Too Little, Too Much or in the Wrong Place

The opening plenary at the AWRA 2014 conference by Kathryn Sullivan explained the emerging role for Environmental Intelligence for handling the need to respond to the increasingly fickle nature of water availability and quality. Dr. Sullivan used several recent examples of unprecedented extreme events to make the point that the world’s attention is focused on the nexus of water security, food security and energy security.

This problem cannot be solved by mining of historic data.

The past is not a reliable predictor of the future. Environmental Intelligence is the coordinated synthesis and analysis of data to produce actionable, reliable predictions. We are relatively successful at predictions at a scale of days allowing us to predict consequences of individual storms. We are relatively successful (we think) at multi-decadal climate predictions. However our ability to successfully anticipate and react to water variability requires information at time scales somewhere between days and decades.

A monitoring/modelling hybrid approach needs to be developed. Models can help inform where and when data are needed. Monitoring is needed to inform model architecture and design. Monitoring is needed to calibrate models. Monitoring is needed to initialize models and constrain boundary conditions. Monitoring is needed to verify model output. Models can predict across spatial scales and forward into time frames to fill critical information voids.

These are big ideas with big implications.

One implication is that the conversation has changed from one of environmental sustainability to water, food and energy security. Dr. Sullivan explained that the environment is the backdrop to this nexus. It is hard to conceive of a future with secure water resources without a largely intact and sustainable environment. Nonetheless, human need has taken primacy in the conversation.

Another implication is for our role in water monitoring. Historically, our primary raison d’etre was to provide data for engineering studies that essentially use the past to anticipate the future. We have become increasingly focused on real-time data delivery to support adaptive management. Dr. Sullivan’s proposal infers that we will have to further adapt to fully integrate our data within a modelling framework to support predictions for anticipatory management.

Water data are complex. Water data are context sensitive.

Streamflow, its constituents (e.g. sediment, solutes), properties (e.g. temperature), and behaviors (e.g. velocity) integrate local and regional processes in non-linear ways that often defy up-scaling. Environmental Intelligence must therefore become smart enough to be able to consume data complete with its meaningful context.

This means that, as a community, we must give careful thought to our metadata management. Environmental Intelligence will need the exposure of Long Tail data to fill critical data voids. However, the burden of even minimal metadata management is a causal factor for many data sources to go dark. We need to develop a viable metadata payload for our data that is sufficient to address emerging roles for our data but is so easy to implement that data hoarding will become a relic of the past.

Addressing the Challenges – The National Water Center

To help address the complex water challenges and improve water prediction and environmental intelligence, Dr. Sullivan shared that NOAA’s National Weather Service (NWS) has opened the National Water Center (NWC) in Tuscaloosa, Alabama. The first facility of its kind in the world, this new national center will revolutionize operational water resources analysis and forecasting. Serving as a central hub, the center will efficiently manage the flow of water information, operating state-of-the-art water models in a high-performance computing environment, and producing, in partnership with NWS River Forecast Centers, a unique, comprehensive suite of new water resources information products and services. It will be the nerve center for the nation’s water resources enterprise, informing and enabling routine high-value and high-impact decision-making across a broad range of water-management and emergency-management sectors. The NWC will produce information necessary to drive the growth of the nation’s emerging water resources economy and help support a Weather Ready Nation.

Photo Credit: Hoover Dam” by LoggaWiggler, used under CC0 1.0.

One response to “Too Little, Too Much or in the Wrong Place”

  1. The AWRA plenary address by Kathryn Sullivan was full of truisms but one phrase rank true: the past is not a reliable predictor of the future, especially when it comes to climate change. It’s very likely the present is the predictor of the future.

    Until recently we’ve been able to deconvolute changing climate based on surrogate measurement and the discover of climate cycles like the ENSO indices. That no longer holds true because we’re seeing unprecedented changes in the energy budgets of the oceans and atmosphere and the redidistribution of heat and water vapor.

    These effects cannot be understood by analysing past climate cycles. Instead we need new accurate data from dense arrays that can be modeled based on basic chemistry, physics and the boundary conditions for the dynamics of the oceans and atmosphere. The best models will use now-casting to check our understanding of those dynamics. Data assimilation is only the first step.

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