Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Interactions between lead(II) ions and dissolved organic matter derived from organic fertilizers incubated in the field

This work was to study composition characteristics and the subsequent effect on the lead (Pb) binding properties of dissolved organic matter (DOM) derived from seaweed-based (SWOF) and chicken manure organic fertilizers (CMOF) during a one-year field incubation experiment using the excitation-emission matrix-parallel factor (EEM-PARAFAC) and two-dimensional correlation spectroscopy (2DCOS) analysis. Results showed that high aromatic and hydrophobic fluorescent substances were enriched in CMOF-derived DOM and SWOF-derived DOM and enhanced over time. And phenolic groups in the fulvic-like substances for SWOF-derived DOM and carboxyl groups in the humic-like substances for CMOF-derived DOM had the fastest responses over time, respectively. Moreover, both non-fluorescent polysaccharides and fluorescent humic-like substances or fulvic-like substances with aromatic (C=C) groups first participated in the binding process of Pb to SWOF-derived DOM on day 0 and 180 during the lead binding process. In contrast, humic-like substances associated with aromatic (C=C) and phenolic groups gave a faster response to Pb binding on day 360. Regarding CMOF-derived DOM, the fulvic-like substances associated with aromatic (C=C) and carboxylic groups displayed a faster response to Pb ions on day 0. Nonetheless, polysaccharides and humic-like associated with phenolic groups had a faster response on days 180 and 360. It is noteworthy that the polysaccharides, which participated in Pb binding to CMOF-derived DOM, posed a higher risk of Pb in the environment after 360 days. Therefore, these findings gave new insights into the long-term applications of commercial organic fertilizers for the amendment of soil.     

Seasonal variation of HCH isomers in open soil and plant-rhizospheric soil system of a contaminated environment

Background, aim, and scope  

Lindane, technically 1, 2, 3, 4, 5, 6-hexachlorocyclohexane (γ- HCH), is the most commonly detected organochlorine pesticide from diverse environmental compartments. Currently, India is the largest consumer and producer of lindane in the world. The production of lindane results in the generation of large quantities of waste HCH isomers (mainly α-, β- and δ-). All these isomers are toxic and have a long-range environmental transport potential. The aim of this study was to monitor the seasonal variation of HCH isomers in an open soil–plant–rhizospheric soil system of a contaminated industrial area. For this, selected plant species and their rhizospheric soil (soil samples collected at a depth range of 0–45 cm near to the root system) and open soil samples (soil samples collected (0–30 cm depth) from 1–1.5 m away from the plant root system) were collected for 2 years (two summer seasons and two winter seasons).     

Transport of metanil yellow in the rat plasma and interaction of its metabolite,p‐aminodiphenylamine with serum proteins

Binding affinity of metanil yellow and its breakdown product p‐aminodiphenylamine to serum proteins has been studied employing chromatographic separation on Sephadex G‐200 and by paper and polyacrylamide gel electrophoresis. Metanil yellow has more affinity towards albumin than to globulins. The complexing is presumably through electrostatic forces. p‐Aminodiphenylamine on the other hand, preferably binds to globulin fractions of serum protein. However, a stable binding with BSA alone was also observed. The binding was quite stable and was accompanied by a shift in absorbance from 430 nm to 500 nm. Aspartic acid moiety of protein was found to be one of the units involved in the binding of p‐ADPA to proteins.     

Identification of weather patterns impacting 24-h average fine particulate matter pollution

Methods are presented to extract intra-seasonal meteorological patterns at three scales to explain 24-h fine particulate matter (PM_2.5) pollution events: evolving large-scale meteorological scenarios, synoptic regimes driving diurnal variability near the surface, and localized meteorological triggers. The methods were applied to understand how winter weather conditions impacted PM_2.5 around the San Francisco Bay Area (SFBA). Analyzing data across 12 winters (November–March) ensured robust characterization of the SFBA conditions. SFBA 24-h PM_2.5 exceedances (35 μg m^?3) required several simultaneous characteristics: a ridge of aloft high pressure moving over SFBA, providing weak surface pressure gradients over Central California; persistent easterly flows through SFBA extending vertically to around the 925-hPa pressure level; orographically channeled winds resulting from stability; enhanced nocturnal cooling under clear-sky conditions providing for enhanced drainage flows off the Central California slopes; and at least two consecutive days of these conditions.     

Evaluation of environmental impacts from municipal solid waste management in the municipality of Aarhus, Denmark (EASEWASTE).

A new computer based life cycle assessment model (EASEWASTE) was used to evaluate a municipal solid waste system with the purpose of identifying environmental benefits and disadvantages by anaerobic digestion of source-separated household waste and incineration. The most important processes that were included in the study are optical sorting and pre-treatment, anaerobic digestion with heat and power recovery, incineration with heat and power recovery, use of digested biomass on arable soils and finally, an estimated surplus consumption of plastic in order to achieve a higher quality and quantity of organic waste to the biogas plant. Results showed that there were no significant differences in most of the assessed environmental impacts for the two scenarios. However, the use of digested biomass may cause a potential toxicity impact on human health due to the heavy metal content of the organic waste. A sensitivity analysis showed that the results are sensitive to the energy recovery efficiencies, to the extra plastic consumption for waste bags and to the content of heavy metals in the waste. A model such as EASEWASTE is very suitable for evaluating the overall environmental consequences of different waste management strategies and technologies, and can be used for most waste material fractions existing in household waste.