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A greenhouse experiment was carried out to examine the differential morpho‐physiological responses of five cultivars of turnip (Brassica rapa L.) to salt stress. Five diverse cultivars of turnip (shaljum desi surakh, shaljum purple top, shaljum golden bal, neela shaljum, and peela shaljum) were subjected for 6 weeks to varying levels of NaCl, i.e. 0, 80 and 160 mm in Hoagland’s nutrient solution in sand culture. Imposition of varying levels of salt substantially decreased shoot and root fresh and dry weights, chlorophyll contents, leaf osmotic potential, relative water contents, different gas exchange attributes, total phenolics, malondialdehyde, activities of superoxide dismutase, peroxidase catalase, and leaf and root K+ levels while enhanced the proline contents, membrane permeability, level of H2O2, leaf and root Na+ and Cl− and leaf Ca2+ in all turnip cultivars under study. Of all cultivars, peela shaljum and neela shaljum were consistently higher in their growth than the other turnip cultivars at all salt concentrations of the growth medium. Photosynthetic capacity (A) and stomatal conductance (gs) were higher in high biomass‐producing cultivars, i.e. peela shaljum and neela shaljum, which provide to be potential selection criteria of salt tolerance in turnip. However, the regulation of antioxidant system was cultivar‐specific under saline conditions.

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At-site flood frequency analysis is a direct method of estimation of flood frequency at a particular site. The appropriate selection of probability distribution and a parameter estimation method are important for at-site flood frequency analysis. Generalized extreme value, three-parameter log-normal, generalized logistic, Pearson type-III and Gumbel distributions have been considered to describe the annual maximum steam flow at five gauging sites of Torne River in Sweden. To estimate the parameters of distributions, maximum likelihood estimation and L-moments methods are used. The performance of these distributions is assessed based on goodness-of-fit tests and accuracy measures. At most sites, the best-fitted distributions are with LM estimation method. Finally, the most suitable distribution at each site is used to predict the maximum flood magnitude for different return periods.

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At-site flood frequency analysis is a direct method of flood estimation at a given site. The choice of an appropriate probability distribution and parameter estimation method plays a vital role in at-site frequency analysis. In the current article, flood frequency analysis is carried out at five gauging sites of the Ume River in Sweden. Generalised extreme value, three-parameter lognormal, generalised logistic and Gumbel distributions are fitted to the annual maximum peak flow data. The L-moment and the maximum likelihood methods are used to estimate the parameters of the distributions. Based on different goodness-of-fit tests and accuracy measures, the three-parameter lognormal distribution has been identified as the best-fitted distribution by using the L-moments method of estimation for gauging sites Harrsele Krv, Gardiken and Överuman Nedre. The generalised extreme value distribution with the Lmoments estimation provided the best fit to maximum annual streamflow at gauging sites Solberg and Stornorrfors Krv. Finally, the best-fitted distribution for each gauging site is used to predict the maximum flow of water for return

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