Environmental water allocated to rivers to mimic natural flows has long been recognised by governments across the world as being important for stimulating healthy freshwater ecosystems.

The term “environmental water” can have many meanings, but generally it refers to water that is actively managed to benefit the environment. In the Murray–Darling Basin, it has delivered some observable benefits with native fish populations spawning more frequently in some parts of the river system and with healthier streambank vegetation.

However, our current access to environmental water and the benefits it delivers cannot necessarily be expected in the future, according to Andrew John, University of Melbourne PhD candidate.

Many of our environmental-water programs have been developed without considering how climate change might affect the viability of their objectives

In his PhD research, Andrew seeks to understand the outcomes that environmental water can deliver in a changing climate and what this means for water managers. Given that Australia has one of the most variable climate and hydrological systems in the world, this is no easy task.

Most of Australia’s environmental watering programs typically depend on setting up a set of hydrologic reference conditions, based on past natural or pristine environments. These reference conditions can provide a useful benchmark for comparison or targets to aim for.

But under climate change this ignores how the environment will respond to a wider range of changes and it makes a lot of assumptions about how the future will unfold.

Models need to be future-focused, not based on past scenarios or data

Andrew worked with other researchers to conduct a systematic review of scientific literature to understand how different hydrological and ecological methods were being used to assess the effects of climate change on freshwater ecosystems.

They found a sample of 61 modelling studies across the globe that were relevant to freshwater ecosystems and that had well-defined records of their methodologies.

Of these studies, more than three-quarters based their ecological responses only on historical data rather than looking at what might dynamically happen in the future.  The methods used in these studies are usually rapid to implement and might be useful when the rivers are unregulated by dams, weirs and other structures, and there is a high level of confidence in climate-change projections.

But given the complexity and connected nature of ecosystems, and a very high level of uncertainty about future rainfall and stream flows, we really need more dynamic approaches.

Less than 10 per cent of the studies reviewed took an integrated approach to consider how the range of possible climate futures interacts with natural variability, including the sequence of droughts and floods, and how the environment might dynamically respond to these changes.

Many models are based on “stationarity”, which means they look at the past to predict the future, but this assumes ecological relationships and practices do not change.

For example, if the climate changes in a way that increases the distribution of a pest fish species such as carp, native species such as golden perch may be affected by carp’s tendency to remove aquatic plants and stir up the mud in the stream. This means parts of the ecosystem can be affected even if the direct climate-based changes to hydrology do not present a threat.

Golden perch (Macquaria ambigua) will move hundreds of kilometres up and down stream. Research has found that more young fish will survive when there’s free flowing water (0.3m/s) over large distances. (Photo: Gunther Schmida / http://www.guntherschmida.com.au via the Atlas of Living Australia. License: CC BY Attribution-Noncommercial-ShareAlike)

We need more process-based modelling rather than relying only on statistical modelling. If you can simulate the more novel ecological conditions that might happen under climate change, you’ll get a better picture of future scenarios and how effective management responses may be.

Different models can lead to a different understanding of climate change risk

In one example, Andrew and colleagues used two different kinds of models to look at the response of a river red gum forest to flows under climate change.

The first model simply looked at whether flows were large enough to flood important habitat and compared this to the average historical frequency. If this was close, the forest was assumed to remain in a similar condition under climate change.

This however did not tell us how the river red gum forest actually responded or was still suffering from the previous year’s drought, so a simple dynamic model to simulate flows changing over time and project the condition of the forest.

This model took into account that the existing condition of the forest in one year will affect its health in the next, which simulates processes of recovery and decline.

We found that the sequence of flows really matters to the health of the forest and if there were evenly spaced high flow pulses, then there were likely good outcomes for the forest.

But if the flows were spread out and separated by periods of drought, the forest was likely to be under stress.

The simple dynamic model suggested there was a much larger risk from climate change to the health of the river red gum forest compared to the results from the first model, which just looked at whether flows were large enough.

We need models that track condition over time to see how river red gums and other species respond, otherwise we can misrepresent the risks from climate change.

 

 The health of river red gum forests under a changing climate will depend on how they have adapted to a series of changing river flows (Photo: Elizabeth Donoghue/Flickr, CC BY-NC-SA)

 

Using a simple model to stress test climate and environmental changes

Models need to link climatology, hydrology and ecology to achieve a multidisciplinary understanding of the possible effects of climate change.  However, this can lead to complicated models with significantly increased computing time.

Instead, simple models that focus on the main processes mean researchers can rapidly undertake many simulations each with different scenarios, and can quickly assess the impacts of various risks.

Andrew has built a simple model of the Goulburn River to test a wide array of climate and environmental changes. This research part of an Australian Research Council Linkage Project with the Victorian Department of Environment, Land, Water and Planning; the Bureau of Meteorology; the Victorian Environmental Water Holder; and the Goulburn Broken Catchment Management Authority.

 

A simplified model of the Goulburn River would concentrate on the most important aspects of the river, such as large storages and tributaries, and important environmental sites.

The work aims to  find out what the freshwater ecosystems are vulnerable to in terms of climatic changes, and how likely this is to happen. At what point can you just not deliver your environmental water? At what point do you have to make difficult trade-off decisions? For example, if there’s not enough water to meet the needs of all the important fish species, do we concentrate on those with higher conservation values?

The model is ready to be run with a million different scenarios of how the climate might change.  For example, along with long-term changes in average rainfall and temperature, it can also look at changes in climate variability or the characteristics of drivers of persistent drought such as El Niño.

For further information:

Please contact Andrew John through The University of Melbourne, andrew.john@unimelb.edu.au or through Alluvium andrew.john@alluvium.com.au