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Mobile wireless sensor networks have been developed as a result of recent advancements in wireless technologies. Sensors in the network are low-cost and have a short battery life, in addition to their mobility. They are more applicable in terms of the essential properties of these networks. These networks have a variety of uses, including search and rescue operations, health and environmental monitoring, and intelligent traffic management systems, among others. According to the application requirements, mobile wireless sensor nodes are energy limited equipment, so energy conservation is one of the most significant considerations in the design of these networks. Aside from the issues posed by sensor node mobility, we should also consider routing and dynamic clustering. According to studies, cluster models with configurable parameters have a substantial impact on reducing energy usage and extending the network's lifetime. As a result, the primary goal of this study is to describe and select a smart method for clustering in mobile wireless sensor networks utilizing evolutionary algorithms in order to extend the network's lifetime and ensure packet delivery accuracy. For grouping sensor nodes in this work, the Genetic Algorithm is applied initially, followed by Bacterial Conjugation. The simulation's results show a significant increase in clustering speed acceleration. The speed of the nodes is taken into account in the suggested approach for calibrating mobile wireless sensor nodes.

The increase in water demand due to increase in anthropogenic activities and changes in the hydrological phenomenon has led to water scarcity. The groundwater exploration, utilization, management and recharging by creation of appropriate water harvesting structure is an important aspect for its sustainable management. This current study was carried out for Ghaggar river basin to delineate groundwater potential zones using analytical hierarchical process based multi criteria decision analysis followed by identification of suitable sites and structures for water harvesting. The thematic layers for Landuse landcover, drainage density, soil texture, geomorphology, slope, lineament density and runoff were prepared and weights were assigned to each thematic layer. The weights were than normalized using the analytical hierarchical process based on their characteristic and relationship with groundwater recharge. Finally, the groundwater prospect zones were delineated by integrating the thematic maps using the weighted sum overlay analysis tool in ArcGIS 10.5. The areal distribution of the groundwater potential reveals that 0.02, 36.55, 43.18, 19.29 and 0.96 % falls under very poor, poor, moderate, good and very good groundwater potential category, respectively. The groundwater potential map was validated using the existing well data. The resultant groundwater potential zones falling in good to very good zones were integrated with slope and stream order as per the Integrated Mission for Sustainable Development (IMSD) guidelines and three types of water harvesting structures were suggested i.e. check dam (24), percolation tank (27) and farm ponds (50).

The landuse and landcover change is considered as one of the most vital components of the global environmental change responsible for influencing the quantity, seasonal patterns and durations of the water flow within basins around the world. The aim of this study is to assess the impacts of changes in landuse landcover on the various hydrological components for Ghaggar river basin for a period of 1985-2015 using Soil and Water Assessment Tool model. The landuse landcover maps have been prepared using various Landsat satellite images for the year 1985, 1995, 2005 and 2015.The fixing changing method has been employed to quantify the impacts of landuse changes on hydrological components by changing the landuse maps of different year and keeping rest of the inputs same. The correlation and Partial Least square regression are used to examine the impacts of change in landuse on the hydrological components. The results unveiled that the increase in agriculture and built-up area and decrease in area of evergreen, deciduous and mixed forest. During the period 1985-2015 there is increase in annual stream flow (0.20%), wet season streamflow (1.55%), surface runoff (12.23%) and water yield (0.22%) on the contrary there is decrease in dry season streamflow (2.1%), Evapotranspiration (0.08%), groundwater flow (8.62%), Percolation (8.02%) and lateral flow (3.92%) owing to changes in landuse landcover. There is an urgent need to adopt soil and water conservation practices in the area to avert these deleterious effects of landuse landcover changes.