—Predicting the groundwater level has recently become very important research topic especially with the rise of population density and consequently increasing the water demand. This paper uses the Random Forest and linear regression neural network models to predict the groundwater level of Wadi-Alshaty district in the South West part of Libya. The results are compared with that obtained using the hydrologic long-term forecasting graphical approach. One of the most important findings of this study is the effectiveness of the neural network models to investigate the fluctuation of the groundwater levels over time (20 years)
Amna Elhawil, Alarabi Naji, Malak Nuesry, Almabruk Sanossi(12-2021)

Abstract In this study, seepage phenomena through the foundation of Megenin dam are investigated. Most of the recorded dam’s failure around the world are related to seepage problems. Therefore to avoid failure of earth dams due to seepage, settlement, and piping, continuous field observations are essential. The Megenin dam is a 38 m high rock fill dam. A concrete cut-off wall and grout curtain were constructed below the dam body to prevent reservoir seepage through the foundation.The dam was constructed in 1972, for two main purposes; first to control floods for the cultivated fields downstream and to protect Tripoli city, secondly to collect water for irrigation. On 15thMay 2003 during the 3rd filling, the water level in the reservoir reached 271.86 m, while seepage water was observed in the wadi bed downstream of the main dam. This phenomena were also observed in previous times. The Piezometric water level was much higher compared to that previously measured. To assess the seepage phenomena and the impact on dam safety, the folowing were applied: the technique of ground penetrating radar survey (GPR), piezometric analysis, and temperature field evaluation. Constructed a flow net model for the dam.The results of the study showed that: GPR profiles describe critical zones in the dam site. Identify the water seepage paths from dam reservoir to down stream of dam.Determine the amount of total water seepage capacity through the dam foundation (Q= 0.08 Ɩ / s ).The essential points to avoid any problem that may occur in the future in Megenin dam due to seepage problems.
ناجي محمد شكشم (2009)

Abstract The ever-growing numbers of people and vehicles seen by the Libyan cities at the present time, and the consequent increase economic and social development was held after the last incumbent to think of future supply in the system of road network in Tripoli after a decade or several decades to respond to the request and in particular the urgent need for radical solutions to all problems of congestion and bottlenecks and traffic accidents that were not the same size, severity and loss of physical and moral than ever before. This study addressed the focus of transportation planning, transport and highlighted the various stages of transport planning and reviewed the most important models used to predict the future traffic volumes, a resurgence or trip generation, trip distribution, mode of choice and traffic Assignment, where the focus of this study the first type of models which trip generation in the study area in Tripoli. And has been a review of some international studies in this area in both the United States of America, China, Korea, Iran, Nigeria, Egypt, Saudi Arabia, the focus in these studies to examine the variables affecting the creation of trips, the so-called independent variables affecting a number of family members and the number of vehicles and number of employees and income, the same factors that have been taken into account in the study area in Tripoli. Were identified the study area within the Centre for the city of Tripoli Commercial (CBD) called green belt area and specifically (range locality Martyrs coast and Aleneuvliyn), which recently experienced jams unprecedented, was the use of both methods for regression analysis to create a mathematical model is calculated both (Average trips, vehicle trips, and work trips) and Cross Classification Analysis to find work trips of the classification (number of vehicles / household size) and finding vehicle trips from category (the number of employees / income). Data were collected and information on the ground and through the questionnaire prepared by families in the region through the use of home Meetups and interviews necessary for the formation of mathematical models for the study and were compared with the results of both methods as used was to highlight the most important software modern and universally used in the travel demand. The study concluded the adoption of two models of regression to find trips generated, the first to find the average trips and the second vehicle trips The model work trips, he was excluded for being unfit, the Statistical The comparison higher efficiency of the regression model vehicle trips than cross classification analysis table to find the estimated values in generated trip, as a set of recommendations aimed at reducing the obstacles and difficulties in finding and the formation of specialized models to calculate the demand for mobility in cities of Libya
أمل فتح الله زايد (2010)