mai, J.,

CMIP5 and CMIP6 Model Projection Comparison for Hydrological Impacts Over North America. Geophysical Research Letters, 49, e2022GL098364

2022
Martel, J.-L. Brissette, F., Troin, M., et al.

Generating ensemble streamflow forecasts: A review of methods and approaches over the past 40 years. Water Resources Research 57, e2020WR028392.

2021
Troin, M., Arsenault, R., Brissette, F., Martel, J.

Our R&D partners