Hydrologic nonstationarity and extrapolating models to predict the future: overview of session and proceeding <s> Hydrologic nonstationarity and implications -Overview <s> Summary This paper presents results from a modelling study carried out to investigate whether the calibrated parameter values for rainfall–runoff models based on historical observed data can be used to reliably predict runoff responses to changes in future climate inputs. The modelling experiments are carried out for four rainfall–runoff models using long records of historical daily climate and streamflow data from 61 catchments in southeast Australia. The results indicate that the models, when calibrated using more than 20 years of data, can generally be used for climate impact studies where the future mean annual rainfall is not more than 15% drier or 20% wetter than the mean annual rainfall in the model calibration period. It is generally more difficult for a model calibrated over a wet period to predict runoff over a dry period compared to a model calibrated over a dry period to predict runoff over a wet period. For southeast Australia, there is a good reason to use the recent records to calibrate rainfall–runoff models to represent the current prolonged drought over the region and for climate change impact studies where the large majority of climate models predict a drier future across this region. <s> BIB001 </s> Hydrologic nonstationarity and extrapolating models to predict the future: overview of session and proceeding <s> Hydrologic nonstationarity and implications -Overview <s> [1] Climate impact analyses are usually based on driving hydrological models by future climate scenarios, assuming that the model parameters calibrated to past runoff are representative of the future. In this paper we calibrate the parameters of a conceptual rainfall-runoff model to six consecutive 5 year periods between 1976 and 2006 for 273 catchments in Austria and analyze the temporal change of the calibrated parameters. The calibrated parameters representing snow and soil moisture processes show significant trends. For example, the parameter controlling runoff generation doubled, on average, in the 3 decades. Comparisons of different subregions, comparisons with independent data sets, and analyses of the spatial variability of the model parameters indicate that these trends represent hydrological changes rather than calibration artifacts. The trends can be related to changes in the climatic conditions of the catchments such as higher evapotranspiration and drier catchment conditions in the more recent years. The simulations suggest that the impact on simulated runoff of assuming time invariant parameters can be very significant. For example, if using the parameters calibrated to 1976 – 1981 for simulating runoff for the period 2001 – 2006, the biases of median flows are, on average, 15% and the biases of high flows are about 35%. The errors increase as the time lag between the simulation and calibration periods increases. The implications for hydrologic prediction in general and climate impact analyses in particular are discussed. <s> BIB002 </s> Hydrologic nonstationarity and extrapolating models to predict the future: overview of session and proceeding <s> Hydrologic nonstationarity and implications -Overview <s> AbstractThis paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–... <s> BIB003 </s> Hydrologic nonstationarity and extrapolating models to predict the future: overview of session and proceeding <s> Hydrologic nonstationarity and implications -Overview <s> [1] This paper investigates the actual extrapolation capacity of three hydrological models in differing climate conditions. We propose a general testing framework, in which we perform series of split-sample tests, testing all possible combinations of calibration-validation periods using a 10 year sliding window. This methodology, which we have called the generalized split-sample test (GSST), provides insights into the model's transposability over time under various climatic conditions. The three conceptual rainfall-runoff models yielded similar results over a set of 216 catchments in southeast Australia. First, we assessed the model's efficiency in validation using a criterion combining the root-mean-square error and bias. A relation was found between this efficiency and the changes in mean rainfall (P) but not with changes in mean potential evapotranspiration (PE) or air temperature (T). Second, we focused on average runoff volumes and found that simulation biases are greatly affected by changes in P. Calibration over a wetter (drier) climate than the validation climate leads to an overestimation (underestimation) of the mean simulated runoff. We observed different magnitudes of these models deficiencies depending on the catchment considered. Results indicate that the transfer of model parameters in time may introduce a significant level of errors in simulations, meaning increased uncertainty in the various practical applications of these models (flow simulation, forecasting, design, reservoir management, climate change impact assessments, etc.). Testing model robustness with respect to this issue should help better quantify these uncertainties. <s> BIB004
The commentary by  has initiated significant discussions and continuing progression of research on hydrologic nonstationarity. The term "hydrologic nonstationarity" has been used to describe many things, ranging from different climate-runoff relationships evident in different periods within a long hydroclimate time series to changes in hydroclimate characteristics and dominant hydrological processes in an increasingly warmer and higher CO 2 world. Hydrologists have always represented stationarity and nonstationarity (which is difficult to distinguish statistically in natural systems) as best they could and their implications on water resources and related systems, but modelling this adequately will become increasingly challenging in a world driven by anthropogenic changes. The constancy of laws and patterns has always been and will always be "stationary". It is our understanding or lack of these and the constancy of variables or characteristics at different times that may appear "nonstationary". For example, a hydroclimate time series can be considered "stationary" over thousands or millions of years, in that we can represent statistically or stochastically the characteristics and variability over time and space scales or even develop a precise understanding of the processes from the very long record. But of course, the characteristics of the different periods will always be different (exhibiting variability over different time and space scales), that is, nonstationary over time. The practical issue then is not whether hydroclimate systems are station-ary or nonstationary, but whether the nonstationarity is substantial enough to require a change in existing system characterisation, conceptualisation or modelling for a particular hydrologic design, operation and planning. Hydrologists have excelled in developing models for numerous applications, through analysing and interpreting climate and hydrologic data to understand hydrologic processes, conceptualising the processes in hydrological models, and calibrating and testing models against observations. These models are particularly good in predicting the streamflow response to changes in the climate inputs and catchment characteristics. These models, when developed adequately using relatively long historical records that encapsulate the range of hydroclimate conditions, should be able to predict hydrologic responses to changes in the climate inputs over the near and medium term. However, extrapolating hydrological models to predict further into the future that is influenced by anthropogenic change is challenging as we will then be predicting system behaviours that are beyond the range of observed variability in the instrumental record (changed rainfall characteristics, higher temperature, higher CO 2 ) or that result from significant alterations of the physical system characteristics. Therefore, whilst near-term future projections of water availability (and streamflow, hydrological fluxes and stores) are influenced mainly by the large uncertainty in the rainfall projections BIB003 , water projections further into the future will be increasingly influenced also by the uncertainty in hydrological modelling. Published by Copernicus Publications on behalf of the International Association of Hydrological Sciences.  presents an example of hydrologic nonstationarity and the implications on hydrologic prediction exposed by the prolonged 1997-2009 Millennium Drought in far south-eastern Australia (Fig. 1 ). The unprecedented runoff decline during the drought was caused not only by the lower annual rainfall, but also by changes in other climate characteristics (lack of high rainfall years, change in rainfall seasonality and higher temperatures) and dominant hydrological processes (reduced surface-groundwater connection and farm dams intercepting proportionally more water during dry periods). Because of the significantly different climate-runoff relationship and model conceptualisations that do not adequately represent surface-groundwater connection through long dry spells, it is not surprising then that models developed and calibrated against the pre-1997 data were not able to estimate the flow volumes and runoff characteristics during the drought. However, because the Millennium Drought has exposed these extreme conditions, models can now be developed or adapted to also represent these conditions. There are many similar examples of models not being able to simulate the hydrology of a period with very different hydroclimate characteristics from the period used to develop the models. However, when the models are developed or calibrated using a long data set that encapsulates the different hydroclimate characteristics of different data periods, the models can generally reasonably simulate the hydrology through the different times (although not as well as if the model was calibrated only against data from the period it is simulating) BIB001 BIB002 BIB004 . Therefore, following on from the above Millennium Drought example, hydrological models developed and tested against long historical records are generally reliable until there is a significantly 'changed' condition (like the Millennium Drought). After the changed hydroclimate conditions have been observed (following the end of the Millennium Drought), new conceptualisations can be introduced to the models to also represent these conditions. These newly developed models will then continue to be robust until there is another significant and unexpected changed condition. As we can never have a perfect and complete understanding of the ecohydroclimatological processes and interactions, this future prediction problem can only be overcome if we can anticipate all the plausible changes and conceptualise them adequately in models.