�ݺ�ߣshows by User: AmroElfeki

�ݺ�ߣshows by User: AmroElfeki / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: AmroElfeki / Mon, 06 Dec 2021 17:06:36 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: AmroElfeki Simulation of Tracer Injection from a Well in a Nearly Radial Flow /slideshow/simulation-of-tracer-injection-from-a-well-in-a-nearly-radial-flow/250792383 tracerinradialflow-211206170637
This is a result of Simulation of Tracer Injection from a well in a nearly radial flow using finite difference and particle tracking Radom walks. To observe the animation of the plume progress in time, one has to download the file. ]]>
This is a result of Simulation of Tracer Injection from a well in a nearly radial flow using finite difference and particle tracking Radom walks. To observe the animation of the plume progress in time, one has to download the file. ]]> Mon, 06 Dec 2021 17:06:36 GMT /slideshow/simulation-of-tracer-injection-from-a-well-in-a-nearly-radial-flow/250792383 AmroElfeki@slideshare.net(AmroElfeki) Simulation of Tracer Injection from a Well in a Nearly Radial Flow AmroElfeki This is a result of Simulation of Tracer Injection from a well in a nearly radial flow using finite difference and particle tracking Radom walks. To observe the animation of the plume progress in time, one has to download the file. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/tracerinradialflow-211206170637-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is a result of Simulation of Tracer Injection from a well in a nearly radial flow using finite difference and particle tracking Radom walks. To observe the animation of the plume progress in time, one has to download the file.

Simulation of Tracer Injection from a Well in a Nearly Radial Flow from Amro Elfeki

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0 Aquifer recharge from flash floods in the arid environment: A mass balance approach at the catchment scale /slideshow/aquifer-recharge-from-flash-floods-in-the-arid-environment-a-mass-balance-approach-at-the-catchment-scale/250494960 aquiferrechargeblackrevised-211021194527
Estimation of the infiltration/natural recharge to groundwater from rainfall is an important issue in hydrology, particularly in arid regions. This paper proposes the application of The Natural Resources Conservation Service (NRCS) mass balance model to develop infiltration (F)–rainfall (P) relationship from flash flood events. Moreover, the NRCS method is compared with the rational and the Ф-index methods to investigate the discrepancies between these methods. The methods have been applied to five gauged basins and their 19 sub-basins (representative basins with detailed measurements) in the southwestern part of Saudi Arabia with 161 storms recorded in 4 years. The F–P relationships developed in this study based on NRCS method are: F = 39% P with R2 = 0.932 for the initial abstraction factor, λ = 0.2. However, F = 77% P with R2 = 0.986 for λ = 0.01. The model at λ = 0.01 is the best to fit the data, therefore, it is recommended to use the formula at λ = 0.01. The results show that the NRCS model is appropriate for the estimation of the F–P relationships in arid regions when compared with the rational and the Ф index methods. The latter overestimates the infiltration because they do not take λ into account. There is no significant difference between F–P relationships at different time scales. This helps the prediction of infiltration rates for aquifer recharge at ungauged basins from monthly and annual rainfall data with a single formula.]]>
Estimation of the infiltration/natural recharge to groundwater from rainfall is an important issue in hydrology, particularly in arid regions. This paper proposes the application of The Natural Resources Conservation Service (NRCS) mass balance model to develop infiltration (F)–rainfall (P) relationship from flash flood events. Moreover, the NRCS method is compared with the rational and the Ф-index methods to investigate the discrepancies between these methods. The methods have been applied to five gauged basins and their 19 sub-basins (representative basins with detailed measurements) in the southwestern part of Saudi Arabia with 161 storms recorded in 4 years. The F–P relationships developed in this study based on NRCS method are: F = 39% P with R2 = 0.932 for the initial abstraction factor, λ = 0.2. However, F = 77% P with R2 = 0.986 for λ = 0.01. The model at λ = 0.01 is the best to fit the data, therefore, it is recommended to use the formula at λ = 0.01. The results show that the NRCS model is appropriate for the estimation of the F–P relationships in arid regions when compared with the rational and the Ф index methods. The latter overestimates the infiltration because they do not take λ into account. There is no significant difference between F–P relationships at different time scales. This helps the prediction of infiltration rates for aquifer recharge at ungauged basins from monthly and annual rainfall data with a single formula.]]> Thu, 21 Oct 2021 19:45:26 GMT /slideshow/aquifer-recharge-from-flash-floods-in-the-arid-environment-a-mass-balance-approach-at-the-catchment-scale/250494960 AmroElfeki@slideshare.net(AmroElfeki) Aquifer recharge from flash floods in the arid environment: A mass balance approach at the catchment scale AmroElfeki Estimation of the infiltration/natural recharge to groundwater from rainfall is an important issue in hydrology, particularly in arid regions. This paper proposes the application of The Natural Resources Conservation Service (NRCS) mass balance model to develop infiltration (F)–rainfall (P) relationship from flash flood events. Moreover, the NRCS method is compared with the rational and the Ф-index methods to investigate the discrepancies between these methods. The methods have been applied to five gauged basins and their 19 sub-basins (representative basins with detailed measurements) in the southwestern part of Saudi Arabia with 161 storms recorded in 4 years. The F–P relationships developed in this study based on NRCS method are: F = 39% P with R2 = 0.932 for the initial abstraction factor, λ = 0.2. However, F = 77% P with R2 = 0.986 for λ = 0.01. The model at λ = 0.01 is the best to fit the data, therefore, it is recommended to use the formula at λ = 0.01. The results show that the NRCS model is appropriate for the estimation of the F–P relationships in arid regions when compared with the rational and the Ф index methods. The latter overestimates the infiltration because they do not take λ into account. There is no significant difference between F–P relationships at different time scales. This helps the prediction of infiltration rates for aquifer recharge at ungauged basins from monthly and annual rainfall data with a single formula. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aquiferrechargeblackrevised-211021194527-thumbnail.jpg?width=120&height=120&fit=bounds" /> Estimation of the infiltration/natural recharge to groundwater from rainfall is an important issue in hydrology, particularly in arid regions. This paper proposes the application of The Natural Resources Conservation Service (NRCS) mass balance model to develop infiltration (F)–rainfall (P) relationship from flash flood events. Moreover, the NRCS method is compared with the rational and the Ф-index methods to investigate the discrepancies between these methods. The methods have been applied to five gauged basins and their 19 sub-basins (representative basins with detailed measurements) in the southwestern part of Saudi Arabia with 161 storms recorded in 4 years. The F–P relationships developed in this study based on NRCS method are: F = 39% P with R2 = 0.932 for the initial abstraction factor, λ = 0.2. However, F = 77% P with R2 = 0.986 for λ = 0.01. The model at λ = 0.01 is the best to fit the data, therefore, it is recommended to use the formula at λ = 0.01. The results show that the NRCS model is appropriate for the estimation of the F–P relationships in arid regions when compared with the rational and the Ф index methods. The latter overestimates the infiltration because they do not take λ into account. There is no significant difference between F–P relationships at different time scales. This helps the prediction of infiltration rates for aquifer recharge at ungauged basins from monthly and annual rainfall data with a single formula.

Aquifer recharge from flash floods in the arid environment: A mass balance approach at the catchment scale from Amro Elfeki

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0 Basics of Contaminant Transport in Aquifers (Lecture) /slideshow/basics-of-contaminant-transport-in-aquifers-lecture/236791621 ch5basicscontaminanttransport-200710165124
This is a basic lecture on contaminant transport in aquifers. It covers various aspects. Types of transport in aquifers. Reactive and non-reactive, governing equations of solute transport. Method of solutions and simulations. ]]>
This is a basic lecture on contaminant transport in aquifers. It covers various aspects. Types of transport in aquifers. Reactive and non-reactive, governing equations of solute transport. Method of solutions and simulations. ]]> Fri, 10 Jul 2020 16:51:24 GMT /slideshow/basics-of-contaminant-transport-in-aquifers-lecture/236791621 AmroElfeki@slideshare.net(AmroElfeki) Basics of Contaminant Transport in Aquifers (Lecture) AmroElfeki This is a basic lecture on contaminant transport in aquifers. It covers various aspects. Types of transport in aquifers. Reactive and non-reactive, governing equations of solute transport. Method of solutions and simulations. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ch5basicscontaminanttransport-200710165124-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is a basic lecture on contaminant transport in aquifers. It covers various aspects. Types of transport in aquifers. Reactive and non-reactive, governing equations of solute transport. Method of solutions and simulations.

Basics of Contaminant Transport in Aquifers (Lecture) from Amro Elfeki

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0 Well Hydraulics (Lecture 1) /slideshow/well-hydraulics-lecture-1/236790867 ch3wellhydraulics1-200710162454
This is a lecture on well hydraulics. The basics of flow towards the well in confined and unconfined aquifers. Well interactions. Method of images. Flow nets in case of multiple wells. Superposition theory for multiple wells. ]]>
This is a lecture on well hydraulics. The basics of flow towards the well in confined and unconfined aquifers. Well interactions. Method of images. Flow nets in case of multiple wells. Superposition theory for multiple wells. ]]> Fri, 10 Jul 2020 16:24:53 GMT /slideshow/well-hydraulics-lecture-1/236790867 AmroElfeki@slideshare.net(AmroElfeki) Well Hydraulics (Lecture 1) AmroElfeki This is a lecture on well hydraulics. The basics of flow towards the well in confined and unconfined aquifers. Well interactions. Method of images. Flow nets in case of multiple wells. Superposition theory for multiple wells. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ch3wellhydraulics1-200710162454-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is a lecture on well hydraulics. The basics of flow towards the well in confined and unconfined aquifers. Well interactions. Method of images. Flow nets in case of multiple wells. Superposition theory for multiple wells.

Well Hydraulics (Lecture 1) from Amro Elfeki

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0 Gradually Varied Flow in Open Channel /slideshow/gradually-varied-flow-in-open-channel/236082616 gvflecture-200623075727
This is a lecture on the hydraulics of gradually varied flow in open channels. It shows the profiles common in the open channels and some numerical examples using numerical integration. ]]>
This is a lecture on the hydraulics of gradually varied flow in open channels. It shows the profiles common in the open channels and some numerical examples using numerical integration. ]]> Tue, 23 Jun 2020 07:57:27 GMT /slideshow/gradually-varied-flow-in-open-channel/236082616 AmroElfeki@slideshare.net(AmroElfeki) Gradually Varied Flow in Open Channel AmroElfeki This is a lecture on the hydraulics of gradually varied flow in open channels. It shows the profiles common in the open channels and some numerical examples using numerical integration. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/gvflecture-200623075727-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is a lecture on the hydraulics of gradually varied flow in open channels. It shows the profiles common in the open channels and some numerical examples using numerical integration.

Gradually Varied Flow in Open Channel from Amro Elfeki

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0 Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS and GIS (Case Study in Jeddah City, Saudi Arabia) /slideshow/two-dimensional-flood-inundation-modelling-in-urban-area-using-wms-hecras-and-gis-case-study-in-jeddah-city-saudi-arabia/182884706 cajg-2018-ppt-kuswantoromarko-191016184910
This research presents a two-dimensional flood inundation modelling in urbanized areas when some features such as roads, buildings, and fences have great effect on flood propagation. Wadi Qows located in Jeddah City, Saudi Arabia was chosen as case study area because of the flood occurrence of 2009 causing lots of losses either economic or loss of life. The WMS and HEC-RAS program were used for a hydraulic simulation based on channel geometry built by incorporating urban features into DEM using GIS effectively. A resampling method of DEM 90 × 90 m become 10 × 10 m grid cell sizes was conducted to produce a higher resolution DEM suitable for urban flood inundation modelling. The results show that a higher resolution leads to increasing the average flood depth and decreasing the flood extent. Although the change of the grid cell sizes does not affect its elevation values, this approach is helpful to perform flood simulations in urban areas when high resolution DEM availability is limited. In addition, the integration of WMS, HEC-RAS and GIS are powerful tools for flood modelling in rural, mountainous and urban areas. https://www.researchgate.net/publication/330004725_Two_Dimensional_Flood_Inundation_Modelling_in_Urban_Areas_Using_WMS_HEC-RAS_and_GIS_Case_Study_in_Jeddah_City_Saudi_Arabia_IEREK_Interdisciplinary_Series_for_Sustainable_Development]]>
This research presents a two-dimensional flood inundation modelling in urbanized areas when some features such as roads, buildings, and fences have great effect on flood propagation. Wadi Qows located in Jeddah City, Saudi Arabia was chosen as case study area because of the flood occurrence of 2009 causing lots of losses either economic or loss of life. The WMS and HEC-RAS program were used for a hydraulic simulation based on channel geometry built by incorporating urban features into DEM using GIS effectively. A resampling method of DEM 90 × 90 m become 10 × 10 m grid cell sizes was conducted to produce a higher resolution DEM suitable for urban flood inundation modelling. The results show that a higher resolution leads to increasing the average flood depth and decreasing the flood extent. Although the change of the grid cell sizes does not affect its elevation values, this approach is helpful to perform flood simulations in urban areas when high resolution DEM availability is limited. In addition, the integration of WMS, HEC-RAS and GIS are powerful tools for flood modelling in rural, mountainous and urban areas. https://www.researchgate.net/publication/330004725_Two_Dimensional_Flood_Inundation_Modelling_in_Urban_Areas_Using_WMS_HEC-RAS_and_GIS_Case_Study_in_Jeddah_City_Saudi_Arabia_IEREK_Interdisciplinary_Series_for_Sustainable_Development]]> Wed, 16 Oct 2019 18:49:10 GMT /slideshow/two-dimensional-flood-inundation-modelling-in-urban-area-using-wms-hecras-and-gis-case-study-in-jeddah-city-saudi-arabia/182884706 AmroElfeki@slideshare.net(AmroElfeki) Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS and GIS (Case Study in Jeddah City, Saudi Arabia) AmroElfeki This research presents a two-dimensional flood inundation modelling in urbanized areas when some features such as roads, buildings, and fences have great effect on flood propagation. Wadi Qows located in Jeddah City, Saudi Arabia was chosen as case study area because of the flood occurrence of 2009 causing lots of losses either economic or loss of life. The WMS and HEC-RAS program were used for a hydraulic simulation based on channel geometry built by incorporating urban features into DEM using GIS effectively. A resampling method of DEM 90 × 90 m become 10 × 10 m grid cell sizes was conducted to produce a higher resolution DEM suitable for urban flood inundation modelling. The results show that a higher resolution leads to increasing the average flood depth and decreasing the flood extent. Although the change of the grid cell sizes does not affect its elevation values, this approach is helpful to perform flood simulations in urban areas when high resolution DEM availability is limited. In addition, the integration of WMS, HEC-RAS and GIS are powerful tools for flood modelling in rural, mountainous and urban areas. https://www.researchgate.net/publication/330004725_Two_Dimensional_Flood_Inundation_Modelling_in_Urban_Areas_Using_WMS_HEC-RAS_and_GIS_Case_Study_in_Jeddah_City_Saudi_Arabia_IEREK_Interdisciplinary_Series_for_Sustainable_Development <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/cajg-2018-ppt-kuswantoromarko-191016184910-thumbnail.jpg?width=120&height=120&fit=bounds" /> This research presents a two-dimensional flood inundation modelling in urbanized areas when some features such as roads, buildings, and fences have great effect on flood propagation. Wadi Qows located in Jeddah City, Saudi Arabia was chosen as case study area because of the flood occurrence of 2009 causing lots of losses either economic or loss of life. The WMS and HEC-RAS program were used for a hydraulic simulation based on channel geometry built by incorporating urban features into DEM using GIS effectively. A resampling method of DEM 90 × 90 m become 10 × 10 m grid cell sizes was conducted to produce a higher resolution DEM suitable for urban flood inundation modelling. The results show that a higher resolution leads to increasing the average flood depth and decreasing the flood extent. Although the change of the grid cell sizes does not affect its elevation values, this approach is helpful to perform flood simulations in urban areas when high resolution DEM availability is limited. In addition, the integration of WMS, HEC-RAS and GIS are powerful tools for flood modelling in rural, mountainous and urban areas. https://www.researchgate.net/publication/330004725_Two_Dimensional_Flood_Inundation_Modelling_in_Urban_Areas_Using_WMS_HEC-RAS_and_GIS_Case_Study_in_Jeddah_City_Saudi_Arabia_IEREK_Interdisciplinary_Series_for_Sustainable_Development

Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS and GIS (Case Study in Jeddah City, Saudi Arabia) from Amro Elfeki

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0 Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Simulations and Reduction of Uncertainties) /slideshow/lecture-6-stochastic-hydrology-estimation-problemkriging-conditional-simulations-and-reduction-of-uncertainties/140082962 lecture6-190408192313
Estimation Problem (Kriging), Conditional Simulations and Reduction of Uncertainties ]]>
Estimation Problem (Kriging), Conditional Simulations and Reduction of Uncertainties ]]> Mon, 08 Apr 2019 19:23:13 GMT /slideshow/lecture-6-stochastic-hydrology-estimation-problemkriging-conditional-simulations-and-reduction-of-uncertainties/140082962 AmroElfeki@slideshare.net(AmroElfeki) Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Simulations and Reduction of Uncertainties) AmroElfeki Estimation Problem (Kriging), Conditional Simulations and Reduction of Uncertainties <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lecture6-190408192313-thumbnail.jpg?width=120&height=120&fit=bounds" /> Estimation Problem (Kriging), Conditional Simulations and Reduction of Uncertainties

Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Simulations and Reduction of Uncertainties) from Amro Elfeki

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0 Lecture 5: Stochastic Hydrology /slideshow/lecture-5-stochastic-hydrology/140082715 lecture5-190408192109
Stochastic Differential Equations and Methods of Solution: Theory and Exercise]]>
Stochastic Differential Equations and Methods of Solution: Theory and Exercise]]> Mon, 08 Apr 2019 19:21:09 GMT /slideshow/lecture-5-stochastic-hydrology/140082715 AmroElfeki@slideshare.net(AmroElfeki) Lecture 5: Stochastic Hydrology AmroElfeki Stochastic Differential Equations and Methods of Solution: Theory and Exercise <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lecture5-190408192109-thumbnail.jpg?width=120&height=120&fit=bounds" /> Stochastic Differential Equations and Methods of Solution: Theory and Exercise

Lecture 5: Stochastic Hydrology from Amro Elfeki

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0 Lecture 4: Stochastic Hydrology (Site Characterization) /AmroElfeki/lecture-4-stochastic-hydrology-site-characterization lecture4-190408191902
Stochastic Models for for Site Characterization: Computer Exercise ]]>
Stochastic Models for for Site Characterization: Computer Exercise ]]> Mon, 08 Apr 2019 19:19:02 GMT /AmroElfeki/lecture-4-stochastic-hydrology-site-characterization AmroElfeki@slideshare.net(AmroElfeki) Lecture 4: Stochastic Hydrology (Site Characterization) AmroElfeki Stochastic Models for for Site Characterization: Computer Exercise <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lecture4-190408191902-thumbnail.jpg?width=120&height=120&fit=bounds" /> Stochastic Models for for Site Characterization: Computer Exercise

Lecture 4: Stochastic Hydrology (Site Characterization) from Amro Elfeki

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0 Lecture 3: Stochastic Hydrology /slideshow/lecture-3-stochastic-hydrology/140082354 lecture3-190408191752
Stochastic models for site characterization: Theory]]>
Stochastic models for site characterization: Theory]]> Mon, 08 Apr 2019 19:17:52 GMT /slideshow/lecture-3-stochastic-hydrology/140082354 AmroElfeki@slideshare.net(AmroElfeki) Lecture 3: Stochastic Hydrology AmroElfeki Stochastic models for site characterization: Theory <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lecture3-190408191752-thumbnail.jpg?width=120&height=120&fit=bounds" /> Stochastic models for site characterization: Theory

Lecture 3: Stochastic Hydrology from Amro Elfeki

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0 Lecture 2: Stochastic Hydrology /slideshow/lecture-2-stochastic-hydrology/140082157 lecture2-190408191619
Representation of of Stochastic Processes in Stochastic Processes in Real and Spectral Domains Real and Spectral Domains and and Monte Monte-Carlo sampling]]>
Representation of of Stochastic Processes in Stochastic Processes in Real and Spectral Domains Real and Spectral Domains and and Monte Monte-Carlo sampling]]> Mon, 08 Apr 2019 19:16:19 GMT /slideshow/lecture-2-stochastic-hydrology/140082157 AmroElfeki@slideshare.net(AmroElfeki) Lecture 2: Stochastic Hydrology AmroElfeki Representation of of Stochastic Processes in Stochastic Processes in Real and Spectral Domains Real and Spectral Domains and and Monte Monte-Carlo sampling <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lecture2-190408191619-thumbnail.jpg?width=120&height=120&fit=bounds" /> Representation of of Stochastic Processes in Stochastic Processes in Real and Spectral Domains Real and Spectral Domains and and Monte Monte-Carlo sampling

Lecture 2: Stochastic Hydrology from Amro Elfeki

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0 Stochastic Hydrology Lecture 1: Introduction /AmroElfeki/stochastic-hydrology-lecture-1-introduction lecture1-190407221228
Introduction Introduction to Probability to Probability Theory and Statistics of Theory and Statistics of Single and Multi Single and Multi-Variate]]>
Introduction Introduction to Probability to Probability Theory and Statistics of Theory and Statistics of Single and Multi Single and Multi-Variate]]> Sun, 07 Apr 2019 22:12:28 GMT /AmroElfeki/stochastic-hydrology-lecture-1-introduction AmroElfeki@slideshare.net(AmroElfeki) Stochastic Hydrology Lecture 1: Introduction AmroElfeki Introduction Introduction to Probability to Probability Theory and Statistics of Theory and Statistics of Single and Multi Single and Multi-Variate <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lecture1-190407221228-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introduction Introduction to Probability to Probability Theory and Statistics of Theory and Statistics of Single and Multi Single and Multi-Variate

Stochastic Hydrology Lecture 1: Introduction from Amro Elfeki

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0 Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case Study Taibah and Islamic Universities' Campuses /slideshow/development-of-flash-flood-risk-assessment-matrix-in-arid-environment-case-study-taibah-and-islamic-universities-campuses/139952422 powerpointprenstation219-190407220349
Risk indices and risk matrix have been used among governmental agencies for assessing risks and ranking alternatives protection measures. The popularity of risk matrices can be associated with its characteristics to quick assessing risk and providing inexpensive solutions. The risk assessment is associated with flood protection as: economic, environmental, and life-safety. Economic risks are reasonably well dealt with by the well-known traditional cost-benefit analysis, insurance, and financial markets. Environmental risks are difficult to assess by traditional methods in flood project evaluation. Environmental consequences cannot be directly measured, while social risks represent the most challenge to quantify. It may be possible to estimate the number of fatalities, and cost of damaged infrastructures, while the social aspects cannot be measured. This paper is proposing a flood risk matrix technique for assessing risks in urban arid and extreme arid regions demonstrated through case-study application on the catchment of Taibah University (TU) and Islamic University (IU) in Medina, KSA. The study focused on assessing the geographical impacts of the flash flood inundated depths for different frequencies from 5 to 100 years return periods leading to identification of the flood channels, and its floodplains that may be vulnerable to different degrees of flood hazards. ]]>
Risk indices and risk matrix have been used among governmental agencies for assessing risks and ranking alternatives protection measures. The popularity of risk matrices can be associated with its characteristics to quick assessing risk and providing inexpensive solutions. The risk assessment is associated with flood protection as: economic, environmental, and life-safety. Economic risks are reasonably well dealt with by the well-known traditional cost-benefit analysis, insurance, and financial markets. Environmental risks are difficult to assess by traditional methods in flood project evaluation. Environmental consequences cannot be directly measured, while social risks represent the most challenge to quantify. It may be possible to estimate the number of fatalities, and cost of damaged infrastructures, while the social aspects cannot be measured. This paper is proposing a flood risk matrix technique for assessing risks in urban arid and extreme arid regions demonstrated through case-study application on the catchment of Taibah University (TU) and Islamic University (IU) in Medina, KSA. The study focused on assessing the geographical impacts of the flash flood inundated depths for different frequencies from 5 to 100 years return periods leading to identification of the flood channels, and its floodplains that may be vulnerable to different degrees of flood hazards. ]]> Sun, 07 Apr 2019 22:03:49 GMT /slideshow/development-of-flash-flood-risk-assessment-matrix-in-arid-environment-case-study-taibah-and-islamic-universities-campuses/139952422 AmroElfeki@slideshare.net(AmroElfeki) Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case Study Taibah and Islamic Universities' Campuses AmroElfeki Risk indices and risk matrix have been used among governmental agencies for assessing risks and ranking alternatives protection measures. The popularity of risk matrices can be associated with its characteristics to quick assessing risk and providing inexpensive solutions. The risk assessment is associated with flood protection as: economic, environmental, and life-safety. Economic risks are reasonably well dealt with by the well-known traditional cost-benefit analysis, insurance, and financial markets. Environmental risks are difficult to assess by traditional methods in flood project evaluation. Environmental consequences cannot be directly measured, while social risks represent the most challenge to quantify. It may be possible to estimate the number of fatalities, and cost of damaged infrastructures, while the social aspects cannot be measured. This paper is proposing a flood risk matrix technique for assessing risks in urban arid and extreme arid regions demonstrated through case-study application on the catchment of Taibah University (TU) and Islamic University (IU) in Medina, KSA. The study focused on assessing the geographical impacts of the flash flood inundated depths for different frequencies from 5 to 100 years return periods leading to identification of the flood channels, and its floodplains that may be vulnerable to different degrees of flood hazards. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/powerpointprenstation219-190407220349-thumbnail.jpg?width=120&height=120&fit=bounds" /> Risk indices and risk matrix have been used among governmental agencies for assessing risks and ranking alternatives protection measures. The popularity of risk matrices can be associated with its characteristics to quick assessing risk and providing inexpensive solutions. The risk assessment is associated with flood protection as: economic, environmental, and life-safety. Economic risks are reasonably well dealt with by the well-known traditional cost-benefit analysis, insurance, and financial markets. Environmental risks are difficult to assess by traditional methods in flood project evaluation. Environmental consequences cannot be directly measured, while social risks represent the most challenge to quantify. It may be possible to estimate the number of fatalities, and cost of damaged infrastructures, while the social aspects cannot be measured. This paper is proposing a flood risk matrix technique for assessing risks in urban arid and extreme arid regions demonstrated through case-study application on the catchment of Taibah University (TU) and Islamic University (IU) in Medina, KSA. The study focused on assessing the geographical impacts of the flash flood inundated depths for different frequencies from 5 to 100 years return periods leading to identification of the flood channels, and its floodplains that may be vulnerable to different degrees of flood hazards.

Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case Study Taibah and Islamic Universities' Campuses from Amro Elfeki

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0 Soft Computing and Simulation in Water Resources: Chapter 1 introduction /slideshow/soft-computing-and-simulation-in-water-resources-chapter-1-introduction/98679053 chapter1introduction-180525131528
This is the introductory lecture to Soft Computing and Simulation in Water Resources course. ]]>
This is the introductory lecture to Soft Computing and Simulation in Water Resources course. ]]> Fri, 25 May 2018 13:15:27 GMT /slideshow/soft-computing-and-simulation-in-water-resources-chapter-1-introduction/98679053 AmroElfeki@slideshare.net(AmroElfeki) Soft Computing and Simulation in Water Resources: Chapter 1 introduction AmroElfeki This is the introductory lecture to Soft Computing and Simulation in Water Resources course. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/chapter1introduction-180525131528-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is the introductory lecture to Soft Computing and Simulation in Water Resources course.

Soft Computing and Simulation in Water Resources: Chapter 1 introduction from Amro Elfeki

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0 Derivation of unit hydrograph of Al-Lith basin in the south west of saudi arabia /slideshow/derivation-of-unit-hydrograph-of-allith-basin-in-the-south-west-of-saudi-arabia/86702968 0106derivationofunithydrographofallithbasininthesouthwestofsaudiarabia-180125182452
Mohammad Albishi, Jarbou Bahrawi and Amro Elfeki (2016). Derivation of the Unit Hydrograph of Allith Basin in the South West of Saudi Arabia. 7 International Conference on Water Resources and the Arid Environments (ICWRAE 7): 621-628 4-6 December 2016, Riyadh, Saudi Arabia. Abstract: Most studies on unit hydrograph theory is developed for temperate regions and to the best of the authors’ knowledge, there is no studies on this topic in arid regions because of the lack of runoff measurements. This paper presents the derivation of a unit hydrograph of a Allith basin and its S-curve in the south western part of Saudi Arabia to be used to predict flash flood more accurately in this region. The derivation is based on the method of stream flow data that has been collected from measured rainfall and runoff storms in the region. The study resulted in the unit hydrograph of 1 hr duration and the S-curve that is used to transfer the hydrograph to any other durations. This unit hydrograph can be used to predict flash floods in Allith basin and similar watersheds. ]]>
Mohammad Albishi, Jarbou Bahrawi and Amro Elfeki (2016). Derivation of the Unit Hydrograph of Allith Basin in the South West of Saudi Arabia. 7 International Conference on Water Resources and the Arid Environments (ICWRAE 7): 621-628 4-6 December 2016, Riyadh, Saudi Arabia. Abstract: Most studies on unit hydrograph theory is developed for temperate regions and to the best of the authors’ knowledge, there is no studies on this topic in arid regions because of the lack of runoff measurements. This paper presents the derivation of a unit hydrograph of a Allith basin and its S-curve in the south western part of Saudi Arabia to be used to predict flash flood more accurately in this region. The derivation is based on the method of stream flow data that has been collected from measured rainfall and runoff storms in the region. The study resulted in the unit hydrograph of 1 hr duration and the S-curve that is used to transfer the hydrograph to any other durations. This unit hydrograph can be used to predict flash floods in Allith basin and similar watersheds. ]]> Thu, 25 Jan 2018 18:24:52 GMT /slideshow/derivation-of-unit-hydrograph-of-allith-basin-in-the-south-west-of-saudi-arabia/86702968 AmroElfeki@slideshare.net(AmroElfeki) Derivation of unit hydrograph of Al-Lith basin in the south west of saudi arabia AmroElfeki Mohammad Albishi, Jarbou Bahrawi and Amro Elfeki (2016). Derivation of the Unit Hydrograph of Allith Basin in the South West of Saudi Arabia. 7 International Conference on Water Resources and the Arid Environments (ICWRAE 7): 621-628 4-6 December 2016, Riyadh, Saudi Arabia. Abstract: Most studies on unit hydrograph theory is developed for temperate regions and to the best of the authors’ knowledge, there is no studies on this topic in arid regions because of the lack of runoff measurements. This paper presents the derivation of a unit hydrograph of a Allith basin and its S-curve in the south western part of Saudi Arabia to be used to predict flash flood more accurately in this region. The derivation is based on the method of stream flow data that has been collected from measured rainfall and runoff storms in the region. The study resulted in the unit hydrograph of 1 hr duration and the S-curve that is used to transfer the hydrograph to any other durations. This unit hydrograph can be used to predict flash floods in Allith basin and similar watersheds. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/0106derivationofunithydrographofallithbasininthesouthwestofsaudiarabia-180125182452-thumbnail.jpg?width=120&height=120&fit=bounds" /> Mohammad Albishi, Jarbou Bahrawi and Amro Elfeki (2016). Derivation of the Unit Hydrograph of Allith Basin in the South West of Saudi Arabia. 7 International Conference on Water Resources and the Arid Environments (ICWRAE 7): 621-628 4-6 December 2016, Riyadh, Saudi Arabia. Abstract: Most studies on unit hydrograph theory is developed for temperate regions and to the best of the authors’ knowledge, there is no studies on this topic in arid regions because of the lack of runoff measurements. This paper presents the derivation of a unit hydrograph of a Allith basin and its S-curve in the south western part of Saudi Arabia to be used to predict flash flood more accurately in this region. The derivation is based on the method of stream flow data that has been collected from measured rainfall and runoff storms in the region. The study resulted in the unit hydrograph of 1 hr duration and the S-curve that is used to transfer the hydrograph to any other durations. This unit hydrograph can be used to predict flash floods in Allith basin and similar watersheds.

Derivation of unit hydrograph of Al-Lith basin in the south west of saudi arabia from Amro Elfeki

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0 Empirical equations for flood analysis in arid zones /slideshow/empirical-equations-for-flood-analysis-in-arid-zones/86702865 empiricalequationsforfloodanalysisinaridzones-180125182227
Mohammad Albishi, Jarbou Bahrawi, and Amro Elfeki (2016). Empirical Equations for Flood Analysis in Arid Zones. Published in the book of abstracts at IWC 2016 International Water Conference 2016 on Water Resources in Arid Areas: the Way Forward. ]]>
Mohammad Albishi, Jarbou Bahrawi, and Amro Elfeki (2016). Empirical Equations for Flood Analysis in Arid Zones. Published in the book of abstracts at IWC 2016 International Water Conference 2016 on Water Resources in Arid Areas: the Way Forward. ]]> Thu, 25 Jan 2018 18:22:27 GMT /slideshow/empirical-equations-for-flood-analysis-in-arid-zones/86702865 AmroElfeki@slideshare.net(AmroElfeki) Empirical equations for flood analysis in arid zones AmroElfeki Mohammad Albishi, Jarbou Bahrawi, and Amro Elfeki (2016). Empirical Equations for Flood Analysis in Arid Zones. Published in the book of abstracts at IWC 2016 International Water Conference 2016 on Water Resources in Arid Areas: the Way Forward. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/empiricalequationsforfloodanalysisinaridzones-180125182227-thumbnail.jpg?width=120&height=120&fit=bounds" /> Mohammad Albishi, Jarbou Bahrawi, and Amro Elfeki (2016). Empirical Equations for Flood Analysis in Arid Zones. Published in the book of abstracts at IWC 2016 International Water Conference 2016 on Water Resources in Arid Areas: the Way Forward.

Empirical equations for flood analysis in arid zones from Amro Elfeki

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0 Simulation of the central limit theorem /slideshow/simulation-of-the-central-limit-theorem/86702504 simulationofthecentrallimittheorem-180125181501
This presentation illustrates the concept of the central limit theorem. How the uniform distribution converges to the normal distribution. ]]>
This presentation illustrates the concept of the central limit theorem. How the uniform distribution converges to the normal distribution. ]]> Thu, 25 Jan 2018 18:15:01 GMT /slideshow/simulation-of-the-central-limit-theorem/86702504 AmroElfeki@slideshare.net(AmroElfeki) Simulation of the central limit theorem AmroElfeki This presentation illustrates the concept of the central limit theorem. How the uniform distribution converges to the normal distribution. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/simulationofthecentrallimittheorem-180125181501-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation illustrates the concept of the central limit theorem. How the uniform distribution converges to the normal distribution.

Simulation of the central limit theorem from Amro Elfeki

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0 Empirical equations for estimation of transmission losses /slideshow/empirical-equations-for-estimation-of-transmission-losses/86702336 empiricalequationsforestimationoftransmissionlosses-180125181127
Transmission losses is caused by infiltration into the streambed in ephemeral streams. The conventional methods for flood routing in wadis is impossible to achieve due to transmission losses. The Muskingum routing procedure in its basic form has two parameters, the channel time lag, Km, and the weighting parameter, x. However, both parameters do not consider transmission losses of floods in channels. O’Donnell 1985 introduced a third parameter, α, in the continuity equation to allow for the lateral movement of floodwater. Elfeki et. Al (2014) carry some modifications of the assumptions such that the negative sign of the parameter α represents transmission losses. In this research, the third-parameter α has been investigated as a tool for estimation of transmission losses using data from Yiba catchment in the Kingdom of Saudi Arabia. A spreadsheet model will be developed to deduce the equations. Proceedings of the Second International Symposium on Flash Floods in Wadi Systems: Disaster Risk Reduction and Water Harvesting in the Arab Region (2016): 166-170 ]]>
Transmission losses is caused by infiltration into the streambed in ephemeral streams. The conventional methods for flood routing in wadis is impossible to achieve due to transmission losses. The Muskingum routing procedure in its basic form has two parameters, the channel time lag, Km, and the weighting parameter, x. However, both parameters do not consider transmission losses of floods in channels. O’Donnell 1985 introduced a third parameter, α, in the continuity equation to allow for the lateral movement of floodwater. Elfeki et. Al (2014) carry some modifications of the assumptions such that the negative sign of the parameter α represents transmission losses. In this research, the third-parameter α has been investigated as a tool for estimation of transmission losses using data from Yiba catchment in the Kingdom of Saudi Arabia. A spreadsheet model will be developed to deduce the equations. Proceedings of the Second International Symposium on Flash Floods in Wadi Systems: Disaster Risk Reduction and Water Harvesting in the Arab Region (2016): 166-170 ]]> Thu, 25 Jan 2018 18:11:27 GMT /slideshow/empirical-equations-for-estimation-of-transmission-losses/86702336 AmroElfeki@slideshare.net(AmroElfeki) Empirical equations for estimation of transmission losses AmroElfeki Transmission losses is caused by infiltration into the streambed in ephemeral streams. The conventional methods for flood routing in wadis is impossible to achieve due to transmission losses. The Muskingum routing procedure in its basic form has two parameters, the channel time lag, Km, and the weighting parameter, x. However, both parameters do not consider transmission losses of floods in channels. O’Donnell 1985 introduced a third parameter, α, in the continuity equation to allow for the lateral movement of floodwater. Elfeki et. Al (2014) carry some modifications of the assumptions such that the negative sign of the parameter α represents transmission losses. In this research, the third-parameter α has been investigated as a tool for estimation of transmission losses using data from Yiba catchment in the Kingdom of Saudi Arabia. A spreadsheet model will be developed to deduce the equations. Proceedings of the Second International Symposium on Flash Floods in Wadi Systems: Disaster Risk Reduction and Water Harvesting in the Arab Region (2016): 166-170 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/empiricalequationsforestimationoftransmissionlosses-180125181127-thumbnail.jpg?width=120&height=120&fit=bounds" /> Transmission losses is caused by infiltration into the streambed in ephemeral streams. The conventional methods for flood routing in wadis is impossible to achieve due to transmission losses. The Muskingum routing procedure in its basic form has two parameters, the channel time lag, Km, and the weighting parameter, x. However, both parameters do not consider transmission losses of floods in channels. O’Donnell 1985 introduced a third parameter, α, in the continuity equation to allow for the lateral movement of floodwater. Elfeki et. Al (2014) carry some modifications of the assumptions such that the negative sign of the parameter α represents transmission losses. In this research, the third-parameter α has been investigated as a tool for estimation of transmission losses using data from Yiba catchment in the Kingdom of Saudi Arabia. A spreadsheet model will be developed to deduce the equations. Proceedings of the Second International Symposium on Flash Floods in Wadi Systems: Disaster Risk Reduction and Water Harvesting in the Arab Region (2016): 166-170

Empirical equations for estimation of transmission losses from Amro Elfeki

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0 Representative elementary volume (rev) in porous /AmroElfeki/representative-elementary-volume-rev-in-porous representativeelementaryvolumerevinporous-171004201545
This presentation shows the concept of Representative elementary volume known in porous media. The presentation is the results of an excel spreadsheet prepared to generate hypothetical porous media in 2D. It calculates the porosity of the medium at different scales until it reaches the rev value.]]>
This presentation shows the concept of Representative elementary volume known in porous media. The presentation is the results of an excel spreadsheet prepared to generate hypothetical porous media in 2D. It calculates the porosity of the medium at different scales until it reaches the rev value.]]> Wed, 04 Oct 2017 20:15:45 GMT /AmroElfeki/representative-elementary-volume-rev-in-porous AmroElfeki@slideshare.net(AmroElfeki) Representative elementary volume (rev) in porous AmroElfeki This presentation shows the concept of Representative elementary volume known in porous media. The presentation is the results of an excel spreadsheet prepared to generate hypothetical porous media in 2D. It calculates the porosity of the medium at different scales until it reaches the rev value. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/representativeelementaryvolumerevinporous-171004201545-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation shows the concept of Representative elementary volume known in porous media. The presentation is the results of an excel spreadsheet prepared to generate hypothetical porous media in 2D. It calculates the porosity of the medium at different scales until it reaches the rev value.

Representative elementary volume (rev) in porous from Amro Elfeki

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0 Civil Engineering Drawings (Collection of Sheets) /slideshow/civil-engineering-drawings-collection-of-sheets/74538076 civildrawings-170406112428
This is the civil engineering drawing course as a power-point presentation (samples of drawings). It helps Civil Engineers. ]]>
This is the civil engineering drawing course as a power-point presentation (samples of drawings). It helps Civil Engineers. ]]> Thu, 06 Apr 2017 11:24:28 GMT /slideshow/civil-engineering-drawings-collection-of-sheets/74538076 AmroElfeki@slideshare.net(AmroElfeki) Civil Engineering Drawings (Collection of Sheets) AmroElfeki This is the civil engineering drawing course as a power-point presentation (samples of drawings). It helps Civil Engineers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/civildrawings-170406112428-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is the civil engineering drawing course as a power-point presentation (samples of drawings). It helps Civil Engineers.

Civil Engineering Drawings (Collection of Sheets) from Amro Elfeki

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0 https://public.slidesharecdn.com/v2/images/profile-picture.png https://cdn.slidesharecdn.com/ss_thumbnails/tracerinradialflow-211206170637-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/simulation-of-tracer-injection-from-a-well-in-a-nearly-radial-flow/250792383 Simulation of Tracer I... https://cdn.slidesharecdn.com/ss_thumbnails/aquiferrechargeblackrevised-211021194527-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/aquifer-recharge-from-flash-floods-in-the-arid-environment-a-mass-balance-approach-at-the-catchment-scale/250494960 Aquifer recharge from ... https://cdn.slidesharecdn.com/ss_thumbnails/ch5basicscontaminanttransport-200710165124-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/basics-of-contaminant-transport-in-aquifers-lecture/236791621 Basics of Contaminant ...