A Tool for Classification and Regression Using Random Forest Methodology: Applications to Landslide Susceptibility Mapping and Soil Thickness Modeling

Classification and regression problems are a central issue in geosciences. In this paper, we present Classification and Regression Treebagger (ClaReT), a tool for classification and regression based on the random forest (RF) technique. ClaReT is developed in Matlab and has a simple graphic user interface (GUI) that simplifies the model implementation process, allows the standardization of the method, and makes the classification and regression process reproducible. This tool performs automatically the feature selection based on a quantitative criterion and allows testing a large number of explanatory variables. First, it ranks and displays the parameter importance; then, it selects the optimal configuration of explanatory variables; finally, it performs the classification or regression for an entire dataset. It can also provide an evaluation of the results in terms of misclassification error or root mean squared error. We tested the applicability of ClaReT in two case studies. In the first one, we used ClaReT in classification mode to identify the better subset of landslide conditioning variables (LCVs) and to obtain a landslide susceptibility map (LSM) of the Arno river basin (Italy). In the second case study, we used ClaReT in regression mode to produce a soil thickness map of the Terzona catchment, a small sub-basin of the Arno river basin. In both cases, we performed a validation of the results and a comparison with other state-of-the-art techniques. We found that ClaReT produced better results, with a more straightforward and easy application and could be used as a valuable tool to assess the importance of the variables involved in the modeling.     

Application of Adjoint Approach to Oil Spill Problems

Adjoint method is applied to various oil spill problems. A three-dimensional model for describing the dispersion of a quasi-passive substance (a pollutant or a nutrient) and its adjoint model are considered in a limited sea region. Direct and adjoint estimates are used to get dual (equivalent) estimates of the mean concentration of the substance in important zones of the region. The role of dual estimates is illustrated with a few examples. They include such oil spill problems as the search of the most dangerous point of the oil tanker route, the oil dispersion with a climatic velocity, and the dependence of the oil concentration estimates on the oil spill rate. One more example is the application of optimal bioremediation strategy for cleaning a few zones polluted by oil. In this case, instead of oil, the model describes the dispersion of a nutrient released to marine environment. Balanced, unconditionally stable second-order finite-difference schemes based on the splitting method for the solution of the dispersion model and its adjoint are suggested. The main and adjoint difference schemes are compatible in the sense that at every fractional step of the splitting algorithm, the one-dimensional split operators of both schemes satisfy a discrete form of Lagrange identity. In the special unforced and non-dissipative case, each scheme has two conservation laws. Every split one-dimensional problem is solved by Thomas’ factorization method.     

Effects of northeast monsoon on trace metal distribution in the South China Sea off Peninsular Malaysia

Concentrations of trace metals in the South China Sea (SCS) were determined off the coast of Terengganu during the months of May and November 2007. The concentrations of dissolved and particulate metals were in the range of 0.019–0.194 μg/L and 50–365 μg/g, respectively, for cadmium (Cd), 0.05–0.45 μg/L and 38–3,570 μg/g for chromium (Cr), 0.05–3.54 μg/L and 21–1,947 μg/g for manganese (Mn), and 0.03–0.49 μg/L and 2–56,982 μg/g for lead (Pb). The order of mean log K _D found was Cd?>?Cr?>?Pb?>?Mn. The study suggests that the primary sources of these metals are discharges from the rivers which drain into the SCS, in particular the Dungun River, which flows in close proximity to agricultural areas and petrochemical industries. During the northeast monsoon, levels of particulate metals in the bottom water samples near the shore were found to be much higher than during the dry season, the probable result of re-suspension of the metals from the bottom sediments.     

Characterization of As and trace metals embedded in PM10 particles in Puebla City, México

Forty-eight air-filter samples (PM₁₀) were analysed to identify the concentration level of partially leached metals (PLMs; As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and V) from Puebla City, México. Samples were collected during 2008 from four monitoring sites: (1) Tecnológico (TEC), (2) Ninfas (NIN), (3) Hermanos Serdán (HS) and (4) Agua Santa (AS). The results indicate that in TEC, As (avg. 424 ng m^?3), V (avg. 19.2 ng m^?3), Fe (avg. 1,202 ng m^?3), Cu (avg. 86.6 ng m^?3), Cr (41.9 ng m^?3) and Ni (18.6 ng m^?3) are on the higher side than other populated regions around the world. The enrichment of PLMs is due to the industrial complexes generating huge dust particles involving various operations. The results are supported by the correlation of metals (Mn, Cd and Co) with Fe indicating its anthropogenic origin and likewise, As with Cd, Co, Fe, Mn, Pb and V. The separate cluster of As, Fe and Mn clearly signifies that it is due to continuous eruption of fumaroles from the active volcano Popocatépetl in the region.     

Use of the land snail Helix aspersa for monitoring heavy metal soil contamination in Northeast Algeria

The objective of this study was to investigate the impact of anthropogenic activities on soil quality using the land snail Helix aspersa as a bioindicator. Soil samples and snails were collected from several sites in Northeast Algeria during the summer and winter of 2010. All of the sites were chosen due to their proximity to industrial factories—a potential source of soil pollution via heavy metal contamination. The concentration of heavy metals (Pb, Cd, Mn, and Fe) in soil samples was analyzed using atomic absorption spectrophotometry. Activity levels of glutathione S-transferase (GST) and acetylcholinesterase (AChE), indicators of oxidative stress and neurotoxicity, respectively, were measured in snails collected from each site. GST and AChE activity were found to vary between sites and by season. The highest levels of GST activity were registered during the summer at sites closest to potential sources of pollution. AChE activity levels also peaked during the summer with the highest values recorded at the site in El Hadjar. These increased levels of bioindicative stress response correlated with increasing metal concentration in soil samples collected at each site.     

Development of a new risk-based framework to guide investment in water quality monitoring

An innovative framework for optimising investments in water quality monitoring has been developed for use by water and environmental agencies. By utilising historical data, investigating the accuracy of monitoring methods and considering the risk tolerance of the management agency, this new methodology calculates optimum water quality monitoring frequencies for individual water bodies. Such information can be applied to water quality constituents of concern in both engineered and natural water bodies and will guide the investment of monitoring resources. Here we present both the development of the framework itself and a proof of concept by applying it to the occurrence of hazardous cyanobacterial blooms in freshwater lakes. This application to existing data demonstrates the robustness of the approach and the capacity of the framework to optimise the allocation of both monitoring and mitigation resources. When applied to cyanobacterial blooms in the Swan Coastal Plain of Western Australia, we determined that optimising the monitoring regime at individual lakes could greatly alter the overall monitoring schedule for the region, rendering it more risk averse without increasing the amount of monitoring resources required. For water resources with high-density temporal data related to constituents of concern, a similar reduction in risk may be observed by applying the framework.     

A comparative study on mesozooplankton abundance and diversity between a protected and an unprotected coastal area of Andaman Islands

The study was carried out to understand the variability in phytoplankton production (Chlorophyll a) and mesozooplankton diversity from two different shallow coastal regions of south Andaman viz. Port Blair Bay (PBB), the only real urban area among the islands and Mahatma Gandhi Marine National Park, a Marine Protected Area (MPA) at Wandoor. Seasonal sampling was carried out during the Northeast monsoon (NEM—November 2005), Intermonsoon (IM—April 2006), and Southwest monsoon (SWM—August 2006). Significant (P?<?0.05) seasonal variation was observed in the environmental variables at both the regions. Higher average chlorophyll a (Chl. a) and mesozooplankton standing stock were observed at PBB compared to MPA, but the seasonal variation observed was marginal at both the study areas. Chl. a showed a steep increasing gradient from outer to the inner regions of the PBB. The number of zooplankton taxa recorded at both areas was quite similar, but marked differences were noticed in their relative contribution to the total abundance. Eventhough the Copepoda dominated at both the areas, the non-copepod taxa differed significantly between the regions. Dominance of carnivores such as siphonophores and chaetognaths were noticed at PBB, while filter feeders such as appendicularians and decapod larvae were more abundant at MPA. A total of 20 and 21 copepod families was recorded from PBB and MPA, respectively. Eleven species of chaetognaths were observed as common at both areas. Larval decapods were found to be predominant at MPA with 20 families; whereas, at PBB, only 12 families were recorded. In the light of the recent reports on various changes occurring in the coastal waters of the Andaman Islands, it is suspected that the difference in Chl. a as well as the mesozooplankton standing stock and community structure observed between the two study areas may be related to the various anthropogenic events influencing the coastal waters.