Explore the vast range of titles available.

Small communities in the Kingdom of Saudi Arabia (KSA) without a sewerage system commonly rely on septic tanks and long-distance transport of wastewater to the nearest centralized treatment facilities, resulting in high operational costs, social nuisance, and limited opportunities for treated effluent reuse. For a small community of 1300 persons in Al Qaraa (Qassim, KSA), this study performs life cycle analysis (LCA) to evaluate the environmental sustainability of a low-cost membrane bioreactor (LC-MBR)-type for decentralized on-site treatment as an alternative to wastewater transportation to a conventional extended aeration activated sludge process (EA-ASP)-type centralized system operating in the nearest larger city of Al-Bukayriyah. SimaPro® 8.3.0.0 with the ecoinvent 3.0 database and ReCiPe 16 midpoint methodology shows that the decentralized LC-MBR scenario outperformed the centralized option with a 49 km-long wastewater transportation route in 13 out of 15 selected midpoint categories when considering relative and normalized impacts. In the EA-ASP, primary treatment dominated environmental impacts across most categories, driven by high energy demand for wastewater pumping, whereas freshwater and marine eutrophication were primarily influenced by treatment efficiency. With smaller normalized values, secondary treatment had a greater relative impact on urban and agricultural land occupation categories, attributed to the use of clay and rice bran in low-cost membrane fabrication in an LC-MBR. Tertiary treatment in the LC-MBR scenario, incorporating coagulation and granular activated carbon, significantly reduced freshwater eutrophication. Although normalized endpoint impacts indicated comparable ecosystem impacts for both systems, the LC-MBR resulted in 8% lower impacts on human health and 60% lower on resource depletion. Overall, the findings support decentralized wastewater treatment as a sustainable solution for small communities in arid regions and provide valuable insights for policy and decision-making.

The combination of hard (artificial) and soft (natural) solutions i.e., composite defense systems against flooding and tsunami opens a new window for engineering innovation for researchers nowadays. In this study, the experimental investigation of flood energy dissipation phenomena through composite defense systems comprising of embankment and rigid vegetation models in an open channel flume, is conducted. The flow regime through the composite defense system is classified in two main types, which are further subdivided in two sub-categories. Various combinations of embankment and vegetation and spacing between embankment and vegetation are analyzed. Against the selected range of initial Froude numbers, three different sizes of embankment models, three spacings between the embankment and vegetation (Ldv) and vegetated corridors of two different porosities (PR), are tested to examine the effect of these three parameters on the characteristics of the generated hydraulic jumps and flood energy dissipation within the defense system. It is found that embankment size and vegetation porosity have a greater impact on flood energy dissipation while the selected range of Ldv is less effective. Amongst the assessed composite flood defense systems, the maximum energy dissipation (55%) is observed for the combination of maximum embankment height and vegetation porosity (93%). For fixed combinations of embankment size and Ldv, the maximum increase of energy dissipation (18%) is found for decreasing vegetation porosity from 97% to 93%.

Previous experimental research on utilizing pier modifications as countermeasures against local scour has focused primarily on circular pier. It is of utmost importance to further investigate the most suitable pier shape for pier modification countermeasure separately and in combination. This experimental study aims to reduce the stagnation of the flow and vortex formation in front of the bridge pier by providing a collar, a hooked collar, a cable, and openings separately and in combination around a suitable pier shape. Therefore, six different pier shapes were utilized to find out the influence of pier shape on local scouring for a length–width ratio smaller than or equal to 3. A plain octagonal shape was shown as having more satisfactory results in reducing scour compared to other pier shapes. Furthermore, the efficiency of pier modification was then evaluated by testing different combinations of collar, hooked collar, cable, and openings within the octagonal bridge pier, which was compared to an unprotected octagonal pier without any modification. The results show that by applying such modifications, the scour depth reduced significantly. The best combination was found to be a hooked collar with cable and openings around an octagonal pier. It was revealed that the best combination reduced almost 53% of scour depth, as compared to an unprotected octagonal pier.

A probabilistic methodology assessed hydraulics, water consumption, distribution pumping, and households pumping from the ground to rooftop storage for energy consumption in 24/7 and 2-day supply scenarios in two distribution networks, each with 379 and 959 service connections and diverse topographies. A local market survey gathered the characteristics of thirty-two household-level pumps used in the area. Considering a per capita daily water consumption of 250 L, probabilistic analysis revealed that the daily operating time of household pumps varied from 0.155 to 0.17 h at the median and from 0.37 to 0.47 h at a 0.9 probability, highlighting variation in household sizes within the study region. The study observed 26% higher energy consumption with a 24/7 supply compared to a 2-day supply for the average household size of 5.6 persons. The 2-day supply exceeded the 24/7 energy requirement for households larger than 8.7 (exceedance probability of 0.1), due to the longer operational hours. Sensitivity analysis identified the household pump’s operating time as the most critical contributor to the intermittent supply’s energy. Considering the consumers’ concerns on water quality in the realistic case, the study found ~ 60% higher energy (0.069 kWh/person/day) and carbon emissions (18.45 kg CO 2 eq/person/year) for 35% consumers using a household-level purifier, 60% bottled water, and 5% trusting in supplied water in comparison to a 24/7 supply. Instead of controlling water loss through intermittent supply, a shift to continuous supply with proactive maintenance can compensate for the additional costs by providing better water quality, satisfied customers, and a reduced global energy and carbon footprint for water supply systems in arid regions.

Elevated salinity in unconfined aquifers limits residents’ use of groundwater for drinking in agricultural settings in KSA. The study developed a probabilistic dermal risk assessment methodology for heavy metals exposure through washing and bathing activities in farms across the Qassim Region, which addressed the uncertainties associated with limited data and vagueness in site-specific exposure factors, such as skin surface area and body weight. Groundwater monitoring established the probabilities of Ba, Cd, Cr, Mn, and Zn levels exceeding the maximum allowable concentrations (MAC) as 0.03 mg/L, 0.003 mg/L, 0.15 mg/L, 0.01 mg/L, and 0.01 mg/L, respectively. A hazard index with a 0.99 probability of less than 1 indicates an insignificant non-cancer risk associated with dermal exposure. The study found an incremental lifetime cancer risk (ILCR) of 6E-5 for Cd and 8E-5 for Cr at median probability, less than the acceptable cancer risk of 1.0E-4. ILCR values of 3.2E-4 for Cd and 2.2E-04 for Cr at 0.9 probability remained lower than the corresponding values of 9E-4 (Cd) and 3.1E-4 (Cr) estimated for the MAC values recommended for KSA. Monte Carlo simulations highlighted Zn (59.5%), Cr (18.1%), and exposure time (10.5%) as the primary contributors to variations in non-cancer health risks to infants. Cd (60.1%) and Cr (46.2%) concentrations, along with exposure time (12.6% for Cd and 25.8% for Cr), were identified as key contributors to ILCR variations. The estimated heavy metal pollution indices at 0.95 probability indicate non-contaminated groundwater. The study offers insights into the health risks and guidelines for treating raw water at the household level, promoting agricultural sustainability in Saudi Arabia and elsewhere.

As a major component of the hydrologic cycle, rainfall runoff plays a key role in water resources management and sustainable development. Conceptual models of the rainfall-runoff process are governed by parameters that can rarely be directly determined for use in distributed models, but should be either inferred through good judgment or calibrated against the historical record. Artificial neural network (ANN) models require comparatively fewer such parameters, but their accuracy needs to be checked. This paper compares a Hydrologic Engineering Centre-Hydrologic Modeling System (HEC-HMS) conceptual model and an ANN model based on the conjugate gradient method for streamflow prediction. Daily precipitation, temperature, and streamflow data of the Upper Indus River for a period of 20 years (1985–2004) are used as input for calibrating in the case of the HEC-HMS, and for training in case of the ANN. Ten years of data (2005–2014) are used to validate the HEC-HMS model and test the ANN. The performance of the models is assessed using different statistical indicators such as the Nash–Sutcliffe efficiency (NSE), root mean square error (RMSE), mean bias error (MBE), and the coefficient of determination (R2). The results show good predictions for streamflow in the case of both HEC-HMS and ANN models. A parametric study is conducted using Monte Carlo analysis and finds that the most important parameters for HEC-HMS models are the storage coefficient and the time of concentration; while for ANN models, input combinations are the most important. This study investigates the sensitivity of these parameters, which can be used to determine preliminary estimation ranges of their values for future modeling. Finally, evaluating the impact of the simulated streamflow’s accuracy on the flow duration curve shows that the curve is significantly affected by any streamflow simulation inaccuracy.

In this study, a series of laboratory experiments were conducted to investigate the energy loss through the hybrid defense system (HDS) in the order of dike, moat, and emergent vegetation in steady subcritical flow conditions. The results of HDS were compared with a single defense system (SDS) comprising only vegetation (OV). The dimensions of dike were kept constant while two different shapes (trapezoidal and rectangular) of moat were considered. The impacts of vegetation of variable thickness and density were investigated. Two combinations of HDS were investigated including the combination of dike and vegetation (DV) and the combination of dike, moat, and vegetation (DMV). The effect of backwater rise due to the vegetation, hydraulic jump formation and the impact of the arrival time of floodwater on energy dissipation were investigated. It was observed that on the upstream side of obstructions, the backwater depth increased by increasing the Froude number in both the SDS and HDS. The hydraulic jump observed in HDS was classified and the energy dissipation due to it was calculated. Under various conditions investigated in this paper, the maximum average energy dissipation was 32% in SDS and 46% in HDS. The trapezoidal moat performed better than rectangular moat as energy dissipater. The delay time was also greater with trapezoidal moat as compared to that in rectangular one. The maximum delay time was 140 s in the case of HDS. Hence, the hybrid defense system offered maximum resistance to the flow of water, thus causing a significant energy loss. For each case of SDS and HDS, empirical equations were developed by regression analysis to estimate the energy dissipation amounts.

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.

Future predictions of rainfall patterns in water-scarce regions are highly important for effective water resource management. Global circulation models (GCMs) are commonly used to make such predictions, but these models are highly complex and expensive. Furthermore, their results are associated with uncertainties and variations for different GCMs for various greenhouse gas emission scenarios. Data-driven models including artificial neural networks (ANNs) and adaptive neuro fuzzy inference systems (ANFISs) can be used to predict long-term future changes in rainfall and temperature, which is a challenging task and has limitations including the impact of greenhouse gas emission scenarios. Therefore, in this research, results from various GCMs and data-driven models were investigated to study the changes in temperature and rainfall of the Qassim region in Saudi Arabia. Thirty years of monthly climatic data were used for trend analysis using Mann–Kendall test and simulating the changes in temperature and rainfall using three GCMs (namely, HADCM3, INCM3, and MPEH5) for the A1B, A2, and B1 emissions scenarios as well as two data-driven models (ANN: feed-forward-multilayer, perceptron and ANFIS) without the impact of any emissions scenario. The results of the GCM were downscaled for the Qassim region using the Long Ashton Research Station’s Weather Generator 5.5. The coefficient of determination (R2) and Akaike’s information criterion (AIC) were used to compare the performance of the models. Results showed that the ANNs could outperform the ANFIS for predicting long-term future temperature and rainfall with acceptable accuracy. All nine GCM predictions (three models with three emissions scenarios) differed significantly from one another. Overall, the future predictions showed that the temperatures of the Qassim region will increase with a specified pattern from 2011 to 2099, whereas the changes in rainfall will differ over various spans of the future.

The present study investigated the performance of three different stilling basins, i.e., modified United State Bureau of Reclamation (USBR) Type III, USBR Type II, and wedge-shaped baffle blocks (WSBB), using FLOW-3D scour models. Field data of the riverbed profile are employed to validate the present models. After comparison, the results of statistical indices, i.e., coefficient of determination (R2) and Nash–Sutcliffe model efficiency coefficient (NSE), indicated that the Renormalization Group (RNG-K-ϵ) showed good agreement with the field data, with R2 and NSE values of 0.9094 and 0.896, respectively. Validated models are used to simulate velocity field and local bed shear stress (BSS) and scour for design and flood discharges of 28.30 m3/s/m and 17.5 m3/s/m, respectively. At 28.30 m3/s/m, the results indicated that the riverbed downstream of the remodeled basin was completely exposed, while, at 17.5 m3/s/m, the net change in bed reached 85%. At 28.30 m3/s/m, the net change at the centerline of models reached 51% and 67% in USBR Type III and WSBB basins, respectively. At 17.5 m3/s/m, compared to Type II and III basins, the WSBB basin indicated less BSS, which significantly reduced the scour. Conclusively, the Type II basin showed less energy dissipation for the studied flows, while the WSBB basin improved flow fields downstream of the barrage.