Limited groundwater resources in arid regions have been found polluted for drinking purpose due to the presence of natural minerals and radioactive substances, in the sub-soils, higher than the drinking water quality standards. Municipalities in these regions are spending extensive resources to transport (from well fields) and treat this raw water to provide safe water to the community. Regular monitoring of various physical, chemical, and radioactive water quality parameters (WQPs) in raw water generates large datasets, which makes it difficult to come up with convenient findings for both the decision-makers and general public. A hierarchical water quality assessment framework develops three sub-indices, an overall water quality index, and a system for ranking of groundwater wells. Fuzzy analytical hierarchy process (fuzzy-AHP) establishes the importance weights of different WQPs and the sub-indices based on their impacts on human health, treatment processes, distribution system infrastructure, and irrigation applications. Fuzzy VIekriterijumsko KOmpromisno Rangiranje (fuzzy-VIKOR) method aggregates the WQPs’ performance for each well and ranks all the wells in a well field based on their overall pollution levels, i.e., remoteness from the applicable standards. For evaluating the pragmatism of the framework, data of 11 WQPs were obtained for 39 wells operating in three different well fields located along the boundaries and the central part of Buraydah, Qassim, Saudi Arabia. Spatial water quality maps showing physical, chemical, radioactive, and overall water quality assessment results revealed that the oldest well field located in the middle of the city outperforms the other two more recently developed well fields with lesser anthropogenic activities in their catchments. These findings testify that the primary source of contamination in deep aquifers is the natural sub-soil condition. The water quality indices will be useful to demonstrate the current situation of groundwater quality in Qassim Region and will facilitate the decision-makers for defining the intended uses of raw water sources (i.e., drinking, unrestricted irrigation, and restricted irrigation) and rehabilitation and renewal planning of the groundwater wells. The framework is applicable in the Kingdom of Saudi Arabia (KSA), Gulf Region, and elsewhere for groundwater quality assessment with desired modifications.

In arid regions such as Saudi Arabia, wastewater treatment (WWT) facilities (meeting promulgated standards) need to adapt their continuous performance improvement (CPI) for long-term sustainability. To achieve this, the facilities need to improve their performance to comply with more strict objectives for broader reuse applications of treated effluent. The present research proposes a CPI framework based on performance benchmarking process for the stepwise improvement of WWT facilities. A grey rational analysis water quality index (GWQI) based on exceedance probability was developed. For weights’ estimation of 11 physical, chemical, and biological water quality parameters, the entropy method effectively accommodated the changes in relative importance of the parameters with including additional future reuse applications. For existing effluent reuse scenarios of restricted and unrestricted irrigation, the GWQI values were found consistent with the modified version of the Canadian WQI (CWQI). The indices’ values (ranged between 0 and 100) greater than 80 showed the efficient operation of four WWT plants in the Qassim Region of Saudi Arabia. Two hypothetical CPI scenarios with future reuse applications (fish, livestock drinking, and recreation) showed an overall decline in the average (of four plants) values of the GWQI (97 to 78) and CWQI (85 to 60). CWQI predicted stricter results for the facilities with parameters’ concentrations exceeding the targets with larger margins and was found applicable for the CPI of WWT facilities in arid regions. For existing scenarios, the assessment results suggest the facilities to control and monitor the chlorination practice. For future targets, tertiary treatment needs to be enhanced for desired nutrients and total dissolved solids removal. The proposed CPI framework provides a platform to initiate the performance benchmarking process for WWT facilities at local or regional levels in Saudi Arabia and elsewhere.

Management of backwash water (BW) generated from sand filtration of groundwater naturally contaminated with iron (Fe), manganese (Mn), and radium (Ra) remains a challenge worldwide. The present study investigated the effectiveness of a low-cost clay ceramic filter for BW recycling along with residual sludge utilization for Ra removal from BW. A 15 day continuous ceramic filtration process operated at a constant flux of 2000 L/m²/d (83 LMH) showed 99% removal of Fe, Mn, and turbidity. The treated BW was found suitable for recycling back to the sand filters. Subsequently, the residual sand filter backwash sludge (BS) was collected, characterized by scanning electron microscopy (SEM) and X-ray diffraction, and examined as a potential adsorbent to the Ra. Results showed that the sludge constituted heterogeneous basic elements, with higher percentages of iron and manganese oxides. The sludge can be classified as typical mesoporous and poorly crystalline minerals consisting primarily of quartz and Mn₂O₃. Over 60% of Ra from the initial 2.1 bq/L could be removed by sludge in 30 min at neutral pH. The adsorption kinetics of sludge described well by the pseudo-second order model and Ra adsorption on the sludge were mainly controlled by chemisorption rate-controlling steps, intraparticle diffusion, and external mass transfer processes. Treatment of BW by low-cost clay ceramic filters and the utilization the BS for Ra removal would be a sustainable sand filter BW management practice.

The conventional point-estimate human health risk assessment (HHRA) primarily uses average concentrations of a limited number of samples due to the high monitoring costs of heavy metals in groundwater. The results can be erroneous when concentrations significantly deviate from the average across the collected samples in an investigation region. The present research developed a hierarchical fuzzy-based HHRA (F-HHRA) framework to handle variations in limited data sets and subjectively established a broader range of risks for various exposure groups. Groundwater samples from 80 to 120 m deep in shallow wells were collected from agricultural farms along Wadi Rumah in the Qassim Region of Saudi Arabia. Laboratory testing found total dissolved solids much higher than the promulgated drinking water quality standards. As the aftertaste issue eliminated the raw water potability, the study considered dermal exposure for HHRA. The collected samples were tested for thirteen potential heavy metals (HMs), including barium (Ba), boron (B), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), lead (Pb), lithium (Li), manganese (Mn), silver (Ag), strontium (Sr), thallium (TI), and zinc (Zn). Cu, Fe, Pb, Ag, and TI were lower than the detectable limit of the inductively coupled plasma mass spectrometry device. Concentrations of the remaining HMs in wastewater outfalls that were much less than the groundwater eradicated the impact of anthropogenic activities and affirmed natural contamination. Apart from 10% of the samples for Mn and 90% of the samples for Sr, all the other HMs remained within the desired maximum allowable concentrations. Point-estimate and fuzzy-based approaches yielded ‘low’ dermal non-cancer risk and cancer risk for all groups other than adults, where dermal cancer risk of Cr remained in the ‘acceptable’ (1 × 10⁻⁶ and 1 × 10⁻⁵) risk zone. Although dermal risk does not require controls, scenario analysis established the rationality of F-HHRA for more contaminated samples. The proposed hierarchical F-HHRA framework will facilitate the decision-makers in concerned agencies to plan risk mitigation strategies (household level and decentralized systems) for shallow well consumers in Saudi Arabia and other arid regions.