Cl-37 in the Dead Sea system---preliminary results

This study presents the first set of δ measurements in the Dead Sea environment. δ values for the meromictic (long term stratified) Dead Sea water column prior to its complete overturn in 1979 were −0.47‰ SMOC for the UWM (Upper Water Mass) and +0.55‰ SMOC for the LWM (Lower Water Mass). The δ values for the pre-overturn Dead Sea cannot be explained by the prevailing model on the evolution of the Dead Sea during the last few centuries and require corroboration by more measurements. The 1979 overturn wiped out almost completely the isotopic differences between the UWM and LWM. Even so, Cl isotope data could be used to decipher physical processes related to the overturn such as incomplete homogenization of the deep water mass. Inputs into the lake, comprising freshwaters (springs and the Jordan River) and saline springs gave a range of −0.37‰ to +1.0‰ with the freshwater sources being more enriched in δ . Based on the δ measurements of the End-Brine (the effluent from Dead Sea evaporation ponds) and of recent Dead Sea halite, the Cl isotopic composition of the originating brines have been estimated. They gave a narrow isotopic spread, +0.01‰ and +0.07‰ and fall within the same range with Dead Sea pore water (+0.13‰) and with the post-overturn Dead Sea (−0.03‰ and +0.16‰). Rock salt from Mount Sdom gave a value of −0.59‰ indicating its formation at the last stages of halite deposition from evaporating sea water. The hypersaline En Ashlag spring gave a depleted δ value of −0.32‰, corresponding to a residual brine formed in the very latest stages (including bishofite deposition) of seawater evaporation.     

Redefining the trophic importance of seagrasses for fauna in tropical Indo-Pacific meadows

Fauna species living in seagrass meadows depend on different food sources, with seagrasses often being marginally important for higher trophic levels. To determine the food web of a mixed-species tropical seagrass meadow in Sulawesi, Indonesia, we analyzed the stable isotope (δ¹³C and δ¹⁵N) signatures of primary producers, particulate organic matter (POM) and fauna species. In addition invertebrates, both infauna and macrobenthic, and fish densities were examined to identify the important species in the meadow. The aims of this study were to identify the main food sources of fauna species by comparing isotopic signatures of different primary producers and fauna, and to estimate qualitatively the importance of seagrass material in the food web. Phytoplankton and water column POM were the most depleted primary food sources for δ¹³C (range −23.1 to −19.6‰), but no fauna species depended only on these sources for carbon. Epiphytes and Sargassum sp. had intermediate δ¹³C values (−14.2 to −11.9‰). Sea urchins, gastropods and certain fish species were the main species assimilating this material. Seagrasses and sedimentary POM had the least depleted values (−11.5 to −5.7‰). Between the five seagrass species significant differences in δ¹³C were measured. The small species Halophila ovalis and Halodule uninervis were most depleted, the largest species Enhalus acoroides was least depleted, while Thalassia hemprichii and Cymodocea rotundata had intermediate values. Fourteen fauna species, accounting for 10% of the total fauna density, were shown to assimilate predominantly (>50%) seagrass material, either directly or indirectly by feeding on seagrass consumers. These species ranged from amphipods up to the benthic top predator Taeniura lymma. Besides these species, about half of the 55 fauna species analyzed had δ¹³C values higher than the least depleted non-seagrass source, indicating they depended at least partly for their food on seagrass material. This study shows that seagrass material is consumed by a large number of fauna species and is important for a large portion of the food web in tropical seagrass meadows.     

Photo Orientation Under Unstable Conditions: A Robust Trial and Error Approach Using Range Ratios

Relative orientation is one of the fundamental steps in forming a photogrammetric model. Whilst relative orientation is straightforward in most cases of aerial photogrammetry this may not be the case in close range photogrammetry where the nature of the photographs and the cameras being used often raise unfamiliar problems. This paper addresses the problem of performing relative orientation of non-metric photographs under unstable conditions where there are no ground control points and the ray intersection geometry is poor. The relative orientation problem is approached from several viewpoints, including a method that relies on little information about the exterior or relative orientation parameters. The solution is based on an iterative process, in which a set of three virtual control points (VCPs) is created, using photo coordinates and range ratios. The validity of the VCPs is checked during every iteration by an estimation of the coplanarity condition using two or more conjugate checkpoints. During the iteration a database is formed, which is then used to obtain a net of VCPs that fulfil the coplanarity condition for the checkpoints. The VCPs are then used to compute the "relative" exterior orientation by space resection. The proposed method was tested on both simulated and real photographs and was found to have some advantages over more commonly used techniques.     

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.