Construction of Deep Thermal Models Based on Integrated Thermal Properties Used for Geothermal Risk Management

Mathematical Geosciences - The development of deep geothermal energy may be at risk from the economic point of view if the estimated deep thermal field is far from its real state. The strong...     

Fluoride in Quaternary groundwater aquifer,Nile Valley,Luxor, Egypt

The occurrence of fluoride in ground water is the focus of the public and has attracted the attention of many scientists all over the world due to its importance in public health. Deficiency or increase of fluoride uptake is considered a public health problem due to the narrow permissible limit which should not exceed 1.5 mg/l according to the World Health Organization (WHO). The range of fluoride tolerance and toxicity is narrow. Deviation from the optimal levels therefore results in dental health effects such as caries and fluorosis. Many studies have found fluorosis to be invariably associated with high concentrations of fluoride in drinking water. Fluorosis is a considerable health problem in many areas of the world including Brazil, China, East Africa, Ghana, India, Kenya, Korea, Malawi, Mexico, Pakistan, South Africa, southeastern Korea, Spain, Sri Lanka, Sudan, Taiwan, Tanzania, and Turkey. Fluoride in groundwater of Quaternary aquifer of the Nile Valley, Egypt, does not gain the attention of the authors in the Nile Valley which makes the public health status of fluoride is not certain. The present work aims at investigating the fluoride concentration of Quaternary groundwater aquifer at Luxor as a representative area of the Nile Valley to be a base line for subsequent studies and criteria for public health. Ground water samples were collected from Quaternary groundwater aquifer at Luxor area, Egypt and analyzed for the purpose of investigating fluoride content. The results showed that fluoride concentration in the study area ranges between 0.113 and 0.452 with an average of 0.242 mg/l. Sources of fluoride in the study area can result from the natural dissolution from fluoride-rich minerals, fertilizers and from groundwater recharge. It is worth mentioning that low fluoride content in the study area is considered a public health threat specially limited growth, fertility, and dental caries. Corrective measures should be taken to avoid the public health impacts of fluoride deficiency at Luxor area as well as similar areas in the Nile Valley. A public health program should be initiated to account for the deficiency of fluoride in groundwater and deal with the other supplementary fluoride sources in food or fluoridation of drinking water supplies.     

Structural Setting of Northern Tunisia Insights from Gravity Data Analysis Jendouba Case Study

Detailed gravity data in conjunction with available surface geology are analyzed to infer the organization of the underlying structures in Jendouba area. Gravity data analysis benefits from the gravity Bouguer anomaly, upward continuations, residual distribution, derivatives and Euler deconvolved maps. The main results display a positive amplitude gravity anomaly as the response of Triassic evaporitic bodies and important NE trending features at the boundaries between the Triassic outcrops and their enveloping strata. Integration of gravity, geological and structural maps let to the identification of major structural directions and trends of the study area. It confirms some structural elements gathered from outcrops. It defines also new ones.     

Reliability assessment of water structures subject to data scarcity using the SCS-CN model

ABSTRACT

When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall–runoff model to estimate a hydrograph. The Soil Conservation Service (SCS) method estimates the design hydrograph first through a rainfall–runoff transformation and next by propagating runoff to the basin outlet via the SCS unit hydrograph (UH) method. The method uses two parameters, the Curve Number (CN) and the time of concentration (T_c). However, in data-scarce areas, the calibration of CN and T_c from nearby gauged watersheds is limited and subject to high uncertainties. Therefore, the inherent uncertainty/variability of the SCS parameters may have considerable ramifications on the safety of design. In this research, a reliability approach is used to evaluate the impact of incorporating the uncertainty of CN and T_c in flood design. The sensitivity of the probabilistic outcome against the uncertainty of input parameters is calculated using the First Order Reliability Method (FORM). The results of FORM are compared with the conventional SCS results, taking solely the uncertainty of the rainfall event. The relative importance of the uncertainty of the SCS parameters is also estimated. It is found that the conventional approach, used by many practitioners, might grossly underestimate the risk of failure of water structures, due to neglecting the probabilistic nature of the SCS parameters and especially the Curve Number. The most predominant factors against which the SCS-CN method is highly uncertain are when the average rainfall value is low (less than 20 mm) or its coefficient of variation is not significant (less than 0.5), i.e. when the resulting rainfall at the design return period is low. A case study is presented for Egypt using rainfall data and CN values driven from satellite information, to determine the regions of acceptance of the SCS-CN method.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Efstratiadis     

Assimilation of historical head data to estimate spatial distributions of stream bed and aquifer hydraulic conductivity fields

Management of water resources in alluvial aquifers relies mainly on understanding interactions between hydraulically connected streams and aquifers. Numerical models that simulate this interaction often are used as decision support tools for water resource management. However, the accuracy of numerical predictions relies heavily on unknown system parameters (e.g., streambed conductivity and aquifer hydraulic conductivity), which are spatially heterogeneous and difficult to measure directly. This paper employs an ensemble smoother to invert groundwater level measurements to jointly estimate spatially varying streambed and alluvial aquifer hydraulic conductivity along a 35.6‐km segment of the South Platte River in Northeastern Colorado. The accuracy of the inversion procedure is evaluated using a synthetic experiment and historical groundwater level measurements, with the latter constituting the novelty of this study in the inversion and validation of high‐resolution fields of streambed and aquifer conductivities. Results show that the estimated streambed conductivity field and aquifer conductivity field produce an acceptable agreement between observed and simulated groundwater levels and stream flow rates. The estimated parameter fields are also used to simulate the spatially varying flow exchange between the alluvial aquifer and the stream, which exhibits high spatial variability along the river reach with a maximum average monthly aquifer gain of about 2.3 m³/day and a maximum average monthly aquifer loss of 2.8 m³/day, per unit area of streambed (m²). These results demonstrate that data assimilation inversion provides a reliable and computationally affordable tool to estimate the spatial variability of streambed and aquifer conductivities at high resolution in real‐world systems.     

Geochemical constraints and uranium potential of the younger granitic rocks in El Maghrbia area,Central Eastern Desert,Egypt

Acta Geochimica - The present work deals with the mineralogy, geochemical behavior and uranium potentiality of the monzogranites of El Maghrbia area, which comprise G. El Maghrbia and G. El Eredyia...     

Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster

Natural Hazards - Due to the need to reduce the flooding disaster, river streamflow prediction is required to be enhanced by the aid of deep learning algorithms. To achieve accurate model of...