Biomedical subjects

V Krishna Prasad

Publications and source records attributed to V Krishna Prasad.

3 recordsLinked to original sources

PubMed2005

Climatic controls of vegetation vigor in four contrasting forest types of India--evaluation from National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer datasets (1990-2000).

Ten-day advanced very high resolution radiometer images from 1990 to 2000 were used to examine spatial patterns in the normalized difference vegetation index (NDVI) and their relationships with climatic variables for four contrasting forest types in India. The NDVI signal has been extracted from homogeneous vegetation patches and has been found to be distinct for deciduous and evergreen forest types, although the mixed-deciduous signal was close to the deciduous ones. To examine the decadal response of the satellite-measured vegetation phenology to climate variability, seven different NDVI metrics were calculated using the 11-year NDVI data. Results suggested strong spatial variability in forest NDVI metrics. Among the forest types studied, wet evergreen forests of north-east India had highest mean NDVI (0.692) followed by evergreen forests of the Western Ghats (0.529), mixed deciduous forests (0.519) and finally dry deciduous forests (0.421). The sum of NDVI (SNDVI) and the time-integrated NDVI followed a similar pattern, although the values for mixed deciduous forests were closer to those for evergreen forests of the Western Ghats. Dry deciduous forests had higher values of inter-annual range (RNDVI) and low mean NDVI, also coinciding with a high SD and thus a high coefficient of variation (CV) in NDVI (CVNDVI). SNDVI has been found to be high for wet evergreen forests of north-east India, followed by evergreen forests of the Western Ghats, mixed deciduous forests and dry deciduous forests. Further, the maximum NDVI values of wet evergreen forests of north-east India (0.624) coincided with relatively high annual total precipitation (2,238.9 mm). The time lags had a strong influence in the correlation coefficients between annual total rainfall and NDVI. The correlation coefficients were found to be comparatively high (R2=0.635) for dry deciduous forests than for evergreen forests and mixed deciduous forests, when the precipitation data with a lag of 30 days was correlated against NDVI. Using multiple regression approach models were developed for individual forest types using 16 different climatic indices. A high proportion of the temporal variance (>90%) has been accounted for by three of the precipitation parameters (maximum precipitation, precipitation of the wettest quarter and driest quarter) and two of the temperature parameters (annual mean temperature and temperature of the coldest quarter) for mixed deciduous forests. Similarly, in the case of deciduous forests, four precipitation parameters and three temperature parameters explained nearly 83.6% of the variance. These results suggest differences in the relationship between NDVI and climatic variables based upon the time of growing season, time interval and climatic indices over which they were summed. These results have implications for forest cover mapping and monitoring in tropical regions of India.

Climate↗

PubMed2005

Exploring the relationship between hydrologic parameters and nutrient loads using digital elevation model and GIS - a case study from Sugarcreek headwaters, Ohio, U.S.A.

Ohio is typical among the Midwestern and Eastern United States with high levels of water pollutants, the main sources being from agriculture. In this study, we used a digital elevation model in conjunction with hydrological indices to determine the role of landscape complexity affecting the spatial and temporal variation in pollutant levels, in one of the most impaired headwater streams in Ohio. More than eighty five percent of the study area is dominated by agriculture. Spatial distribution of slope (S), altitude and wetness index along with other watershed parameters such as flow direction, flow accumulation, stream networks, flow stream orders and erosion index were used within a Geographic Information Systems framework to quantify variation in nitrate and phosphate loads to headwater streams. Stream monitoring data for nutrient loads were used to correlate the observed spatial and temporal patterns with hydrological parameters using multiple linear regressions. Results from the wetness index calculated from a digital elevation model suggested a range of 0.10-16.39, with more than 35% having values less than 4.0. A Revised Universal Soil Loss Equation (RUSLE) predicted soil loss in the range of 0.01-4.0 t/ha/yr. Nitrate nitrogen levels in the study area paralleled precipitation patterns over time, with higher nitrate levels corresponding to high precipitation. Atmospheric deposition through precipitation could explain approximately 35% of total nitrate levels observed in streams. Among the different topographic variables and hydrological indices, results from the step-wise multiple regression suggested the following best predictors, (1) elevation range and upstream flow length for nitrate, (2) flow direction and upstream flow length for ammonia-nitrogen and slope, and (3) elevation range for phosphate levels. Differences in the landscape models observed for nitrate, phosphate and ammonia-nitrogen in the surface waters were attributed partly to differences in the chemical activity and source strengths of the different forms of these nutrients through agricultural management practices. The results identify geomorphologic and landscape characteristics that influence pollutant levels in the study area.

Ammonia↗

PubMed2004

Regional inventory of soil surface nitrogen balances in Indian agriculture (2000-2001).

Nitrogen regulates several ecological and biogeochemical processes and excess reactive nitrogen in the environment can lead to pollution problems, including the deterioration of air quality, disruption of forest processes, acidification of lakes and streams, and degradation of coastal waters. Much of the excess nitrogen inputs are related to food and energy production. An important step to understanding the sources of nitrogen and ultimately defining solutions to excess nitrogen is to describe the geographic distribution of agricultural nitrogen contributions from different regions. In this study, soil surface nitrogen loads were quantified for different states of India for the period 2000-2001. Nearly 35.4 Tg of nitrogen has been estimated as inputs from different sources, with output nitrogen from harvested crops of about 21.20 Tg. The soil surface nitrogen balance, estimated as inputs minus outputs, is found to be about 14.4 Tg surplus from the agricultural land of India. Livestock manure constituted a major percentage of total inputs (44.06%), followed by inorganic fertilizer (32.48%), atmospheric deposition (11.86%) and nitrogen fixation (11.58%). Nitrogen balance varied from deficit to surplus for different states. The highest nitrogen surplus was found in Uttar Pradesh (2.50 Tg) followed by Madhya Pradesh (1.83 Tg), Andhra Pradesh (1.79 Tg), etc. A negative nitrogen balance was found in Orissa (-0.01 Tg), Andaman Nicobar Islands (-0.32 Tg) and for some of the northeastern states. Major fertilizer consumption states were found to be Tamilnadu (204 kg/ha), Haryana (132 kg/ha), Punjab (148 kg/ha), followed by others. Similarly, nitrogen inputs from total livestock excretions were found to be high for Kerala (616 kg/ha), Jammu and Kashmir (389 kg/ha), Tamil Nadu (338 kg/ha), etc. The average nitrogen surplus of about 54 kg/ha observed for the agricultural land of the entire country of India is comparatively higher than the average surplus of about 31 kg/ha reported for European countries. These results, obtained from nutrient mass balance calculations, will be useful to formulate nutrient management plans relating to fertilizer usage, livestock management and for adopting some best management strategies at a state level in India.

Agriculture↗