Groundwater drought hazard zoning and relationship between meteorological and hydrological drought indices in the Urmia aquifer

Extended Abstract

Introduction

In recent years, the study of climatic changes has gained significant importance due to the exposure of many regions to climate change conditions. Iran, with its predominantly arid and semi-arid climate, is no exception. Groundwater is a vital resource for Iran’s drinking water, agriculture, and industry, playing a crucial role in its economic development. The horticulture and agriculture sectors in the Urmia aquifer plain heavily depend on groundwater resources. Over the past three decades, reductions in precipitation and excessive extraction of water resources for agricultural and other purposes have led to severe drought, causing irreparable damage to agriculture, industry, and human life. Groundwater drought is characterized by reduced groundwater levels or storage and is influenced by natural and human-induced factors, such as climate change and excessive groundwater extraction. The SPI and SPEI are commonly used to monitor meteorological drought, while the SGI measures hydrological drought. This study investigates sustainable management and protection strategies for the Urmia aquifer, emphasizing the effects of climate change and drought on its groundwater resources. The findings highlight the need for climate change adaptation measures.



Materials and Methods

To analyze the status of the Urmia aquifer, monthly groundwater depth data from piezometers within the aquifer were used to calculate the SGI index. Monthly precipitation data from the Urmia meteorological station in the aquifer plain were utilized to derive the SPI and SPEI indices. The analysis used monthly data from the Urmia aquifer, each providing consistent 20-year datasets. While 30 years is generally recommended as the standard for drought indices, statistical tools such as the correlation coefficient (CC), coefficient of determination (R²), root mean square error (RMSE), Hanna and Heinold index (HH), kappa coefficient (k), Cramer coefficient (V), and class correlation percentage were employed to compare and validate the SPI and SPEI indices for both 20- and 30-year periods. The Pearson correlation coefficient was applied to compare SPI and SPEI at 3, 6, 9, and 12-month scales with the monthly SGI index. ArcMap generated a groundwater drought hazard zoning map, ranking each piezometer based on drought severity, duration, and hazard. The drought severity and duration values were classified into five classes using the Jenks natural interval classification method. The final drought risk values, graded from 1 to 9, were assigned to areas covered by each piezometer using the Thiessen polygon method. Additionally, the correlation for different time lags was estimated to analyze the impact on the correlation between meteorological and hydrological drought indices.



Results and Discussion

The SPI and SPEI indices from 2001 to 2021 exhibited a strong positive correlation with those calculated from 1991 to 2021. Based on the Pearson coefficient, evaluating the correlation of SPI and SPEI indices with the SGI index at 3- to 12-month time scales for each piezometer revealed that correlations were insignificant at 3- and 6-month scales in most piezometers. However, the highest correlations between SGI and SPEI were observed at 9- and 12-month scales. Applying a time lag initially improved correlations across all scales, but correlations diminished beyond a certain point. On average, a time lag of 3 to 5 months increased the correlation. Analysis of the duration and intensity of hydrological drought events indicated that areas with prolonged but low-intensity droughts remained in a drought state for extended periods, struggling to return to equilibrium. Conversely, areas with shorter but more intense droughts experienced intense droughts over short periods but, despite the severity, managed to return to equilibrium. These findings provide practical implications for understanding and predicting drought conditions, offering valuable information for effective groundwater management strategies.



Conclusion

This study investigated the relationship between the hydrological drought SGI derived from groundwater level data and meteorological drought indices over a 20-year statistical period (2001-2021). The shorter analysis period was due to the lack of statistical data and the adequate correspondence between the 20-year monthly data for meteorological drought indices (SPI and SPEI) and the drought index time series obtained from 30-year monthly data. The hydrological drought index (SGI) in the piezometers, which correlated significantly with the drought indices (SPI, SPEI), is primarily influenced by climatic conditions. The low correlation between SPI, SPEI, and the SGI index can be primarily attributed to human factors. Groundwater extraction and social and economic issues are the primary causes of drought in aquifer regions with low SPI-SGI correlation. By assessing drought duration and severity across Thiessen polygons affected by the piezometer, a hydrological drought risk zoning map was developed for the Urmia aquifer. The results indicated that hazard levels 9 and 8 dominated the southern areas of the aquifer, covering 14% and 13% of the surface area, respectively. This map can be a critical tool for selecting appropriate methods to maintain the groundwater level balance. Management plans in high-risk areas should prioritize monitoring human activities such as drilling and water withdrawal, changing crop patterns, and implementing artificial recharge projects. Climatic factors exerted heterogeneous effects on the occurrence of hydrological drought across the entire aquifer. These measures can substantially help the planners and managers in the Urmia Lake Restoration Headquarters and the Regional Water Organization.