Non-stationary Hydrology

When 'normal' changes: non-stationary hydrology

As we have discussed at length above, floods and droughts can have significant impacts on society and the environment. However, as also discussed above, we can characterize the frequency, duration and magnitude of these rare or extreme events and both human and natural systems have mechanisms to deal with them. For example, we can estimate the magnitude of a 100 year flood and build a bridge sufficiently large to pass the flood with minimal risk of damage to the bridge or changes in water depth (i.e., from water backing up behind the bridge and therefore flooding additional land upstream). Similarly, we can compute the width of floodplain that would be inundated from that 100 year flood and choose to not build within that flood corridor, or choose to require those who do build within the flood corridor to purchase flood insurance to cover costs of potential damages.

Similarly, as we discussed in module 3, river channels naturally adapt their width and depth to accommodate common floods. Thus, society and the environment naturally develop some amount of resiliency to historical climate extremes. However, all of the prediction methods we have discussed so far in this module rely on the assumption that the future will look statistically similar to the past (i.e., the distribution of events will not change and occurrence of events in the future will be consistent with the probabilities computed from the histograms or probability density functions such as those shown in Figures 3 and 4). This assumption is known as the Stationarity Assumption in hydrology. Specifically, stationarity implies that while there is considerable variability in precipitation and streamflow, that variability is bouncing around a relatively constant average value and has a relatively constant spread, as shown in the hypothetical plot of peak streamflow over time in the left panel of Figure 17. From left to right, the mean ( ?) and standard deviation (s, i.e., the spread of the data around the mean) don't change. However, as climate changes, the magnitudes, durations and frequencies of floods and droughts may occur that are outside the historical range of observations, resulting in a change in the average magnitude of floods (Figure 17, middle panel) or a change in the variability of floods (Figure 17, right panel). In either of these situations the statistics from the left side of the graph don't provide a good basis for making predictions about the right side of the graph (or predicting what will happen in the future!). Understanding and accounting for such non-stationary patterns in precipitation and streamflow are among the greatest challenges in hydrology today because we need to make accurate future predictions for many decisions about flood and drought risk, infrastructure design (roads, bridges, culverts, ditches, parking lots, detention basins, sewers, etc.!) and water availability. So this is a hot topic in the field and many new techniques are emerging!

Non-stationarity will be common in the future as regional climates systematically change. According to the Intergovernmental Panel on Climate Change, climatic warming will increase the risk of both floods and droughts (Table SPM2 in IPCC, 2007; see also IPCC, 2014). The multitude of factors that combine to ultimately cause floods and droughts are exceptionally difficult to predict over the next few decades. Nevertheless, there is a high level of agreement among the competing IPCC climate simulation models regarding the general trends of several metrics. For example, precipitation intensity increases are expected most places and especially at mid- and high-latitudes where mean precipitation also increases. Summer droughts are also expected to increase over low and mid-latitude continental interiors. Snowpack is expected to decline overall as more precipitation will fall as rain rather than snow, especially in areas with temperatures near 0 °C in fall and spring. Relatedly, snowmelt is projected to occur earlier. The combination of less snowpack and earlier snowmelt increases risk of summer to fall drought in snowmelt dependent regions, such as the western US. Some regions outside the US are highly dependent on melt water from glaciers for water supply. Accelerated melting due to climatic warming increases the risk of flooding downstream in the near-term. In the long-term, glaciers in many of these areas will shrink and ultimately cease to exist, posing a serious threat to downstream water supply. This poses a serious risk to the hundreds of millions of people in China and India who depend on glacial melt water from the Hindu Kush-Himalayas. In closing, there is good reason to expect floods and droughts to become more severe in the coming decades, increasing the urgency for improved predictions, mitigation efforts, and adaptation strategies.