A trading-space-for-time approach to probabilistic continuous streamflow predictions in a changing climate – accounting for changing watershed behavior

Abstract

Abstract. Projecting how future climatic change might impact streamflow is an important challenge for hydrologic science. The common approach to solve this problem is by forcing a hydrologic model, calibrated on historical data or using a priori parameter estimates, with future scenarios of precipitation and temperature. However, several recent studies suggest that the climatic regime of the calibration period is reflected in the resulting parameter estimates and model performance can be negatively impacted if the climate for which projections are made is significantly different from that during calibration. So how can we calibrate a hydrologic model for historically unobserved climatic conditions? To address this issue, we propose a new trading-space-for-time framework that utilizes the similarity between the predictions under change (PUC) and predictions in ungauged basins (PUB) problems. In this new framework we first regionalize climate dependent streamflow characteristics using 394 US watersheds. We then assume that this spatial relationship between climate and streamflow characteristics is similar to the one we would observe between climate and streamflow over long time periods at a single location. This assumption is what we refer to as trading-space-for-time. Therefore, we change the limits for extrapolation to future climatic situations from the restricted locally observed historical variability to the variability observed across all watersheds used to derive the regression relationships. A typical watershed model is subsequently calibrated (conditioned) on the predicted signatures Correspondence to: R. Singh (rus197@psu.edu) for any future climate scenario to account for the impact of climate on model parameters within a Bayesian framework. As a result, we can obtain ensemble predictions of continuous streamflow at both gauged and ungauged locations. The new method is tested in five US watersheds located in historically different climates using synthetic climate scenarios generated by increasing mean temperature by up to 8 • C and changing mean precipitation by −30 % to +40 % from their historical values. Depending on the aridity of the watershed, streamflow projections using adjusted parameters became significantly different from those using historically calibrated parameters if precipitation change exceeded −10 % or +20 %. In general, the trading-space-for-time approach resulted in a stronger watershed response to climate change for both high and low flow conditions.

A framework for testing the ability of models to project climate change and its impacts

“…In such situations space-time-substitution offers the possibility to use data from other areas with different climates to infer about climate change impacts in the area of interest. Space-timesubstitution is used in freshwater ecology (Meerhoff et al 2012) and has also been attempted in hydrology (Singh et al 2011) and agroecology (Elsgaard et al 2012). …”

“…For many designs of space-time-substitution schemes it would be possible to add a DSS-test to evaluate how well such projections are able to reproduce temporal variability at different locations. To our knowledge the only example where this has been carried out is the study by Singh et al (2011) who first regionalised climate dependent streamflow characteristics from 394 catchments in the USA and then assumed that this spatial relationship between climate and streamflow characteristics is similar to the one that would occur under a future climate change. They subsequently tested this assumption for five catchments by use of five 10-year historical datasets, where they calibrated on one period and made DSS-tests on four other periods with different precipitation characteristics.…”

Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development

“…Section 5.2 discusses the implementation and success of a small-scale experimental approach to assess the effectiveness of restoration strategies in the Ethiopian uplands. In the Peruvian case (Section 5.1), such a controlled approach is not possible, and therefore a comparative analysis of land-cover types is used as a proxy (sometimes also known as a "trading-space-for-time approach" Singh et al, 2011). However, in other cases simulation experiments will be the only alternative to experiments (Beven et al, 2012, Section 3.5) …”

Advancing catchment hydrology to deal with predictions under change

“…Searching for hydrologic similarities and their organizing principles can help to estimate the future behaviour of existing catchments under changed boundary conditions by trading space for time (Singh et al, 2011). The question of whether spatial and temporal variability can be traded in hydrology has so far been insufficiently addressed.…”