Characterizing the potential for drought action from combined hydrological and societal perspectives

Drought is a function of both natural and human influences, but fully characterizing the interactions between human and natural influences on drought remains challenging. To better characterize parts of the drought feedback loop, this study combines hydrological and societal perspectives to characterize and quantify the potential for drought action. For the hydrological perspective, we examine historical groundwater data, from which we determine the decadal likelihoods of exceeding hydrologic thresholds relevant to different water uses. Stakeholder interviews yield data about how people rate the importance of water for different water uses. We combine these to quantify the Potential Drought Action Indicator (PDAI). The PDAI is demonstrated for a study site in south-central Oklahoma, where water availability is highly influenced by drought and management of water resources is contested by local stakeholders. For the hydrological perspective, we find that the historical decadal likelihood of exceedance for a moderate threshold associated with municipal supply has ranged widely: from 23&thinsp;% to 75&thinsp;%, which corresponds well with natural drought variability in the region. For the societal perspective, stakeholder interviews reveal that people value water differently for various uses. Combining this information into the PDAI illustrates that potential drought action increases as the hydrologic threshold is exceeded more often; this occurs as conditions get drier and when water use thresholds are more moderate. The PDAI also shows that for water uses where stakeholders have diverse views of importance, the PDAI will be diverse as well, and this is exacerbated under drier conditions. The variability in stakeholder views of importance is partially explained by stakeholders' cultural worldviews, pointing to some implications for managing water when drought risks threaten. We discuss how the results can be used to reduce potential disagreement among stakeholders and promote sustainable water management, which is particularly important for planning under increasing drought.</p

Precipitation downscaling in Canadian Prairie Provinces using the LARS-WG and GLM approaches

Two stochastic precipitation simulation models, namely the Long Ashton Research Station weather generator (LARS-WG) and a Generalized Linear Model-based weather generator (GLM-WG), are evaluated for downscaling daily precipitation at four selected locations (Banff, Calgary, Saskatoon and Winnipeg) in the Canadian Prairies. These weather generators model precipitation occurrence and amount components separately. Large-scale climate variables (including mean temperature, sea level pressure and relative humidity, derived from National Centers for Environmental Prediction reanalysis data) and observed precipitation records are used to calibrate and validate GLM-WG, while only observed precipitation records are used to calibrate and validate LARS-WG. A comparison of common statistical properties (i.e. annual/monthly means, variability of daily and monthly precipitation and monthly proportion of dry days) and characteristics of drought and extreme precipitation events derived from simulated and observed daily precipitation for the calibration (1961-1990) and validation (1991-2003) periods shows that both weather generators are able to simulate most of the statistical properties of the historical precipitation records, but GLM-WG appears to perform better than LARS-WG for simulating precipitation extremes and temporal variability of drought severity indices. For developing projected changes to precipitation characteristics, a change factor approach based on Canadian Global Climate Model (CGCM) simulated current (1961-1990) and future (2071-2100) period precipitation is used for driving simulations of LARS-WG, while for driving GLM-WG simulations, large-scale predictor variables derived from CGCM current and future period outputs are used. Results of both weather generators suggest significant increases to the mean annual precipitation for the 2080s. Changes to selected return levels of annual daily precipitation extremes are found to be both location- and generator-dependent, with highly significant increases noted for Banff with LARS-WG and for both Banff and Calgary with GLM-WG. Overall, 5- and 10-yr return levels are associated with increases (with the exception of Winnipeg) while 30- and 50-yr return levels are associated with site-dependent increases or decreases. A simple precipitation-based drought severity index suggests decreases in drought severity for the 2080s. © 2013 Canadian Water Resources Association