Developing quantifiable approaches for delineating suitable options for irrigating fallow areas during dry season-a case study from Eastern India.

Harvesting surface runoff during monsoon season for further utilization in crop production during the post-monsoon season is now becoming an effective solution to mitigate water scarcity problems. In this study, multi-criteria analysis-analytic hierarchy process (MCA-AHP)-based approach was envisaged for rainwater harvesting (RWH) zoning for a case study area, i.e., two districts of Odisha state situated in Eastern India. In spite of having a large irrigation network in the study area, major portion of these two densely populated and agriculture dominated districts remains fallow during dry seasons. Suitable locations for RWH structures such as farm pond, check dam, and percolation tanks were identified through Boolean conditions. RWH potential map was generated using different thematic layers namely land use/land cover (LU/LC), geomorphology, slope, stream density, soil type, and surface runoff. AHP-based MCA technique was used to integrate these thematic layers by assigning weights to the thematic layers and ranks to the individual theme features on 1-9 AHP Saaty's scale, considering their relative importance on RWH potential of the study area. The Natural Resources Conservation Service-Curve Number method was used to derive surface runoff using Climate Hazards Group Infra-Red Precipitation with Station rainfall data, satellite-derived LU/LC and FAO soil maps. In comparison to single cropped areas in 48% of the total study area, only 4% area was under double and triple cropped areas during 2016-2017. Moderate runoff was observed in > 50% of the study area dominated by agricultural landscape. Nearly 40%, 25.11%, and 32.45% of the study area indicated very high, high, and moderate RWH potentials, respectively. Particularly, very high RWH potential is observed in the eastern and central portion of the study area. The use of appropriate RWH structures in less irrigated areas will facilitate multiple cropping and will substitute the use of sub-surface water harvesting practices. In these two districts, 73 check dams and 153 percolation tanks are prescribed along the 2nd- and 3rd-order streams. In coarser textured soil, nearly 306 km2 and 608 km2 areas are identified as moderate and highly suitable zones for percolation tank construction on ground, while in fine soil, around 786 km2 area is identified as suitable for farm pond construction. Majority of the suitable zones for percolation tanks is found in Jajpur district, while suitability for adoption of farm pond and check dam is more in Bhadrak district. It is expected that implementation of the prescribed RWH structures can mitigate the threats of flood, drought, soil erosion, and enhance the soil moisture and cropping intensity significantly. The use of GIS platform with the spatial layers and the methodology adopted can be updated and replicated in larger regions in a shorter time. The spatially explicit maps are offering insights to different themes, providing useful information to the water resource managers, and may improve the decision-making process.

Seroprevalence of influenza A H1N1 (swine) infection in the human population in a cantonment.

BACKGROUND: Various serosurveys and studies were conducted globally on pandemic influenza. H1N1 virus reported so far provides ample evidence of differing perspectives, regarding its epidemiology especially with regard to prevalence, populations groups, and behaviour related to vaccine acceptance. A multigroup, cross-sectional survey among 658 healthy subjects was carried out, in Pune among students, health-care workers (HCWs), and soldiers to assess the seroprevalence of pandemic influenza H1N1 virus and its associated factors. METHODS: The total sample size, based on forecasted prevalence of 33%, worked out to be 640. We studied 658 subjects including 103 students, 201 HCWs, and 354 serving soldiers. The sample for each group was selected from the respective study population by simple random sampling using a random number table. Haemagglutination inhibition test was carried out at the National Institute of Virology. RESULTS: The overall seroprevalence of pandemic influenza H1N1 (2009) virus was found to be 46.5% (95% confidence interval 42.6-50.4) which was adjusted to 39.4% after excluding those vaccinated. The availability of vaccine for high-risk group such as HCWs did not find much favour with the HCWs who did not accept vaccine for various reasons. Whereas only one student was vaccinated, 21.4% of HCWs and 32.5% of soldiers were vaccinated. CONCLUSION: Based on high seroprevalence of antibodies against H1N1 virus during pandemic, vaccination of general population is not recommended. However, high-risk groups and HCWs need to be protected with flu vaccine. There is a need to encourage HCWs for accepting vaccination.

Characterization of spatial variability of soil physicochemical properties and its impact on Rhodes grass productivity.

Characterization of soil properties is a key step in understanding the source of spatial variability in the productivity across agricultural fields. A study on a 16 ha field located in the eastern region of Saudi Arabia was undertaken to investigate the spatial variability of selected soil properties, such as soil compaction 'SC', electrical conductivity 'EC', pH (acidity or alkalinity of soil) and soil texture and its impact on the productivity of Rhodes grass (Chloris gayana L.). The productivity of Rhodes grass was investigated using the Cumulative Normalized Difference Vegetation Index (CNDVI), which was determined from Landsat-8 (OLI) images. The statistical analysis showed high spatial variability across the experimental field based on SC, clay and silt; indicated by values of the coefficient of variation (CV) of 22.08%, 21.89% and 21.02%, respectively. However, low to very low variability was observed for soil EC, sand and pH; with CV values of 13.94%, 7.20% and 0.53%, respectively. Results of the CNDVI of two successive harvests showed a relatively similar trend of Rhodes grass productivity across the experimental area (r = 0.74, p = 0.0001). Soil physicochemical layers of a considerable spatial variability (SC, clay, silt and EC) were utilized to delineate the experimental field into three management zones (MZ-1, MZ-2 and MZ-3); which covered 30.23%, 33.85% and 35.92% of the total area, respectively. The results of CNDVI indicated that the MZ-1 was the most productive zone, as its major areas of 50.28% and 45.09% were occupied by the highest CNDVI classes of 0.97-1.08 and 4.26-4.72, for the first and second harvests, respectively.