Organic matter-metal interactions in Recent sediments: the role of humic substances

Atomic emission spectrographic analysis of the trace inorganic constituents of marine humic substances gave the following range of concentrations: Si, 200 ppm to > 2%; Al, 400 ppm to ~ 1%; Fe, 600–3000 ppm; Ca, 600 ppm to > 2%; Mg, 20–6000 ppm; Na, 600 ppm to > 2%; Ag, < 6–600 ppm; B, < 60–1000 ppm; Cu, 600–4000 ppm; Mn, 8–100 ppm; Mo, <20–3000 ppm; Ni, 100–1000 ppm; Pb, < 40–600 ppm; Sn, 40–600 ppm; Ti, < 20–2500 ppm; V, 20–200 ppm; Zn, 350–4500 ppm; Zr, < 60–500 ppm.Humic substances contain a sizeable portion of the Cu, Mo and Zn found in sediments, but are less important for Ni, Co and Pb, and are insignificant for the Mn, V and Fe content. The metals are mostly introduced into the humates during their diagenetic formation in sediment by dissolution of metals from various mineralogical phases. A precursor of the sedimentary humates, the polymeric organic material dissolved in interstitial water, contains most of the Cu and Zn, about half of the Ni, Fe and Co, and very little of the Mn found in interstitial water. Comparison of the data on humates with that obtained by H₂O₂ treatment of sediments indicates that Cu, Zn and possibly most of the Mo are associated with organic matter, but that Ni and Co are associated with sulfides.     

Maximal discharges observed in Israel

Maximal discharges observed in Israel since 1938 are plotted on a log-log paper against the catchment area of the measuring sites. Four envelope lines, parallel to one another, are drawn on the paper. The formula of these lines is Q=c A^0.83, in which Q is the maximal observed discharge, in m³/sec, A is the catchment area, in km², and c is an empirical coefficient, in m³/sec km^1.65. The value of c varies from 1.7 to 4.5 units, depending on the precipitation and the lithology of the watershed. Higher discharges are observed where the mean annual depth of the precipitation is lower. With respect to the lithological units found in Israel, the highest discharges are observed where the lithology is of thin deposited limestone and the surface slopes are steep. The lowest maximal discharges are observed where the lithology is heavy deposited limestone and dolomite, or conglomerates. No high discharges are observed from watersheds where the lithology is Holocenean sand. In general, impervious, steeply sloped surfaces generate higher discharges than pervious or mildly sloped surfaces.     

Asphalt in iron age excavations from the Philistine Tel Miqne-Ekron city (Israel): Origin and trade routes

Asphalts found as pure lumps or coatings on potsherds were excavated at the Philistine site of Tel Miqne-Ekron (12th to 7th century BC) in the southern Inner Coastal Plain of Israel. They were studied using the techniques of petroleum geochemistry and were compared to some natural asphalts from the area: Dead Sea floating blocks (Israel), Wadi Weida’a asphalt (Jordan) and Hasbeya (Lebanon).Tel Miqne-Ekron bitumens show evidence of weathering, indicating biodegradation and oxidation. They contain less aromatics and more asphaltenes than Dead Sea asphalt. Evaporation and biodegradation are recorded at a molecular level, especially via the phenanthrenes and dibenzothiophenes. However, several isotopic and molecular parameters allowed us to correlate the Tel Miqne-Ekron asphalt with the Dead Sea asphalt from the floating blocks. The asphalts of Hasbeya and Wadi Weida’a do not match the Tel Miqne-Ekron asphalt. The latter, in particular, is much more biodegraded, based on its steranes. The study shows that the Dead Sea asphalt was imported to Tel Miqne-Ekron over a 500 year period. This trade posed no problem in the 7th century BC when Philistia, Israel and Judah were at peace as part of the Pax Assyriaca of the Assyrian Empire. However, trade during the 12th century BC is puzzling since the asphalt had to be transported across Israelite territory that was hostile to the Philistines, as indicated in the Bible (e.g., Samson and Delilah, David and Goliath). Consequently it seems that profitable commerce surpassed ethnic, religious and political conflict, as can also be observed in the contemporary world.     

Using Statistical Learning Algorithms in Regional Landslide Susceptibility Zonation with Limited Landslide Field Data

Regional Landslide Susceptibility Zonation(LSZ) is always challenged by the available amount of field data, especially in southwestern China where large mountainous areas and limited field information coincide. Statistical learning algorithms are believed to be superior to traditional statistical algorithms for their data adaptability. The aim of the paper is to evaluate how statistical learning algorithms perform on regional LSZ with limited field data. The focus is on three statistical learning algorithms, Logistic Regression(LR), Artificial Neural Networks(ANN) and Support Vector Machine(SVM). Hanzhong city, a landslide prone area in southwestern China is taken as a study case. Nine environmental factors are selected as inputs. The accuracies of the resulting LSZ maps are evaluated through landslide density analysis(LDA), receiver operating characteristic(ROC) curves and Kappa index statistics. The dependence of the algorithm on the size of field samples is examined by varying the sizes of the training set. The SVM has proven to be the most accurate and the most stable algorithm at small training set sizes and on all known landslide sizes. The accuracy of SVM shows a steadilyincreasing trend and reaches a high level at a small size of the training set, while accuracies of LR and ANN algorithms show distinct fluctuations. The geomorphological interpretations confirm the strength of SVM on all landslide sizes. Our results show that the strengths of SVM in generalization capability and model robustness make it an appropriate and efficient tool for regional LSZ with limited landslide field samples.     

Assessment of transmission losses and groundwater recharge from runoff events in a wadi under shortage of data on lateral inflow,Negev, Israel

A hydrological–lithostratigraphical model was developed for assessment of transmission losses and groundwater recharge from runoff events in arid water courses where hydrological and meteorological records are incomplete. Water balance equations were established for reaches between hydrometric stations. Because rainfall and tributary flow data are scarce, lateral inflow, which is an essential component of the water balance equation, could not be estimated directly. The solution was obtained by developing a method which includes a hydrological–lithostratigraphical analogy. This is based on the following assumptions: (a) runoff resulting from a given rainfall event is related to the watershed surface lithology; (b) for a given event, the spatial distribution of runoff reflects the distribution of rainfall: and (c) transmission losses are uniquely related to the total inflow to the reach. The latter relationship, called the loss function, and the water balance equation comprise a model which simultaneously assesses lateral inflow and transmission losses for runoff events recorded at the terminal stations. The model was applied to three reaches of the arid Nahal Tsin in Israel. In this case study, the transmission losses were of the same order of magnitude as the flow at the major hydrometric stations. The losses were subdivided into channel moistening, which subsequently evaporates, and deep percolation, which recharges groundwater. For large runoff events, evaporation was substantially smaller than the losses. The mean annual recharge of groundwater from runoff events in the Tsin watershed was 4·1×10⁶ m³, while the mean annual flow volume at the major stations ranged from 0·6 to 1·5×10⁶ m³. Once in 100 years, the annual recharge may be seven times higher than the mean annual value, but the recharge during most years is very small. Copyright © 1999 John Wiley & Sons, Ltd.     

#Earthquake: Twitter as a Distributed Sensor System

Social media feeds are rapidly emerging as a novel avenue for the contribution and dissemination of information that is often geographic. Their content often includes references to events occurring at, or affecting specific locations. Within this article we analyze the spatial and temporal characteristics of the twitter feed activity responding to a 5.8 magnitude earthquake which occurred on the East Coast of the United States (US) on August 23, 2011. We argue that these feeds represent a hybrid form of a sensor system that allows for the identification and localization of the impact area of the event. By contrasting this with comparable content collected through the dedicated crowdsourcing ‘Did You Feel It?’ (DYFI) website of the U.S. Geological Survey we assess the potential of the use of harvested social media content for event monitoring. The experiments support the notion that people act as sensors to give us comparable results in a timely manner, and can complement other sources of data to enhance our situational awareness and improve our understanding and response to such events.     

From the dawn of organic geochemistry (1933, 1938): Estrogenic substances in bituminous deposits and in the Dead Sea

We describe several pioneering organic geochemical studies from the 1930s on estrogenic substances isolated from various fossil fuels and bituminous materials and from water and sediments of the Dead Sea. The techniques employed were bioanalytical and not chemical. One of the studies, although not done on the same molecular level as his, precedes the work of Alfred Treibs, who is considered the father of organic geochemistry. By shedding light on a relatively unknown chapter of organic geochemistry, the roots of this discipline are shown to extend wider than usually recognized.     

Comment on “Reassessment of rain experiments and operations in Israel including synoptic considerations” by Zev Levin,Noam Halfon and Pinhas Alpert [Atmos. Res. 97 (2010) 513–525]

Levin et al. (referred here as LHA) made a sweeping conclusion that cloud seeding has been ineffective in Israel. They claimed that the results of the Israel-2 experiment could be fully ascribed to synoptic bias. However, the cross over analysis of Israel-2 has shown the same already in 1990 by Gabriel and Rosenfeld. While LHA only showed differences in the 850 hPa winds being stronger in the north seeded days of Israeli-2, Rosenfeld and Farbstein had already shown quantitatively in 1992 that this synoptic bias explains less than half of the indicated seeding effect in the north. Furthermore, accepting that a cross over design protects against synoptic bias means that the highly positive and statistically significant indicated seeding effect in Israeli-1, which was based on a cross-over design, cannot be explained by such synoptic bias. Instead, LHA completely ignored the Israeli-1 experiment.LHA's evaluation of the operational seeding used implied assumption that amounted to historical comparisons that have already been shown to be invalid, especially for the Israeli situation due to the decreasing trend of target–control ratio, especially over the eastern upper Galilee. For all of the above reasons, the conclusion of LHA that cloud seeding is ineffective in Israel is not supported by the data.Given the uncertainties, both physical and statistical, the Israeli water authority has embarked on the Israeli-4 randomized cloud seeding experiment, which is aimed at testing the hypothesis that cloud seeding might be affecting mainly the precipitation in the orographic clouds developing over the hills in the catchment of the Jordan River.