Drought in California,

It’s All About the Data – Illuminating Our Water Options

The droughts that are occurring in California, Puerto Rico, North Korea, Sao Paolo, and India are climatologically driven events, but the droughts of recent times have almost certainly been aggravated by water over-use, mis-use, and abuse. An attractive alternative to the scenarios that are currently playing out around the world is one in which monitoring is in place and provides:

  • water supply statistics (so that planning and policies strategically prevent over-use);
  • real-time data (to inform adaptive management practices to prevent mis-use); and
  • strategically located high-resolution hydrological information (to prevent abuse).

While it’s alarming to learn that one third of global aquifers are under stress, one might reasonably expect to see equal proportions at ‘normal’, ‘above,’ and ‘below’ at any given time as a result of decadal-scale climate processes constantly re-arranging global water distribution. Our problem is that we don’t have enough data to characterize what these patterns are so we can’t plan for the likelihood of the intensity and duration of these excursions. Furthermore we need more data to characterize the nature of groundwater/surface water interactions during all phases including surplus and deficit.

Living with the hydrological cycle is a bit like managing your personal finances.

You want to try to live within your means. The GreenBiz Post 7 drought lessons from the West: ‘It’s all about the data’ places data and analysis as the first — and most important lesson — learned about the drought in the western United States. The mess we’re in now is largely as a result of water supply decisions that have been based more on wishful thinking than on hard data.

This is not the last excursion from our comfort zone that the climate is going to take us on.

There will be more droughts and more floods in more places. We need to be better prepared for both extremes. The climate is changing and we cannot predict exactly what those changes will bring. The influence of greenhouse gases on the climate is very well explained in both theory and empirical evidence. What’s not so well understood is how to plan for these influences on water distribution in the absence of useful hydrological information.

Whereas governments around the world have been spending a lot of money building ever-more sophisticated climate models, budgets for basic monitoring are, in many cases, lower in real dollar terms than they were before climate was the most important security threat to human society. In spite of the vast disparity in investments in modeling versus monitoring, I don’t think you want to be using model results for the design of essential infrastructure just yet.

Newer and better models are extremely valuable for identifying gaps in our knowledge.

Knowing what we don’t know, informs what monitoring needs to be done, in order to fill our knowledge gaps. In other words, models are useful for providing questions; data are valuable for providing answers.

As an example, consider a recent report in Geophysical Research Letters attributing small volcanoes as the cause for the global warming hiatus since 1998. If it weren’t for the models being wrong, we would not have had the research question for this study that greatly improves our understanding of an important variable in climatological processes. The good thing is that we can now use this knowledge to build more robust climate models. The bad thing is that we now have to re-build our models to properly account for the timing, size, and geographic location of volcanoes. Model output has no legacy value.

In contrast data from reputable monitoring programs never becomes obsolete.

In fact, as I point out in my eBook The Value of Water Monitoring, properly curated water monitoring data increases in value exponentially through time.

There is a story about the streetlight effect wherein a drunk is looking for his keys under a lamppost. When asked if this is where he lost his keys, he says no but this is where the light is. Water data are the only illumination we have in our search for solutions for our water problems. If we don’t have the right data, in the right place, at the right time, we will never find the answers we seek.

Given that we still have problems predicting the weather for the weekend, never mind decades into the future, perhaps we should be diverting a portion of the funding for modeling to improving basic monitoring.  Do we really think that finding the right questions is more important that finding the right answers? Maybe, but I am not sure everyone would agree. Please respond below.

Photo Credit: Patrick Emerson | DroughtLicense

eBook: The Value of Water Monitoring

There is a solution … you understand the value of water monitoring but need additional, sustainable funding. Know that you are not alone. The gap between water monitoring capability and the rapidly evolving need for evidence-based policies, planning, and engineering design is growing. Learn how to form persuasive arguments that are sensitive to local politics and priorities to address this global deficit in funding. The benefits of hydrological information DO vastly outweigh investments in water monitoring.

Whitepaper: Monitoring Water in Extreme Droughts

July 2015 was the hottest month in recorded history according to NOAA! Extreme droughts around the world are creating an opportunity for hydrologists to record a historic event. Every drop counts. Every measurement counts. Droughts are a global problem that require new hydrological insight. Stu Hamilton’s latest whitepaper presents 7 best practices for monitoring water during droughts.

1 Comment
  • Jarrett Cziesch
    Posted at 12:14 pm, October 20, 2015

    The article adds some key points that are important topics. Data is of course very important especially the capture and transmittal of real-time data. Hydroinformatics is a useful concept and field that needs to be introduced into the US academic sector because it truly addresses the issues discussed in the article.

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