ANALYTICAL HIERARCHY PROCESS FOR IDENTIFICATION OF SUITABLE WATER HARVESTING SITE IN GEOSPATIAL ENVIRONMENT

Water is the prime requirement for agriculture, domestic uses and industrial production. In India the per capita available of water is decreasing at a higher rate due to impact of climate change and ever-increasing population. Rainwater harvesting is the technique which is being used in effective storing of surface runoff. There are various types of water harvesting structures namely check dam, farm pond, percolation tank, etc. However, identification of potential site for the construction of the particular water harvesting structure is bit difficult as it depends upon numerous parameters such as soil type, slope, water availability, land use and land cover of the site and the surrounding, etc. The guidelines such as Food and Agriculture Organization; Integrated Mission for Sustainable Development are available for selecting suitable site for water harvesting structures. As the site suitability analysis involves multiple parameters for decision making, in the present study, the selection of suitable site for check dam is made through analytical hierarchy process (AHP) in geospatial domain for Hatni watershed, Madhya Pradesh, India. As location for check dam construction is influenced by soil texture, slope of the terrain, land use land cover, stream order and water availability; these parameters were derived from remote sensing data and analysed. The slope and stream network layers were generated from the digital elevation model (DEM). Further, the influence of soil and water availability in identifying the suitable sites was studied through soil texture and curve number. Different parameters influence the site suitability analysis, therefore, in the present study, IMSD guidelines were used to assign weights to each parameter under consideration. The layers were assigned weights by AHP technique based on pairwise comparison. The layers were reclassified according to the weights, then overlay analysis has been done to get the final site suitability map. As remote sensing provides the synoptic coverage of the earth, it has been further utilised to study the impact of water harvesting structure on its surrounding. The land use land cover map of before and after the construction of water harvesting structure was analysed for change in vegetation condition. It was observed that the vegetative cover has increased after implementation of the water conservation measures. It may be concluded that the geospatial technology has immense potential in site suitability studies for water harvesting structures

ASSESSMENT AND MONITORING OF AGRICULTURAL DROUGHTS IN MAHARASHTRA USING METEOROLOGICAL AND REMOTE SENSING BASED INDICES

Drought is a recurring climatic event characterized by slow onset, a gradual increase in its intensity, and persistence for a long period depending upon the availability of water. Droughts, broadly classified into meteorological, hydrological and agricultural drought, which are interconnected to each other. India, being an agriculture based economy depends primarily on agriculture production for its economic development and stability. The occurrence of agriculture drought affects the agricultural yield, which affects the regional economy to a larger extent. In present study, agricultural and meteorological drought in Maharashtra state was monitored using traditional as well as remote sensing methods. The meteorological drought assessment and characterization is done using two standard meteorological drought indices viz. standard precipitation index (SPI) and effective drought index (EDI). The severity and persistency of meteorological drought were studied using SPI for the period 1901 to 2015. However, accuracy of SPI in detection of sub-monthly drought is limited. Therefore, sub-monthly drought is effectively monitored using EDI. The monthly and sub-monthly drought mapped using SPI and EDI, respectively were then compared and assessed. It was concluded that EDI serves as a better indicator to monitor sub-monthly droughts. The agricultural drought monitoring was carried out using the remote sensing based indices such as vegetation condition index (VCI), temperature condition index (TCI), vegetation health index (VHI), shortwave angle slope index (SASI) and the index which maps the agricultural drought in a better way was identified. The area under drought as calculated by various agricultural drought indices compared with that of the EDI, it was found that the results of SASI matched with results of EDI. SASI denotes different values for the dry and wet soil and for the healthy and sparse vegetation. SASI monitors the agricultural drought better as compared to other indices used in this study

ESTIMATION OF INSTANTANEOUS EVAPOTRANSPIRATION USING REMOTE SENSING BASED ENERGY BALANCE TECHNIQUE OVER PARTS OF NORTH INDIA

Evapotranspiration (ET) is an essential element of the hydrological cycle and plays a significant role in regional and global climate through the hydrological circulation. Estimation and monitoring of actual crop evapotranspiration (ET) or consumptive water use over large-area holds the key for better water management and regional drought preparedness. In the present study, the remote sensing based energy balance (RS-EB) approach has been used to estimate the spatial variation of instantaneous evapotranspiration (ETinst). The (ETinst) is evaluated as the residual value after computing net radiation, soil heat flux and sensible heat flux using multispectral remote sensing data from Landsat-8 for the post-monsoon and summer season of 2016–2017 over the parts of North India. Cloud free temporal remote sensing data of October 12, 2016; November, 13, 2016; March 05, 2017 and May 24, 2017 were used as primary data for this study. The study showed that normalized difference vegetation index and LST are closely related and serve as a proxy for qualitative representation of (ETinst)

Perception towards Livestock Breeding Service Delivery by Dairy Cooperatives

ABSTRACT A study was conducted in Western Maharashtra region to know the perception of farmers towards livestock breeding services delivered by Gokul Dair

TRAINING, EDUCATION, RESEARCH AND CAPACITY BUILDING NEEDS AND FUTURE REQUIREMENTS IN APPLICATIONS OF GEOSPATIAL TECHNOLOGY FOR WATER RESOURCES MANAGEMENT

In India, water resources are managed at different levels, i.e. at central level by Ministry of Water Resources, River Development & Ganga Rejuvenation, Central Water Commission and Central Ground Water Board, at states level by state water resources departments, and at local level by Municipal Corporation and Panchayati Raj Institutions (PRIs). As per India’s national water policy of year 2012 focuses on adaption to climate change, enhancement of water availability, water demand management by efficient water use practices, management of floods and droughts, water supply and sanitation, trans-boundary rivers, conservation of water bodies and infrastructure, and finally research and training needs for each theme. Geospatial technology has unique role in all aforementioned themes. Therefore, research and training in use of Geospatial Technology (GST) in water sector is needed for each theme at different levels of water administration and water utilisation. The current paper discusses the existing framework and content of capacity building in water sector and geospatial technology in use at various government organizations and institutes. The major gap areas and future capacity building requirements are also highlighted, along with duration and timelines of training/capacity building programs. The use of distance learning/educations tools, social media, and e-learning are also highlighted in promoting use of GST in water sector. The emerging technological trends such as, new remote sensing sensors for measuring water cycle components, ground sensors based field instruments, cloud based data integration and computational models, webGIS based water information portals and training needs of new technologies are also emphasised

IMPORTANCE OF INCORPORATION OF GEOSPATIAL TECHNOLOGY APPLICATIONS IN WATER RESOURCES AT GRADUATE AND POST-GRADUATE COURSES OF CIVIL ENGINEERING

Water is a very crucial element to sustain life on earth. The availability of water varies both spatially and temporally. India being a water stress country, the per capita availability of water is reducing with time. It is predicted that by 2050 around 54% of the country will be water scarce. The changing climate along with the ever-increasing population is putting additional stress on water availability. The science of water, its availability and distribution on earth and its atmosphere, is generally regarded as hydrology. The important aspects of hydrology and hydraulic or more broadly water resources are taught as the subject or optional subjects the branch of Civil Engineering at almost all engineering institutes/colleges at the undergraduate level. It is also one of the specializations for post-graduate level studies. It is, by now, well proven that the geospatial technology play crucial role in water resources assessment, planning and management. However, the young minds (graduate and post-graduate students) are just being trained for typical hydrology using traditional means and approaches. The advancement and potential of geospatial technology has drawn the attention of academician, and it has been started as a subject mostly at the post-graduate courses. Recently, some of the institutions have started courses on geo-informatics at the graduate level. However, the hydrology and geospatial technology are generally taught as two separate subjects under different course at different levels mostly under the broad subject of Civil Engineering. The present paper emphasis on needs and ways of updating Civil Engineering course curriculum by focusing on incorporation of applications of geospatial technology in hydrology as regular subject

EXPERIMENTAL FLOOD EARLY WARNING SYSTEM IN PARTS OF BEAS BASIN USING INTEGRATION OF WEATHER FORECASTING, HYDROLOGICAL AND HYDRODYNAMIC MODELS

The flood early warning for any country is very important due to possible saving of human life, minimizing economic losses and devising mitigation strategies. The present work highlights the experimental flood early warning study in parts of Beas Basin, India for the monsoon season of 2015. The entire flood early warning was done in three parts. In first part, rainfall forecast for every three days in double nested Weather Research and Forecasting (WRF) domain (9 km for outer domain and 3 km for inner domain) was done for North Western Himalaya NWH using National Centres for Environmental Prediction (NCEP) Global Forecasting System (GFS) 0.25 degree data as initialization state. Rainfall forecast was validated using Indian Meteorological Department (IMD) data, the simulation accuracy of WRF in rainfall prediction above 100 mm is about 60%. Rainfall induced flood event of August 05–08, 2015 in Sone River (tributary of Beas River) Basin, near Dharampur, Mandi district of Himachal Pradesh caused very high damages. This event was picked three days in advance by WRF model based rainfall forecast. In second part, mean rainfall at sub-basin scale for hydrological model (HEC-HMS) was estimated from forecasted rainfall at every three hours in netcdf format using python script and flood hydrographs were generated. In third part, flood inundation map was generated using Hydrodynamic (HD) model (MIKE 11) with flood hydrographs as boundary condition to see the probable areas of inundation

INTERCOMPARISON OF DIFFERENT RAINFALL PRODUCTS AND VALIDATION OF WRF MODELLED RAINFALL ESTIMATION IN N-W HIMALAYA DURING MONSOON PERIOD

Extreme precipitation events are responsible for major floods in any part of the world. In recent years, simulations and projection of weather conditions to future, with Numerical Weather Prediction (NWP) models like Weather Research and Forecast (WRF), has become an imperative component of research in the field of atmospheric science and hydrology. The validation of modelled forecast is thus have become matter of paramount importance in case of forecasting. This study delivers an all-inclusive assessment of 5 high spatial resolution gridded precipitation products including satellite data products and also climate reanalysis product as compared to WRF precipitation product. The study was performed in river basins of North Western Himalaya (NWH) in India. Performance of WRF model is evaluated by comparing with observational gridded (0.25° × 0.25°) precipitation data from Indian Meteorological Department (IMD). Other products include TRMM Multi Satellite Precipitation Analysis (TMPA) 3B42-v7 product (0.25° × 0.25°) and Global Precipitation Measurement (GPM) product (0.1° × 0.1°). Moreover, climate reanalysis rainfall product from ERA Interim is also used. Bias, Mean Absolute Error, Root Mean Square Error, False Alarm Ratio (FAR), Probability of False Detection (POFD), and Probability of Detection (POD) were calculated with particular rainfall thresholds. TRMM and GPM products were found to be sufficiently close to the observations. All products showed better performance in the low altitude areas i.e. in planes of Upper Ganga and Yamuna basin and Indus basin, and increase in error as topographical variation increases. This study can be used for identifying suitability of WRF forecast data and assessing performance of other rainfall datasets as well

SEASONAL COMPARISON OF ERA-INTERIM PRECIPITATION DATASET FOR ENTIRE INDIAN REGION

Era-Interim (ECMWF Re- analysis) is a global reanalysis atmospheric product which is being continuously updated in real time since 1979. It is also termed as third generation reanalysis product. The Era–Interim gives meteorological products like precipitation, temperature, etc. In the present work, 3-hourly Era–Interim product for the entire India is compared with gridded data provided by IMD for period 1979–2013 and APHRODITE data for period 1979–2007, respectively. The comparison is done on seasonal basis and the seasons are taken based on the pattern of rainfall, hence, the four seasons selected are DJF (December, January & February), MAM (March, April & May), JJAS (June, July, August & September) and ON (October & November). In the methodology the Era-Interim 3-hourly products are converted into the daily products and then it is used to form seasonal images for each year. All the images are then taken to form four images as outcome for the entire study period which represents the average rainfall (mm/day) for the entire region. This is being done for the IMD and for the APHRODITE Data. All the four images are then taken for the comparison with the reference images of the IMD 0.5º × 0.5º gridded rainfall data and with the APHRODITE 0.5º × 0.5º gridded rainfall data. The correlation coefficient and the RMSE for each season is calculated. The mean value is compared with the mean of IMD and APHRODITE rainfall products, respectively and a bias in mean is also calculated along with the scatter plots of Era-Interim with the reference datasets. The Era – Interim data came out with suitable comparative parameters with high correlation coefficient and low RMSE value in certain regions and in specific seasons. Scatter plots have also given good correlation in all the seasons. Bias maps have also shown very less bias in specific seasons for certain regions. The suitability maps prepared for the study region also shows that most of the region lies in most suitable range and very less in unsuitable range