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HS6

HS – Hydrological Sciences

HS6 – Remote Sensing and Data Assimilation

HS6.3

The monitoring of river water levels, river discharges, water bodies extent, storage in lakes and reservoirs, flooding and floodplain dynamics plays a key role in assessing water resources, understanding surface water dynamics, characterizing and mitigating water related risks and enabling integrated management of water resources and aquatic ecosystems.

While in situ measurement networks play a central role in the monitoring effort, remote sensing techniques are expected to contribute in an increasing way, as they can provide homogeneous and near real time measurements over large areas, from local to basin wide, regional and global.

In this context, remote sensing represents a value source of data and observations that may alleviate the decline in field surveys and gauging stations, especially in remote areas and developing countries. The implementation of remotely-sensed variables (such as digital elevation model, river width, flood extent, water level, land cover, etc.) in hydraulic modelling promises to considerably improve our process understanding and prediction and during the last decades, an increasing amount of research has been undertaken to better exploit the potential of current and future satellite observations. In particular, in recent years, the scientific community has shown how remotely sensed variables have the potential to play a key role in the calibration and validation of hydraulic models, as well as provide a breakthrough in real-time monitoring applications. However, except for a few pioneering studies, the potential of remotely sensed data to enhance water-related modelling and applications has not yet been fully enough explored, and the use of such data for operational decision-making is far from being consolidated. In this scenario, the forthcoming satellite missions dedicated to global water surfaces monitoring will enhance the quality, as well as the spatial and temporal coverage, of remotely sensed data, thus offering new frontiers and opportunities to enhance the understanding of flood dynamics and our capability to map their extents.

We encourage presentations related to flood monitoring, water level, storage and discharge etc through remotely sensed data including:

- Remote sensing data for flood hazard and risk mapping;
- Remote sensing techniques to monitor flood dynamics;
- The use of remotely sensed data for the calibration, or validation, of hydrological or hydraulic models;
- Data assimilation of remotely sensed data into hydrological and hydraulic models;
- Improvement of river discretization and monitoring by means of satellite based observations;
- River flows estimation by means of remote sensed observations;
- River and flood dynamics estimation from satellite (especially time lag, flow velocity, etc.)

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Co-organized as NH6.19
Convener: Guy J.-P. Schumann | Co-conveners: Alessio Domeneghetti, Ben Jarihani, Angelica Tarpanelli, Jérôme Benveniste
Orals
| Tue, 09 Apr, 14:00–18:00
 
Room C
Posters
| Attendance Tue, 09 Apr, 10:45–12:30
 
Hall A
HS6.4

We invite presentations concerning soil moisture estimation, including remote sensing, field experiments, land surface modelling and data assimilation. The technique of microwave remote sensing has made much progress toward its high potential to retrieve surface soil moisture at different scales. From local to landscape scales several field or aircraft experiments (e.g. SMAPex) have been organised to improve our understanding of active and passive microwave soil moisture sensing, including the effects of soil roughness, vegetation, spatial heterogeneities, and topography. At continental scales a series of several passive and active microwave space sensors, including SMMR (1978-1987), AMSR(2002-), ERS/SCAT (1992-2000) provided information on surface soil moisture. Current investigations in L-band passive microwave with SMOS (2009-) and the new SMAP mission (Q1 2015) and in active microwave with Metop/Ascat series (2006-) open new possibilities in the quantification of the soil moisture at regional and global scales. Comparison between soil moisture simulated by land surface models, in situ observations, and remotely sensed soil moisture is also relevant to characterisation of regional and continental scale soil moisture dynamic (e.g., ALMIP2, GSWP3).

We encourage presentations related to soil moisture remote sensing, including:
- Field experiment, theoretical advances in microwave modelling and calibration/validation activities.
- Root zone soil moisture retrieval and soil moisture assimilation in land surface models as well as in Numerical Weather Prediction models.
- Inter-comparison and inter-validation between land surface models, remote sensing approaches and in-situ validation networks.
- Evaluation and trend analysis of soil moisture data record products such as the soil moisture CCI product or soil moisture re-analysis products (e.g. MERRA-Land, ERA-Land).
- Application of satellite soil moisture products for improving hydrological applications such as flood prediction, drought monitoring, rainfall estimation.

Invited Speaker: Wolfgang Wagner from Vienna University of Technology with the title "Resolving the Daily Water Cycle over Land with a Geosynchronous C-band Radar Satellite"

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Convener: Luca Brocca | Co-conveners: Patricia de Rosnay, Yann Kerr, Jian Peng, Niko Verhoest
Orals
| Thu, 11 Apr, 08:30–12:30
 
Room B
Posters
| Attendance Thu, 11 Apr, 14:00–15:45
 
Hall A
HS6.5

Ensuring long-term water sustainability for increasing human populations is a common goal for water resource managers. Measuring evapotranspiration (ET) at watershed or river-reach scales, upland or urban areas is required to estimate how much water can be apportioned for human needs while maintaining healthy vegetation and habitat for wildlife.
Consequently, much research has been devoted to this topic. However although there have been many advances in meteorological equipment and observations, more universal recognition of the impact of climate and land cover changes on evaporation and hydrology, and the increased accessibility of many parts of the world, evaporation from much of the globe remains elusive to quantify. This is particularly true in areas with few meteorological observations, in regions where precipitation is particularly hard to predict such as in arid and semi-arid or mountain environments. ET measurements are often made on local scales, but scaling up has been problematic due to spatial and temporal variability.
There are challenges associated with handling temporal variability over complex agro-climatic regions and in places with strong effects of unpredictable climate oscillations. For instance, crop/plant coefficients vary seasonally, particularly for riparian, upland vegetation, and urban greenery; traditional approaches of ET estimation commonly neglect the heterogeneity of microclimate, density, species, and phenology that have often led to gross overestimates of plant water use.
In this session, we want to focus on quantifying evapotranspiration dynamics in diverse climates and environments as a tool for improving hydrologic assessments and predictions at a catchment scale. Remote sensing products in many cases are the only spatially distributed information available to account for seasonal climate and vegetation variability and are thus extremely valuable data sources for ET estimation on larger scales.
We invite researchers to contribute theoretical and empirical ET model applications for a variety of dryland vegetation associations and other sensitive environments. We welcome studies that estimate ET using both prognostic and diagnostic approaches from process-based models that rely on the integration of precipitation and soil-vegetation dynamics to a more direct estimation of ET using e.g. remote sensing based data streams. Applications in drought-prone forests, rangelands, mountain and urban areas at a range of spatial and temporal scales are encouraged.

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Co-organized as BG1.44/ESSI1.12/GI3.12
Convener: Pamela Nagler | Co-conveners: Claire Brenner, Chris Jarchow, Hamideh Nouri, Gabriel Senay, Natalie Ceperley, Mathew Herrnegger
Orals
| Fri, 12 Apr, 14:00–15:45, 16:15–18:00
 
Room B
Posters
| Attendance Fri, 12 Apr, 10:45–12:30
 
Hall A
HS6.7 | PICO

Remote sensing techniques are widely used to estimate and monitor the relationship between vegetation dynamics and the water cycle. Measurements of vegetation water content, transpiration and water stress contribute to a better global understanding of the water movement in the soil-plant system, which is critical for the detection and monitoring of droughts and their impact on biomass. With the number of applications and (planned) missions increasing, this session aims to bring researchers together to discuss the current state in the remote observation of the interactions between vegetation and hydrology. We aim to (1) discuss novel research and findings, (2) exchange views on what should be done to push the field forward, and (3) identify current major challenges.

We encourage authors to submit presentations on:
• Modelling studies,
• Remote sensing data analyses,
• New hypothesis,
• Enlightening opinions.

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Co-organized as BG1.36
Convener: Mariette Vreugdenhil | Co-conveners: Joris Timmermans, Tim van Emmerik, Julia K. Green, Leon T. Hauser, Philip Marzahn, Brianna Pagán, Arturo Sanchez-Azofeifa
PICOs
| Mon, 08 Apr, 08:30–12:30
 
PICO spot 5b
HS6.8

Drones (also Unmanned Aerial Vehicles/Systems (UAV/UAS), Remotely Piloted Aircraft Systems) have revolutionised the ability to collect ultra-high spatial resolution spatial data at the scale of millimetres to centimetres. This has allowed a new scale of mapping and process research in the geosciences. Drones and associated sensors can be cost-effective compared with high spatial resolution airborne and satellite data, providing flexibility in deployment. The development curve of miniaturized drone sensors and data processing software / hardware solution has been transformative, but has not perhaps satisfied scientists’ expectations. Many geoscientists are grappling with quality, stability and reliability in the collection and calibration of data from sensors that have over-promised but under-delivered in practice, or are simply not suited to particular applications. Drone hardware and software has provided tools to process the data, but many tools are black-box, and the resulting observations have quality issues that can impact the questions that are being answered by geoscientists in mapping and process studies. This PICO session will share peoples’ knowledge of the issues and limits of sensors and processing workflows, focusing on communicating and sharing solutions for addressing and advancing our understanding of how ultra-high spatial resolution drone data can (and cannot) be collected, calibrated, processed and then used to answer research questions in the geosciences. Specific themes we wish to promote include:
- Work quantifying sensor quality, stability and reliability in the collection of data, with a focus on sharing information around quantifying limits, providing solutions and communicating best (or limits on) use of data,
- Best practice in the calibration of data (particularly spectral and thermal sensors), and relating this to levels of processing/calibration/validation required to answer geoscience questions,
- Collection and processing of LiDAR and photogrammetry Structure from Motion (SfM) data and the use of fine-resolution digital elevation models (DEMs) in the geosciences,
- Limitations and opportunities in using drones for mapping studies in the geosciences,
- Limitations and opportunities in using drones for process studies in the geosciences,
- Related work that focuses on solutions to issues experienced in using drone data in the geosciences.
- Examples of applications that are affected or overcome issues related to sensor quality, calibration and data pre-processing (orthomosaicing, radiometric correction, vignette correction, BRDF correction, conversion of digital numbers to at-surface reflectance).


We are pleased to announce a keynote presentation from Dr Patrice Carbonneau (University of Durham).

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Co-organized as GM2.13
Convener: Kasper Johansen | Co-conveners: Nik Callow, Andrew Cunliffe, Ben Jarihani
Posters
| Attendance Wed, 10 Apr, 08:30–10:15
 
Hall A
GI4.5

The IR (MWIR 3-5micron and LWIR 7-12micron) sensing technologies have reached a significant level of maturity and has become a powerful method of Earth surface sensing.
Thermal sensing is currently used for characterize land surface Temperature (LST) and Land Surface Emissivity (LSE) and many other environmental proxy variables, which part of them can have a further relevance when assimilated into hydrological and climatological models.
The usefulness of IR sensing has been experimented in many environmental applications and also in the spatio-temporal domain for spatial patterns identification.
The session welcomes communications based on the actual of next future IR imagery from broadband to multi/hyperspectral applied to proximal or remote sensing (ECOSTRESS, ASTER, Sentinel3, Landsat etc. and airborne sensors) in the following specific objectives:
- IR instruments solution
- Instrument radiometric calibration procedures
- Algorithms retrieval for Temperature and Emissivity
- Soil properties characterization
- Evapo-Transpiration, water plants stress and drought
- IR targets identification
- Archaeological prospection
- Urban areas and infrastructure investigation
- Geophysical phenomena characterization
- IR synergy with optical imagery

LINKED TO THIS SESSION IS A REMOTE SENSING JOURNAL SPECIAL ISSUE "Proximal and Remote Sensing in the MWIR and LWIR Spectral Range" WITH DEADLINE DECEMBER 2019.

https://www.mdpi.com/journal/remotesensing/special_issues/EGU_TIR

SUBMISSIONS TO THIS SESSION AND TO THE RS JOURNAL SPECIAL ISSUE ARE WELCOME

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Co-organized as AS5.9/HS6.9/NH6.17/SSS12.14
Convener: Stefano Pignatti | Co-conveners: Eyal Ben Dor, Maria Fabrizia Buongiorno, Angelo Palombo, Francesco Marchese, Nicola Genzano, Vasco Mantas, George Xian
Orals
| Mon, 08 Apr, 08:30–10:15
 
Room 0.96
Posters
| Attendance Mon, 08 Apr, 10:45–12:30
 
Hall X1