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A Trading-space-for-time Approach to Probabilistic Continuous Streamflow Predictions in a Changing Climate : Volume 8, Issue 4 (01/07/2011)

By Singh, R.

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Book Id: WPLBN0004012968
Format Type: PDF Article :
File Size: Pages 33
Reproduction Date: 2015

Title: A Trading-space-for-time Approach to Probabilistic Continuous Streamflow Predictions in a Changing Climate : Volume 8, Issue 4 (01/07/2011)  
Author: Singh, R.
Volume: Vol. 8, Issue 4
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2011
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Singh, R., Wagener, T., Werkhoven, K. V., Mann, M., & Crane, R. (2011). A Trading-space-for-time Approach to Probabilistic Continuous Streamflow Predictions in a Changing Climate : Volume 8, Issue 4 (01/07/2011). Retrieved from http://hawaiilibrary.net/


Description
Description: Department of Civil and Environmental Engineering, The Pennsylvania State University, Sackett Building, University Park, PA 16802, USA. Understanding the implications of potential future climatic conditions for hydrologic services and hazards is a crucial and current science question. The common approach to this problem is to force a hydrologic model, calibrated on historical data or using a priori parameter estimates, with future scenarios of precipitation and temperature. Recent studies suggest that the climatic regime of the calibration period is reflected in the resulting parameter estimates and that the model performance can be negatively impacted if the climate for which projections are made is significantly different from that during calibration. We address this issue by introducing a framework for probabilistic streamflow predictions in a changing climate wherein we quantify the impact of climate on model parameters. The strategy extends a regionalization approach (used for predictions in ungauged basins) by trading space-for-time to account for potential parameter variability in a future climate that is beyond the historically observed one. The developed methodology was tested in five US watersheds located in dry to wet climates using synthetic climate scenarios generated by increasing the historical mean temperature from 0 to 8 °C and by changing historical mean precipitation from −30 % to +40 % of the historical values. Validation on historical data shows that changed parameters perform better if future streamflow differs from historical by more than 25 %. We found that the thresholds of climate change after which the streamflow projections using adjusted parameters were significantly different from those using fixed parameters were 0 to 2 °C for temperature change and −10 % to 20 % for precipitation change depending upon the aridity of the watershed. Adjusted parameter sets simulate a more extreme watershed response for both high and low flows.

Summary
A trading-space-for-time approach to probabilistic continuous streamflow predictions in a changing climate

Excerpt
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