No abstract

The recent global upsurge in anthropogenic activities has resulted in a decline in the quality of water. This by extension has resulted in increased ubiquity of water pollution in terms of sources. The application of traditional water quality assessment methods usually involves the use of conventional water quality parameters and guideline values. This may be associated with bias and errors during the computation of various sub-indices. Hence, to overcome this limitation, it is critical to have a visual appraisal of the water quality in terms of source and human health risks exposure for sustainable water resource management and informed decision-making. Therefore, the present study has integrated multiple water quality assessment indices, spatio-temporal, and statistical models to assess the suitability of fifty groundwater samples (n = 50) within the Firozabad industrial area for irrigation and drinking; as well as the likely health risks from oral intake and dermal contact by inhabitants. Electrical conductivity (mean = 1,576.6 μs/cm), total hardness (mean = 230.9 mg/L), dissolved sodium (mean = 305.1 mg/L) chloride (mean = 306.1 mg/L) and fluoride (mean = 1.52 mg/L) occurred in the water at concentrations above the recommended standards; attributed influxes from agricultural and industrial wastewater. The pollution index of groundwater and water quality index revealed that 100% of the groundwater samples are extremely polluted; this was also supported by the joint multivariate statistical analyses. The majority of the irrigational water quality indices (sodium adsorption ratio, Kelly’s Ratio, permeability index, percent sodium) revealed that the long-term use of the groundwater for irrigation in the area will result in reduced crop yield unless remedial measures are put in place. Higher Hazard index (HI > 1) for nitrate and fluoride ingestion was recorded in water for the children population compared to adult; an indication that the children population is more predisposed to health risks from the oral intake of water. Generally, risk levels from ingestion appear to increase in the western and north-eastern parts of the study area. From the findings of this study, it is highly recommended that adequate agricultural practices, land use, and water treatment regulatory strategies be put in place for water quality sustainability for enhanced agricultural production and human health protection.

No abstract

<abstract> <p>Trash mulches are remarkably effective in preventing soil erosion, reducing runoff-sediment transport-erosion, and increasing infiltration. The study was carried out to observe the sediment outflow from sugar cane leaf (trash) mulch treatments at selected land slopes under simulated rainfall conditions using a rainfall simulator of size 10 m × 1.2 m × 0.5 m with the locally available soil material collected from Pantnagar. In the present study, trash mulches with different quantities were selected to observe the effect of mulching on soil loss reduction. The number of mulches was taken as 6, 8 and 10 t/ha, three rainfall intensities viz. 11, 13 and 14.65 cm/h at 0, 2 and 4% land slopes were selected. The rainfall duration was fixed (10 minutes) for every mulch treatment. The total runoff volume varied with mulch rates for constant rainfall input and land slope. The average sediment concentration (SC) and sediment outflow rate (SOR) increased with the increasing land slope. However, SC and outflow decreased with the increasing mulch rate for a fixed land slope and rainfall intensity. The SOR for no mulch-treated land was higher than trash mulch-treated lands. Mathematical relationships were developed for relating SOR, SC, land slope, and rainfall intensity for a particular mulch treatment. It was observed that SOR and average SC values correlated with rainfall intensity and land slope for each mulch treatment. The developed models' correlation coefficients were more than 90%.</p> </abstract>

Soil fertility (SF) assessment is an important strategy for identifying agriculturally productive lands, particularly in areas that are vulnerable to climate change. This research focuses on detecting SF zones in Firozabad district, Uttar Pradesh, India, for agricultural purposes, so that they can be prioritized for future management using the fuzzy technique in the Arc GIS model-builder. The model computing technique was also deployed to determine the different fertility zones, considering 17 soil parameters. The derived fuzzy technique outperformed the traditional method of dividing the sampling sites into clusters to correlate soil fertility classes with the studied soil samples. The prioritization of the soil factors and a spatial analysis of the fertility areas were carried out using the Analytic Hierarchy Process (AHP) and GIS tools, respectively. The AHP analysis outcome indicated that hydraulic properties had the highest weighted value, followed by physical and chemical properties, regarding their influence on SF. The spatial distribution map of physico-chemical properties also clearly depicts the standard classification. A fuzzy priority map was implemented based on all the classes parameters to identify the five fertility classes of the soil, namely very high (0.05%); high (16.59%); medium (60.94%); low (22.34%); and very low (0.07% of total area). This study will be of significant value to planners and policymakers in the future planning and development of activities and schemes that aim to solve similar problems across the country.