Ajanta Goswami

Accuracy assessment of MODIS, NOAA and IRS data in snow cover mapping under Himalayan conditions

Snow cover information is an essential parameter for a wide variety of scientific studies and management applications, especially in snowmelt runoff modelling. Until now NOAA and IRS data were widely and effectively used for snow‐covered area (SCA) estimation in several Himalayan basins. The suit of snow cover products produced from MODIS data had not previously been used in SCA estimation and snowmelt runoff modelling in any Himalayan basin. The present study was conducted with the aim of assessing the accuracy of MODIS, NOAA and IRS data in snow cover mapping under Himalayan conditions. The total SCA was estimated using these three datasets for 15 dates spread over 4 years. The results were compared with ground‐based estimation of snow cover. A good agreement was observed between satellite‐based estimation and ground‐based estimation. The influence of aspect in SCA estimation was analysed for the three satellite datasets and it was observed that MODIS produced better results. Snow mapping accuracy with respect to elevation was tested and it was observed that at higher elevation MODIS sensed more snow and proved better at mapping snow under mountain shadow conditions. At lower elevation, IRS proved better in mapping patchy snow cover due to higher spatial resolution. The temporal resolution of MODIS and NOAA data is better than IRS data, which means that the chances of getting cloud‐free scenes is higher. In addition, MODIS has an automated snow‐mapping algorithm, which reduces the time and errors incorporated during processing satellite data manually. Considering all these factors, it was concluded that MODIS data could be effectively used for SCA estimation under Himalayan conditions, which is a vital parameter for snowmelt runoff estimation.

Identification of drought-vulnerable areas using NOAA AVHRR data

Drought is a recurring phenomenon in many parts of India, bringing significant water shortages, economic losses and adverse social consequences. The western regions of India (Rajasthan and Gujarat provinces) have suffered with severe droughts several times in the past. In this study meteorological and satellite data were used for monitoring drought in the southern part of Rajasthan. Monthly rainfall data from six stations were used to derive the Standardized Precipitation Index (SPI). The Advanced Very High Resolution Radiometer (AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) series of satellite was used for calculating brightness temperature (BT), the Normalized Difference Vegetative Index (NDVI) and the Water Supplying Vegetation Index (WSVI). BT was converted to the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI), which are useful indices for the estimation of vegetation health and drought monitoring. The analysis was carried out for a period of four years (2002–2005) and from the SPI analysis it was observed that 2002 was a drought year. On the basis of the satellite‐based indices, the study area was divided into categories of extreme, severe, moderate and slight drought and normal condition. We found that in 2002 all of the area under study was affected by drought with greater intensity, mostly classed as extreme and severe drought conditions. An analysis was carried out of the study area divided into four zones on the basis of rainfall distribution, soil characteristics, cropping patterns and other physical characteristics. This analysis revealed that zone 1 was the most drought‐prone area in all four years; zone 4 was the next area most affected by severe drought, followed by zones 2 and 3, which were less affected by drought conditions.

Snowmelt runoff modelling in a Himalayan basin with the aid of satellite data

The Himalayan basins have runoff contributions from rainfall as well as from snow and ice. In the present study a snowmelt runoff model (SRM) was applied to estimate the streamflow for Satluj basin located in the western Himalayan region. This model uses the direct input of remotely sensed snow-cover area (SCA) data for calibration and simulation. The SCA in the basin was determined using remote sensing data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectrometer (MODIS) onboard the Terra-Aqua satellite. In addition, daily precipitation and temperature data, as well as a Shuttle Radar Topography Mission digital elevation model (SRTM-DEM), were used to prepare the area elevation curves. The model was calibrated using the dataset for a period of 3 years (1996–1997, 1997–1998 and 1998–1999) and model parameters for streamflow routing were optimized. Using the optimized parameters, streamflow simulations were made for four years of data (i.e. 2000–2003 and 2004–2005). The accuracy of the streamflow verification was determined using different criteria such as shape of the outflow hydrograph, efficiency and difference in volume. The seasonal temperature lapse rates (TLRs) estimated from land surface temperature (LST) maps were used in the model and considerable improvement in simulation was observed. It was found that the overall efficiency increased when using varying TLRs.

Glacier changes using satellite data and effect of climate in Tirungkhad basin located in western Himalaya

Glaciers are widely recognized as key indicators of climate change, and melt water obtained from them is an important source of fresh water and for hydropower generation. Regular monitoring of a large number of Himalayan glaciers is important for improving our knowledge of glacier response to climate change. In the present study, Survey of India topographical maps (1966) and Landsat datasets as ETM+ (2000, 2006) and TM (2011) have been used to study glacier fluctuations in Tirungkhad basin. A deglaciation of 26.1% (29.1 km2) in terms of area from 1966 to 2011 was observed. Lower altitude small glaciers (area < 1 km2) lost more ice (34%), while glaciers with an area <10 km2 lost less (20%). The percentage of change in glacier length was 26% (31.9 km) from 1966 to 2011. The south-facing glaciers showed high percentages of loss. From 2000 to 2011, debris cover has increased by 1.34%. The analysis of the trend in meteorological data collected from Kalpa and Purbani stations was carried out by Mann Kendall non-parametric method. During the last two decades, the mean annual temperature (Tmax and Tmin) has increased significantly, accompanied with a fall in snow water equivalent (SWE) and rainfall. The increasing trend in temperature and decreasing trend in SWE were significant at 95% confidence level. This observation shows that the warming of the climate is probably one of the major reasons for the glacier change in the basin.

Decline in snowfall in response to temperature in Satluj basin, western Himalaya

Snow is an essential resource present in the Himalaya. Therefore, monitoring of the snowfall changes over a time period is important for hydrological and climatological purposes. In this study, variability of snowfall from 1976–2008 were analysed and compared with variability in temperature (Tmax and Tmin) from 1984–2008 using simple linear regression analysis and Mann–Kendall test in the Satluj Basin. The annual, seasonal, and monthly analyses of average values of snowfall and temperature (Tmax and Tmin) have been carried out. The study also consists an analysis of average values of annual snowfall and temperature over six elevation zones (<1500 to >4000 m amsl). During the study, it was observed that the snowfall exhibited declining trends in the basin. The snowfall trends are more sensitive to the climate change below an elevation of 4000 m amsl. Over the elevation zones of 3000–3500 and 4000–4500 m amsl, positive trends of mean annual values of snowfall were observed that may be due to higher precipitation as snowfall at these higher elevations. Although, both negative and positive snowfall trends were statistically insignificant, however, if this decreasing trend in snowfall continues, it may result in significant however, changes in future. Furthermore, the Tmin is also increasing with statistically significant positive trend at 95% confidence level for November, winter season, annually as well as for the elevation zones of 2500–3000, 3000–3500, and 3500–4000 m amsl. There are dominantly increasing trends in Tmax with negative trends for February, June–September, monsoon season, and for elevation zone <1500 m amls. It is important to state that in the present basin, during the months of winter season, most of the precipitation is produced as snowfall by the westerly weather disturbances. Thus, the declining nature in snowfall is concurrent with the positive trends in temperature particularly Tmin, therefore, reflecting that the positive trends in Tmin may be the dominant factor besides Tmax in controlling the snowfall trends. The snowfall data were also compared with SCA and this showed a highly positive correlation of 0.95% which validates the utilisation of time series of snowfall for the trend analysis.

Determination of land surface temperature and its lapse rate in the Satluj River basin using NOAA data

Temperature lapse rate (TLR), an essential parameter for snowmelt runoff analysis, was determined for the Satluj River basin in the Western Himalayas. National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) data sets were used to determine the land surface temperature (LST) of the region using the split‐window algorithm proposed by Coll and Caselles (Journal of Geophysical Research, 1997, 102, pp. 16697–16713). The LST was correlated with the elevation values obtained from a US Geological Survey digital elevation model (USGS‐DEM) of the same area and the trend showed an inverse relationship between LST and elevation. The TLRs for the study area on 2 February, 1 March, 26 March, 16 October, 1 November and 20 November 2004 were in the range 0.6–0.74°C/100 m. The results obtained were compared with lapse rates determined using Moderate Resolution Imaging Spectroradiometer (MODIS) LST maps. TLR determination in the past was based on air temperature data available from meteorological stations that are sparsely located in rugged terrain such as the Himalayas. As these measurements were point data and had been measured manually, they may have led to erroneous results. Satellite data, however, provide continuous and potentially unbiased recording provided an accurate radiometric calibration and atmospheric correction can be achieved. A previous TLR calculation using air temperature from meteorological stations for the western Himalayan region was found to be 0.65°C/100 m. Air temperature and LST from NOAA‐AVHRR and MODIS‐Terra data were found to be in good agreement. This type of study will be useful for snowmelt runoff modelling studies for the Himalayan region.

Accuracy assessment and trend analysis of MODIS-derived data on snow-covered areas in the Sutlej basin, Western Himalayas

Snow is important for hydrological studies and is a variable very sensitive to climatic variations. In the present study, the variability of snow-covered areas (SCAs) obtained through Moderate Resolution Imaging Spectroradiometer (MODIS) snow data products was analysed using the Mann–Kendall test and Sen’s slope estimator in the Sutlej basin, Western Himalayas, India. However, due to the limitations of long time-series snow cover data, the study has been carried out for a time period from 2000 to 2009. Before trend analysis, the estimated SCA was validated using the ground-based snowfall data. A simple linear regression test was applied to analyse the relationship between the variation in SCA and snowfall. The relationship between the mean annual snowfall and SCA indicated a highly significant correlation (R2 = 0.95). In order to have a better insight into the relationship, the regression test was also carried out for six elevation zones. The coefficient of determination (R2) varied from 0.78 at the 1500–2000 m asl zone to 0.96 at the 3000–3500 m asl zone. The trend analysis indicated reduction in SCA with significant negative behaviour for annual, winter, and post-monsoon seasons and for November and December months. The negative trend was observed for an elevation of <2500 m asl in the basin. Moreover, during the same period (2000–2009), the temperature (Tmax and Tmin) increased while there was a decrease in snowfall. The trend analysis of temperature from 1984 to 2009 revealed positive trends with significant trend in Tmin as determined by using the Mann–Kendall statistical test. The reduction in SCA was, therefore, attributed to the increasing trends in temperature, particularly Tmin, associated with reduction in snowfall. These SCA variations have significant implications for water resources managers in the area as some of these observed trends, if continue, may result in changes in hydrological/ecological balance of the Sutlej basin.