Extreme flows are extremely hard to gauge, hence we get very few gaugings to accurately define the top-end of stage-discharge rating curves. This is a problem. Whereas empirically calibrated functional relationships can be trustworthy for the purpose of interpolation, they can be notoriously unreliable for extrapolation. One needs to be very careful about extrapolating any rating curve to an ungauged extreme.
By 2050, a world population of 9 billion will require 60% more food. The security of our global food supply is highly reliant on adequate water supply. According to the United Nations, “agriculture is the biggest water user, with irrigation accounting for 70% of global water withdrawals.” While the global population is growing, water supply is not. So to meet 2050 food demands, it’s important we learn to better utilize limited water resources for optimal agricultural production. Today’s irrigation districts are being smarter about water use!
It is increasingly the case that when I am talking to people about what AQUARIUS software ‘should’ do, I find that there are multiple motivations for what ‘should’ means. There are many different ways that value can be perceived and product development depends on this perception. The concept of “shared value” is where companies can solve society’s problems and make profit at the same time.
Water monitoring is a place-based activity. The work is wherever the water is, which is all over the planet. A stream hydrographer can cover a very large geographic area so regional offices typically only concentrate a small number of hydrographers at any one location and there are many locations. Water monitoring agencies have limited resources available to develop specialized training material or to send hydrographers on specialized courses so the most prevalent mode of career development is on-the-job training.
Imagine, for a minute, your stereotype of a person of learning; especially one with detailed knowledge in some specialized field of science. I expect the person filling your mind’s eye is not a ruddy-faced bloke with a substantial belly and a thick Queenslander accent wearing shorts and R.M.Williams boots. Appearances are deceiving. I first met Ray ‘Rainman’ Maynard in Nelson, New Zealand.
Stage-discharge rating curves define a unique relation between water level and discharge, enabling continuous derivation of streamflow from water level record. This is important because water level (which is relatively easy to monitor) is only locally relevant whereas discharge (which is relatively difficult to measure directly) is the integral of all runoff processes upstream of the gauge. The vast majority of all streamflow data that has ever been produced is a derived result of a rating curve. In other words, almost everything that we know (or rather that we think we know) about hydrology is a result of rating curves.
In my last post, I announced the winners of the 2016 AQUARIUS Impact Awards. I congratulated Chris Smith, Water Resource Analyst at Murrumbidgee Irrigation for his outstanding achievements with AQUARIUS Time-Series. Today, while I visit our customers in Australia, I’d like to celebrate the country’s very progressive water monitoring practices. In many ways, Australia is one of the most advanced countries in the world when it comes to monitoring water.
Last week I attended the Environmental Industry Summit XIV in San Diego, California where Grant Ferrier, President and CEO of Environmental Business International Inc., presented EBI’s annual overview of market performance, segment trends and an outlook for 2016 and beyond. The Summit is a great event that brings together industry leaders to network and discuss opportunities for all of us working in the environmental space. The results for 2015 and the outlook for 2016 are very exciting.
Many people believe that it makes no sense to store data at a resolution that is more precise than the resolution that it can be observed. For example, it is believed that if you round water level to the nearest millimeter then the value will never be more than half a millimeter from the original. This idea was accepted as a reasonable compromise in the 20th century, and data management systems from that era were designed around it as a core concept. Modern data processing requirements, however, demand a different approach.
If there is one theme that dominated water news in February it must be innovation. Starting with how Microsoft is taking water cooling to a whole new level to create fully scalable data centers under ocean waters. I don’t think we can believe that the waste heat in the receiving waters will be totally benign, but it is entirely possible that this is a less impactful solution than any of the other mass computing options. So what if computing and data storage get much, much, cheaper as a result of this technology?
Last month was a busy one for water news. The biggest story of the month has to be that 2015 was the hottest on record. This is true globally with the WMO reporting that 2015 broke all previous records by a strikingly wide margin at 0.76° C above the 1961-1990 average. This marks the first time that global temperatures have been 1° C above the pre-industrial era.
One objective of the Hydrology Corner is to provide a forum where hydrometric problems can be discussed and clever solutions to those problems can be shared. The stream gaugers vs. beavers post is a good example of a discussion of a difficult problem. Not only have several people posted on the blog but the post also resulted in an email exchange with Jeff Watson from Horizons Regional Council who realized that New Zealand may have a solution to a North American problem.
Incremental change is an insidious thing. Like a frog in a pot of water on the stove it can be difficult to know what is going on when your attention is moment-to-moment. It could be that from day-to-day there is no noticeable change but year-to-year there is major change and decade-to-decade there is transformative change. The business of water monitoring is vastly different than when I was in the field.
We usually report water quantity information as a volumetric rate (e.g. m3/s); we usually report water quality information as a concentration (e.g. mg/l); and we usually report precipitation as a length (e.g. mm). But we don’t have to. The mass of water is related to its volume by its density which, conveniently, can be assumed to be unity (1). This means that we could just as easily report water information using the dimension of mass. Would reporting water information in a different dimension change the way that we understand water?