Assessment of hydrologic impact on flow regime due to dam inception using IHA framework.

In the last century, thousands of dams and diversions have been built to regulate the streamflow, resulting in water impoundment in the upstream and frequent drought conditions in the downstream. It has pressured researchers to study flow regime change and its complication on the downstream biota. The present study planned to develop a framework for trend analyzing of river flow and detecting flow regime change after the inception of Isapur and Arunavati dams, situated on the upstream side of Penganga bridge. Mann-Kendall (MK) and Sen's slope estimator for trend analysis and Indicators of Hydrologic Alteration (IHA) for flow regime alteration analysis were utilized. A total 26 parameters showed negatively altered flow regime with a magnitude varying from - 5.56 to - 100%. Fourteen altered parameters were modified drastically (more than 50% decrease) with the highest modification in 30-day maximum (100%) post-single dam inception. a total of 13 parameters were negatively altered with alteration value - 9.09 to - 86.36% post-double dam inception, out of which, three parameters were severely altered, with the highest alteration in the month of June. The period (1983-1994) was more altered than 1995-2016. This shows that Isapur dam has higher impact on flow regime change than Arunavati dam. Information about alteration of hydrological parameters will be helpful to improve the water flow regulation at Isapur and Arunavati dams for restoring river ecology on the downstream side.

Capability assessment of conventional and data-driven models for prediction of suspended sediment load.

Information about suspended sediment concentration (SSC) in the stream is vital for sustainability of water conservation and erosion control planning, designing and monitoring. In this research, prediction of SSC has been done using artificial neural network (ANN), support vector regression (SVR) and multi-linear regression (MLR) models. Performance evaluation of developed models has been carried out on the basis of root mean square error (RMSE), correlation coefficient (r), coefficient of efficiency (CE) and pooled average relative error (PARE). Cross-correlation function (CCF) validated that gamma test (GT) is an appropriate tool for the selection of most responsive input variables. On the basis of GT and CCF, GT-6 model was selected as the model with most effective input variables, with the values of gamma, standard error and V-ratio as 0.0643, 0.00583 and 0.2570, respectively. The ANN (6-3-1) model performed better than the other single and double hidden layered ANN models with the values of r, RMSE, CE and PARE as 0.939, 0.0063 g/l, 85.17 and 0.0160, respectively. The performance of the SVR model was found better with the values of r, RMSE, CE and PARE as 0.906, 0.018 g/l, 79.09 and 0001, respectively, but slightly poor than the selected ANN (6-3-1) model. The values of r, RMSE, CE and PARE were found as 0.899, 0.0312 g/l, 65.15 and - 0.0031, respectively, in the case of MLR model. The present study revealed that among the ANN, SVR and MLR models, the ANN model with a single hidden layer is most suitable for observed SSC. The present study offers the simple efficient model to estimate the suspended sediment concentration in the stream with minimum error using limited data set.

Impact of municipal wastewater reuse through micro-irrigation system on the incidence of coliforms in selected vegetable crops.

The incidence of coliforms in soil and agricultural produce was evaluated in two vegetable crops, namely, cauliflower and eggplant, which were grown using wastewater for irrigation. Field experiment was conducted at Indian Agricultural Research Institute (IARI), New Delhi, India. In the field experiments to irrigate the crop, municipal wastewater was applied through drip system. The filtration of irrigation water was done through sand media, disk media and their combination. The laterals were placed at surface and subsurface of soil. All filtration processes significantly reduced total coliforms (12-20%) and E. coli (15-25%) populations when evaluated against untreated wastewater. The population dynamics of coliforms in soil profiles indicated that the maximum population of E. coli was estimated on the surface of soil profile when using surface drip, which decreased with soil depth under subsurface placement of drip lateral. After crop harvesting, E. coli in the soil reduced until 20 days after the cessation of irrigation and was highly correlated with soil moisture. E. coli and total coliforms availability were noticed on the surface and in the tissues of leaf and fruit, the coliform count is higher on the surface of plants under surface placement of drip lateral. The concentration of coliforms was lower with eggplant in comparison to cauliflower due to the smooth fruit surface of eggplant. Our study reveals the critical role of subsurface drip irrigation in reducing the load of coliform both in the soil and the crop produce ensuring safety of the consumers against health hazards. In another way protect the environment from wastewater disposal and reduce the burden on synthetic fertilizers as well as shrinking freshwater resources.