Environmental contamination research has been quite interesting in bioindicators recently. The basic objective of bioindicator research is to find species that can reliably detect environmental disturbances and demonstrate how those disturbances affect other species or biodiversity as a whole. Since they frequently come into contact with the harmful substances found in soil, water, and air, insects are particularly valuable for evaluating how human activities affect the terrestrial ecosystem, the aquatic system, and the atmosphere. In this review article, we’ve emphasized the use of insects as a resource for assessing contaminants and monitoring environmental contamination. Insects have been our main focus since they are key indicators of changes in soil, water, and air quality. The majority of insects, including beetles, ants, honey bees, and butterflies are employed in this study as biological indicators since they are sensitive to even the slightest environmental changes and are also used to monitor different environmental toxins.
Taguchi introduced the concept of split-unit design to sort factors into different groups with respect to difficulties involved in changing the levels of factors. Li et al. have developed all possible group structures for eight factors in an L16 orthogonal array for resolution IV with split-plot design. Chen et al. have searched for a best design, according to the various criteria for two-level fractional factorial design and have presented a catalogue. In this paper, we have developed an algorithm for generating group structure and possible allocations for various 2n- k fractional factorial designs that correspond to the designs given by Chen et al.
Standard Precipitation Index (SPI) computed at multiple time scales is considered as a key indicator for short-term agricultural to long-term hydrological drought monitoring. SPI computed at multiple timescales namely 1, 3-6 and 12 months represent meteorological, agricultural and hydrological droughts, respectively. Traditionally, precipitation based SPI drought index is being computed using raingauge station data, which is often limited by sparse and uneven distribution of raingauge stations. However, uncertainty in aerial estimation of rainfall and data scarcity regions can be overcome by envisaging various quasi-global satellite derived precipitation products such as TRMM multi-satellite Precipitation Analysis (TMPA), Climate Hazards Group Infrared Precipitation with Stations data (CHIRPS), Climate Research Unit (CRU) data for drought monitoring. Hence in this study, characterization of spatially varying drought occurrences and its severity at different time scales was carried out using various precipitation gridded products (TRMM, CRU and CHIRPS) for part of Indo-Gangetic Plain, India. Further, drought severities assessed by these gridded products were relatively evaluated with reference to rain gauge based IMD gridded product. The spatial pattern of TRMM and IMD based SPI for all the time scales were observed to be similar for both wet and dry years. The spatial pattern of low and high number of drought events is mostly similar for CHIRPS, TRMM and IMD. Overall, it was observed that spatial pattern of drought frequency identified through CRU based SPI was completely distinct compared to
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