Projections of meteorological drought severity-duration variations based on CMIP6.

This research utilized the outputs from three models of the Coupled Model Intercomparison Project Phase 6 (CMIP6), specifically CanESM5, GFDL-ESM4, and IPSL-CM6A-LR. These models were used under the SSP1-2.6 and SSP5-8.5 scenarios, along with the SPI and SPEI, to assess the impacts of climate change on drought in Iran. The results indicated that the average annual precipitation will increase under some scenarios and decrease under others in the near future (2022-2050). In the distant future (2051-2100), the average annual precipitation will increase in all states by 8-115 mm. The average minimum and maximum temperature will increase by up to 4.85 â„ƒ and 4.9 â„ƒ, respectively in all states except for G2S1. The results suggest that severe droughts are anticipated across Iran, with Cluster 5 expected to experience the longest and most severe drought, lasting 6 years with a severity index of 85 according to the SPI index. Climate change is projected to amplify drought severity, particularly in central and eastern Iran. The SPEI analysis confirms that drought conditions will worsen in the future, with southeastern Iran projected to face the most severe drought lasting 20 years. Climate change is expected to extend drought durations and increase severity, posing significant challenges to water management in Iran.

Decline in Iran's groundwater recharge.

Groundwater recharge feeds aquifers supplying fresh-water to a population over 80 million in Iran-a global hotspot for groundwater depletion. Using an extended database comprising abstractions from over one million groundwater wells, springs, and qanats, from 2002 to 2017, here we show a significant decline of around -3.8 mm/yr in the nationwide groundwater recharge. This decline is primarily attributed to unsustainable water and environmental resources management, exacerbated by decadal changes in climatic conditions. However, it is important to note that the former's contribution outweighs the latter. Our results show the average annual amount of nationwide groundwater recharge (i.e., ~40 mm/yr) is more than the reported average annual runoff in Iran (i.e., ~32 mm/yr), suggesting the surface water is the main contributor to groundwater recharge. Such a decline in groundwater recharge could further exacerbate the already dire aquifer depletion situation in Iran, with devastating consequences for the country's natural environment and socio-economic development.

Field studies, ion analysis, and modeling of Kashan plain aquifer to predict the source of salinization.

The shortage of freshwater and salinization are considered two major development problems in arid and semi-arid regions. The growth of population, development of industry and agriculture, and climate change cause over-extraction of groundwater resources; consequently, the quality and quantity of groundwater decreased, especially in the arid and semi-arid areas. The present study investigates the reasons for salinization of the Kashan aquifer. In this study, 53 observation wells located in the aquifer were examined for qualitative study. A total of 80 samples were collected from selected wells over a period of 5 years (2005-2009) and analyzed for 9 chemical parameters (electrical conductivity (EC), pH, total dissolved solids (TDS), sodium (Na+), potassium (K+), calcium(Ca2+, magnesium (Mg2+), chlorine (Cl-), and bicarbonate (HCO-3)). Groundwater table study shows that the direction of groundwater flow throughout the aquifer is often from the west to the east of the aquifer, except for the northeastern part of the aquifer, where a backflow from the northeast (salt lake) into the aquifer is visible. Results of ion analysis in different areas of the aquifer indicate the occurrence of upconing phenomenon in the center and south regions and the occurrence of saline water intrusion phenomenon in northeast regions. To simulate the condition of the Kashan aquifer for the next 50 years, a model of the quantity and quality of the aquifer was developed using the SEAWAT code. According to the results, the salinization of the Kashan plain aquifer should occur due to two main reasons: irregular groundwater extraction and upconing phenomenon and the intrusion of saline water from the salt lake towards the aquifer. The Kashan aquifer salinization forecast results show that the continuation of the current pumping activities for the next 50 years should increase the numbers of wells affected by salinity. Considering the critical situation of the Kashan aquifer and the existing serious threats, serious decisions and measures for the proper management of groundwater and aquifer protection are vital.

Performance evaluation and verification of groundwater balance using WA + as a new water accounting system.

In this study, to increase the accuracy of determining the parameters of groundwater balance and finally the aquifer reservoir deficit, WA + as a new water accounting system has been applied by calculating six sheets in the Plasjan basin, central Iran. According to the results, the volume of rainfall and transfer flow to the basin was 548.8 MCM in the water year 2016-2017, which entered the hydrological cycle as input. Moreover, the results of FAO's Water Productivity Open-Access Portal (WaPOR) product showed that evapotranspiration was equal to 465 MCM, of which 345 and 120 MCM belonged to green water and blue water, respectively, at the basin level. The results of the WaPOR product showed that 264 MCM of evapotranspiration was beneficial, while the rest was non-beneficial in the basin. Finally, investigating the runoff and utilization of water resources showed that the return flow to surface water and groundwater resources was 35.5 MCM and 62 MCM, respectively. Therefore, the aquifer deficit was estimated to be 56.3 MCM based on the results of the WA + system. By calculating the evapotranspiration using remote sensing in WA + , the return water flow was estimated at 28%, being more accurate compared to the classical groundwater balance. Consequently, the amount of aquifer deficit calculated by the WA + method was accurate according to the balance and the aquifer hydrograph. The findings of this study show that as a suitable tool, the water accounting system can reduce the uncertainty of groundwater balance calculations.

Using insights from water isotopes to improve simulation of surface water-groundwater interactions.

Understanding interactions between surface water (SW) and groundwater (GW) is challenging because of the lack of information available and the complexity of the processes involved. In this paper, SW-GW interactions are simulated using numerical modelling integrated with insights from water isotopes. Isotope analysis can be used to (i) determine the relative contribution from different sources of water into aquifer recharge and (ii) identify areas with high SW-GW interactions. The results, for the Shiraz catchment in Iran, show that (i) SWAT-MODFLOW has better performance than stand-alone SWAT (R2 improvement from 0.50 to 0.54) and (ii) SWAT-MODFLOW calibrated with insights from isotope data (SWAT-MODFLOW-ISO) has significantly better performance than SWAT-MODFLOW (R2 improvement from 0.54 to 0.68 and RMSE reduction from 1.67 to 1.33). This demonstrates that insights into SW-GW interactions that are revealed by isotopes can be used to improve hydrological modelling performance.

DRASTIC framework improvement using Stepwise Weight Assessment Ratio Analysis (SWARA) and combination of Genetic Algorithm and Entropy.

Hybrid and integrated techniques can be used to investigate intrinsic uncertainties of the overlay and index groundwater vulnerability assessment methods. The development of a robust groundwater vulnerability assessment framework for precise identification of susceptible zones may contribute to more efficient policies and plans for sustainable managements. To achieve an overall view of the groundwater pollution potential, the DRASTIC framework (Depth to the water table, net Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, and hydraulic Conductivity) can be used for intrinsic vulnerability assessment. However, the unreliability of this index is because of its inherent drawbacks, including the weight and rating assignment subjectivity. To modify the rating range, this study recommended a new DRASTIC modification using a recently introduced Multi-Criteria Decision-Making (MCDM) method, namely the Stepwise Weight Assessment Ratio Analysis (SWARA); in addition, the Entropy and Genetic Algorithm (GA) methods were employed to alter the relative weights of DRASTIC parameters. To improve the DRASTIC index, nitrate concentration data from 50 observation wells in the study site were used. To assess the models' overall performance, the datasets obtained from new observation wells, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) were studied. The experiments were carried out in the aquifer of the Qazvin Plain in Iran. The results indicated the higher performance of the modified DRASTIC framework, manifested as an increase in the AUC value from 0.58 for generic DRASTIC to 0.68 for the SWARA-Ent framework and 0.74 for the SWARA-GA framework. The application of the SWARA technique, as an effective MCDM method, resulted in the DRASTIC rating system enhancement. The generic DRASTIC optimization by integrating SWARA and GA provided an effective framework to assess groundwater vulnerability to nitrate contamination in the Qazvin Plain.

A new hybrid framework for optimization and modification of groundwater vulnerability in coastal aquifer.

Effects of pollution caused by seawater intrusion into groundwater in coastal aquifers cannot be ignored. Identification of areas exposed to this pollution by preparing vulnerability maps is one way of preventing aquifer pollution. In its primary section, the present study compared three different index ranking methods of DRASTIC, GALDIT, and SINTACS to select an optimal model for determining vulnerability of the Gharesoo-Gorgan Rood coastal aquifer. Initial results led to selection of the GALDIT model for vulnerability assessment of the selected coastal aquifer. Since this type of models use a rating system, the model must be modified and optimized in various regions to show the vulnerable areas more accurately. In the next step, and for the first time, the ratings in this index were modified using the Wilcoxon nonparametric statistical method and its weights were optimized employing particle swarm optimization (PSO) and single-parameter sensitivity analysis (SPSA) methods. Finally, in order to select the best hybrid model, the total dissolved solids (TDS) parameter was used to determine correlation coefficients. Results indicated that the GALDT model modified by the Wilcoxon-PSO method has the strongest correlation (0.77) with the TDS parameter. Moreover, the correlations of the Wilcoxon-GALDIT and Wilcoxon-SPSA models were 0.66 and 0.73, respectively. Final results of the Wilcoxon-PSO model revealed that the northwestern and western areas of the study region needed considerable protection against pollution. In general, we can conclude that by combining statistical, mathematical, and metaheuristic methods, we can obtain more accurate results for preparing vulnerability maps.