<p><strong>Abstract.</strong> 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 (ET<sub>inst</sub>). The (ET<sub>inst</sub>) 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 (ET<sub>inst</sub>).</p>
Accurate demarcation of river basin boundaries is an important input for any programme connected with watershed management. In the present study, the boundary of the Varuna river basin is automatically derived using coarse-and medium-resolution digital elevation models (DEMs) of SRTM-30 m, ASTER-30 m, Cartosat-30 m, ALOS Palsar-12.5 m and Cartosat-10 m as well as manually through on-screen digitisation from a very high-resolution 1 m × 1 m remote sensing data available as Google Earth image. The study demonstrated the efficacy of on-screen digitisation from high-resolution Google Earth image supported by detailed field observations in the precision mapping of the place of origin of the Varuna River, its stream network and basin boundary when compared to the maps generated through automatic methods using DEMs of various resolutions. The Varuna river system takes its headwaters from the areas surrounding Umran and Dain 'tals' (shallow, large depressions/basins) but not from the west of Mau Aima town as has been previously reported.
Evapotranspiration and water availability are driven by changing climate and land cover parameters. In the present study, climatological records and land cover data were analysed simultaneously to accomplish the spatial distributions of climate change effects on water resources in Varanasi district, north India. Humidity–aridity was assessed by Lang's rain factor and De Martonne's aridity index, based on mean monthly rainfall and air temperature from seven meteorological stations. The climate change effect on water resources was evaluated using a 5 × 5 matrix that includes water availability and the aridity index by considering two time periods: 1941–1970 (1950s) and 1971–2000 (1980s). The methodology is based on seasonal crop evapotranspiration (ETc) (initial, mid‐season, end season and cold season) and annual water availability calculations. The high values (≤ 1,045 mm) of ETc were identified during the mid‐season stage. Water availability indicates decreases in the maximums from 718 to 636 mm during the two analysed periods, with a negative impact at the spatial scale. Lang's rain factor (< 40) indicates an arid climate in the northwest, west, east and central parts of the district and a humid climate (Lang's rain factor > 40) in the south. De Martonne's aridity index indicates rapid aridization from south to north (28.3 in the 1950s and 25.6 in the 1980s). The high and very high climate effects on water resources in Varanasi district were found mainly in the crop lands, while in the urban areas the climate effect is low. The much affected area by climate change and land cover was depicted during the recent period (1980s). This statement was proved also by the Mann and Kendall test, which indicates a negative trend for annual precipitation at all stations (for the period 1941–2000), while the mean annual temperature had a positive trend for four stations. These findings suggest that climate change had a negative effect on water resources during the last 60 years in the study area.
Understanding ecosystem functional behaviour and its response to climate change necessitates a detailed understanding of vegetation phenology. The present study investigates the effect of an elevational gradient, temperature, and precipitation on the start of the season (SOS) and end of the season (EOS), in major forest types of the Kumaon region of the western Himalaya. The analysis made use of the Normalised Difference Vegetation Index (NDVI) time series that was observed by the optical datasets between the years 2001 and 2019. The relationship between vegetation growth stages (phenophases) and climatic variables was investigated as an interannual variation, variation along the elevation, and variation with latitude. The SOS indicates a delayed trend along the elevational gradient (EG) till mid-latitude and shows an advancing pattern thereafter. The highest rate of change for the SOS and EOS is 3.3 and 2.9 days per year in grassland (GL). The lowest rate of temporal change for SOS is 0.9 days per year in mixed forests and for EOS it is 1.2 days per year in evergreen needle-leaf forests (ENF). Similarly, the highest rate of change in SOS along the elevation gradient is 2.4 days/100 m in evergreen broadleaf forest (EBF) and the lowest is −0.7 days/100 m in savanna, and for EOS, the highest rate of change is 2.2 days/100 m in EBF and lowest is −0.9 days/100 m in GL. Winter warming and low winter precipitation push EOS days further. In the present study area, due to winter warming and summer dryness, despite a warming trend in springseason or springtime, onset of the vegetation growth cycle shows a delayed trend across the vegetation types. As vegetation phenology responds differently over heterogeneous mountain landscapes to climate change, a detailed local-level observational insight could improve our understanding of climate change mitigation and adaptation policies.
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