Water Extraction Rates Research Articles

Feasibility study of underground CO2 storage through Water Alternative Gas (WAG) operation: A case study in Southwestern Ontario

Geological CO2 storage (GCS) offers a promising, low-risk, long-term solution for carbon sequestration. This study assesses the feasibility of GCS water-alternating-gas (WAG) operations in a brine formation targeted for the Western Ontario GCS plan. The Cambrian strata shows potential for CO2 storage but faces challenges like limited lateral extension and geopolitical issues from plume migration. To mitigate these risks, a deep evaluation of CO2 trapping mechanisms is crucial. CO2 dissolution into brine provides secure storage by reducing the free plume. The proposed WAG operation promotes dissolution, using a vertical equilibrium model coupled with a black oil model to estimate CO2 trapping proportions during and post-injection. The Taguchi design of experiments investigates various WAG scenarios with minimal simulations, reducing numerical costs. Sensitivity analysis/optimization of WAG parameters, including water extraction rate (WER), water injection rate (WIT), and CO2 injection time (CIT), ranked their effectiveness in CO2 dissolution. Optimal WAG operations can reduce the free plume by 49 % and increase the dissolution ratio from 0.26 to 0.52. CIT and WIT were found to be the most influential factors, contributing 42 % and 31 % to CO2 dissolution, and 43 % and 34 % to overall CO2 trapping, respectively, while WER exhibited a lower impact of 8–9%.

Effect of ultrasonic pretreatment on textural properties and sensory attributes of cooked faba beans

Drying process extends the shelf-life of fresh faba beans and makes them available all year round. Dried and cooked faba beans are used to make a variety of traditional food products. Ultrasonic pretreatment, as a modern food processing technology, can shorten the drying time of fresh legumes and improve the quality and sensory properties of products. So, the present study aimed to analyze the impact of the ultrasonic treatment process (0, 5, 10, and 15 min, 40 kHz, and 150 W) on the mass transfer rate, drying time, and effective moisture diffusivity (Deff) of fresh faba beans. Also, the effect of ultrasonic treatment on textural properties and sensory attributes of cooked faba beans was studied. By using the ultrasonic process, the rate of water extraction from fresh faba beans, and thus their dehydration rate, can be increased. With increasing the duration of ultrasonic pretreatment from 0 to 15 min, the drying time of fresh faba beans decreased from 250 min to 150 min (p < 0.05). The Deff was calculated by Fick’s second law, and it significantly increased from 0.70 × 10−9 m2 s−1 to 1.05 × 10−9 m2 s−1 when the sonication duration was extended from 0 to 15 min (p < 0.05). The Page model best fitted the drying kinetic of fresh faba beans with a coefficient of determination (r) > 0.9968, and the sum of squared error (SSE) and root mean squared error (RMSE) were also closer to zero compared to other models. The rehydration ratio of dried faba beans (after cooking) significantly increased from 308.4 % to 327.1 % with the extension of processing time from 0 to 15 min (p < 0.05). The maximum and minimum crust hardness and texture firmness values were for the untreated and sonicated samples for 15 min, respectively. The sonication increased the sensory acceptance of the cooked faba beans and the highest appearance, odor, texture, flavor, and overall acceptance were for the 10 min sonicated faba beans.

A review of surfactants as synergists in the field of enhanced oil recovery

The efficient development of oil resources is significant for alleviating the increasingly serious contradiction between oil supply and demand and ensuring national oil security. Surfactant flooding technology is one of the essential methods to enhance oil recovery and has been widely used in oil and gas development. The screening and development of traditional surfactants for oil displacement are mainly focused on reducing interfacial tension based on the theory of capillary number while ignoring the emulsification effect of surfactants. For different types of residual oil/remaining oil, the main contradictions faced by the target reservoir should be thoroughly analyzed to clarify whether the performance of surfactants used for oil displacement is mainly to reduce interfacial tension or strong emulsification capacity, and then screen surfactants suitable for reservoir characteristics and crude oil properties. In this article, the principle and application of surfactant flooding technology are reviewed from two aspects of interfacial tension and emulsification performance, the interrelationship between interfacial tension and emulsification capacity is explored, and the evaluation indicators and existing problems of surfactant used for oil displacement are analyzed in detail. Most of the evaluation methods for emulsification in the past were based on water extraction rate. A method for evaluating the emulsification ability of surfactants to crude oil is introduced. It is expected to provide scientific guidance for the screening and development of surfactants for oil displacement.

Research on the ratio of multicomponent emulsion flooding system

In recent years, field test and industrialized application of ASP (alkaline/surfactant/polymer) flooding has been carried out in oilfields, which has obtained an obvious effect on increasing oil and decreasing water and good economic efficiency. However, due to the large proportion of alkali in the ASP flooding system, there are problems such as severe scaling and high cost during field tests, which restrict the promotion of ASP flooding. In order to reduce the amount of alkali used, achieve the goal of reducing scaling and costs, and meanwhile improve emulsification performance while maintaining interfacial activity, a multicomponent emulsion flooding system was developed by combining emulsifier HEFR2 with petroleum sulfonate and sacrificial agent LSCP1 with NaOH.Through laboratory experiments, the water extraction rate, particle diameter, Tsi value, and interfacial activity of the multicomponent emulsion flooding system were tested under different conditions. The results show that when the mass ratio of petroleum sulfonate to emulsifier HEFR2 is between 3:1 and 5:1, and the mass ratio of sacrificial agent LSCP1 to NaOH is between 3:1 and 7:1, the multicomponent emulsion flooding system can maintain good emulsification stability and interfacial activity. The multicomponent emulsion flooding system significantly reduces the amount of alkali used, and the cost of chemical agents is 11% lower than that of the ASP flooding system. At the same time, it achieves the goal of improving the stability of emulsifiers, maintains interfacial activity and reduces costs. This technology has broad application prospects.

Extraction, Purification, and Structural Characterization of Polysaccharides from Sanghuangporus vaninii with Anti-Inflammatory Activity.

In order to obtain homogeneous Sanghuangporus vaninii polysaccharides with antioxidant and anti-inflammatory activities, a response surface method (RSM) was used to compare the polysaccharide extraction rate of hot water extraction and ultrasonic-assisted extraction from Sanghuangporus vaninii. The optimal conditions for ultrasonic-assisted extraction were determined as follows: an extraction temperature of 60 °C, an extraction time of 60 min, a solid-liquid ratio of 40 g/mL, and an ultrasonic power of 70 W. An SVP (Sanghuangporus vaninii polysaccharides) extraction rate of 1.41% was achieved. Five homogeneous monosaccharides were obtained by gradient ethanol precipitation with diethylaminoethyl-cellulose (DEAE) and SephadexG-100 separation and purification. The five polysaccharides were characterized by high performance liquid chromatography, the ultraviolet spectrum, the Fourier transform infrared spectrum, TG (thermogravimetric analysis), the Zeta potential, and SEM (scanning electron microscopy). The five polysaccharides had certain levels of antioxidant activity in vitro. In addition, we the investigated the anti-inflammatory effects of polysaccharides derived from Sanghuangporus vaninii on lipopolysaccharide (LPS)-induced RAW 264.7 cells and Kupffer cells. Further, we found that SVP-60 significantly inhibited the levels of pro-inflammatory cytokines, such as interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α in lipopolysaccharide (LPS)-induced RAW 264.7 cells and promoted the level of the anti-inflammatory cytokine IL-10 in lipopolysaccharide (LPS)-induced RAW 264.7 cells. Our study provides theoretical support for the potential application of Sanghuangporus vaninii in the field of antioxidant and anti-inflammatory activities in vitro.

Semi-analytical model of heat transport around a well with wellbore mixing effect under multi-step flow rate

Modeling heat transport around a well is critical for evaluations of aquifer thermal energy storage (ATES). In this study, an innovative heat transport model considering the wellbore mixing effect under multi-step flow rate in an aquifer system is proposed, where thermal conduction, thermal dispersion, and convection occur in the aquifer. Wellbore mixing effect refers to the influence of mixing processes between the injected water and original water in the well on heat transport in aquifer, which was ignored in existing models. A semi-analytical solution derived from Laplace transform method and Green’s function method has been validated by the numerical modeling and field experimental studies. Results show that the wellbore mixing effect should not be ignored in analyzing heat transport around a well in the ATES system, and the new solution satisfactorily interprets the field data. The influence of the thermal dispersion on thermal transfer near the injection/extraction well is sensitive and should not be negligible. Morris global sensitivity analysis demonstrates that the output temperature is most sensitive to the variations of the parameters of wellbore water volume and extraction rate than the others. The influence of water volume decreases with time, and the most sensitive parameter becomes extraction rate in the late stage of the extraction phase. The newly developed model can shed some light on the thermal transfer processes in the ATES system and better interpret the experimental data of the single-well push–pull tests.

An improved sharp interface model for characterizing the transport and extraction of subsurface LNAPL

Multiphase extraction (MPE) is widely used as an in situ method for the remediation of groundwater contaminated by light non-aqueous liquid (LNAPL). For the purpose of achieving the best performance of MPE remediation, it is critical to accurately characterize the LNAPL transport processes above the groundwater table with an easy-to-use model. In this study, we developed an improved sharp interface model considering constant head at the well screen and shark-fin distribution of LNAPL saturation above groundwater table. The model was successfully validated using the test data of Lari et al. (2018). The results indicate, the LNAPL extraction rate is most sensitive to the properties of fluid and media. Also, this improved model was used to analyze the effects of technical parameters such as submersible position of oil pump and water extraction rate on remediation performance, we observed that in the case of a single-pump MPE, even after changing the hydraulic conductivity and porosity of the media, the optimized location of the submersible LNAPL pump is halfway inside the well. Similarly, in the case of dual-pump MPE, an increasing pump rate of water (Qw) promotes the LNAPL extraction rate, and an empirical relationship between the optimized LNAPL pump position (ms) varies with the Qw exhibiting a certain pattern. Overall, the improved sharp interface model better interprets the field MPE data compared to the interphase mass-transport model proposed by Lari et al. (2018). Therefore, the proposed model characterizes LANPL transport during LNAPL extraction better and can also be utilized to optimize the MPE more comprehensively.

Prediction of various parameters of desalination system using BOA- GPR machine learning technique for sustainable development: A case study

The present study examines the performance of desalination based atmospheric water extraction system under various climate situations. The Bayesian optimisation for model training hyperparameters was used to make the process autoregressive, and the Gaussian Process Regression (GPR) technique was used to develop the prediction model. Because of its capacity to incorporate data-specific uncertainties and non-linearities, the GPR model was highly efficient in calculating the efficiency of system in different environmental circumstances. For its prognostic efficiency, the model was examined using multiple statistical methods such as R2, mean squared error (MSE), and mean absolute error (MAE). The findings revealed that the GPR model. The prediction model's statistical parameters showed a high prognostic efficiency, with a training R2 of 0.97, MSE of 7282.3, RMSE of 85.34, and MAE of 63.93, and a test R2 of 0.98, MSE of 7596.3, RMSE of 87.16, and MAE of 72.49. Overall, this paper provides a valuable contribution to developing Desalination technology in different climatic regions. The research also sheds light on the relationship between input variables (climatic conditions) and output variables (energy intensity and water extraction rate) for constructing and optimizing desalination based water extraction system for various geographies and climates.

Management of water Issues in Taiz basin, Yemen

Generally, the study area including the city of Taiz, in particular is suffering from an acute shortage of water due to the increase of the growing demand on water for domestic and industrial needs as well as the water needs for agriculture in the region. In addition, the water resources in the study area are limited to the aquifers while water extraction rates exceed the natural recharge and the use is not effective. Therefore, it highlights the importance of water demand management to maintain the quantity and quality of drinking water and domestic use, irrigation and industry. The objectives of this study is to evaluate current and future vulnerability of water sources in the study area; Development of scenarios and analysis of future water balance to find out the best solution to the problem of water in Taiz basin as the study area; Select the appropriate scenario to resolve the water problem. The results of this study will assist decision makers in the field of water resources for better planning and management in the future. During the period 15/1/2013 to 15/4/2013 Implementation of the field study in 1501water points, these water points are distributed between 954 hand-dug well, 479 deep well, 50 springs, five water collection tanks, two dams, and six water retaining walls. For calculating the amount of water supply in the region and the amount of water deficit, in addition to knowing the amount of needs that must be secured in the future, Water Evaluation And Planning (WEAP) application as Decision Support System (DSS) to manage the supply and demand for water in Taiz basin as the study area. The analysis and results using WEAP program include the following themes: Ground water storage in the aquifers: The usable storage for the base year of the model (2013) has been calculated for the five sub-basins in the study area, Estimated ground water storage in alluvial aquifer (in Mm3) ranged 221.52-&#x0D; 415.36 Mm3 at best estimate at 332.29 Mm3, groundwater storage in Volcanic aquifer ranged 129.98-2599.52 Mm3 at best estimate 259.95, whereas groundwater storage in sandstone aquifer ranged 5.044- 50.44Mm3 at best estimate at 10.088; Unmet water demand, The gap between supply and demand for water in the study area was estimated as (47,692,840.9 m3). Preliminary, set of adaptation strategies that address water scarcity; Interpret the proposed set of adaptation strategies to solve water issue from improve water services and water management for the urban area as part of the study in Central and Al Hawban Sub Catchment:&#x0D; (Increase the coverage rates for water services, Diversify water sources for the city, Efficient water management, Implementation of control and water quality program in water sources and drinking water factories, Development of specialized human cadres technically and administratively for the development of water management, Flow of water services from different water sources….. etc.); and Improve water projects and water management for the rural area as part of the study area Al Dabab Sub Catchment, Al Janad Sub Catchment and Thi- Sufal Al Haimah Sub Catchment: Commitment of the Commission basin management to Upper Rasyan Valley, The formation of committees Sub-water basin to ensure the management of water resources from the lower level, Resolving water conflicts in different regions of the study area and the basin provider of water to the city of Taiz, Community participation by establishment of water users associations (WUAs) in the sub- basin areas.&#x0D;

MOF-Derived nanoarchitectured carbons in wood sponge enable solar-driven pumping for high-efficiency soil water extraction

Soil-water extraction based on interfacial solar-thermal technology is a promising strategy to provide affordable freshwater in remote and poor inland areas. A double-layer solar evaporator is prepared on a wood sponge with a one-step brush-printing coating of zeolitic imidazolate framework-8 (ZIF-8)-derived nanostructured carbon. In this typical architecture, the ZIF-8-derived carbon coating inherits the original porous, dodecahedral framework, thus forming a chapped, rough morphology that synergistically promotes photothermal conversion. Wood sponges manufactured from raw wood offer privileged water-extraction advantages, including an abundance of super hydrophilic channels that ensure efficient bulk-water pumping and steam release. The double-layer solar evaporator shows high sunlight absorbance (∼97.8 %), low thermal conductivity (0.12 W m−1 K−1), stronger capillary force, and rapid water transport (30 cm min−1). Consequently, apparent pure water-evaporation and soil water-extraction rates reach 1.42 and 0.57 kg m-2h−1 under a one-sun light intensity, respectively. Therefore, the ZIF-8-based wood sponge can efficiently achieve interfacial evaporation and soil water extraction, providing a novel pathway for obtaining clean drinking water in arid inland areas.

Postmortem analysis of safe-yield estimation of a heterogeneous aquifer for rural water supply

Sustainable groundwater management is founded on the sound understanding of the effects of water extraction on the aquifer water level and the springs and streams receiving groundwater discharge. Pumping test data are commonly used in extraction licence applications to evaluate aquifer properties and assess the magnitude of storage depletion resulting from pumping. However, a short duration (eg 48 hours) pumping test can fail to detect the presence of aquifer boundaries, as the cone of depression is not large enough to reach the boundaries. This may cause an underestimation of long-term drawdown and an overestimation of permissible extraction rate (ie safe yield). In the rural town of Irricana in Alberta, groundwater extraction licences for municipal water supply wells were issued in the early 1980s based on the analysis of 48-hour pumping tests. Actual water extraction rates were substantially below the licensed rates, but the unanticipated and excessive drawdown in the aquifer forced the town to discontinue pumping and switch to surface water supply after 25 years. To examine the cause of overallocation, a new 48-hour pumping test was conducted in the same aquifer, which included an extended drawdown analysis using 26 days of recovery data. Geological formation logs for existing wells in the area surrounding Irricana were used to infer the extent of sandstone aquifer units within the heterogeneous bedrock formation. The new data analysis showed that the aquifer is semi-closed, contrary to the infinite-aquifer assumption used in the original pumping test, which caused additional drawdown due to the aquifer boundary effects. This study suggests an improved procedure for estimation of storage depletion using standard hydrogeological methods and readily available data. The new procedure provides a useful tool as part of adaptive groundwater management, in which water levels and other relevant variables are monitored and licensed extraction rates are adjusted accordingly.

Dry Season Transpiration and Soil Water Dynamics in the Central Amazon.

With current observations and future projections of more intense and frequent droughts in the tropics, understanding the impact that extensive dry periods may have on tree and ecosystem-level transpiration and concurrent carbon uptake has become increasingly important. Here, we investigate paired soil and tree water extraction dynamics in an old-growth upland forest in central Amazonia during the 2018 dry season. Tree water use was assessed via radial patterns of sap flow in eight dominant canopy trees, each a different species with a range in diameter, height, and wood density. Paired multi-sensor soil moisture probes used to quantify volumetric water content dynamics and soil water extraction within the upper 100 cm were installed adjacent to six of those trees. To link depth-specific water extraction patterns to root distribution, fine root biomass was assessed through the soil profile to 235 cm. To scale tree water use to the plot level (stand transpiration), basal area was measured for all trees within a 5 m radius around each soil moisture probe. The sensitivity of tree transpiration to reduced precipitation varied by tree, with some increasing and some decreasing in water use during the dry period. Tree-level water use scaled with sapwood area, from 11 to 190 L per day. Stand level water use, based on multiple plots encompassing sap flow and adjacent trees, varied from ∼1.7 to 3.3 mm per day, increasing linearly with plot basal area. Soil water extraction was dependent on root biomass, which was dense at the surface (i.e., 45% in the upper 5 cm) and declined dramatically with depth. As the dry season progressed and the upper soil dried, soil water extraction shifted to deeper levels and model projections suggest that much of the water used during the month-long dry-down could be extracted from the upper 2–3 m. Results indicate variation in rates of soil water extraction across the research area and, temporally, through the soil profile. These results provide key information on whole-tree contributions to transpiration by canopy trees as water availability changes. In addition, information on simultaneous stand level dynamics of soil water extraction that can inform mechanistic models that project tropical forest response to drought.

Development of lean, efficient, and fast physics-framed deep-learning-based proxy models for subsurface carbon storage

We present deep-learning-based surrogate models for CCUS developed with four different algorithms and a physics-framed two-phase flow problem involving displacement of water by CO2. The deep-learning models were trained using 3D datasets describing the pressure plume, CO2 saturation plume, and water extraction rate generated by numerical simulation. The hyperparameters defining the architecture of the neural networks were optimized to determine the slimmest network size and training parameters that give the most efficient performance at the least training cost. To develop a robust model that closely mimics the governing physical laws, the discretized form of the two-phase fluid transport equation was used to formulate the supervised deep-learning task. The algorithms investigated in this study predicted the data to above 95% accuracy, with the multi-layer perceptron model demonstrating the best performance by balancing training speed, prediction time, and prediction accuracy with lean network capacity. Furthermore, the surrogate models simultaneously predict reservoir pressure and CO2 saturation in every grid block, including the surface well extraction rate and bottomhole pressure, at all simulation times for a given static model realization in just a few seconds on a standard desktop computer. A key outcome of this study is that limits can be placed on network design parameters to avoid over designing neural networks, with associated efficiencies in training and prediction times. This is very useful because large volumes of data may be generated in CCUS projects and over-design of neural network architectures imposes penalties that are antithetical to the goal of near-real time forecasting.

Topographically moderated soil water seasons impact vegetation dynamics in semiarid mountain catchments: Illustrations from the Dry Creek Experimental Watershed, Idaho, USA

AbstractWater stored in soils, in part, controls vegetation productivity and the duration of growing seasons in wildland ecosystems. Soil water is the dynamic product of precipitation, evapotranspiration and soil properties, all of which vary across complex terrain making it challenging to decipher the specific controls that soil water has on growing season dynamics. We assess how soil water use by plants varies across elevations and aspects in the Dry Creek Experimental Watershed in southwest Idaho, USA, a mountainous, semiarid catchment that spans low elevation rain to high elevation snow regimes. We compare trends in soil water and soil temperature with corresponding trends in insolation, precipitation and vegetation productivity, and we observe trends in the timing, rate and duration of soil water extraction by plants across ranges in elevation and aspect. The initiation of growth‐supporting conditions, indicated by soil warming, occurs 58 days earlier at lower, compared with higher, elevations. However, growth‐supporting conditions also end earlier at lower elevations due to the onset of soil water depletion 29 days earlier than at higher elevations. A corresponding shift in peak NDVI timing occurs 61 days earlier at lower elevations. Differences in timing also occur with aspect, with most threshold timings varying by 14–30 days for paired north‐ and south‐facing sites at similar elevations. While net primary productivity nearly doubles at higher elevations, the duration of the warm‐wet period of active water use does not vary systematically with elevation. Instead, the greater ecosystem productivity is related to increased soil water storage capacity, which supports faster soil water use and growth rates near the summer solstice and peak insolation. Larger soil water storage does not appear to extend the duration of the growing season, but rather supports higher growing season intensity when wet‐warm soil conditions align with high insolation. These observations highlight the influence of soil water storage capacity in dictating ecological function in these semiarid steppe climatic regimes.

The fate of the Caspian Sea under projected climate change and water extraction during the 21st century

The Caspian Sea (CS) delivers considerable ecosystem services to millions of people. It experienced water level variations of 3 m during the 20th century alone. Robust scenarios of future CS level are vital to inform environmental risk management and water-use planning. In this study we investigated the water budget variation in the CS drainage basin and its potential impact on CS level during the 21st century using projected climate from selected climate change scenarios of shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs), and explored the impact of human extractions. We show that the size of the CS prescribed in climate models determines the modelled water budgets for both historical and future projections. Most future projections show drying over the 21st century. The moisture deficits are more pronounced for extreme radiative forcing scenarios (RCP8.5/SSP585) and for models where a larger CS is prescribed. By 2100, up to 8 (10) m decrease in CS level is found using RCP4.5 (RCP8.5) models, and up to 20 (30) m for SSP245 (SSP585) scenario models. Water extraction rates are as important as climate in controlling future CS level, with potentially up to 7 m further decline, leading to desiccation of the shallow northern CS. This will have wide-ranging implications for the livelihoods of the surrounding communities; increasing vulnerability to freshwater scarcity, transforming ecosystems, as well as impacting the climate system. Caution should be exercised when using individual models to inform policy as projected CS level is so variable between models. We identify that many climate models either ignore, or do not properly prescribe, CS area. No future climate projections include any changes in CS surface area, even when the catchment is projected to be considerably drier. Coupling between atmosphere and lakes within climate models would be a significant advance to capture crucial two-way feedbacks.

A novel two-step approach for optimal groundwater remediation by coupling extreme learning machine with evolutionary hunting strategy based metaheuristics

We propose a simulation-optimization (SO) model based on a novel two-step strategy for the optimal design of groundwater remediation systems. The SO models are developed by coupling simulation models directly or through the extreme learning machine (ELM) with evolutionary hunting strategy based metaheuristics (EHSMs). In the first step, EHSMs with a combinatorial optimization technique are used to obtain optimal pumping locations by minimizing the percentage of contaminant mass that remained in the aquifer while keeping the pumping strategy as constant. In the second step, the optimal pumping locations are directly used as input, and a composite function is employed to minimize the sum of the water extraction rates and the percentage of extracted contaminant mass by constraining hydraulic heads and contaminant concentrations. The performance of the two-step strategy is found to be slightly better and computationally more efficient than the alternate approach. Moreover, various statistical measures suggest the superiority of EHSMs over other metaheuristics for groundwater remediation.

Groundwater extraction reduces tree vitality, growth and xylem hydraulic capacity in Quercus robur during and after drought events

Climate change is expected to pose major direct and indirect threats to groundwater-dependent forest ecosystems. Forests that concurrently experience increased rates of water extraction may face unprecedented exposure to droughts. Here, we examined differences in stem growth and xylem hydraulic architecture of 216 oak trees from sites with contrasting groundwater availability, including sites where groundwater extraction has led to reduced water availability for trees over several decades. We expected reduced growth and xylem hydraulic capacity for trees at groundwater extraction sites both under normal and unfavourable growing conditions. Compared to sites without extraction, trees at sites with groundwater extraction showed reduced growth and hydraulic conductivity both during periods of moderate and extremely low soil water availability. Trees of low vigour, which were more frequent at sites with groundwater extraction, were not able to recover growth and hydraulic capacity following drought, pointing to prolonged drought effects. Long-term water deficit resulting in reduced CO2 assimilation and hydraulic capacity after drought are very likely responsible for observed reductions in tree vitality at extraction sites. Our results demonstrate that groundwater access maintains tree function and resilience to drought and is therefore important for tree health in the context of climate change.

Performance assessment of waste heat/solar driven membrane-based simultaneous desalination and liquid desiccant regeneration system using a thermal model and KNN machine learning tool

In this work, the waste heat/solar heat-driven membrane-based liquid desiccant regenerator performance, as well as desalinated water extraction rate, are predicted and analyzed by developing a thermal model and KNN–ML tool. In the membrane-based liquid desiccant regenerator, water is used as a working fluid instead of scavenging air for desalinated water extraction purpose. The proposed thermal model and KNN-ML tool are validated with the literature data and found in good agreement. Optimal inlet conditions were determined for the given operating range using the thermal model and KNN–ML tool. With vapor flux and energy exchange as the performance indicators, the water extraction rate and thermal performance of the membrane-based liquid desiccant regenerator are predicted for the optimal inlet condition using the KNN-ML tool. Also, the heat and mass transfer characteristics such as Lewis number and NTUm across the membrane in the liquid desiccant regenerator are assessed using the developed thermal model. Further, for the optimal inlet conditions, utilizing waste heat from thermal power plants (Method–I) and solar energy from solar heater (Method–II), the thermal performance and water extraction rate across the membrane in the liquid desiccant regenerator are assessed based on the developed thermal model.

A regret-based behavioral model for shared water resources management: Application of the correlated equilibrium concept

The competition over water use in shared water resources systems may lead to conflict. Conflict can lead to strategic behaviors with the consequence of “Tragedy of Common” in water resources. In this paper, a novel approach is proposed for the quantity and quality management of shared water resources using the Correlated Equilibrium (CE) concept. For the first time in water resources management studies, a Reinforcement Learning (RL)-based method, namely Regret Matching (RM), is proposed to simulate agents' behaviors. In the proposed methodology, an agent, which is responsible for water allocations, tries to reduce illegal water withdrawal from resources, using some non-mandatory and mandatory suggestions. This agent's objectives are leading the system towards social optimality (SO) and reaching the environmental sustainability goal. A modified RM algorithm is also developed for behavioral simulation in urban areas. The proposed methodology's applicability and efficiency are evaluated considering some criteria such as the concentration of the nitrate pollutant in groundwater, the groundwater table fluctuations, the rate of illegal water extraction from the groundwater, and the stakeholders' general satisfaction. The results of applying the methodology to the western part of the Tehran metropolitan area show its ability to deal with the water and treated wastewater allocation problems in urban areas and increase in the learning and cooperation among agents. According to the results, a meaningful decrease in nitrate concentration in the aquifer and an increase in groundwater table levels are observed. The results also indicate that the model could teach the stakeholders to act more responsibly towards protecting the environment and conserving shared water resources.

Use of mature willows (Salix nigra) for hydraulic control of landfill-impacted groundwater in a temperate climate

Phreatophytic trees such as willows and poplars have a large capacity for extracting shallow groundwater, as evidenced by diurnal water table fluctuations corresponding to intensified transpiration during the day. As a result, they have been employed for phytoremediation of shallow contaminated groundwater. In this study, the water extraction (i.e. pumping) capacity of mature willows (Salix nigra) to capture shallow polluted groundwater in Belle Park, the site of a former landfill in Kingston, Ontario (Canada), was assessed using continuous field measurements of sap flow and water table levels associated with a single willow tree, combined with a transient numerical model (FEFLOW). On an annual basis, the sapflow averaged 2.3 m3d-1, with 70% of the cumulative sap flow occurring during the active growing season (May to September). The calibration showed a good fit (0.91 < R2<0.97) between measured groundwater levels from three shallow wells installed near the willow and the calculated water table level fluctuations, thus confirming that the water extraction rate based on sap flow data for the willow was appropriate. At stand level, additional modelling suggests that 3.4–4.7 ha of mature willows (i.e. between 7.8% and 10.6% of the Park area), could compensate for the current water volumes extracted by the municipality using a conventional pump and treat system. The results of this study indicate that willows can play a significant role in capturing contaminated groundwater underlying Belle Park, and potentially at other sites where removal of contaminants from shallow aquifers is desired.