Attribution of detected changes in streamflow using multiple working hypotheses

Abstract

Abstract. This paper revisits a widely cited study of the Boyne catchment in east Ireland that attributed greater streamflow from the mid-1970s to increased precipitation linked to a shift in the North Atlantic Oscillation. Using the method of multiple working hypotheses we explore a wider set of potential drivers of hydrological change. Rainfallrunoff models are used to reconstruct streamflow to isolate the effect of climate, taking account of both model structure and parameter uncertainty. The Mann-Kendall test for monotonic trend and Pettitt change point test are applied to explore signatures of change. Contrary to earlier work, arterial drainage and simultaneous onset of field drainage in the 1970s and early 1980s are now invoked as the predominant drivers of change in annual mean and high flows within the Boyne. However, a change in precipitation regime is also present in March, thereby amplifying the effect of drainage. This new explanation posits that multiple drivers acting simultaneously were responsible for the observed change, with the relative contribution of each driver dependant on the timescale investigated. This work demonstrates that valuable insights can be gained from a systematic application of the method of multiple working hypotheses in an effort to move towards more rigorous attribution, which is an important part of managing emerging impacts on hydrological systems.

Nonstationarity of low flows and their timing in the eastern United States

“…In parallel with calls for more rigorous efforts at attributing changes in flood time series (Merz et al, 2012), increased effort is also needed for understanding and attributing changes in low flows. Several new approaches have been put forward recently that show promise for detecting and attributing changes in hydrological time series, including extremes, based on multiple working hypotheses (Harrigan et al, 2014) and complex statistical modeling (Prosdocimi et al, 2015). The results of this study can help in understanding changes in low flows across the eastern US, and the impact of anthropogenic and natural changes.…”

Human amplified changes in precipitation–runoff patterns in large river basins of the Midwestern United States

“…Despite this apparent correlation, the magnitude of precipitation increases alone cannot explain the observed increases in flow for agricultural basins according to the water balances. Therefore, it appears that the pervasive and extensive artificial drainage in agricultural basins has contributed to increased streamflow, not only at 10 2 -10 3 km watershed scales (e.g., Foufoula-Georgiou et al, 2015;Harrigan et al, 2014;Schilling and Libra, 2003;Schottler et al, 2014;Xu et al, 2013;Zhang and Schilling, 2006), but also at the scale of the very large basins studied here. Harrigan et al (2014) recognize that often multiple drivers explain hydrologic change.…”

“…However, several studies report a reduction of ET early in the growing season (Hickman et al, 2010;McIsaac et al, 2010;Schottler et al, 2014;Zeri et al, 2013) and greater evapotranspiration rates than native prairie during the peak growing season (Wolf and Market, 2007;Zeri et al, 2013). Thus changes in land cover (and ET) and drainage expansion have been found to alter watershed hydrology and increase mean annual flows (Harrigan et al, 2014;Kibria et al, 2016), base flows (Juckem et al, 2008;Robinson, 1990;Schilling and Libra, 2003;Xu et al, 2013), annual peak flows (Dumanski et al, 2015;Magner et al, 2004;Skaggs et al, 1980Skaggs et al, , 1994, and total flow volumes (Dumanski et al, 2015;Frans et al, 2013;Lenhart et al, 2011). While it seems inevitable that altering ET and subsurface drainage efficiency should have measurable effects on streamflow, the combined effects have proven difficult to isolate empirically, especially across scales, due to measurement uncertainties, high temporal and spatial variability in antecedent moisture conditions and runoff processes, a shift towards a wetter climate today than in the historical past, as well as limited documentation of artificial drainage installation in the US.…”

“…While time series and statistical analyses reveal useful insights regarding the timing, magnitude, and significance of precipitation and streamflow changes, as well as provide a qualitative indication of whether or not changes in precipitation and streamflow may be correlated and proportional, they cannot fully deconvolve or attribute the influence of artificial drainage and climate on streamflows (Harrigan et al, 2014). Therefore, we calculate water budgets for each basin as a tool to understand whether the observed changes in precipitation are large enough to account for the changes in streamflow, and whether there is more or less watershed storage in recent times than in the past (Healy et al, 2007).…”

Detection and attribution of urbanization effect on flood extremes using nonstationary flood‐frequency models

“…In this study, the effects of the changes in land use on peak flows are investigated by assessing if any changes can be identified in the observed peak flows of the paired catchments. A possible different approach would be to compare the observed peak flows and the peak flows which one could expect from an hydrological model simulated under a different land use scenario, as in, among others, Brath et al [2006] and Harrigan et al [2014]. Furthermore, in this study a variable which actually describes the dynamic evolution of the catchment land use is used rather than relying on time as a surrogate covariate.…”