Global Indian Scientists and Technocrats Forum

Water Resource management: Water Security, Policy
We invite contributions, especially from early career scientists, who will share experiences (e.g. lessons learned, best practices), offer critical perspectives, or discuss future ways forward for water resources management, security, and policy. This session provides the opportunity to discuss and address the necessary skills to facilitate the uptake of hydrological sciences in policy formulation and implementation. We will discuss expectations, actual practice, research challenges, and the skills that enable (or prevent) advances in the field.

Chairs

To Be AnnouncedTo Be AnnouncedTo Be Announced

Water Resource management: Water Security, Policy
We invite contributions, especially from early career scientists, who will share experiences (e.g. lessons learned, best practices), offer critical perspectives, or discuss future ways forward for water resources management, security, and policy. This session provides the opportunity to discuss and address the necessary skills to facilitate the uptake of hydrological sciences in policy formulation and implementation. We will discuss expectations, actual practice, research challenges, and the skills that enable (or prevent) advances in the field.

Chairs

To Be Announced

Extreme Event, Climate Change and Adaptation Strategies
In the current context of global change, assessing the impact of climate variability and changes on hydrological systems and water resources is increasingly crucial for society to better adapt to future shifts in water resources, as well as extreme conditions (floods and droughts). However, important sources of uncertainty have often been neglected in projecting climate impacts on hydrological systems, especially uncertainties associated with internal/natural climate variability, whose contribution to near-future changes could be as important as forced anthropogenic climate changes at the regional scales.

Internal climate modes of variability (e.g. ENSO, NAO, AMO) and their impact on the continent are not always properly reproduced in the current global climate models, leading to large underestimations of decadal climate and hydro-climatic variability at the global scale. At the same time, hydrological response strongly depends on catchment properties, whose interactions with climate variability are little understood at the decadal timescales. These factors significantly reduce our ability to understand long-term hydrological variability and improve projections and reconstructions of future and past hydrological changes upon which improvement of adaption scenarios depends. We welcome abstracts capturing recent insights for understanding past or future impacts of large-scale climate variability on hydrological systems and water resources as well as newly developed projection and reconstruction scenarios. Results from model intercomparison studies are encouraged.

Chairs

To Be AnnouncedTo Be AnnouncedTo Be Announced

Extreme Event, Climate Change and Adaptation Strategies
In the current context of global change, assessing the impact of climate variability and changes on hydrological systems and water resources is increasingly crucial for society to better adapt to future shifts in water resources, as well as extreme conditions (floods and droughts). However, important sources of uncertainty have often been neglected in projecting climate impacts on hydrological systems, especially uncertainties associated with internal/natural climate variability, whose contribution to near-future changes could be as important as forced anthropogenic climate changes at the regional scales.

Internal climate modes of variability (e.g. ENSO, NAO, AMO) and their impact on the continent are not always properly reproduced in the current global climate models, leading to large underestimations of decadal climate and hydro-climatic variability at the global scale. At the same time, hydrological response strongly depends on catchment properties, whose interactions with climate variability are little understood at the decadal timescales. These factors significantly reduce our ability to understand long-term hydrological variability and improve projections and reconstructions of future and past hydrological changes upon which improvement of adaption scenarios depends. We welcome abstracts capturing recent insights for understanding past or future impacts of large-scale climate variability on hydrological systems and water resources as well as newly developed projection and reconstruction scenarios. Results from model intercomparison studies are encouraged.

Chairs

To Be Announced

AI-ML tools and techniques in earth sciences
AI-ML has seen accelerated adoption across Hydrology and broader Earth Sciences. This session highlights the continued integration of deep learning and its many variants into traditional and emerging hydrology-related workflows. Abstracts are solicited related to novel theory development, new methodologies, or practical applications of deep learning in hydrological modeling and process understanding. This might include, but is not limited to, the following:

(1) Development of novel AI-ML models or modeling workflows
(2) Integrating AI-ML with process-based models and/or physical understanding
(3) Improving understanding of the (internal) states/representations of deep learning models
(4) Understanding the reliability of AI-ML, e.g., under non-stationarity
(5) Deriving scaling relationships or process-related insights with AI-ML
(6) Modeling human behavior and impacts on the hydrological cycle
(7) Extreme event analysis, detection, and mitigation
(8) Natural Language Processing in support of models and/or modeling workflows

Chairs

To Be AnnouncedTo Be AnnouncedTo Be Announced

AI-ML tools and techniques in earth sciences
AI-ML has seen accelerated adoption across Hydrology and broader Earth Sciences. This session highlights the continued integration of deep learning and its many variants into traditional and emerging hydrology-related workflows. Abstracts are solicited related to novel theory development, new methodologies, or practical applications of deep learning in hydrological modeling and process understanding. This might include, but is not limited to, the following:

(1) Development of novel AI-ML models or modeling workflows
(2) Integrating AI-ML with process-based models and/or physical understanding
(3) Improving understanding of the (internal) states/representations of deep learning models
(4) Understanding the reliability of AI-ML, e.g., under non-stationarity
(5) Deriving scaling relationships or process-related insights with AI-ML
(6) Modeling human behavior and impacts on the hydrological cycle
(7) Extreme event analysis, detection, and mitigation
(8) Natural Language Processing in support of models and/or modeling workflows

Chairs

To Be Announced

Earth and Space Science Informatics
The aim of this session is to provide a platform and an opportunity to demonstrate and discuss innovative and recent advances of Earth and Space Science Informatics applications and methodologies for analysing and producing diagnostics and prognostics of hazards. It also aims to provide a forum for researchers from a variety of fields to effectively communicate their research. Submissions related to the following non-exhaustive topics are particularly welcome:-

1. Spatial and temporal analysis of the incidence and distribution of geo/hydrometeorological hazards
2. Machine learning (e.g., CNN, GNN) in analyzing and predicting geo/hydrometeorological hazards.
3. Uncertainty quantification of coupled models, such as atmospheric-hydrological/hydrodynamic in the applications of diagnosing and predicting hydrometeorological hazards
4. Development in quantitative methods for analyzing compound hydrometeorological hazards, Data assimilation and fusion of heterogeneous observations in hazard modeling, e.g., satellite-borne sensors and rainfall radars
5. HPC (GPU) based algorithms and practice dealing with very large size datasets in prognostic modeling of hydrometeorological hazards, e.g., climate projections.
6. Modeling interface with human interactions in decision-making, mitigation, and impact studies.

Chairs

To Be AnnouncedTo Be AnnouncedTo Be Announced

Earth and Space Science Informatics
The aim of this session is to provide a platform and an opportunity to demonstrate and discuss innovative and recent advances of Earth and Space Science Informatics applications and methodologies for analysing and producing diagnostics and prognostics of hazards. It also aims to provide a forum for researchers from a variety of fields to effectively communicate their research. Submissions related to the following non-exhaustive topics are particularly welcome:-

1. Spatial and temporal analysis of the incidence and distribution of geo/hydrometeorological hazards
2. Machine learning (e.g., CNN, GNN) in analyzing and predicting geo/hydrometeorological hazards.
3. Uncertainty quantification of coupled models, such as atmospheric-hydrological/hydrodynamic in the applications of diagnosing and predicting hydrometeorological hazards
4. Development in quantitative methods for analyzing compound hydrometeorological hazards, Data assimilation and fusion of heterogeneous observations in hazard modeling, e.g., satellite-borne sensors and rainfall radars
5. HPC (GPU) based algorithms and practice dealing with very large size datasets in prognostic modeling of hydrometeorological hazards, e.g., climate projections.
6. Modeling interface with human interactions in decision-making, mitigation, and impact studies.

Chairs

To Be Announced

Big Earth Data for Disaster Risk Reduction, Multi-Hazards
This session seeks innovative presentations for interdisciplinary research and applications, including but not limited to Earth Science data and service activities. Presentations addressing the specific societal needs, best practices, learned lessons, and new challenges in data provenance, information access, visualization, and analysis are highly encouraged.

Chairs

To Be AnnouncedTo Be AnnouncedTo Be Announced

Big Earth Data for Disaster Risk Reduction, Multi-Hazards
This session seeks innovative presentations for interdisciplinary research and applications, including but not limited to Earth Science data and service activities. Presentations addressing the specific societal needs, best practices, learned lessons, and new challenges in data provenance, information access, visualization, and analysis are highly encouraged.

Chairs

To Be Announced