Burnishing my notes for UNM Water Resources class this afternoon to talk about Elinor Ostrom, I spent a bit of my morning going back through the underlined bits in my copy of her seminal book Governing the Commons. I first read it in the fall of 2009, when she won the Swedish prize. My initial scratchings in the book – Wait, what? They imposed constraints on themselves? – are instructive.
My rereading of Ostrom comes as I’m in the midst of a little side project digging into the history of something called the “Colorado River Simulation System”, a computer model that is central to 21st century Colorado River management. CRSS, as it’s called, brings together the best hyrdologic understanding of how the basin operates with policy rules, serving as a sort of common language for talking about the river and making decisions about its future.
It is impossible to overstate the impact of the intellectual light bulb that fall when I first read Ostrom. I’d recently finished my first book and was eyeing taking a stab at writing something about the Colorado River. Lake Mead had been steadily dropping and, fully steeped in the “tragedy of the commons” narrative, I imagined that my task was to chronicle its collapse. The federal government did not seem up to the task of imposing a centralized authority on the system, and the “tragedy of the commons” conventional wisdom suggested water users would be unwilling to impose constraints on themselves?
Yet here was Ostrom, as characterized by the Nobel committee’s press release:
Elinor Ostrom has challenged the conventional wisdom that common property is poorly managed and should be either regulated by central authorities or privatized. Based on numerous studies of user-man-aged fish stocks, pastures, woods, lakes, and ground-water basins, Ostrom concludes that the outcomes are, more often than not, better than predicted by standard theories. She observes that resource users frequently develop sophisticated mechanisms for decision-making and rule enforcement to handle conflicts of interest, and she characterizes the rules that promote successful outcomes.
Crucially, Ostrom argued that such successful problem solving was not a given. But she offered an intellectual toolkit for understanding what to look for.
Central to that is what, in Governing the Commons, she described (in her case study of Southern California’s Raymond Basin) as “a single, authoritative ‘image’ of the problem.” This amounts to a common, data-based understanding of the system on which decisions can be based, scenarios played out.
In the years since, I have come to understand the way CRSS plays that role. A sophisticated model built on the Riverware platform, it is used by the Bureau of Reclamation, major water agencies across the basin, environmental groups, and university researchers to study the implications of drought, climate change, and water policy options as we navigate the Colorado River Basin’s future. It is, to borrow a phrase from one of the people I spoke with while working on my little dive into CRSS’s history, the common language we speak in the basin.
Want to know what the risk of Lake Powell dropping to levels at which Glen Canyon Dam can no longer generate electricity? The Colorado River District’s Risk Study used CRSS to do that. Want to know the risk of a continuation of the dry conditions of the 21st century continuing, or worsening? We have the “Stress Test” and the “Super Stress Test”, simulations written in the language of CRSS, a language that basin managers can understand, to help us. Want to evaluate climate change scenarios against paleo droughts? Homa Salehabadi and colleagues at Utah State have done that, offering their answers in CRSS, a language decision makers can understand.
It is not without its limitations. It constrains the questions you can ask, and I watch people struggle now to bend it to the task of sorting out things like environmental flows through the Grand Canyon, or better understanding the Upper Colorado River Basin’s consumptive uses, past and future. Some of the constraints are technical. Some are political. But for the basic task of helping the basin’s water management community understand its choices, providing an “authoritative image”, it continues to perform admirably.
Although the CRSS simulations behind the 2007 Guidelines were the best that we could do at that time, I came to know that the modeling and its algorithms wasn’t problematic, as were the assumptions made that went into the model. For example, I would have preferred to see the stress test hydrology or a worst-case hydrology incorporated in 2007 than what was simulated at the time. The paleo reconstructions were a good start but didn’t go far enough to simulate the system. As it turned out, the guidelines needed modification with the drought contingency plans, which essentially indicated the model was not calibrated to current conditions.
John, thank you for refreshing our memories of the important work and writings of Elinor Ostrum, and in particular, for her emphasis on the great importance of “a single, authoritative image of the problem.” I’ve seen how difficult it is to make progress in river management or policy-making in absence of agreement around a consensus image (e.g., ‘the battle of the models’). I agree that the CRSS has provided a very useful mechanism or tool for framing an image of the water problems we face in the Colorado River Basin. But a computer model is not in itself an image; instead, it is the output of the model that helps to frame the image, and in this sense it is critically important to gain agreement around the INPUTS into the model. For example, some climate scientists have argued that the way that climate change forecasts have been formulated for input into CRSS-based planning need to be substantially improved. In this sense, the existence of “a single authoritative image” will always be an ephemeral one, always requiring that we continually sharpen and renew that image as learning advances.
Thanks, I think I meant but didn’t explain well something slightly different than your interpretation regarding, for example, the role CRSS might plan in climate change scenario analysis. I did not mean, by talking about shared understanding, to imply the one particular operational version of CRSS used by the Bureau, doing index sequential analysis using the historic record. I meant the shared understanding provided by the underlying representation of the river system’s performance under a range of scenarios, which provides the shared confidence and understanding when people want to apply different inputs, do the “stress test” hydrology, or the new “super stress test” people are using, or the work Homa Salehabadi and colleagues are doing to study paleo and climate change, etc.
alas, if her point was true the world wouldn’t be in such rotten shape and still getting worse. some parts are doing ok, but where there is a shared resource to be exploited if it doesn’t get exploited by those immediately around it then others from further away will come along to do the honors.
cases in point abound.