A5074011001- Soil Moisture and Remote Sensing
- Hydrology and Drought Analysis
- Climate variability and models
- Hydrology and Watershed Management Studies
- Advanced Control Systems Optimization
- Iterative Learning Control Systems
- Climate change impacts on agriculture
- Metallurgy and Material Forming
- Water resources management and optimization
- Remote Sensing in Agriculture
- Fault Detection and Control Systems
- Plant Water Relations and Carbon Dynamics
- Hydrological Forecasting Using AI
- Climate Change Policy and Economics
- Plant Ecology and Soil Science
- Plant responses to elevated CO2
- Water-Energy-Food Nexus Studies
- Meteorological Phenomena and Simulations
- Atmospheric chemistry and aerosols
- Precipitation Measurement and Analysis
- Smart Agriculture and AI
- Soil Geostatistics and Mapping
- History of Medicine Studies
- Climate change and permafrost
- Historical and Scientific Studies
Centre National de la Recherche Scientifique
2023-2025
Laboratoire des Sciences du Climat et de l'Environnement
2022-2025
CEA Paris-Saclay
2022-2025
Université de Versailles Saint-Quentin-en-Yvelines
2023-2025
Université Paris-Saclay
2023-2025
Commissariat à l'Énergie Atomique et aux Énergies Alternatives
2022-2025
UK Centre for Ecology & Hydrology
2025
The University of Queensland
2023
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
2023
Institut Pierre-Simon Laplace
2023
Abstract A prolonged drought affected Western Europe and the Mediterranean region in 2022 producing large socio-ecological impacts. The role of anthropogenic climate change (ACC) exacerbating this has been often invoked public debate, but link between atmospheric circulation ACC not received much attention so far. Here we address question by applying method analogs, which allows us to identify patterns period 1836-2021 very similar those occurred 2022. By comparing analogs when global...
Climate change threatens food security by affecting the productivity of major cereal crops. To date, agroclimatic risk projections through indicators have focused on expected hazards exposure during crop's current vulnerable seasons, without considering non-stationarity their phenology under evolving climatic conditions. We propose a new method for spatially classifying risks wheat, combining high-resolution data with wheat's phenological model. The is implemented French wheat involving...
Abstract Climate change, one of the major environmental challenges facing mankind, has caused intermittent droughts in many regions resulting reduced water resources. This study investigated impact climate change on characteristics (occurrence, duration, and severity) meteorological drought across Ankara, Turkey. To this end, observed monthly rainfall series from five meteorology stations scattered Ankara Province as well dynamically downscaled outputs three global models that run under RCP...
Abstract Increasing the awareness of society about climate change by using a simplified way for explanation its impacts might be one key elements to adaptation and mitigation possible effects. This study investigates analogs, which allow possibility find, today, place on land where climatic conditions are similar those that specific area will face in future. The grid‐based calculation analogs over selected European domain was carried out newly proposed distance between multivariate...
Given the increasing vulnerability due to more frequent and severe hydrological hazards under a changing climate, it is imperative develop accurate reliable global local prediction systems at subseasonal-to-seasonal (S2S) timescales. However, operational forecasts tailored specific regions remain limited lack of both observations regional models, while models often calibration for conditions, making challenging them capture local-scale dynamics. Additionally, users decision-makers face...
Drought events significantly challenge communities and ecosystems worldwide, emphasising the urgent need for effective predictive methods to facilitate proactive management mitigate their impacts. A clear gap exists between theoretical drought indices, such as SPI, SPEI, SSMI, real-world impacts of droughts. This study aims address this disparity by leveraging machine learning (ML) techniques predict reported impacts, using data from European Impact Database (EDID). variety ML algorithms,...
This study evaluates the performance of widely-used remotely sensed- and model-based soil moisture products, including: The Advanced Scatterometer (ASCAT), Microwave Scanning Radiometer-Earth Observing System (AMSR-E), European Space Agency Climate Change Initiative (ESA-CCI), Antecedent Precipitation Index (API), Global Land Data Assimilation (GLDAS-NOAH). Evaluations are performed between 2008 2011 against calibrated station-based observations collected by General Directorate Meteorology...
Abstract Linear Model Predictive Control (MPC) has been applied successfully to numerous industrial problems, but its various extensions the nonlinear case have not enjoyed same measure of success. One major obstacles in this development is prohibitive online computation required execute receding horizon minimization predicted cost. This paper combines recent linear techniques, which allow for significant reductions computational load, with Difference Inclusion order apply MPC a rolling mill...
A method of modelling and controlling profile flatness in hot strip tandem rolling mills is described. The for the based on explicit manipulation thickness across its width. controlled by appropriately distributing constraining actuators, so that defects do not occur. Model-based predictive control employed to generate signal each stand co-ordinate stands optimal shape control. Simulation results are presented demonstrate performance proposed co-ordinated scheme.
One of the main objectives in hot strip rolling is to produce which has a good flatness and shape profile. Control profile involves use actuators throughout mill. There are also significant transport delays between stands. Predictive control may be used at all levels hierarchy but it particularly effective supervisory where constraints important complexity total system apparent. In this paper, generalised predictive method discussed. The physical its model described. Finally, simulation...
This paper introduces two practical supervisory control configurations for use in industrial applications. The theory developed within the framework of generalised predictive is used these structures. Their simple realisation and ability to handle constraints are considered as major assets approaches. An implementation results on a hot strip mill application will be presented demonstrate effectiveness proposed methods.
Bu çalışmada, Tropical Rainfall Measuring Mission (TRMM, Tropik Yağmur Ölçme Misyonu) 3B42 v7 uydu kaynaklı aylık yağmur verileri, Meteoroloji Genel Müdürlüğü tarafından işletilen 257 adet gözlem istasyonunda 1998 - 2014 yılları arasında ölçülen yağış verilerinin kümülatif toplamları kullanılarak doğrulanmıştır. İstasyon ve uzun dönem ortalama değerleri, birbirleri arasındaki korelasyonları, anomali bileşenlerinin standart sapmaları ile hata oranlarının incelenmiştir. Uydu yüksekliğe...
The application of the efficient nonlinear predictive control algorithms, emerging from recent research, to hot strip finishing mills is discussed. method controlling profile based on explicit manipulation thickness across its width. An model-based algorithm employed generate signal for stands and coordinate optimal shape control. Simulation results are presented demonstrate performance proposed coordinated scheme.
Shape control involves regulation of the internal stress in rolled strip so that when it is cut into sections will lie flat on a surface. The paper presents two approaches to shape metal rolling applications and develops methods assessing quality shape, or flatness control, may be improved. Two particular cases hot mills are considered compared against newly defined benchmark. Finally, simulation results presented illustrate techniques.
A complex system usually comprises numerous loops that are controlled by local SISO controllers. The decision to retune or replace any one of these controllers should be based on an investigation as whether a change will improve the performance. Such procedure is referred benchmarking. With benchmarking tool, engineer can justify proposed retuning controller, since it provides measure for quality control achieved. In paper, first, basic theory minimum variance presented. Then, results arise...