Monitoring early-season agricultural drought using temporal Sentinel-1 SAR-based combined drought index.

Early-season agricultural drought is frequent over South Asian region due to delayed or deficient monsoon rainfall. These drought events often cause delay in sowing and can even result in crop failure. The present study focuses on monitoring early-season agricultural drought in a semi-arid region of India over 5-year period (2016-2020). It utilizes hydro-climatic and biophysical variables to develop a combined drought index (CDI), which integrates anomalies in soil moisture conditions, rainfall, and crop-sown area progression. Synthetic aperture radar (SAR)-based soil moisture index (SMI) represents in situ measured soil moisture with reasonable accuracy (r=0.68). Based on the highest F1-score, SAR backscatter in VH (vertical transmit-horizontal receive) polarization with specific values for parameter threshold (-18.63 dB) and slope threshold (-0.072) is selected to determine the start of season (SoS) with a validation accuracy of 73.53%. The CDI approach is used to monitor early-season agricultural drought and identified drought conditions during June-July in 2019 and during July in 2018. Conversely, 2020 experienced consistently wet conditions, while 2016 and 2017 had near-normal conditions. Overall, the study highlights the use of SAR data for early-season agricultural drought monitoring, which is mainly governed by soil moisture-driven crop-sowing progression. The proposed methodology holds potential for effective monitoring, management, and decision-making in early-season agricultural drought scenarios.

Net ecosystem CO2 exchange from jute crop (Corchorus olitorius L.) and its environmental drivers in tropical Indo-Gangetic plain using open-path eddy covariance technique.

Present study is a maiden attempt to assess net ecosystem exchange (NEE) of carbon dioxide (CO2) flux from jute crop (Corchorus olitorius L.) in the Indo-Gangetic plain by using open-path eddy covariance (EC) technique. Diurnal variations of NEE were strongly influenced by growth stages of jute crop. Daytime peak NEE varied from - 5 µmol m-2 s-1 (in germination stage) to - 23 µmol m-2 s-1 (in fibre development stage). The ecosystem was net CO2 source during nighttime with an average NEE value of 5-8 µmol m-2 s-1. Combining both daytime and nighttime CO2 fluxes, jute ecosystem was found to be a net CO2 sink on a daily basis except the initial 9 days from date of sowing. Seasonal and growth stage-wise NEEs were computed, and the seasonal total NEE over the jute season was found to be - 268.5 gC m-2 (i.e. 10.3 t CO2 ha-1). In different jute growth stages, diurnal variations of NEE were strongly correlated (R2 > 0.9) with photosynthetic photon flux density (PPFD). Ecosystem level photosynthetic efficiency parameters were estimated at each growth stage of jute crop using the Michaelis-Menten equation. The maximum values of photosynthetic capacity (Pmax, 63.3 ± 1.15 µmol CO2 m-2 s-1) and apparent quantum yield (α, 0.072 ± 0.0045 µmol CO2 µmol photon-1) were observed during the active vegetative stage, and the fibre development stage, respectively. Results of the present study would significantly contribute to understanding of the carbon flux from the Indian agro-ecosystems, which otherwise are very sparse.

Assessing lodging damage of jute crop due to super cyclone Amphan using multi-temporal Sentinel-1 and Sentinel-2 data over parts of West Bengal, India.

The present study is a maiden attempt to assess jute crop lodging due to super cyclone Amphan (20 May 2020) by synergistic use of Sentinel-2 (optical) and Sentinel-1 (SAR) data over part of West Bengal, India. Pre-event Sentinel-2 data (9 April, 14 May) along with the ground information were used to map the jute crop of the affected districts with accuracy of 85%. The cross-polarized backscatter (σ0VH) of Sentinel-1 was found to be sensitive to the sudden change in the canopy structure due to lodging and partial flooding. [Formula: see text](σ0VH_22 May - σ0VH_16 May) indicating post-event damage was > 2.5 dB over the affected jute crop and [Formula: see text] (σ0VH_22 May - σ0VH_28 May) representing post-event recovery showed > 1.5 dB for recovered crop, depending on the crop vigor/height. Decision matrix was prepared combining [Formula: see text] and [Formula: see text] for NDVI-based crop vigor strata (low, medium, and high) to classify the area into affected, marginally affected and normal. Overall accuracy of the classified map was found to be 84.12% with kappa coefficient of 0.74. Nearly, 12.5% of the jute area, i.e., 38,119 ha was found to be either affected or marginally affected due to Amphan and distributed in the southern part of Murshidabad, north-eastern Nadia, northern 24 Paraganas (N), and middle region of Hooghli district. Geospatial map of block-wise affected jute area was prepared to facilitate informed decision making. The study demonstrated an operational methodology for assessing crop lodging due to natural calamities to support relief management and crop insurance.

A study on agricultural drought vulnerability at disaggregated level in a highly irrigated and intensely cropped state of India.

Drought is an important global hazard, challenging the sustainable agriculture and food security of nations. Measuring agricultural drought vulnerability is a prerequisite for targeting interventions to improve and sustain the agricultural performance of both irrigated and rain-fed agriculture. In this study, crop-generic agricultural drought vulnerability status is empirically measured through a composite index approach. The study area is Haryana state, India, a prime agriculture state of the country, characterised with low rainfall, high irrigation support and stable cropping pattern. By analysing the multiyear rainfall and crop condition data of kharif crop season (June-October) derived from satellite data and soil water holding capacity and groundwater quality, nine contributing indicators were generated for 120 blocks (sub-district administrative units). Composite indices for exposure, sensitivity and adaptive capacity components were generated after assigning variance-based weightages to the respective input indicators. Agricultural Drought Vulnerability Index (ADVI) was developed through a linear combination of the three component indices. ADVI-based vulnerability categorisation revealed that 51 blocks are with vulnerable to very highly vulnerable status. These blocks are located in the southern and western parts of the state, where groundwater quality is saline and water holding capacity of soils is less. The ADVI map has effectively captured the spatial pattern of agricultural drought vulnerability in the state. Districts with large number of vulnerable blocks showed considerably larger variability of de-trended crop yields. Correlation analysis reveals that crop condition variability, groundwater quality and soil factors are closely associated with ADVI. The vulnerability index is useful to prioritise the blocks for implementation of long-term drought management plans. There is scope for improving the methodology by adding/fine-tuning the indicators and by optimising the weights.

Mapping of electrostatic potential in deep submicron CMOS devices by electron holography.

Quantitative two-dimensional maps of electrostatic potential in device structures are obtained using off-axis electron holography with a spatial resolution of 6 nm and a sensitivity of 0.17 V. Estimates of junction depth and variation in electrostatic potential obtained by electron holography, process simulation, and secondary ion mass spectroscopy show close agreement. Measurement artifacts due to sample charging and surface "dead layers" do not need to be considered provided that proper care is taken with sample preparation. The results demonstrate that electron holography could become an effective method for quantitative 2D analysis of dopant diffusion in deep-submicron devices.

Spectroscopy in the gas phase with GaAs/AlGaAs quantum-cascade lasers.

We demonstrate what we believe is the first application of the recently developed electrically pumped GaAs/AlGaAs quantum-cascade lasers in a spectroscopic gas-sensing system by use of hollow waveguides. Laser light with an emission maximum at 10.009 microm is used to investigate the mid-infrared absorption of ethene at atmospheric pressure. We used a 434-mm-long silver-coated silica hollow waveguide as a sensing element, which served as a gas absorption cell. Different mixtures of helium and ethene with known concentrations are flushed through the waveguide while the laser radiation that passes through the waveguide is analyzed with a Fourier-transform infrared spectrometer. The experimentally obtained discrete ethene spectrum agrees well with the calculated spectrum. A detection threshold of 250 parts per million is achieved with the current setup.