A Dynamic, Multivariate Sustainability Measure for Robust Analysis of Water Management under Climate and Demand Uncertainty in an Arid Environment

Water

Christian Hunter²  Jorge Gironás²  Diogo Bolster³  Christos A. Karavitis¹ 

[1] Department of Natural Resources Management & Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, Athens 118 55, Greece; E-Mail:;Departamento de Ingeniería Hidráulica y Ambiental, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna, Santiago 4860, Chile; E-Mail:;Civil Engineering, Environmental and Earth Sciences Department (CEEES), University of Notre Dame, Notre Dame, IN 46556, USA; E-Mail:

关键词: sustainability assessment;    arid zone hydrology;    watershed modeling;    groundwater;    water supply;    system analysis;    predicative modeling;    climate change;    sociohydrology;    vulnerability;   

DOI  :  10.3390/w7115928

来源: mdpi

【 摘 要 】

Considering water resource scarcity and uncertainty in climate and demand futures, decision-makers require techniques for sustainability analysis in resource management. Through unclear definitions of “sustainability”, however, traditional indices for resource evaluation propose options of limited flexibility by adopting static climate and demand scenarios, limiting analysis variables to a particular water-use group and time. This work proposes a robust, multivariate, dynamic sustainability evaluation technique and corresponding performance indicator called Measure of Sustainability (MoS) for resource management that is more adapted to withstand future parameter variation. The range of potential future climate and demand scenarios is simulated through a calibrated hydrological model of Copiapó, Chile, a case study example of an arid watershed under extreme natural and anthropogenic water stresses. Comparing MoS and cost rankings of proposed water management schemes, this paper determines that the traditional evaluation method not only underestimates future water deficits, but also espouses solutions without considering uncertainties in supply and demand. Given the uncertainty of the future and the dependence of resources upon climate and market trajectories, the MoS methodology proposes solutions that, while perhaps are not the most optimal, are robust to variations in future parameter values and are thus the best water management options in a stochastic natural world.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.