A Probabilistic Approach for Characterization of Sub-Annual Socioeconomic Drought Intensity-Duration-Frequency (IDF) Relationships in a Changing Environment

Hadi Heidari,Travis Warziniack,Mahshid Ghanbari,Mazdak Arabi

doi:10.3390/w12061522

Hadi Heidari, Travis Warziniack + Show 2 more

Open Access

https://doi.org/10.3390/w12061522

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Abstract

Changes in climate, land use, and population can increase annual and interannual variability of socioeconomic droughts in water-scarce regions. This study develops a probabilistic approach to improve characterization of sub-annual socioeconomic drought intensity-duration-frequency (IDF) relationships under shifts in water supply and demand conditions. A mixture Gamma-Generalized Pareto (Gamma-GPD) model is proposed to enhance characterization of both the non-extreme and extreme socioeconomic droughts. Subsequently, the mixture model is used to determine sub-annual socioeconomic drought intensity-duration-frequency (IDF) relationships, return period, amplification factor, and drought risk. The application of the framework is demonstrated for the City of Fort Collins (Colorado, USA) water supply system. The water demand and supply time series for the 1985–2065 are estimated using the Integrated Urban water Model (IUWM) and the Soil and Water Assessment Tool (SWAT), respectively, with climate forcing from statistically downscaled CMIP5 projections. The results from the case study indicate that the mixture model leads to enhanced estimation of sub-annual socioeconomic drought frequencies, particularly for extreme events. The probabilistic approach presented in this study provides a procedure to update sub-annual socioeconomic drought IDF curves while taking into account changes in water supply and demand conditions.

Highlights

Climate change and rapid population growth can significantly beget shifts in water supply and demand at various spatial and temporal scales [1,2,3,4,5]
S2) as awas test demonstrated case to investigate the City applicability of the framework water supply system
Population growth along with changes in climate can lead to nonstationary drought conditions where water demand exceeds water supply

Summary

Introduction

Climate change and rapid population growth can significantly beget shifts in water supply and demand at various spatial and temporal scales [1,2,3,4,5]. As the balance between water supply and demand becomes more unequal, socioeconomic drought becomes a major concern [6,7]. Socioeconomic drought refers to the condition when water demand exceeds water supply [6,8,9]. Enhanced probabilistic characterization of socioeconomic drought properties in a changing environment plays an important role in water resource planning and management [7,10,11]. Relationships, return periods, amplification factors, and drought risk under shifts in water supply and demand conditions. This study develops a probabilistic approach to characterize sub-annual socioeconomic drought intensity-duration-frequency (IDF)

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Discussion

Conclusion