Attributing Changes in Streamflow to Land Use and Climate Change for 472 Catchments in Australia and the United States

Abstract

A data-based method to distinguish climate and land use change impacts on streamflow has been previously developed and needs further evaluation through a large sample study. This study aims to apply the method to a large sample set of 472 catchments in the United States and Australia. The method calculates the water and energy budget of a catchment which can be translated to climate and land use induced changes in streamflow between two periods: a pre-change and post-change period. Several geographical characteristics (e.g., aridity index, average catchment slope, historical land use) were considered for the interpretation of the results. The results show that in general as expected, an increase of the annual discharge is caused by deforestation and a wetter climate, and a decrease of the annual discharge is caused by afforestation and a drier climate. In addition, changes in streamflow of American catchments are likely caused by a wetter climate, while changes in streamflow of Australian catchments are caused by a wetter or drier climate. It can be concluded that the method performs reasonably well and that the results are best explained by the location of the catchment, the aridity index and historical land use.

Climate change and other trends in streamflow observations in Australian forested catchments since 1970

“…For example: some studies focused on a few rivers (Petrone et al, 2010;Potter & Chiew, 2011), some focused on the whole Murray-Darling water balance (Cai & Cowan, 2008). In contrast other studies used a more comprehensive data base of catchments (Booij et al, 2019;Chiew, 2006;Trancoso et al, 2017).…”

“…Finally, the models and types of analyses varied across the studies, including simple linear regression on un-transformed and transformed data (Cai & Cowan, 2008;Chiew, 2006;Chiew, Potter, et al, 2014;Potter, Petheram, et al, 2011), non-parametric Mann-Kendall and step change methods (Petrone et al, 2010;Potter & Chiew, 2011), statistical analyses and using rainfall runoff models (Chiew, 2006;Potter, Chiew, et al, 2010) and applying an energy framework (Booij et al, 2019) and focussing on baseflow (Trancoso et al, 2017). As a result, despite a consistent view of a sharply declining streamflow in response to changing rainfall, it is difficult to compare across studies.…”

“…There is a further issue with the earlier work, including some of the latest work on the changes in catchment responses with drought (Ajami et al, 2017; Booij et al, 2019; Saft et al, 2015). Most studies included in a mixture of land covers and in some cases post‐analysed for the effect of land cover.…”

“…An alternative approach to biophysical modelling with future climate scenarios to understand changes in future water yield, would be to analyse historical data sets (Booij et al, 2019; Cai & Cowan, 2008; Chiew, Whetton, et al, 1995; Petrone et al, 2010; Potter, Petheram, et al, 2011; Trancoso et al, 2017). However, there are several reasons why the issue of trends in streamflow might need revisiting.…”

“…For example: some studies focused on a few rivers (Petrone et al, 2010; Potter & Chiew, 2011), some focused on the whole Murray‐Darling water balance (Cai & Cowan, 2008). In contrast other studies used a more comprehensive data base of catchments (Booij et al, 2019; Chiew, 2006; Trancoso et al, 2017). Finally, the models and types of analyses varied across the studies, including simple linear regression on un‐transformed and transformed data (Cai & Cowan, 2008; Chiew, 2006; Chiew, Potter, et al, 2014; Potter, Petheram, et al, 2011), non‐parametric Mann‐Kendall and step change methods (Petrone et al, 2010; Potter & Chiew, 2011), statistical analyses and using rainfall runoff models (Chiew, 2006; Potter, Chiew, et al, 2010) and applying an energy framework (Booij et al, 2019) and focussing on baseflow (Trancoso et al, 2017).…”