Pumping Wells Research Articles

Association rules mining for long uptime sucker rod pumping units

The uptime of sucker rod pumping units (SRPUs) varies significantly due to differences in geological reservoir conditions, as well as design and operation parameters of the SRPUs. Conventional approaches encounter challenges in accurately quantifying the intricate interplay of these factors with uptime. This study investigates the application of association rules mining in exploring reliable measures in long uptime SRPUs. We create an uptime dataset for 5789 sucker rod pumping wells with 16 features encompassing reservoir conditions, production characteristics, SRPUs design, operational settings, and uptime. A novel algorithm is proposed to mine association rules between uptime and other features, yielding over 1,000,000 rules. These rules reveal relationships and impacts on long uptime. By following these rules, adjustments can be made to improve the uptime of SRPUs through alterations in design and operational parameters. Two case studies were presented to illustrate that by adjusting the design and operational parameters of SRPUs based on the association rules, the probability of improved operational performance can be increased by 30 % and 8 % respectively. This study explores the association rules of long uptime SRPUs from a data-driven paradigm, providing scientific guidance for subsequent oil well design. The research methodology is also valuable for other mechanical equipment.

The Impact of Injection/Pumping Wells on the Pollution Transport in Groundwater

The natural quality of groundwater tends to be degraded by industry, agriculture, and wastewater. There are several alternatives to prevent migration and the spread of pollution in groundwater. Some alternatives are physical such as grouting, or slurry walls. Others could be hydrodynamic containment by injection or pumping wells. Injection wells are used to confine a pollutant in place or dilute its concentration by injecting clean water into the aquifer. Pumping wells are used to discharge the pollutants out of the groundwater reservoir or act as interceptors. In this research, the hydraulic characteristics and behavior of the hydrodynamic methods are investigated by using numerical simulation. In this investigation, the numerical model MT3D has been integrally used with the flow model MODFLOW. Injection/pumping rate, screen length and layer, and the number of wells are considered. The results have shown that increasing the rate or the number of injection/pumping wells permits less pollution spread. Changing the screen length of the injection/pumping wells is not effective in preventing pollution from spreading in the long term. Changing the number of wells has more effect on a containment spread. Injection wells can prevent the spread of contaminants more than pumping wells.

Clean Water Quality Study in Bima City

Changes in water quality are the main focus in water management because they can have a major impact on the ecosystem. Water quality includes physical, chemical and biological conditions. Coverage of clean water and drinking water inspection data in Bima City reached 97.41%, while the feasibility percentage based on clean water and drinking water quality tests only reached 51.13%. The low percentage of appropriate clean water quality requires special attention. Based on this, researchers studied problems related to water quality, supply and level of need for clean water in Bima City. This research is an analytical observational study, and sampling was carried out using a non-random purposive sampling technique, and analyzed descriptively. Based on the results of physical water quality tests on 31 samples, the results showed that the physical quality of water met the requirements, the chemical quality of water in all measured samples met the requirements for class 1 and 2 clean water quality standards for the parameters DO, COD, total chlorine, nitrate, nitrite, and six valence chrome, while the BOD, Phosphate and Iron values did not meet the requirements (1/31 samples). The biological quality test showed that 12 samples did not meet the requirements for total coliforms (38.7%) and 3 samples showed the presence of E. coli bacteria (9.7%). On the other hand, it was recorded that 95.8% of respondents used shallow drilled wells for clean water; pump wells for 12.5% of respondents; PDAM constituted 16.6% of respondents; shallow drilled wells and PDAM 16.6%; and those using shallow drilled wells and hand pump wells 12.5%. Meanwhile, 37.5% use clean, untreated water and 62.5% use refilled drinking water

Soil moisture forecasting for precision irrigation management using real-time electricity consumption records

The installation of the smart electricity meters (SEMs) to the high-density pumping wells in the North China Plain (NCP) provided a method to control the groundwater withdraw. The record in real-time electricity consumption from SEMs also provided an alternative method to forecast soil moisture to make irrigation decisions to improve irrigation efficiency. The irrigation timing and the irrigation amount could be obtained on-line from the SEMs based on the coefficients obtained for electricity-to-water conversion (E-Wc). The real-time recordings in the irrigation timing and amounts were further used to forecast the next irrigation timing and amount based on the water rights per area of land, the lower limit of soil water contents for different crops at their different growing stages and online meteorological data. A smartphone app was developed based on this framework. The running of the app to simulate soil water contents based on the soil water balance equation was supported by databases on soil texture, crop coefficients, water rights, E-Wc and threshold soil water content values as well as the real-time collection of electricity consumption and meteorological data. The simulated real-time soil water contents were shown on the mobile phone screen and could be compared with the threshold values for making irrigation decisions for users. The accuracy in forecasting the soil water contents using the methods developed in this framework was tested under different irrigation schedules for winter wheat and summer maize during 2018–2019 and 2021–2022, and the app was tested for three locations starting from sowing winter wheat in October 2022 to April in 2023. The results showed that the app could be easily run, and precise real-time soil water contents were simulated. With the application of the pumping well renovation project in the NCP, most of the pumping wells were installed with the SEMs, and using SEMs for groundwater pumping control and irrigation decisions should be possible.

Identifying private pumping wells in a land subsidence area in Taiwan using deep learning technology and street view images

Study regionThe Choushui River Fan, Taiwan. Study focusGroundwater overdraft has led to not only groundwater depletion but also environmental disasters, such as subsidence and seawater intrusion in the Choushui River Alluvial Fan, Taiwan. The influence of land subsidence is gradually shifting from the coast to the center of the fan and threatening Taiwan high-speed rail. However, it remains a great challenge to manage and model the groundwater aquifer due to numerous unregulated wells. This study maps and locates private wells using deep learning technologies. We trained and validated convolutional-based deep learning neural networks (DNNs), using street view images. We applied the DNNs to a land subsidence area along the Taiwan high-speed rail, termed the Golden Corridor in Taiwan. The results showed that DNNs can recognize pumping wells with at least 90% accuracy. The testing cases showed their capability to recall all the pumping wells in three road segments along the Golden Corridor. Finally, we spatially estimated potential pumping of a subsidence area using the fine-trained DNNs. New hydrological insights for the regionGiven the prevalence of unknown private pumping in the Choushui River Fan, our image data-driven computer vision approach not only eases labor-intensive private well investigations but also advances hydrologic understanding for groundwater modeling. We enhance comprehension of unknown sinks and provide their spatial distribution to improve groundwater modeling.

Rapid spatio-temporal pumping volume estimation from electricity consumption big data

Land subsidence due to groundwater over-exploitation is a serious problem worldwide. Acquiring total pumping volumes to assess the stresses imposed that lead to subsidence is often difficult to quantify because groundwater extraction is often an unregulated water source. Consequently, pumping volumes represent a critical step for water resource managers to develop a strategic plan for mitigating land subsidence. In this investigation, we develop a time-dependent spatial regression (TSR) model to estimate monthly pumping volume over a ten-year period based on electricity consumption data. The estimated pumped volume is simplified as the spatial function of the electricity consumption and the electric power used by the water pump. Results show that the TSR approach can reduce the errors by 38% over linear regression models. The TSR model is applied to the Choshui alluvial fan in west-central Taiwan, where hundreds of thousands of unregulated pumping wells exist. The results show that groundwater peak extraction across the region occurs from January to May. Monthly pumping volume, and rainfall information are available to provide a better understanding of seasonal patterns and long-term changes of subsidence. Thus, the temporal regional subsidence patterns are found to respond to variations in pumping volume and rainfall.

Determination of groundwater pumpage for dewatering construction site of Happy complex in Tay Ho district, Hanoi

Groundwater is unfavorable for construction activities, so groundwater dewatering or freezing needs to be carried out. The Happy complex is located in Tay Ho District, Hanoi city. The complex is to be constructed with 47 stations which are evenly distributed over a construction area of 10,000 m2 in the depth from 12.1 to 18.25 m below the ground surface. It is required to dewater groundwater to have the groundwater level to be 1.5 m lower the bottom of the stations. Vertical groundwater wells have been selected for the. The determination of groundwater pumping rates for the dewatering had been carried out by numerical modeling. GMS10.3.2 software had been used to model the groundwater flow using the MODFLOW modul. The modeling area is expanded to cover the construction site with dimensions of 370m x 420m. The grid cells are 4m x 4m. The groundwater pumping rates were determined by solving forward analysis of different options to select the optimal solution, which includes 29 pumping wells with the same well pumping rate of 1,040 m3/day. The lowered groundwater levels at all the construction stations have met the requirement.

Research on early warning model of electric submersible pump wells failure based on the fusion of physical constraints and data-driven approach

At present, there are too few characteristic parameters for early identification of electric submersible pump (ESP) wells failures. In addition, existing predictive models rely only on data-driven techniques, which do not provide a comprehensive understanding of the intrinsic mechanisms behind the occurrence of failures. This article presents the development of a health index calculation approach for evaluating the operational status of the ESP wells. The wellbore energy conservation equation and the health index calculation formula were employed to develop a physical constraints (PC) for the loss function in the network model of Long Short-Term Memory (LSTM). This constraint was then utilized to construct the PC-LSTM ESP health warning model. The study examines the health index trends associated with three types of faults: ESP clogging, sand production in oil wells, and reservoir pressure rise. The results indicate that the PC-LSTM network structure exhibits faster convergence during training. In relation to the accuracy of prediction, PC-LSTM demonstrates a notable enhancement. Specifically, when the ESP clogging fault, the traditional LSTM achieves a mean relative error (MRE) of 211.15%, whereas the PC-LSTM achieves a reduced MRE of 12.74%. Similarly, for sand production in oil wells, the traditional LSTM yields an MRE of 19.07%, while the PC-LSTM achieves a reduced MRE of 9.62%. Lastly, in the scenario of reservoir pressure rise, the traditional LSTM exhibits an MRE of 41.07%, whereas the PC-LSTM achieves a reduced MRE of 12.74%. In the meantime, the model demonstrates a high level of accuracy in capturing the pre- and post-trends of the health status of the ESP wells. This improved prediction accuracy and interpretability of the underlying mechanisms serve as valuable tools for analyzing the lift performance of ESP wells and providing early warning signals for potential failures.

A construction strategy of Kriging surrogate model based on Rosenblatt transformation of associated random variables and its application in groundwater remediation

When using simulation-optimization models for optimizing the design of groundwater pumping-treatment plans for pollution, building a surrogate model for the numerical simulation model has become an effective means of overcoming the computational load of such models. However, previous studies often treated pumping time as a single optimization variable, leading to unnecessary excessive pumping. This paper considers the location, pumping rate, start time, and end time of each candidate pumping well as optimization variables, and proposes a Rosenblatt-transform-based optimal Latin hypercube sampling method for the associated random variables to ensure that the start time is less than or equal to the end time. This method is coupled with an adaptive sampling method based on batch local optimal solutions to construct a dynamic adaptive Kriging surrogate model for the numerical model, ensuring that the true value of the optimal remediation scheme is not lost. The results show that, at the final stage of remediation, the pollutant concentration in the 4 scenarios achieves comprehensive compliance. However, when considering the minimization of remediation costs as the evaluation criterion, the remediation scheme in scenario 1 (the pumping start and end times are independent optimization variables for all candidate pumping wells) is optimal. In the optimization design of groundwater pumping-treatment plans, the pumping wells should be arranged in the midstream and downstream regions of the contaminant plume and parallel to the regional flow direction. This paper provides a method reference for the construction and adaptive updating of surrogate models involving associated random variables, as well as guidance for the dynamic optimization of groundwater pumping and treatment at contaminated sites.

Optimization of pumping and injection regimes for mitigation of seawater intrusion

Seawater intrusion (SWI) stands as a significant challenge impacting coastal aquifers worldwide. The emergence of SWI is a natural phenomenon owing to the density difference between seawater and freshwater. Even without any pumping, the seawater naturally advances inland until a hydrostatic equilibrium between the two water sources is reached. However, human interventions, such as excessive groundwater extraction, coastal developments, and land use as well as climate change intensify the SWI predicament. Efficient solutions to counteract the SWI problem involve the implementation of hydraulic barriers. By employing the Henry problem as a benchmark, the Finite Element Simulator (FEFLOW), which is a numerical modeling software, was used for simulating the flow and transport processes. An integrated FEFLOW-Python code was developed to optimize hydraulic barriers for mitigating SWI. The methodology aims to achieve the maximum possible reduction in SWI by iteratively adjusting the locations and rates of pumping and injection wells. Unlike other investigations, this study explores the utilization of negative SWI barriers to extract brackish water from the dispersion zone and potentially offer a cost-effective alternative water source for desalination plants’ intakes. For the Henry Problem, to maximize the reduction in of SWI, brackish water extraction wells should be situated near the center-bottom of the intrusion zone, with a pumping rate of 2.5 m3/day. For injection wells, the optimal location varies depending on the injection rate (I). Achieving the highest retardation (61%) occurs when the injection rate is 1 m3/day, positioned at the aquifer’s bottom and close to the coastal boundary. However, for injection rates below 0.7 m3/day, the injection well’s optimal location shifts towards the seawater intrusion toe. This study presents a novel approach by establishing explicit correlations for optimizing hydraulic barriers to effectively manage and mitigate SWI.

OPTIMIZATION IN THE RECONSTRUCTION OF THE RESERVOIR PRESSURE MAINTENANCE SYSTEM (RPMS) USING SIMULATION MODELING

The paper considers the optimization of reservoir pressure maintenance systems using simulation methods. The main goal is to consider the impact of various technological indicators on capital and operating costs. The initial parameters for calculating optimization options are the cost of electricity and the density of the injected water; fiberglass pipes (SPT-80, SPT -100) are used as pipes, the wall roughness of which is assumed to be 0.015 mm.The costs of capital construction during the reconstruction of pipelines and the pumping unit, as well as operating costs for overcoming hydraulic losses in pipelines, in well piping and for energy losses of pumping units are calculated. When calculating, special attention is paid to losses that make up 90% of the total power losses in the pressure maintenance system, such as power losses associated with imperfect pump design; power losses for choke of injection wells; losses of electricity for the operation of pipelines.The results are presented on the example of a small cluster pumping station. 4 options for optimizing calculated in terms of capital and operating costs for three main points are presented: pumping equipment, pipelines and wells. To assess the impact on production, a reservoir model was built using the material balance method. It should be noted that synthetic data were used for this case, because in reality, this CPS is just a part of the pressure maintenance system.When optimizing 20 facilities, the following results were obtained: on average, over 20 years, the difference in operating and capital costs between the basic reconstruction option and the most profitable reconstruction option with optimization is about 350 million rubles.

Analysis of Steady Groundwater Flow in Confined Aquifer Due to Long-Strip Pit Dewatering with Suspended Cut-Off Wall

This study investigates the steady flow resulting from dewatering by a partially penetrating well in a confined aquifer with a cut-off barrier. By considering flow in both horizontal and vertical directions and incorporating the barrier and pumping well as flow boundary conditions, separate mathematical models are established for the inside and outside of the cut-off barrier. The interaction between these zones is ensured through continuous conditions along the opening of the two zones. A semi-analytical solution is derived for the problem using the finite Fourier cosine transform and boundary transformation methods. The effectiveness of the method is verified by comparing it with the finite element numerical results and pumping test data respectively. Based on the proposed solutions, we proceed to analyze the influence of some relevant factors: the extent to which the cut-off wall is embedded within the confined aquifer, the depth of the partially penetrating well, and the distance to the lateral head boundary. Results indicate that a greater depth of the cut-off wall leads to a reduced pumping rate requirement for achieving a desired drawdown of the confined water level within the excavation. According to the presented solution, placing pumping wells near the top of the confined aquifer in excavation dewatering projects can facilitate a faster reduction of the confined water head at the excavation bottom. Additionally, proximity of lateral head boundary could significantly impact dewatering, with closer boundaries reducing dewatering effectiveness due to improved aquifer recharge. Finally, the use of the Fourier method showcases impressive convergence properties in the approach presented in this study. The computed results maintain a high level of approximation quality, even with extremely coarse discretization.

Estimating Groundwater Flow Velocity in Shallow Volcanic Aquifers of the Ethiopian Highlands Using a Geospatial Technique

The shallow volcanic aquifer is the major rural water supply source in the Ethiopian highlands. A significant number of hand pump wells in these aquifers experience a rapid decline in yield and poor performance within a short period of time after construction. Hence, reliable estimation of groundwater flow velocity is important to understand groundwater flow dynamics, aquifer responses to stresses and to optimize the sustainable management of groundwater resources. Here, we propose the geospatial technique using four essential input raster maps (groundwater elevation head, transmissivity, effective porosity and saturated thickness) to investigate groundwater flow velocity magnitude and direction in the shallow volcanic aquifers of the Ethiopian highlands. The results indicated that the high groundwater flow velocity in the Mecha site, ranging up to 47 m/day, was observed in the fractured scoraceous basalts. The Ejere site showed groundwater flow velocity not exceeding 7 m/day in the fractured basaltic aquifer and alluvial deposits. In the Sodo site, the groundwater flow velocity was observed to exceed 22 m/day in the fractured basaltic and rhyolitic aquifers affected by geological structures. The Abeshege site has a higher groundwater flow velocity of up to 195 m/day in the highly weathered and fractured basaltic aquifer. In all study sites, aquifers with less fractured basalt, trachyte, rhyolite, welded pyroclastic, and lacustrine deposits exhibited lower groundwater flow velocity values. The groundwater flow velocity directions in all study sites are similar to the groundwater elevation head, which signifies the local and regional groundwater flow directions. This work can be helpful in shallow groundwater resource development and management for rural water supply.

Research on fast marking method for indicator diagram of pumping well based on K-means clustering

Indicator diagram is the key basis for fault diagnosis of pumping wells in oil exploitation. With the rapid development of machine learning, the fault diagnosis of indicator diagram based on deep learning has garnered increasing attention. This kind of methods train neural network models with marked samples, and then inputs images into the trained models and outputs their categories. At present, the preparation of indicator diagram sample set relies on experts' analysis of indicator diagram images one by one. However, it involves extensive manual work and manual marking is prone to errors, so the marked samples are often insufficient in quantity. In order to quickly mark a large number of indicator diagram samples, the oil well data was plotted into standardized indicator diagram, and then three feature extraction methods for indicator diagrams were proposed: feature extraction based on original vector, feature extraction based on three-dimensional pixel tensor, feature extraction based on convolutional neural network. These methods convert the indicator diagram into corresponding feature vectors, which are then clustered using the K-means clustering algorithm, enabling the corresponding indicator diagrams to be classified into different categories based on the clustering results. Using 20,000 randomly selected pieces of data from 100 pumping wells, this study clusters the sample set using the three proposed methods. The results indicated that the time consumption were 0.2, 8.3, and 0.7 h, with accuracy rates of 98%, 92%, and 95%, respectively. For indicator diagrams, the clustering method based on the original vector has outstanding performance in terms of efficiency and accuracy. This provides an automatic tool for the preparation of the pumping well fault diagnosis dataset, and its efficiency can be increased by tens of times compared with manual marking.

A new decision-making method for the renewal of agricultural irrigation wells: A case study of Songzhuang town, Tongzhou District, Beijing

Pumping wells (PWs) lie at the core of agricultural irrigation infrastructure, and their spatial configuration is of great significance for the scientific management of regional agriculture and rational use of water resources. To solve the problems of unreasonable and unscientific spatial allocation of regional agricultural irrigation PWs, this paper proposes a new strategy for updating agricultural irrigation PWs based on a spatial decision model, using Songzhuang Town, Tongzhou District, Beijing as a case study. The model utilizes constraints based on local factors such as actual land use, and proposes a novel feasible solution strategy that combines random local search and abrupt jumps to increase the probability that feasible solutions will be found, addressing the performance issues of simulated annealing algorithms, influence of initial values, and parameter sensitivity. Finally, we used the proposed method to perform updated decision analysis on the spatial configuration of PWs in the study area. The results showed that most of the crops in the study area lack irrigation, and the currently available PWs cannot meet the needs for irrigation. The new PWs added based on this decision method can be more evenly distributed within the predefined optimization unit. The proposed number of PWs to be added is 166, the density of PWs is 0.04/ha, and the crop area covered by the PWs is 3350.43 ha. In contrast to the previous PW layout, the optimized PW configuration can meet the irrigation needs of residents, indicating that the new method proposed in this paper has good potential for extension and application.

Field Experiments on 3D Groundwater Flow Patterns in the Deep Excavation of Gravel-Confined Aquifers in Ancient Riverbed Areas

In ancient riverbed areas, the hydro-geological conditions are extremely complex because of the cutting of ancient river channels during the sedimentary process. How to lower groundwater level in water-riched gravel-confined aquifer during deep excavation is vital for underground engineering. Groundwater flow patterns had to be understood during foundation pit dewatering. This paper presents a field case study conducted at the deep foundation pit of the Qianjiang Century City station on Hangzhou Metro Line 6, which is notable for its 52 m deep unclosed waterproof curtain. A total of 34 pumping wells were installed within the pit. During the tests, one well was subjected to a pumping well, while the others served as observation wells. The research included two sets of multi-depth pumping tests, which differed in terms of their filter lengths, aimed at investigating the flow pattern around pump wells and the roots of diaphragm walls. The study found that the use of longer filters, higher pump rates, and filters placed nearer to aquifer roofs enhances dewatering efficiency and minimizes impact on the surrounding geological environment. This paper introduces a novel concept known as the diaphragm wall–pumping well effect, which regulates the water head outside the pit and the subsidence, thereby optimizing the drawdown of the deep foundation pit with an unclosed waterproof curtain. The findings were applied in the foundation pit dewatering of Qianjiang Century City station, and the drawdown in and outside the pit was effectively controlled.

Assessing the Impact of Human Activities and Climate Change Effects on Groundwater Quantity and Quality: A Case Study of the Western Varamin Plain, Iran

In this paper, the effects of climate change and human activities on the groundwater level and the concentration of pollutants, such as total dissolved solids (TDS), chloride, and sodium, were investigated in the western part of the Varamin Plain. The groundwater flow and pollutant transport were simulated with the two models of MODFLOW and MT3D, respectively. To investigate the impacts of climate change, the two parameters of temperature and precipitation were downscaled under the three scenarios of RCP 2.6, RCP 4.5, and RCP 8.5. Four scenarios, including the current condition (Scenario 0), a 25% increase in the extraction from pumping wells (Scenario 1), the climate change effects (Scenario 2), and an increase in the incoming effluent (TDS) to the Shoor River due to industrial activities (Scenario 3), were investigated for a future period of 30 years (2025–2055). The results show that the highest groundwater decline and chloride and sodium concentrations occur under Scenario 1, while Scenario 3 leads to the maximum TDS concentration (milligrams per liter). In Scenario 1, the average and maximum groundwater decline at the end of the simulation period will be 2.5 m and 7.3 m, and the chloride and sodium concentrations will increase by 7 and 5 milligrams per liter, respectively.

Searching for hidden waters: The effectiveness of remote sensing in assessing the distribution and status of a traditional, earthen irrigation system (khettara) in Morocco

This paper presents the results of a multi-year, interdisciplinary project that aimed to assess the holistic status of the khettara system in Morocco. The khettara (also known as qanat) is a traditional, earthen water management system. Historically the system was used for settlement in regions without access to reliable surface water. It is both a world and local heritage structure, found in rural and urban regions throughout 46 countries. Recent evaluations of this traditional system have advocated for its preservation and use in arid and semi-arid regions, as modern technologies (pump wells, industrial dams, drip irrigation, etc.) have proven to be unsustainable. This project evaluates remote sensing as a tool for assessing the distribution and status of the khettara in Morocco. The results of this project demonstrate that (1) the khettara system played a large role in the historic settlement of arid and semi-arid regions, and (2) the system continues to be an important part of agriculture and life in many oases across Morocco.

Assessment of drought conditions and prediction by machine learning algorithms using Standardized Precipitation Index and Standardized Water-Level Index (case study: Yazd province, Iran).

Drought as a natural phenomenon has always been a serious threat to regions with hot and dry climates. One of the major effects of drought is the drop in groundwater level. This paper focused on the SPI (Standardized Precipitation Index) and SWI (Standardized Water-Level Index) to assess meteorological and hydrological drought, respectively. In the first part, we used different time frames of SPI (3, 6, 12, and 24 months) to investigate drought in Yazd, a dry province in the center of Iran for 29 years (1990-2018). Then, in the second part, the relationship between SPI and SWI was investigated in the three aquifers of Yazd by some rain gauge stations and the closest observation wells to them. In addition to using SPI and SWI, we also used different machine learning (ML) algorithms to predict drought conditions including linear model and six non-linear models of K_Nearest_Neighbors, Gradient_Boosting, Decision_Tree, XGBoost, Random_Forest, and Neural_Net. To evaluate the accuracy of the mentioned models, three statistical indicators including Score, RMSE, and MAE were used. Based on the results of the first part, Yazd province has changed from mild wet to mild drought in terms of meteorological drought (the amount of rainfall according to SPI), and this condition can worsen due to climate change. The models used in ML showed that SPI-6 (score ave = 0.977), SPI-3 (score ave = 0.936), SPI-24 (score ave = 0.571), and SPI-12 (score ave = 0.413) indices had the highest accuracy, respectively. The models of Neural_Net (score ave = 0.964-RMSE ave = 0.020-MAE ave = 0.077) and Gradient_Boosting (score ave = 0.551-RMSE ave = 0.124-MAE ave = 0.248) had the highest and lowest accuracy in prediction of the SPI in all four-time scales. Based on the results of the second part, about the SWI, Random_Forest model (score = 0.929-RMSE = 0.052-MAE = 0.150) and model of Neural_Net (score = 0.755-RMSE = 0.235-MAE = 0.456) had the highest and lowest accuracy, respectively. Also, hydrological drought (reduction of the groundwater level) of the region has been much more severe, and according to the low correlation coefficient of average SPI and SWI (R2 = 0.14), we found that the uncontrolled pumping wells, as a main factor than a shortage of rainfall, have aggravated the hydrological drought, and this region is at risk of becoming a more arid region in the future.

Modeling the fate of viruses in aquifers: Multi-kinetics reactive transport, risk assessment, and governing parameters

The transport of viruses in groundwater is a complex process controlled by both hydrodynamic and reaction parameters. Characterizing the transport of viruses in groundwater is of crucial importance for investigating health risks associated with groundwater consumption from private individual or residential pumping wells. Setback distances between septic systems, which are the source of viruses, and pumping wells must be designed to offer sufficient groundwater travel times to allow the viral load to degrade sufficiently to be acceptable for community health needs. This study consists of developing numerical simulations for the reactive transport of viruses in the subsurface. These simulations are validated using published results of laboratory and field experiments on virus transport in the subsurface and applying previously developed analytical solutions. The numerical model is then exploited to investigate the sensitivity of the fate of viruses in saturated porous media to hydraulic parameters and the coefficients of kinetic reactions. This sensitivity analysis provides valuable insights into the prevailing factors governing health risks caused by contaminated water in private wells in rural residential contexts. The simulations of virus transport are converted into health risk predictions through dose–response relationships. Risk predictions for a wide range of input parameters are compared with the international regulatory health risk target of a maximum of 10−4 infections/person/year and a 30 m setback distance to identify critical subsurface contexts that should be the focus of regulators.