Assessing water security and footprint in hypersaline Lake Urmia
Publication Name
Ecological Indicators
Abstract
The quantitative assessment of water security including its distribution helps plan and manage adequate amounts of quality water to sustain livelihoods. This research introduces a hydrological modeling framework designed to evaluate the spatial and temporal fluctuations of blue water and green water, aiming to quantify the water security status of Lake Urmia in Iran. This lake, recognized as the second largest hypersaline lake globally, has experienced a significant decline in its water storage in recent years. This model, based on water consumption and population size was used to investigate water security and footprint while quantifying the spatial and temporal changes in the availability of blue water and green water. As the results demonstrate, the monthly and annual coefficient of variation for blue water (41.1 % and 27.6%, respectively) was greater than for green water (32.3% and 21.7%, respectively), hence green water flow showed more homogeneous than blue water flow distribution among different sub-basins. At the same time, the coefficient of variation for the spatial distribution differs between various components of the water footprint. Agricultural use requires the most water in this basin, with a blue water scarcity of 0.27. The blue water vulnerability value for total water consumption indicates a lower risk of a water crisis under low-flow conditions. In addition, the freshwater provision indicator in each sub-basin varies between the middle (0.64) and lower (0.80) parts. Thus, in these parts, water can be consumed with less negative impact on the environment. In conclusion, the environmental situation of Lake Urmia and its water security has clearly decreased over the last decade which requires urgent management action (e.g., changing irrigation pattern) to mitigate an environmental crisis. This research offers precise and quantifiable references related to water resources and water security, and can enhance targeted water footprint management within the study area. Our hydrological modeling framework provides the basis to inform water management in various similar watersheds across the globe.
Open Access Status
This publication may be available as open access
Volume
155
Article Number
110955