I am a hydrologist. And I'm intrigued by the opportunities I see to incorporate gender into biophysical models.
To many of my hydrology colleagues it may sound like I should be standing up at a self-help meeting if I am going to make such proclamations. After all, we're concerned with the physical and quantifiable world. A world governed by physics, a world where variability and uncertainty are still somewhat quantifiable and predictable. Precipitation, streamflow, runoff, evapotranspiration, and groundwater. These are all measurable, and predictable, inputs and outputs of a system we call the water cycle. When we are asked about how we understand this system, it is quite simple: physics.
(Stereotyped) Perception of social sciences from a biophysical scientist's point of view:
Laws that govern our physical world operate irrespective of gender (or any other social variables you might plug in here), and so when biophysical scientists are asked to incorporate gender into their work, sighs and eye-rolls abound. At best, we may be handed off information from spatially referenced paper surveys that we can't link to physically-based models. In the worst case scenario, we are given “stories” that come from meetings or focus groups where we envision the participants all sitting around holding hands.
The idea that social sciences employ rigorous methods and produce results that are not only beneficial to biophysical sciences, but that can also ensure the uptake, adoption, implementation and therefore longevity of our land and water management recommendations, simply never occurs to many of us.
Why? Well, as I told one of my social science colleagues during the CGIAR Research Program on Water, Land and Ecosystems (WLE) Gender and Water Workshop, “it's because you don't have a Nash-Sutcliffe statistic.” I laughed, but there is some merit to this statement as it relates to the language we use to describe our work, and we simply don't speak the same language.
The things is, it doesn't have to be this way. I have the great fortune of coming into the physical sciences later in my education after obtaining my undergraduate education in Philosophy. One of the first questions I asked as I was being trained in hydrology was, “where are all the people in this research we're doing?” I wanted to know how it was possible to truly understand the system, the bigger picture, without incorporating the why and the how of the people interacting with and upon the landscapes.
Leave that to the social scientists to sort out I was often told. And there we all went off operating in parallel pursuing somewhat independent research projects.
But gender doesn't fit in my equation
Imagine if you hired an electrician and a carpenter to come into your home and put in a new wall with a power outlet and they operated in parallel instead of together? You might get a wall in one place and a new electrical outlet in some other place. In despair you'd shake your head saying, “I wanted a new wall with a power outlet not a new wall and a power outlet.” You'd likely never hire that crew again. And, we won't even go into how the two independently decided where to put your, not their, new wall or the power outlet.
I understood that the biophysical models we use cannot take direct inputs about gender into their equations, but I couldn't accept that the way we develop model inputs was the only valid method. On the other hand, I could accept that while the social scientists may derive valuable information from various field methods they employ, it wasn't particularly useful in putting together a biophysical model.
This last point dominates the mind of many biophysical scientists and misses the point entirely.
There are many approaches to modeling biophysical environments and as all modelers are taught from the beginning, “all models are wrong but some are useful”. What makes a model useful? In the context of research for development, it must have a practical application and be grounded in reality. When used to assess trade-offs, model inputs must reflect people because they are the main drivers of change within systems.
Many of the hydrological models employed by researchers require only a few inputs: topography, land use, climate, and soils. We are able to derive these from field surveys, remotely sensed data products, and instruments.
In some cases, generating data that will be used in a model is as much an art as it is a science because at many points assumptions must be made and not all scientists will make them in the same way and sometimes it is based on … preference. In other words, even at this high level, we accept that there are multiple forms of knowledge within some set of parameters or guidelines.
But then can't we generate model inputs from other forms of knowledge, from people's perceptions? And, if we use these inputs to drive biophysical models, what can we learn? What will it tell us about how people understand and interact with the landscape? Could this even lead us to developing improved models or modeling systems?
My "aha" moment
For me, I had an "aha" moment many years ago that really drove home the value and need for incorporating different types of knowledge and perceptions. After developing scenarios with a team of scientists and community members and then running them through various biophysical models, it seemed that we had collectively come up with good land use management alternatives.
This notion was rocked, however when I was looking at a 3-D map made by women in the Njoro watershed where I was working. I noticed that in one area of the river, a path indicating a crossing was present. I also knew that based on my modeling, this area was often under water during the rainy season. It was an area where children crossed the river for school. None of this had come up during meetings or surveys as an issue, but only when people engaged in making maps that are organically derived from people's experience.
So what? Well, the result is that during a portion of the year children cannot go to school and eventually they stop going to school as they become engaged in other activities. In other words, the alternative land management scenarios were not ok, although from a biophysical and economic perspective they were improvements over the current situation on the ground.
Bringing the social and biophysical sciences together
Within the CGIAR Research Program on Water, Land and Ecosystems (WLE), we are embarking on a journey to bring the social and the biophysical sciences together using novel approaches where we recognize that all knowledge is biased to some extent. While in the physical sciences there is a perception that we approach challenges using dispassionate (e.g. quantitative) methods, by taking a step back we can quickly see that the research questions we formulate are in fact grounded in our own life experiences.
Like all people in all aspects of life, we recognize the things we are “trained” to see or have a particular interest in, but miss others. This doesn't invalidate the science we do, but in fact by actualizing this human limitation to knowledge, we open the door of opportunity to advance our science by embracing and coming up with ways to incorporate other forms of knowledge.