Gangotri glacier dynamics from multi-sensor SAR and optical data

The present study has analyzed dynamics of Gangotri glacier using multiple remote sensing (RS) datasets and ground based observations. Interferometric Synthetic Aperture Radar (InSAR) data pairs from European Remote Sensing satellite (ERS 1/2) tandem pair for spring of 1996, Sentinel-1 SAR pairs and Japanese's Advance Land Observation System (ALOS) PALSAR-2 SAR data for Spring of 2015 were used to derive glacier-surface velocity at seasonal time scale using Differential InSAR (DInSAR) techniques. Bi-static TanDEM-X (Experimental) data was used for the 1st time to estimate glacier surface elevation changes for a period of 22, 44, 88 days during summer of 2012 using InSAR techniques in this study. Annual glacier velocity was also estimated using temporal panchromatic data of LANDSAT-5 (30 m), LANDSAT-7/8 (15 m), Sentinel-2 (10 m) and Indian Remote Sensing Satellite IRS-1C/1D panchromatic (5 m) data during 1998–2019 with feature tracking approach. This study has estimated glacier surface velocity and surface elevation changes for the major parts of Gangotri glacier and its tributary glaciers using medium to high resolution optical and SAR datasets, at annual and seasonal time scale, which is an improvement over earlier studies, wherein snout based glacier recession or only main glacier velocities were reported. The velocity and slope were used to assess glacier-ice thickness distribution using Glabtop-2, slope dependent and laminar flow based methods over the Gangotri group of glaciers. The estimated ice thickness was estimated in the range of 58–550 m for the complete glacier while few small areas in middle &amp; upper regions carry higher thickness of about 607 m. The estimated glacier-ice thickness was found in the range of 58–67 m at the snout region. The estimation was validated using 2014 field measurements from Terrestrial Laser Scanner (TLS) for the first time and correlation was found to be 0.799 at snout of the glacier.</p

High-resolution vegetation drought monitoring in India

Water resources management can benefit from applications of remote sensing and hydrologic models. These tools can be especially valuable during extreme events and in data-sparse regions. Observational platforms include the GPM, SMAP, Terra, Aqua, Landsat, GRACE, and Sentinel satellites, and other satellite and airborne platforms. They can support the operational water resources management community in responding to climate change, increases in climate variability and the frequency of extreme events. This session will highlight advances in the use of satellite, airborne and ground-based sensor networks to: measure the quantity/quality of hydrologic resources in the U.S. and internationally; provide information to water managers to improve water resources management; and support risk-based decision making. Topics of interest include (1) extreme events such as floods and droughts; (2) water supply and snow water resource monitoring and forecasting; (3) evapotranspiration, soil moisture, groundwater, and agricultural water management; (4) water quality and (5) global water sustainability.by Anukesh Krishnankutty Ambika, and Vimal Mishr

Reply to Comment on “Improved Water Savings and Reduction in Moist Heat Stress Caused by Efficient Irrigation” by Meetpal S. Kukal

Abstract Irrigation has a considerable influence on land surface energy and water budgets. Irrigation‐related processes influence energy partitioning, planetary boundary layer, land surface temperature, evapotranspiration, and runoff. However, observations related to irrigation and its influence on land surface hydrology and climate are limited. Among the limited observations available, most are from the field scale experiments that do not provide information on the regional scale impacts of irrigation. While land surface and climate models do not represent the complexity of field‐scale irrigation, these modeling experiments provide valuable insights into regional‐scale effects. We respond to a recent comment on our modeling study of irrigation impacts on regional climate. We acknowledge the limitations of our modeling experiments. However, we aimed to provide an experimental framework to understand the role of improved irrigation efficiency in water savings and in reducing moist heat stress at the regional scale

Observational evidence of irrigation influence on vegetation health and land surface temperature in India

Irrigated area in India has significantly increased after the green revolution. However, quantification of irrigation influence on vegetation health and land surface temperature (LST) remains limited. Here, we develop a high?resolution (250m) remotely sensed data of enhanced vegetation index (EVI) and LST from Moderate Resolution Imaging Spectroradiometer (MODIS) for 2000?2017 at the 8?day temporal resolution for India to quantify the role of irrigation in the modulation of EVI, LST, and vegetation health. We show that irrigation dominated regions have significantly (p?value < 0.05) higher EVI and cooler (1?2 K) LST during the crop?growing season in the Indo?Gangetic Plain. Vegetation health in highly irrigated areas is poorly correlated with meteorological drought primarily due to irrigation. Moreover, vegetation health is negatively correlated with groundwater storage anomalies in the highly irrigated Indo?Gangetic Plain. Irrigation in Indo?Gangetic Plain modulated EVI, LST, and vegetation health and resulted in groundwater depletion during 2002?2016.by Anukesh Krishnankutty Ambika and Vimal Mishr

Data Descriptor: Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015

India is among the countries that uses a significant fraction of available water for irrigation. Irrigated area in India has increased substantially after the Green revolution and both surface and groundwater have been extensively used. Under warming climate projections, irrigation frequency may increase leading to increased irrigation water demands. Water resources planning and management in agriculture need spatially-explicit irrigated area information for different crops and different crop growing seasons. However, annual, high-resolution irrigated area maps for India for an extended historical record that can be used for water resources planning and management are unavailable. Using 250m normalized difference vegetation index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS) and 56m land use/land cover data, high-resolution irrigated area maps are developed for all the agroecological zones in India for the period of 2000–2015. The irrigated area maps were evaluated using the agricultural statistics data from ground surveys and were compared with the previously developed irrigation maps. High resolution (250 m) irrigated area maps showed satisfactory accuracy (R2= 0.95) and can be used to understand interannual variability in irrigated area at various spatial scales

Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015

India is among the countries that uses a significant fraction of available water for irrigation. Irrigated area in India has increased substantially after the Green revolution and both surface and groundwater have been extensively used. Under warming climate projections, irrigation frequency may increase leading to increased irrigation water demands. Water resources planning and management in agriculture need spatially-explicit irrigated area information for different crops and different crop growing seasons. However, annual, high-resolution irrigated area maps for India for an extended historical record that can be used for water resources planning and management are unavailable. Using 250 m normalized difference vegetation index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS) and 56 m land use/land cover data, high-resolution irrigated area maps are developed for all the agroecological zones in India for the period of 2000–2015. The irrigated area maps were evaluated using the agricultural statistics data from ground surveys and were compared with the previously developed irrigation maps. High resolution (250 m) irrigated area maps showed satisfactory accuracy (R2=0.95) and can be used to understand interannual variability in irrigated area at various spatial scales.by Anukesh Krishnankutty Ambika, Brian Wardlow and Vimal Mishr

Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015

Irrigated area maps for the period of 2000-2015 developed using 250m MODIS NDVI.<br