scholarly journals Evaluating the Impacts of Pumping on Aquifer Depletion in Arid Regions Using MODFLOW, ANFIS and ANN

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2297
Author(s):  
Mohammed R. Almuhaylan ◽  
Abdul Razzaq Ghumman ◽  
Ibrahim Saleh Al-Salamah ◽  
Afaq Ahmad ◽  
Yousry M. Ghazaw ◽  
...  
Keyword(s):  
Water Conservation ◽  
Arid Regions ◽  
Fuzzy Inference ◽  
Three Dimensional ◽  
Conservation Strategies ◽  
Pumping Rate ◽  
Groundwater Levels ◽  
Aquifer Depletion ◽  
Inference Systems ◽  
The Impact

In arid regions, the groundwater drawdown consistently increases, and even for a constant pumping rate, long-term predictions remain a challenge. The present research applies the modular three-dimensional finite-difference groundwater flow (MODFLOW) model to a unique aquifer facing challenges of undefined boundary conditions. Artificial neural networks (ANN) and adaptive neuro fuzzy inference systems (ANFIS) have also been investigated for predicting groundwater levels in the aquifer. A framework is developed for evaluating the impact of various scenarios of groundwater pumping on aquifer depletion. A new code in MATLAB was written for predictions of aquifer depletion using ANN/ANFIS. The geotechnical, meteorological, and hydrological data, including discharge and groundwater levels from 1980 to 2018 for wells in Qassim, were collected from the ministry concerned. The Nash–Sutcliffe efficiency and mean square error examined the performance of the models. The study found that the existing pumping rates can result in an alarming drawdown of 105 m in the next 50 years. Appropriate water conservation strategies for maintaining the existing pumping rate can reduce the impact on aquifer depletion by 33%.

scholarly journals Simulation of Pan-Evaporation Using Penman and Hamon Equations and Artificial Intelligence Techniques

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 793
Author(s):  
Abdul Razzaq Ghumman ◽  
Mohammed Jamaan ◽  
Afaq Ahmad ◽  
Md. Shafiquzzaman ◽  
Husnain Haider ◽  
...  
Keyword(s):  
Wind Speed ◽  
Water Resources ◽  
Arid Regions ◽  
Fuzzy Inference ◽  
Sunshine Duration ◽  
Pan Evaporation ◽  
Estimation Of Parameters ◽  
Inference System ◽  
Daunting Task ◽  
The Impact

The evaporation losses are very high in warm-arid regions and their accurate evaluation is vital for the sustainable management of water resources. The assessment of such losses involves extremely difficult and original tasks because of the scarcity of data in countries with an arid climate. The main objective of this paper is to develop models for the simulation of pan-evaporation with the help of Penman and Hamon’s equations, Artificial Neural Networks (ANNs), and the Artificial Neuro Fuzzy Inference System (ANFIS). The results from five types of ANN models with different training functions were compared to find the best possible training function. The impact of using various input variables was investigated as an original contribution of this research. The average temperature and mean wind speed were found to be the most influential parameters. The estimation of parameters for Penman and Hamon’s equations was quite a daunting task. These parameters were estimated using a state of the art optimization algorithm, namely General Reduced Gradient Technique. The results of the Penman and Hamon’s equations, ANN, and ANFIS were compared. Thirty-eight years (from 1980 to 2018) of manually recorded pan-evaporation data regarding mean daily values of a month, including the relative humidity, wind speed, sunshine duration, and temperature, were collected from three gauging stations situated in Al Qassim, Saudi Arabia. The Nash and Sutcliffe Efficiency (NSE) and Mean Square Error (MSE) evaluated the performance of pan-evaporation modeling techniques. The study shows that the ANFIS simulation results were better than those of ANN and Penman and Hamon’s equations. The findings of the present research will help managers, engineers, and decision makers to sustainability manage natural water resources in warm-arid regions.

scholarly journals Development of Machine Learning Models to Evaluate the Toughness of OPH Alloys

Materials ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6713
Author(s):  
Omid Khalaj ◽  
Moslem Ghobadi ◽  
Ehsan Saebnoori ◽  
Alireza Zarezadeh ◽  
Mohammadreza Shishesaz ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mechanical Properties ◽  
Mechanical Alloying ◽  
Fuzzy Inference ◽  
Oxide Dispersion Strengthened ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Anfis Model ◽  
Inference Systems ◽  
The Impact

Oxide Precipitation-Hardened (OPH) alloys are a new generation of Oxide Dispersion-Strengthened (ODS) alloys recently developed by the authors. The mechanical properties of this group of alloys are significantly influenced by the chemical composition and appropriate heat treatment (HT). The main steps in producing OPH alloys consist of mechanical alloying (MA) and consolidation, followed by hot rolling. Toughness was obtained from standard tensile test results for different variants of OPH alloy to understand their mechanical properties. Three machine learning techniques were developed using experimental data to simulate different outcomes. The effectivity of the impact of each parameter on the toughness of OPH alloys is discussed. By using the experimental results performed by the authors, the composition of OPH alloys (Al, Mo, Fe, Cr, Ta, Y, and O), HT conditions, and mechanical alloying (MA) were used to train the models as inputs and toughness was set as the output. The results demonstrated that all three models are suitable for predicting the toughness of OPH alloys, and the models fulfilled all the desired requirements. However, several criteria validated the fact that the adaptive neuro-fuzzy inference systems (ANFIS) model results in better conditions and has a better ability to simulate. The mean square error (MSE) for artificial neural networks (ANN), ANFIS, and support vector regression (SVR) models was 459.22, 0.0418, and 651.68 respectively. After performing the sensitivity analysis (SA) an optimized ANFIS model was achieved with a MSE value of 0.003 and demonstrated that HT temperature is the most significant of these parameters, and this acts as a critical rule in training the data sets.

scholarly journals Contribution to the hydrogeology of Six Hills sandstone aquifer in East El-Oweinat area, south Western desert, Egypt

2019 ◽  
Vol 8 (3) ◽  
Author(s):  
Saad Younes Ghoubachi
Keyword(s):  
Cross Sections ◽  
Land Reclamation ◽  
Groundwater Resources ◽  
Western Desert ◽  
Pumping Rate ◽  
Groundwater Levels ◽  
Monitoring Wells ◽  
Sandstone Aquifer ◽  
Domestic Livestock ◽  
The Impact

El-Oweinat area is located in southwestern Egypt and is considered to be one of the new land reclamation projects in the Western Desert. The Nubian Sandstone aquifer has high potentiality and good groundwater quality. The results of geologic and hydrogeologic studies reveal that the Six Hills sandstone aquifer represents the sole groundwater resource used for all purposes (agriculture, drinking, domestic, livestock and poultry) in East El-Oweinat area. The Six Hills sandstone aquifer overlies directly the Precambrian basement rocks. The concerned aquifer exists under unconfined conditions as it is exposed on the surface. The hydrogeological cross sections show that the fully saturated thickness of the Six Hills sandstone aquifer ranges between 150.2 m and 651 m and increases towards the west. The groundwater generally flows towards the northeast direction with an average hydraulic gradient of 0.6 ‰. The calculated groundwater volume of the Six Hills sandstone aquifer in East El-Oweinat area (4,340 km2) reaches 350 bcm of fresh water. The comparison of the depth to water in the same monitoring wells during 14 years (2003 and 2016) reveals that the head decline rate in groundwater depths were ranging between 5 cm/year and 80 cm/year. The pumping rate increased from 600,000 m3/day in year 2003 to 3,600,000 m3/day in 2016. The average transmissivity attains 2,060 m2/day reflecting the high potential of the Six Hills sandstone aquifer in East El-Oweinat area. The groundwater flow model (MODFLOW) has been used to investigate the impact of groundwater withdrawal on groundwater levels for sustainable groundwater management. Four scenarios were applied to predict the probable head changes in the Six Hills sandstone aquifer and their impact on the availability of groundwater. The fourth scenario is recommended in order to sustain the groundwater resources in the study area and keep the drawdown rates in the range of 0.66 m/year through reducing the present discharging rates (10,000 m3/day/well) by about 40%.

scholarly journals WORLD WATER WEEK, STOCKHOLMSERIOUS WATER ISSUES FOR SUSTAINABLE AGRICULTURAL GROWTH

2016 ◽  
Vol 4 (8) ◽  
pp. 110-117
Author(s):  
Amrit Patel
Keyword(s):  
Water Conservation ◽  
Technology Use ◽  
Sustainable Growth ◽  
Indian States ◽  
Irrigation Network ◽  
Agricultural Growth ◽  
Groundwater Levels ◽  
Road Map ◽  
Financial Arrangements ◽  
The Impact

The Prime Minister of India Shree Narendra Modi on 8th June 2015 said, “India must quickly expand its irrigation network and improve water usage to offset the impact of less monsoon rainfall than usual and asked officials to ensure quick results for farmers by reviewing administrative mechanisms, financial arrangements and technology use in irrigation” He also pushed for a brief, intensive effort to increase the number of farm ponds, adding that falling groundwater levels in some Indian states could force an urgent shift in crop patterns”. Over the years, there has been a manifested lack of attention to water legislation, water conservation, water use efficiency, water harvesting and recycling and infrastructure. Current scenario exhibiting number of incomplete projects accompanied by low utilization of irrigation potential already created shows that return on capital invested in creating irrigation facilities is inordinately delayed or almost lost. All incomplete projects need to be completed by 2020 by drawing a suitable road map indicating specifically the role, responsibility and accountability of officials, department and ministry concerned. It is indeed apt that the Stockholm-based International Water Institute has focused “Water & Sustainable Growth” as its theme during the World Water Week commencing from 22nd August to 2nd September 2016. It is in this context this article briefly highlights the serious issues of water for sustainable agricultural growth in India when droughts and floods are annual features in one or the other parts of the country.

Using measured microcomponent data to model the impact of water conservation strategies on the diurnal consumption profile

2005 ◽  
Vol 5 (3-4) ◽  
pp. 145-150 ◽  
Author(s):  
M. Kowalski ◽  
D. Marshallsay
Keyword(s):  
Water Conservation ◽  
Collaborative Research ◽  
Conservation Strategies ◽  
Research Centre ◽  
Demand Reduction ◽  
Reduction Strategies ◽  
Water Companies ◽  
Environment Agency ◽  
The Uk ◽  
The Impact

A recent collaborative research project by the Water Research Centre (WRc), involving 13 water companies and the UK Environment Agency, has yielded further information on the microcomponents of water use in domestic properties in the UK. Investigating the uncertainty and diurnal variations of the data has allowed the investigation of demand reduction strategies at household and supply area levels. The paper expands on these issues and discusses how this approach can be used to help plan and manage water supply in the future.

scholarly journals Groundwater Flow Model and Statistical Comparisons Used in Sustainability of Aquifers in Arid Regions

Resources ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 134 ◽  
Author(s):  
Javier Alexis Trasviña-Carrillo ◽  
Jobst Wurl ◽  
Miguel Angel Imaz-Lamadrid
Keyword(s):  
Population Growth ◽  
Groundwater Flow ◽  
Arid Regions ◽  
San Jose ◽  
Groundwater Levels ◽  
Regulatory Policies ◽  
Deep Wells ◽  
Growth Increase ◽  
Extraction Volume ◽  
The Impact

Groundwater provides the most important of the water resources used in the maintenance of communities in arid and semi-arid regions. In these areas, the usage of deep wells with motorized pumps in combination with the lack of effective regulatory policies and high human population growth (increase the water demand) impact the quality of the groundwater. This is especially the case for the San José del Cabo aquifer, in Baja California Sur. In the present study the groundwater flow system is analyzed in order to recognize the impact from variations in groundwater extraction and recharge on the phreatic levels and discharge values. In order to achieve this goal, a groundwater model was generated using the MODFLOW program. Different scenarios of extraction and recharge were calculated, based on different estimations of population growth. All the scenarios result in decreasing groundwater levels. As an important result, a relationship between the phreatic level and the extraction volume was found for the middle zone of the aquifer, where an average annual decrease of 0.5 m was observed from every 5 × 106 m3 additional extraction volume. This zone is up to three times more susceptible to changes in extraction values than the southern zone. As the results show, the San José del Cabo aquifer is in a fragile state where an increment in extraction is not an option without the use of remediation technics or new sources for water supply.

scholarly journals Optimization techniques on fuzzy inference systems to detect Xanthomonas campestris disease

2021 ◽  
Vol 11 (4) ◽  
pp. 3510
Author(s):  
Julio Barón Velandia ◽  
Camilo Enrique Rocha Calderón ◽  
Daniel David Leal Lara
Keyword(s):  
Xanthomonas Campestris ◽  
Fuzzy Inference ◽  
Model Performance ◽  
Optimization Techniques ◽  
Training Data ◽  
Fuzzy Inference Systems ◽  
The Status ◽  
And Performance ◽  
Inference Systems ◽  
The Impact

<span>This paper shows the outcomes for four optimization models based on fuzzy inference systems, intervened using Quasi-Newton and genetic algorithms, to early assess</span><span> bean plants’ leaves for Xanthomonas campestris<em> </em>disease. The assessment on the status of the plant (sane or ill) is defined through the intensity of the color in the RGB scale for the data-sets and images to analyze the implementation of the models. The best model performance is 99.68% when compared with the training data and a 94% effectiveness rate on the detection of Xanthomonas campestris in a bean leave image. Therefore, these results would allow farmers to take early measures to reduce the impact of the disease on the look and performance of green bean crops.</span>

Analyzing the Impact of X-Ray Tomography on the Reliability of Integrated Circuits

2015 ◽  
Author(s):  
Halit Dogan ◽  
Md Mahbub Alam ◽  
Navid Asadizanjani ◽  
Sina Shahbazmohamadi ◽  
Domenic Forte ◽  
...  
Keyword(s):  
Integrated Circuits ◽  
Integrated Circuit ◽  
3D Imaging ◽  
Three Dimensional ◽  
Serial Sectioning ◽  
Promising Technique ◽  
Flash Memories ◽  
X Ray ◽  
3D Information ◽  
The Impact

Abstract X-ray tomography is a promising technique that can provide micron level, internal structure, and three dimensional (3D) information of an integrated circuit (IC) component without the need for serial sectioning or decapsulation. This is especially useful for counterfeit IC detection as demonstrated by recent work. Although the components remain physically intact during tomography, the effect of radiation on the electrical functionality is not yet fully investigated. In this paper we analyze the impact of X-ray tomography on the reliability of ICs with different fabrication technologies. We perform a 3D imaging using an advanced X-ray machine on Intel flash memories, Macronix flash memories, Xilinx Spartan 3 and Spartan 6 FPGAs. Electrical functionalities are then tested in a systematic procedure after each round of tomography to estimate the impact of X-ray on Flash erase time, read margin, and program operation, and the frequencies of ring oscillators in the FPGAs. A major finding is that erase times for flash memories of older technology are significantly degraded when exposed to tomography, eventually resulting in failure. However, the flash and Xilinx FPGAs of newer technologies seem less sensitive to tomography, as only minor degradations are observed. Further, we did not identify permanent failures for any chips in the time needed to perform tomography for counterfeit detection (approximately 2 hours).

scholarly journals Numerical simulation of the impact of an integrated renovation project on the Maowei Sea hydrodynamic environment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Cui Wang ◽  
Ling Cai ◽  
Yaojian Wu ◽  
Yurong Ouyang
Keyword(s):  
Water Exchange ◽  
Land Reclamation ◽  
Three Dimensional ◽  
Exchange Capacity ◽  
Reclamation Project ◽  
Hydrodynamic Environment ◽  
Sea Area ◽  
Water Quality Models ◽  
The Impact ◽  
Main Factor

AbstractIntegrated renovation projects are important for marine ecological environment protection. Three-dimensional hydrodynamics and water quality models are developed for the Maowei Sea to assess the hydrodynamic environment base on the MIKE3 software with high resolution meshes. The results showed that the flow velocity changed minimally after the project, decreasing by approximately 0.12 m/s in the east of the Maowei Sea area and increasing by approximately 0.01 m/s in the northeast of the Shajing Port. The decrease in tidal prism (~ 2.66 × 106 m3) was attributed to land reclamation, and accounted for just 0.86% of the pre-project level. The water exchange half-life increased by approximately 1 day, implying a slightly reduced water exchange capacity. Siltation occurred mainly in the reclamation and dredging areas, amounting to back-silting of approximately 2 cm/year. Reclamation project is the main factor causing the decrease of tidal volume and weakening the hydrodynamics in Maowei Sea. Adaptive management is necessary for such a comprehensive regulation project. According to the result, we suggest that reclamation works should strictly prohibit and dredging schemes should optimize in the subsequent regulation works.

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