HS3.6

Many environmental and hydrological problems are spatial or temporal, or both in nature. Spatio-temporal analysis allows identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting hydrological events. Temporal information is sometimes limited; spatial information, on the other hand has increased in recent years due technological advances including the availability of remote sensing data. This development has motivated new research efforts to include data in model representation and analysis.

Statistics are in wide use in hydrology for example to estimate design events, forecast the risk and hazard of flood events, detect spatial or temporal clusters, model non-stationarity and changes and many more. Statistics are useful in the case when only few data are available but information for very rare events (extremes) or long time periods are needed. They are also helpful to detect changes and inconsistencies in the data and give a reliable statement on the significance. Moreover, temporal and spatial changes often lead to the violation of stationarity, a key assumption of many standard statistical approaches. This makes hydrological statistics interesting and challenging for so many researchers.

Geostatistics is the discipline that investigates the statistics of spatially extended variables. Spatio-temporal analysis is at the forefront of geostatistical research these days, and its impact is expected to increase in the future. This trend will be driven by increasing needs to advance risk assessment and management strategies for extreme events such as floods and droughts, and to support both short and long-term water management planning. Current trends and variability of hydrological extremes call for spatio-temporal and/or geostatistical analysis to assess, predict, and manage water related and/or interlinked hazards.

The aim of this session is to provide a platform and an opportunity to demonstrate and discuss innovative applications and methodologies of spatio-temporal analysis in a hydrological (hydrometeorological) context. The session is targeted at both hydrologists and statisticians interested in the spatial and temporal analysis of hydrological events, extremes, and related hazards, and it aims to provide a forum for researchers from a variety of fields to effectively communicate their research.
This session is co-sponsered by ICSH-STAHY (IAHS).

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Convener: Gerald A Corzo P | Co-conveners: A.B. Bardossy, Panayiotis DimitriadisECSECS, Svenja Fischer, Ross Woods
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| Attendance Wed, 06 May, 10:45–12:30 (CEST)

Many environmental and hydrological problems are spatial or temporal, or both in nature. Spatio-temporal analysis allows identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting hydrological events. Temporal information is sometimes limited; spatial information, on the other hand has increased in recent years due technological advances including the availability of remote sensing data. This development has motivated new research efforts to include data in model representation and analysis.

Statistics are in wide use in hydrology for example to estimate design events, forecast the risk and hazard of flood events, detect spatial or temporal clusters, model non-stationarity and changes and many more. Statistics are useful in the case when only few data are available but information for very rare events (extremes) or long time periods are needed. They are also helpful to detect changes and inconsistencies in the data and give a reliable statement on the significance. Moreover, temporal and spatial changes often lead to the violation of stationarity, a key assumption of many standard statistical approaches. This makes hydrological statistics interesting and challenging for so many researchers.

Geostatistics is the discipline that investigates the statistics of spatially extended variables. Spatio-temporal analysis is at the forefront of geostatistical research these days, and its impact is expected to increase in the future. This trend will be driven by increasing needs to advance risk assessment and management strategies for extreme events such as floods and droughts, and to support both short and long-term water management planning. Current trends and variability of hydrological extremes call for spatio-temporal and/or geostatistical analysis to assess, predict, and manage water related and/or interlinked hazards.

The aim of this session is to provide a platform and an opportunity to demonstrate and discuss innovative applications and methodologies of spatio-temporal analysis in a hydrological (hydrometeorological) context. The session is targeted at both hydrologists and statisticians interested in the spatial and temporal analysis of hydrological events, extremes, and related hazards, and it aims to provide a forum for researchers from a variety of fields to effectively communicate their research.
This session is co-sponsered by ICSH-STAHY (IAHS).

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