News

6th Conf. on the Use of Space Tech for Water Management

Jointly sponsored by the United Nations/Costa Rica/PSIPW, the Sixth conference on the use of space technology for water management will be held in SAN JOSÉ, COSTA RICA, 7-10 MAY 2024 (WITH A POSSIBILITY OF ONLINE ATTENDANCE) .  100-150 participants are expected to attend.  There is limited opportunity to seek travel funding support (see registration deadline below).

Registration Deadlines
Applicants seeking funding support: 24 January 2024

Self-funded participants attending on site: 22 February 2024 and those selected will be informed shortly afterwards.
Online participants: 30 April 2024.

To register and find out more visit this website. 

Especially of interest will be themes 2 and 3:

2. Space technology and data for water quality monitoring and sustainable agriculture

Water quality but also our health depend to a significant extent on how water is used in agriculture and how the resulting runoff is managed. Nutrient-rich and containing contaminants from pesticides and fertilisers, such as nitrates, phosphorus and potassium, pathogens from animal life stock, as well as soil particles, agricultural runoff affects the water quality of surrounding water bodies and can e.g., lead to algae blooms or sedimentation. Globally, at least 2 billion people use a drinking water source contaminated with faeces and water used in agriculture needs to be free of toxins and ideally as clean as possible to produce healthy food. Among the great advantages of Earth observation for water quality monitoring is the temporal and spatial resolution compared to in situ data sampling. Noteworthy to say that sampling in situ remains important for the assessment of parameters that cannot be observed from space but also to train, validate and test space-based datasets. Spin-off technology for water quality testing and filtration systems such as sampling kits allow for monitoring of certain water quality parameters on-site without the need for a laboratory Presentations submitted under this theme address any space-based technology to improve, assure or monitor water quality (ideally related to the water food nexus), including Earth observations, satellite communication or spin-off technology as well as the use of in-situ data to train, validate and verify models on large-scale observations from space. Topics include the indirect monitoring of surface water quality such as chlorophyll-a, turbidity, surface water temperature, chemical oxygen demand, and dissolved organic matter. Furthermore, the identification of sources of pollution outside of water bodies allows to trace back information on the type of pollution that is relevant. Finally, topics related to the monitoring of sustainable agriculture practices such as those applied in organic farming and their effects on enhancing water quality are considered.

3. Satellite communication – a facilitator for IoT-supported water applications

A data and information revolution took place under the umbrella term Internet of Things (IoT) which connects devices and all types of sensors to the internet. When combined with satellite communications this technological paradigm shift becomes tangible even in the remotest areas of our planet and can hence overcome certain challenges posed by a digital divide. This theme covers the pivotal role of satellite communication as a facilitator for Internet of Things (IoT) applications to monitor and inform sensible decisions in the field of sustainable management of water, aquatic ecosystem preservation, hydrology and the Water-Food Nexus such as in agricultural applications. Presentations covered under this theme can include but are not limited to:

  • Satellite communication transmission networks and architectures for sensor systems;
  • Systems designed for (near-) real-time monitoring and transmitting water tank levels, irrigation, soil moisture, microclimates, liquid fertilizer levels, nutrient leaching and its impact on water bodies, dam and reservoir water levels to name just a few;
  • IoT for real-time water management solutions for Precision Agriculture (e.g. optimizing irrigation, pest control, and crop health monitoring);
  • Systems for crop yield predictions
  • Satellite communication systems transmitting relevant weather or water availability information to farmers and systems to inform decision-making at a local level; and
  • In-situ data collected by the sensors can feed into larger monitoring systems that observe water resource, hydrological or soil-related variables at a larger scale.

WWQA Seed Funding Call – due January 31st!

The World Water Quality Alliance is delighted to announce that the Seed Funding call is now open for:

  1. Proposals for new World Water Quality Alliance Workstreams (template)
  2. Seed Funding for existing and new World Water Quality Alliance workstreams (template)

In order to access further information and the proposal submission details please see  Call for WWQA Workstream Proposals and Seed Funding Applications 2024

It is important to note the following dates:

  • All proposals must be received by the WWQA coordination team at wwqa-coordination@un.org on the 31st January 2024 at 23:59 East African Time (Nairobi)
  • All proposals will receive an official communication stating whether they have been approved or not on the 21st of February 2024.
  • The approved seed funded proposals will be implemented in the period between the 4th of March 2024 and the 16th of September 2024.

We wish you the very best of luck and we look forward to receiving your ideas.

NASA ARSET ADVANCED TRAINING: SeaDAS 8.4.0…..for Water Quality Monitoring

NASA ARSET ANNOUNCES – Advanced Webinar: Overview of SeaDAS 8.4.0 for the Processing, Analysis, and Visualization of Optical Remote Sensing Data for Water Quality Monitoring
February 13, 2024
10:00-12:15 (Session A) or 14:00-16:15 (Session B) EST (UTC-5)

SeaDAS software, developed by the NASA Ocean Biology Processing Group (OBPG), is used in the processing, analysis, and visualization of satellite images. SeaDAS uses OBPG algorithms to produce water quality data and can be used to obtain water quality parameters from current optical sensors such as OLI, MSI, OLCI, VIIRS, and MODIS. SeaDAS can also be used to apply atmospheric correction and obtain remote sensing reflectance at the water surface level from these sensors. This two-hour training will provide an overview and demonstration of the latest version of SeaDAS 8.4.0, which is useful for remote sensing of water quality monitoring. This training will also serve as a prerequisite for future ARSET training on remote sensing of water quality.

Register

WaterSciCon 2024 – St. Paul MN USA June 24-27, 2024

The AGU Frontiers in Hydrology Meeting has joined with CUAHSI to form a new conference, the Water Science Conference (WaterSciCon) – using the Catalyzing Collaborations theme, which will take place in Saint Paul, MN from June 24 – 27. There are several sessions for the 2024 WaterSciCon related to water quality, including “FCS-01 – Actionable science through water forecasts” “LO-01 – Advances in Cold Regions Hydrology and Water Quality” and a session that several Technical Committee members are convening “LO-02 – AI Innovations for Water Quality Assessment in Diverse Watersheds”.   See Session Descriptions below.

The abstract submission deadline is January 24th. Please consider submitting an abstract!

FCS-01 – Actionable science through water forecasts
Decisions are fundamentally about what we think is going to happen in the future. Probabilistic forecasts offer extremely useful, although imperfect, information to help make these decisions. This type of actionable science, particularly in the realm of forecasting water quantity and quality, is becoming increasingly indispensable as we confront growing socioeconomic and environmental challenges that are exacerbated by global changes. In this session, we extend an invitation to presenters who can illustrate various aspects of using water forecasts, e.g., coastal flooding, water supply, and noxious algal blooms, in decision support applications. Use cases that demonstrate the practical application of water forecasts, innovative improvements to existing forecast methodologies, and research that contributes to our understanding of water forecasts’ role in decision-making processes are highly desired. Join us as we explore the evolving landscape of water forecasts as actionable science and its significance in addressing complex water challenges.
Conveners:
Jacob Zwart, U.S. Geological Survey, jzwart@usgs.gov
Freya Olsson, Virginia Tech
Christopher Brown, University of Maryland
Lauren Fry, National Oceanic and Atmospheric Administration

Here is the session description for the AI in water quality session : Artificial Intelligence (AI) is rapidly emerging as a transformative approach for extracting invaluable knowledge and insights from datasets. Within the realm of hydrology, AI methods, such as machine learning, have emerged as indispensable tools for modeling complex, non-linear dynamics and providing real-world decision-making insights. This session welcomes contributions from researchers, experts, and practitioners who are leveraging AI tools to advance our understanding of water quality patterns, processes, and management strategies across diverse watersheds. This session aims to foster a multidisciplinary dialogue among hydrologists, data scientists, and policymakers. We invite abstract submissions that are not limited to only: Water Quality Monitoring; Predictive Modeling; Decision Support Systems; Sustainable Watershed Management; Case Studies. In this session we will explore how AI is revolutionizing our approach to understanding, managing, and preserving water quality. Share your innovative research and practical insights to contribute to the collective knowledge needed to address pressing global water quality challenges

IGARSS 2024 session: Call for abstracts due January 12th!

We welcome submissions to this session CCS.117 Thermal imaging and visible to shortwave imaging spectroscopy for aquatic resources in the context of SDGs: 2, 6, 14, 15

Description: Enhanced understanding of the water cycle and water management practices are of critical importance for achieving multiple sustainable development goals (SDGs), in particular zero hunger (SDG 2), clean water and sanitation (SDG 6), life below water (SDG 14), and life on land (SDG 15). Remote sensing earth observations (EO) are poised to play a pivotal role in attaining these SDGs by facilitating the science, monitoring, and progress reporting required to meet these goals. In the 2017 Decadal Survey, the Surface Biology and Geology (SBG) mission concept was identified as necessary for addressing both scientific and applications across Earth systems. This forthcoming mission will consist of a visible to shortwave infrared (VSWIR) imaging spectrometer and a multispectral thermal infrared (TIR) imager, offering transformative insights into aquatic ecosystems and hydrology, which are essential for meeting SDGs. We welcome work that leverages the capabilities of VSWIR and TIR technology to advance the realization of these four key SDGs related to water resources and aquatic applications. Example research topics may include imaging processing, validation and calibration processes, water quality analysis, and habitat protection and restoration, and drought assessment across cryospheric and agricultural domains. In addition, we invite works centered on practical applications that explore how managers could utilize the combined capabilities of optical and thermal sensing to support aquatic ecosystem management and monitoring. These works should demonstrate the potential of integrating a variety of sensors, including, but not limited to imaging spectrometers (e.g., AVIRIS-NGs, EMIT, DESIS, PRISM), thermal imagers (e.g., ECOSTRESS, Landsat-TIRS), and visible multispectral sensors (e.g., Sentinel-2, Landsat).

The submission link is:
https://2024.ieeeigarss.org/Papers/Submission.asp?SessionType=CCS&ID=2117__;!!PvBDto6Hs4WbVuu7!MlCiWZZx9__GlRZ9TgXV9Pnw6h3weQDFjm-teAJoVfmDOsktqlcALdqnDEes6EAXGlG7Z6ZH7SV6zzUlfCgCaKVpD_Bs5T6siOjduWUMB8cMCA$