Bioaccumulation of Heavy Metals in Soft Tissues of Bivalve Mollusks from Natural Lakes in Eastern Sikhote Alin (Russia) and the Mekong Delta (Vietnam)

Doklady Earth Sciences - The concentrations of seven heavy metals (HMs) in tissues of bivalve mollusks of the families Unionidae (genera Ensidens, Scabies, Kunashiria) and Cyrenidae (genus...     

Matched field processing of deep-water ambient noise

Matched-field ambiguity surfaces produced by deep-water ambient-noise data are discussed and quantified in terms of power levels and correlation values. Two processors were implemented (Bartlett and minimum variance) using data at 35 and 95 Hz with similar but distinct vertical angular distributions. In general, the ambiguity surfaces have both diffuse and discrete components. The diffuse distribution extends across the sound channel with correlation values increasing with distance. The discrete sources have higher correlation values and are distributed in a convergence-zone sidelobe structure. Local wind conditions appear to affect the received power but not the correlation values or the processor output power     

Simulated annealing technique in discrete fracture network inversion: optimizing the optimization

Simulated annealing (SA) has the capacity to handle complex problem of fracture heterogeneity. However, its applications to characterization and modeling of an actual discrete fracture network are limited. Borrowing the context of geothermal reservoirs (where extensive discrete fractures exist), this paper attempts to solve several key practical issues that persist in current models: objective function’s (OF’s) formulation, modification scheme, and stop criteria. The improvements are examined in a case study on an actual fracture outcrop, where results are compared with a current and advanced SA work.     

Description of a complex,rainfall-induced landslide within a multi-stage three-dimensional model

Natural Hazards - The mechanical processes involved in movements of earth or rock masses under the effect of gravity—a landslide—may include several phases where the failure of one...     

Performances of Different Machine Learning Algorithms for Predicting Saltwater Intrusion in the Vietnamese Mekong Delta Using Limited Input Data: A Study from Ham Luong River

Water Resources - Accurate forecasting of salinity intrusion has a vital role in water resource management to mitigate and prevent its adverse effects. However, monitoring of salinity presents...     

Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions

This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three-dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R-squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically-informed estimates. The results of this work are used to inform a follow-on study that tests additional data-driven approaches in multiple basins within the contiguous United States.     

Remote sensing and avian influenza: A review of image processing methods for extracting key variables affecting avian influenza virus survival in water from Earth Observation satellites

Recent studies have highlighted the potential role of water in the transmission of avian influenza (AI) viruses and the existence of often interacting variables that determine the survival rate of these viruses in water; the two main variables are temperature and salinity.