Using CRD method for quantification of groundwater recharge in the Gaza Strip, Palestine

Rainfall is the main source of groundwater recharge in the Gaza Strip area in Palestine. The area is located in the semi-arid zone and there is no source of recharge other than rainfall. Estimation of groundwater recharge from rainfall is not an easy task since it depends on many uncertain parameters. The cumulative rainfall departure (CRD) method, which depends on the water balance principle, was used in this study to estimate the net groundwater recharge from rainfall. This method does not require much data as is the case with other classical recharge estimation methods. The CRD method was carried out using optimisation approach to minimise the root mean square error (RMSE) between the measured and the simulated groundwater head. The results of this method were compared with the results of other recharge estimation methods from literature. It was found that the results of the CRD method are very close to the results of the other methods, but with less data requirements and greater ease of application. Based on the CRD method, the annual amount of groundwater recharge from rainfall in the Gaza Strip is about 43 million m³. An erratum to this article can be found at     

Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive capability of common landslide prediction models.     

Inorganic chemistry,granulometry and mineralogical characteristics of the dust fall over phosphate mine adjacent area,central Jordan

Eight selected heavy metals and phosphorus (Fe, Zn, Pb, Cu, Cr, Cd, Ni and P) were analyzed in the dust fall samples collected from the surrounding areas adjacent to Al-Hisa phosphate mine central Jordan during summer 2008. The chemical analysis was done using the ICP-AES, after being digested with (HNO₃/HCl/HF) acid mixture, beside the identification of their mineral constituents using the XRD. Moreover, the particulate matter (PM) size was investigated and divided into four fractions (PM_2.5, PM_2.5–10, PMC_10–100 and PM_>100). The PM₁₀–PM₁₀₀ were found to be the most abundant in the local atmosphere followed by PM_2.5–PM₁₀, while the respirable fraction (PM_2.5) and giant fraction (PM_>100) showed lower levels. The studied samples contain less PM_2.5 and PM₁₀ particulates (9.39 and 28.67), respectively, than samples located far from the mine area (blank samples) (17.32 and 51.7) for PM_2.5 and PM₁₀, respectively. The meteorological effects, mainly the prevailing wind direction beside the distance to emission sources affect the distribution of dust particle sizes. Heavy metal contents in studied samples are similar to some extent to those found in Isa Town (Bahraian), which related to similar arid and low precipitation climatic conditions. The effect of phosphate mining activities was obvious as indicated from the presence of apatite as the main mineral phase and the higher P contents. Moreover, the studied samples contain higher Zn, Ni, Cu and to lesser extent Cr than blank samples. They exhibited a significant positive correlation with P, as they are usually associated with the phosphate rocks.     

The planetary spin and rotation period: a modern approach

Using a new approach, we have obtained a formula for calculating the rotation period and radius of planets. In the ordinary gravitomagnetism the gravitational spin (S) orbit (L) coupling, $\vec{L}\cdot\vec{S}\propto L^{2}$ , while our model predicts that $\vec{L}\cdot\vec{S}\propto\frac{m}{M}L^{2}$ , where M and m are the central and orbiting masses, respectively. Hence, planets during their evolution exchange L and S until they reach a final stability at which MS∝mL, or $S\propto\frac{m^{2}}{v}$ , where v is the orbital velocity of the planet. Rotational properties of our planetary system and exoplanets are in agreement with our predictions. The radius (R) and rotational period (D) of tidally locked planet at a distance a from its star, are related by, $D^{2}\propto\sqrt{\frac{M}{m^{3}}}R^{3}$ and that $R\propto\sqrt{\frac {m}{M}}a$ .     

Stochastic modelling and risk analysis of groundwater pollution using FORM coupled with automatic differentiation

The first order reliability method (FORM) has been widely used in probabilistic modelling of groundwater problems. The FORM approach requires an iterative optimization procedure to find out the system failure point (the most probable point).The advantages of this approach are that it does not require many computations in comparison with other methods when applied to simple problems, and it produces reasonably accurate results. However, it has been found that the computations of FORM can equal or exceed that of other methods in case of large number of variables.In this paper, a new implementation of FORM was proposed with more efficiency and accuracy than the traditional FORM method. In the proposed approach, automatic differentiation is used to obtain the gradient vector of the limit state function, which is required by FORM, instead of using finite difference estimation. This way, the first order derivative was obtained with a very good accuracy, and with less computational effort. Based on the obtained results, it is found that the proposed implementation of FORM is a very good tool for probabilistic risk assessment and uncertainty analysis in groundwater problems.     

Size fractionation and optical properties of colloids in an organic-rich estuary (Thurso, UK)

The optical characteristics of a black water river estuary from the north coast of Scotland were examined in the filtered (0.4 µm), ultrafiltered (5 kDa) and colloid-enriched fractions of estuarine samples. The samples were collected over the full salinity range during a period when the pH was relatively constant (8.2–8.5) throughout the estuary, allowing the influence of salinity on estuarine colloidal processes to be distinguished. The properties examined in the bulk, the low molecular weight (LMW) and the colloidal fraction (HMW) were UV–visible absorption, 3-D fluorescence excitation–emission matrix (EEM) spectrum, inorganic and organic carbon, mean size (by dynamic light scattering), and size distribution by flow field-flow fractionation analysis (FlFFF). The combined results of these analyses support the view that river-borne, humic-rich colloids underwent two types of transformation upon mixing with the seawater end member. The first one resulted in an apparent increase in the abundance of LMW constituents and may be explained by coiling of the individual humic macromolecules. The second one resulted in an increase in the mean size measured in both the lower and higher colloidal size ranges, and may be explained by aggregation of colloids to form entities that were still mostly colloidal i.e., smaller than 0.4 µm. The LMW contribution to the bulk optical properties increased with increasing salinity. Very similar findings were obtained from simulated mixing experiments using a Nordic Reference NOM extract as a source of freshwater colloids. This indicates that changes in the molecular architecture and molar mass of river-borne colloids—not changes in their chemical nature—were responsible for the observed variations in the spectral characteristics of CDOM in this estuary.     

Balneological study based on the hydrogeochemical aspects of the sulfate springs water (Hit–Kubaiysa region), Iraq

This research examined the balneological characteristics of spring waters within the area of Abu-Jir Fault Zone throughout the hydrogeologic aspects explained by the setting of the hydrogeologic units including the water-bearing horizons of Euphrates, Ana, and Baba Formations. The groundwater flow in the hydrogeologic system correlated with the trends of enrichment or depletion case processes of mineralization (spatial distribution maps of TDS and other components) show different phenomena of groundwater source and interconnection, which helps in the classification springs into two potential site. The physicochemical characteristics of the water flow from springs indicate a hydrochemical approach throughout the spatial variation of important parameters (using Rockware software) related to the balneological study. The monitoring network of the spring waters performed by seven field measurements and 33 variables (totaling to 720 detected measurements) in 18 springs approved the after desk study and water point inventory using a GPS apparatus (GARMIN SUMMIT-e TREX). The study examined the integrated hydrogeological aspects and spring water properties for evolutions and the classification of minero-medicinal water. The traditional hydrochemical information of the spring waters and their sediment properties correlated with balneological limits (standards and definitions) are used in the selection of springs characterized by balneotherapeutic applications. A suggested screening and ranking technique has been developed for evaluating preferable springs selected for natural therapy. The application of ranking technique indicates four graded consequent preferable springs for balneotherapeutic investment: first grade spring represented by Kubaiysa spring (S-4); second grade springs represented by Tawila spring (S-12); third grade springs represented by Mamora spring (S-15), Arnab spring (S-10), Zazoe spring (S-5), and Maqtoom spring (S-13); and fourth grade springs represented by Khalidiya spring (S-16) and Layeg spring (S-7).     

Using Orthogonal Array Sampling to Cope with Uncertainty in Ground Water Problems

Uncertainty in ground water hydrology originates from different sources. Neglecting uncertainty in ground water problems can lead to incorrect results and misleading output. Several approaches have been developed to cope with uncertainty in ground water problems. The most widely used methods in uncertainty analysis are Monte Carlo simulation (MCS) and Latin hypercube sampling (LHS), developed from MCS. Despite the simplicity of MCS, many runs are required to achieve a reliable result. This paper presents orthogonal array (OA) sampling as a means to cope with uncertainty in ground water problems. The method was applied to an analytical stream depletion problem. To examine the convergence rate of the OA sampling, the results were compared to MCS and LHS. This study shows that OA can be applied to ground water problems. Results reveal that the convergence rate of the OA sampling is faster than MCS and LHS, with a smaller error of estimate when applied to a stream depletion problem.