Browsing by Author "KISHORE KUMAR, G."
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ThesisItem Open Access “DETERMINATION OF WATER FOOT PRINTS FOR IRRIGATED AND RAINFED AREAS OF KINNERASANI BASIN(Professor Jayashankar Telanagana State Agricultural University, 2016) KISHORE KUMAR, G.; MANOJ KUMAR, G.Water use in agriculture (82.8%) is rated as high among other water users in India and there is a need to increase agricultural water productivity in view of its scarcity and demand from other sectors of water use. Water foot print modeling enables to pinpoint the waterrelated impacts, vulnerabilities across agricultural management systems, regions, and time and action that need to be taken for improving water productivity. Hence, the present study has been taken up to estimate the green, blue and grey water footprint of crops in a spatially explicit way in Kinnerasani basin to know about the water consumption in agricultural sector. Since, agriculture is the main occupation of the area and frequent crop failure due to lack of water availability is one of the major causes of distress among the farmer community. Kinnerasani basin comprises Gundala, Palwancha, Tekulapalle and Burgampadumandals of Khammam district. The normal rainfall of the area is 970mm. Crop land is occupying 25% of the area of Kinnerasani basin. The water foot prints for irrigated and rainfed systems of Kinnerasani basin were estimated for a period of 11 years (2003-2013). In addition to that, the water foot prints of crops for dry year (2009), wet year (2010) and the recent year (2013) were also estimated in order to know the impact of rainfall on water foot print of crops. The computations of crop evapotranspiration and yield, required for the estimation of the green and blue water footprint in crop production have been carried out for the case of crop growth under non-optimal conditions using CROPWAT and AquaCrop models. In the case of rain-fed crop production, blue crop water use is zero and green crop water use (m3 /ha) is calculated by summing up the daily values of ETa (mm/day) over the length of the growing period. The green and blue water footprints of primary crops (m3 /ton) are calculated by dividing the total volume of green and blue water use (m3 /yr), respectively, by the quantity of the production (ton/yr). The grey component of the water footprint (m3 /ton) is calculated by multiplying the fraction of nitrogen that leaches or runs off by the nitrogen application rate (kg/ha) and dividing this by the difference between the maximum acceptable concentration of nitrogen (kg/m3) and the natural concentration of nitrogen in the receiving water body (kg/m3 ) and by the actual crop yield (ton/ha). Crop evapotranspiration and effective rainfall values of different crops grown in Kinnersani basin have shown significant regional variation for different years under study. The blue water use (m3/ha) and the greenwater use (m3/ha) have also exhibited spatial variation for the crops grown in Kinnerasani basin. The average water footprint per ton of primary crop differs significantly among crops and across production regions. The blue water foot print was high for chillies (1328.67 m3/ton) followed by mango (830.9 m3/ton), vegetables (340.23 m3/ton) and Paddy (263.95 m3/ton) for the period 2003 to 2013. The blue water foot print is more in Burgampadumandal compared to other mandals in Kinnerasani basin. Green water foot print was more for Tekulapalli for paddy, cotton, Greengram and chillies. Whereas it is more in Gundala for maize and mango. Grey water foot print is more for green gram followed by paddy and is high in Burgampadu mandal. The total green-water footprint of crop production for the basin is dominated by 12 crops for the period 2003 to 2013. Cotton contributed almost 20% to the total green-water footprint, followed by spice crop with a share of some 17%, paddy with 12%, and Green gram and red gram, both contributing about 18%. Mango and Nimma contributed about 8.5%. Vegetables, groundnut and tobacco contributed 5% each. In the case of the blue-water footprint 7 crops - mango (36%), Chillies (31%), paddy (10%), vegetables (9%), groundnut (7%), Nimma (4%) and Tomato (2%). The grey-water footprint in crop production is also largely due to 12 crops: paddy (24%), green gram (22%), cotton (21%), red gram (10%), maize, chillies and groundnut contributed 4% each. The total water footprint of crops grown in Kinnerasani basin is 169456771 m3/yr over the period 2003-2013. The largest water footprint component is the green water, with 89% of the total water footprint of consumption. The blue and grey water footprints of crops of kinnerasani basin are 10% and 1% of the total respectively. The largest water footprint component is the green water, with 86.76% of the total water footprint of consumption. The blue- and grey-water footprints of crops of Kinnerasani basin are 12.16% and 1.07% of the total during the year 2013. The total water footprints of many irrigated crops are actually less than that of rainfed crops. This is because, on an average, irrigated yields are larger than rain-fed yields. An increase in green water use (ETgreen) might actually result in a lowered green water footprint if there are sufficient yield increases accompanying the increased ET. Hence, in order to reduce water foot print, no tillage can be adopted as there may be an increase in infiltration of rainfall and a reduction in non beneficial soil evaporation.ThesisItem Open Access IMPACT OF CLIMATE CHANGE ON CROP WATER PRODUCTIVITY IN GODAVARI EASTERN DELTA(guntur, 2022-08-18) KISHORE KUMAR, G.; RAGHU BABU, M.Climate change has been considered to have calamitous effects on agriculture and global fresh water. Due to the alteration in climate, crop productivity is being affected adversely resulting in food and livelihood security issues. In view of climate changes, there is a need to increase agricultural water productivity for better management in view of less resources and demand. Proper water management is the only option that ensures a squeezed gap between the demand and supply. For proper planning and efficient utilization of the land and water resources it is necessary to understand the hydrological cycle and estimate the hydrological parameters. Rainfall is the major component of the hydrologic cycle and this is the primary source of runoff. Worldwide many attempts have been made to model and predict rainfall behavior using various empirical, statistical, numerical and deterministic techniques. They are still in research stage and needs more focused empirical approaches to estimate and predict rainfall accurately. This study investigated the Impact of Climate change on Crop Water Productivity using CROPWAT 8.0, AquaCrop, RS&GIS and statistical tools used for climate data. Estimation of mean rainfall over Godavari eastern delta of Andhra pradesh and mandals in the delta has been done using different deterministic methods. Weathercock and Mann-Kendall software were used to compute Rainfall variability and trend analysis on time series data for 30 years period from 1987 to 2016 collected at local stations and departments. Godavari eastern delta comprises of around 15 mandals and the same being considered for the present study. The normal rainfall of the area is 1197 mm. Crop land occupying 70% of the area of Godavari eastern delta. Different thematic maps for the study area have been developed for water resources assessment and for the runoff estimation using SCS-CN. Runoff generated through rainfall with the help of RS&GIS softwares, it is very important in various activities of water management. Results indicated that over 30 years of rainfall-runoff 1996 year showing highest 34.79 % runoff following 2006 with 34.13%. NDVI was derived to observe the change in land productivity for 2011-12 and 2016-17 years using RS&GIS techniques. Vegetation has a distinctive spectral signature that is characterized by low reflectance in visible region of solar optical spectrum as xvi well as high reflectance in infrared (IR) spectrums. The combination of these two spectral regions allows classification of vegetation. In this normalized difference vegetation index (NDVI), Where NIR is the reflectance in near infrared band and R is the reflectance in red band of satellite data. NDVI indicates the vigor of vegetation. Higher NDVI indicates higher amount of green vegetation on ground. NDVI of non-vegetation classes are generally lower than vegetation classes. Vegetation was influenced by time due to land usable changes. There was nearly 11% of change in kharif and whereas it was 30% change in rabi season. Estimation of crop water productivity of rice for prime rice-producing region using CROPWAT and AquaCrop model using soil, climate, crop data and management details. With the help of relatively few conservative crop parameters, AquaCrop simulates final crop yield. The results (WP) for the different years and the different mandals in the study area were varied from 0.75 kg/m3 in 1987-88 to 1.17 kg/m3 in 2016-17 for rabi season. In kharif water productivity is varied from 0.46 kg/m3 in 1990-91 to 0.86 kg/m3 in 2016-17. The average water productivity for 30 years in the study area is 0.68 kg/m3 in kharif and 0.98 kg/m3 in rabi season. WP is higher for the rabi (dry) season than for the kharif (monsoon) season. This is may be due to poor irrigation management practices such as inundation, waterlogging and less sunlight due to cloudiness in crop growth stage. Crop water productivity is highly depending upon weather; therefore, future climate change could affect productivity. Conclusively, CROPWAT 8.0 and AquaCrop models may be used to estimate crop water productivity, water requirements for different cultivars in different climatic conditions to ascertain their minimum water requirements for maximum yields. Thus, further study in Crop water productivity should be carried it out. Key words: Water Productivity, Rainfall-Runoff, CROPWAT, AquaCrop, NDVI, RS&GIS