Street Level Flood Monitoring and Warning System, a conceptual model using IoT: A Case of Surat City

Most of the natural disasters are unpredictable, but the most frequent occurring catastrophic event over the globe is flood. Developing countries are severely affected by the floods because of the high frequencies of floods. The developing countries do not have good forecasting system compared to the developed country. The metro cities are also settled near the coast or river bank which are the most vulnerable places to floods. This study proposes plan for street level flood monitoring and warning system for the Surat city, India. Waterlogging happens in the low lying area of the Surat city due to heavy storm and heavy releases from the Ukai dam. The high releases from upstream Ukai dam and heavy rainfall resulted into flooding in the low lying area of the Surat city. This research proposed a wireless water level sensor network system for the street water level flood monitoring. The system is proposed to monitor the water levels of different areas of city through the wireless water level sensors as well as to capture live photos using CCTV camera. This will help authority not only to issue flood warning but also to plan flood mitigation measures and evacuation of people.

Mapping of Groundwater potential zones in Lingasugur Taluk in North-eastern part of Karnataka, India using Remote Sensing, GIS and multi-criteria data analysis

Groundwater research has evolved tremendously as presently it is the need of society. Remote Sensing (RS) and Geographical Information System (GIS) are the main methods in finding the potential zones for the groundwater. They help in assessing, exploring, monitoring and conserving groundwater resources. A case study was conducted to find the groundwater potential zones in Lingasugur taluk, Raichur District, Karnataka State, India. Ten thematic maps were prepared for the study area such as geology, hydrogeomorphology, land use/ land cover, soil type, NDVI, NDWI, slope map, lineament density, rainfall and drainage density. A weighted overlay superimposed method was used after converting all the thematic maps in raster format. Thus from analysis, the classes in groundwater potential were made as very good, moderate, poor and very poor zones covering an area of 10.1 sq.km., 169.25 sq.km., 1732.31 sq.km. and 53.66 sq.km. respectively. By taking the present study into consideration, the future plans for urbanization, recharge structures and groundwater exploration sites can be decided.

Flood hazard zonation of upper kolodyne using GIS and multi criteria decision analysis in Mizoram, India

Kolodyne is the largest river in Mizoram. The river originates in Myanmar where it flows in a southerly direction and enters Mizoram where it is called Chhimtuipui river and it becomes the international border between India and Myanmar. The Kolodyne river meets several rivers in Mizoram before it enters Chin State in Myanmar again. The upper Kolodyne river has caused destructive floods recently, however, attempts to delineate the flood hazard zones have not been carried out. This river is a source of livelihood for many families in the region and it had wrecked havoc in the past monsoon seasons with the loss of lives and property. The potential flood hazard zonation of the upper Kolodyne watershed using geographic information systems and multi-criteria decision analysis has revealed that about 40% of the total watershed fall in the high and very high potential zones and flood control measures are needed to be updated.

Depositional mode and Provenance of Kopili sandstones from parts of Dima Hasao District, Assam, NE India: Evidence from Grain size distribution and Heavy mineral assemblage

This study presents a record of the depositional mode and provenance of the Kopili sandstones outcropped in and around Umrangso, the Dima Hasao district of Assam, India using proxies such as grain size and heavy mineral study. The Grain size study reveals that the sandstones of the Kopili formation consist predominantly of fine-grained sands mixed with medium sands. The grain size statistical parameters divulge that the sandstones are characterized mostly by moderately sorted sands, coarse skewed to near symmetrical, leptokurtic to extremely leptokurtic nature. The frequency distribution curves reflect mostly bimodal as well as polymodal distribution of sediments. The Linear Discriminant Function analysis indicates shallow marine beach sub environment in agitated water depositional condition for the Kopili sediments. The CM pattern discloses that saltation and suspension are the dominant transporting modes. The Heavy mineral analysis discerns that opaques dominate over transparent heavies. Transparent heavies in decreasing order of abundance are zircon, tourmaline, rutile, clinopyroxene, staurolite, hornblende, garnet, chlorite and epidote. The zircontourmaline- rutile (ZTR) maturity index (average 53.15%) discloses sub-mature to mature nature of the Kopili sandstones. The heavy mineral assemblage corroborates their mixed provenance (silicic igneous and metamorphic) for the Kopili sandstones.

Urban Expansion and Rising Surface Temperature: A Multi Temporal Assessment in Kochi Metropolis, Kerala

The process of urbanization and urban growth has resulted in rapid, uncontrolled conversion of natural land cover and spreading of impervious concrete surfaces in many parts of the world leading to serious environmental concerns. There are a myriad of micro climatic effects due to urban growth. One of the significant consequences is the rising urban temperature. Urban surface temperature responds to changes in land use/land cover dynamics and urban expansion. This would ultimately lead to local climatic changes and would accentuate global warming. Geo spatial technology provides sophisticated tools for analyzing urban features and micro climates. Land surface temperature (LST) or the radiant energy from earth surface can be calculated using thermal bands of satellite data. Kochi, the largest urban agglomeration in Kerala, is undergoing hasty developments and land modifications. This study attempts to monitor changes in land surface temperature from 2000 to 2020 along with changes in built up and vegetation cover. The results revealed that the average surface temperature of Kochi recorded an increase of 0.60C and the loss of green cover has contributed to the increased temperature. Moreover, the LST exhibits a strong positive correlation with built up land expansion. The study findings stand helpful for urban planning and sustainable development of the city.

Climate Change Vulnerability of Marginal and Small Farmers in Nuapada District, Odisha

This study attempts to measure the level of livelihood vulnerability of farmers to climate change in Nuapada. Both descriptive and inferential statistics were used based on primary and secondary data. The study found that marginal and small farmers in the study area have different differential livelihood vulnerability to climate change. The study has used composite approach in which seven dimensions including 34 indicators were studied. Composite of factors such as low level of education, lack of access to credit, lack of access to critical irrigation were associated with the relatively higher Livelihood Vulnerability Index (LVI) values. The multiple linear regression analysis revealed that seven socio-economic variables account for 44% of variation in livelihood vulnerability index; three variables among them viz. number of household income sources, landholding size and highest level of education in household were found to have significant impact on LVI. The findings of the study conclude that there is differential vulnerability to climate change in the same context which was mostly determined by various socioeconomic factors. Thus climate change related studies and policies (which mostly limit district as the measuring unit) must expand their scope to understand and act on differential vulnerabilities in the same district.

A combined approach for flood hazard assessment using hydrological, hydraulic and GIS modeling case study of El Hamiz Wadi, Algeria

Flood hazard is one of the most destructive natural phenomena causing a significant material damage and human losses in Algeria during the past decade. The aim of this study is to assess and characterize the flood hazard in El Hamiz watershed (Algeria). In addition, this study identifies areas and elements prone to this hazard to minimize the damages and losses. The methodology used in the present study is based on a combination of hydrological and hydraulic modeling using the Hec-Ras software and mapping techniques using a Geographic Information System (GIS). The flood hazard assessment model of El Hamiz wadi using different hydrological (rainfall / runoff transfer and return period), hydraulic (water level and flow velocity) and exposure (land use data and socio-economic data) parameters revealed that the downstream part of the studied area is the most susceptible to flood events. The mapping of flood-prone areas indicated the extent of this phenomena on the El Hamiz wadi banks, especially through heavy submersion of residential areas characterized by a high urban concentration including inhabitants, activities and infrastructures.

The Landslide Susceptibility Assessment using Bi-variate Statistical Information Value Model of Chenab River Valley, Jammu and Kashmir (India)

Almost every year, the Himalayan region suffers from a landslide disaster that is directly associated with the prosperity and development of the area. The study of landslide disasters helps planners, decision-makers and local communities for the development of anthropogenic structures in order to enhance the safety of society. Therefore, the prime aim of this research is to produce the landslide susceptibility map for the Chenab river valley using the bi-variate statistical information value model to detect and demarcate the areas of potential landslide incidence. The object-based image analysis method identified about 84 potential sites of landslides as landslide inventory. The statistical information value model is derived from the landslide inventory and multiple causative factors. The outcome showed that 23% area of the Chenab river valley falls into the class of a very high landslide susceptibility zone. The ROC curve method is used to validate the model which denoted the acceptable result for the landslide susceptibility zonation with 0.826 AUC value for the Chenab river valley.

Rapid detection of changes in the riverbanks of Laigiang river of the South Central Coast Vietnam: A methodology based on Digital Shoreline Analysis System and Sentinel-2

The research focuses on using Sentinel-2 that can be integrated with the Digital Shoreline Analysis System (DSAS) as an effective tool for the determination of changes in the riverbanks and using linear regression to predict shoreline changes. The research applied the assessment of shoreline changes in the period of 2015- 2020 and forecast to 2025 in Laigiang river of the South Central Coast region of Vietnam. Based on the DSAS tool, parameters such as Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR) and Linear Regression Rate (LRR) were determined. The analysis results show that the accretion process in the Laigiang river in the period of 2015-2020 with the accretion area ranges from 81.47 ha. Meanwhile, the area of shoreline erosion only fluctuates around 54.42 ha. The rhythm of evolution is a determinant element for this transitional system.

Climate Variability and Trend Analyses of Rainfall and Temperature Data of Imphal, Manipur

Understanding local climate variability and change is necessary for improving future climate forecasts and also aids preparation of informed area specific climate mitigation and adaptation strategies. Climate change at local scale is best revealed by studying observed variabilities and trends in rainfall and temperature data through statistical techniques. Therefore, this study employed standard deviation and coefficient of variability and Mann-Kendall test and Sen slope determination non-parametric techniques to perform variability and trends analyses across multiple temporal scales on climate data obtained at Imphal (Tulihal) station. The results indicate prevalence of different patterns between rainfall and temperature trends. Except for the positive trends in the month May (2mm/yr) and in the pre-monsoon season (9.49mm/yr), no other discernable patterns in rainfall data were observed. Temperature trends, on the other hand, witnessed significant positive increase in maximum, minimum and mean values. For mean temperature, all months registered significant increasing trends. At the annual and seasonal scales also, maximum, minimum and mean temperatures have increased although with varying rates. It is noteworthy to mention that temperature change has occurred at two distinct phases; before 1993 slow warming and after 1993 rapid warming. Temporal distribution of annual mean temperature captures this pattern more vividly as warming rate before 1993 was less than 0.01 compared to 0.450c/year in the latter phase. Overall, it can be said that rainfall has higher variability with very little or no pattern but temperature distribution suggests existence of strong trends in the observed data.