S. R. Sreerama Naik

Flooding is one of the most destructive natural disasters, capable of causing significant damage to infrastructure, ecosystems, and human lives. It is triggered by a variety of factors such as persistent rainfall, rapid snowmelt, rising sea levels, cloudbursts and anthropogenic activities. This study focuses on mapping flood-prone areas in the Alappuzha district of Kerala using the Weighted Overlay Method for flood risk mapping, the research integrates geospatial techniques such as Remote Sensing (RS) and Geographic Information Systems (GIS) to create a flood inundation map. Key parameters include physical factors like slope, drainage density, rainfall, geomorphology, soil, land use, NDVI, NDBI, MNDWI, and WRI, along with social factors such as population, households, building conditions, and access to information. The analysis reveals that low-lying areas near water bodies, including Cherthala, Ambalapuzha, and Kuttanad, are highly susceptible to flooding, intensified by poor drainage infrastructure. Kuttanad situated below sea level, faces frequent floods, severely impacting agriculture and livelihoods. Southern taluks like Karthikappally and Mavelikkara, although at higher altitudes, still face moderate flood risks due to proximity to minor rivers. This study underscores the importance of integrating geospatial data and hydrological models for effective flood risk assessment and sustainable flood management practices.

The present study assesses the agricultural suitability and capability for crop cultivation in Bapatla District, Andhra Pradesh, India by Integrating remote sensing techniques. Today, technological resources such as GIS and remote sensing can locate soil types, water resources, and the terrain of a place with great accuracy, even underground. Thus, the specificity in land use planning is increased, hence effective reconciliation of productivity with various conservation efforts nowadays underground. Geospatial and remote sensing methods were used to analyze the agricultural suitability and land capabilities of the Bapatla District in Andhra Pradesh. Factors used in the study include geology, geomorphology, soil type, LULC, slope, elevation, drainage and infrastructure to distinguish zones by their agricultural capabilities. The method uses a Weighted Overlay Approach (WOA) to place land into five groups: those not used for farming, Low Suitability, Medium Suitability, High Suitability and Very High Suitability. The maps produced from the suitability assessment were confirmed using the robust Soil Adjusted Vegetation Index (SAVI) method. The research indicates that about half of the district's area is highly suitable, especially the deltaic and alluvial plains with generous soil and mild slopes and these places are mostly planted with paddy, cotton and pulses. Where there is salinity, steep slopes or city development, special actions such as improving the soil or choosing other uses for the land are considered. It points out that irrigation is important in the district and taking care of water resources helps maintain its productivity as climate conditions and groundwater change. Results from the research suggest policymakers, farmers and land-use planners what they can do to choose crops wisely, use resources more efficiently and address environmental risks. Proper use of land resources can help the district avoid soil damage, secure enough water and increase produce. The combination of GIS and remote sensing technologies is also potential for monitoring real-time crop condition, land use change, and soil moisture to facilitate dynamic decision-making. Verification of suitability classes of SAVI indices confirms the dependability of the approach and proposes its extension to other agriculturally diverse locations.

The deficiency in rainfall leads to meteorological droughts. Its manifestations are visible both in the vegetation cover and soil moisture. The present study assessed the characteristics of agricultural drought following meteorological droughts. The study also assessed the severity of meteorological droughts and their manifestation on the agriculture and soil moisture in a semi-arid area. The study has been carried out for the Malaprabha sub-basin which partly covers three districts of North Interior Karnataka, India. India Meteorological Department’s (IMD) criteria have been used to identify the drought years, and its severity has been assessed through the Standard Precipitation Index (SPI). The IMD’s monthly rainfall data were used to identify the drought years and periods for the region. Among the drought years, the mild, moderate, and severe drought along with deficit and excess rainfall years were considered to assess and characterize the soil moisture conditions and the agricultural drought. The satellite image based indices for these selected years were constructed to determine the soil moisture conditions and the agricultural drought severity. The Temperature-Vegetation Dryness Index (TVDI) was used to determine the soil moisture conditions. The indices employed to determine the agriculture drought are NDVI, Thermal Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI). These satellite-based indices were calculated using the Landsat images of the selected drought and non-drought years. The results showed that the seasonal and annual drought are frequent in the study area. There are spatial and temporal variations in the drought years and their severity. The satellite-based indices clearly indicate the spatial variation in the agriculture droughts and its intensity. It has been found that the impact of drought on agriculture has significantly reduced due to the development of well-irrigation in the sub-basin. VHI is more appropriate in determining the agricultural drought and its characteristics.

Sea Level Rise (SLR) is considered as one of the effects of climate change that leads to Salt Water Intrusion (SWI) into the coastal areas around the world, thereby contaminating the groundwater and making it unusable for household and irrigation pur