Search

There is a growing concern about water scarcity and the associated decline in Australia's agricultural production. Efficient water use as a natural resource requires more precise and adequate monitoring of crop water use and irrigation scheduling. Therefore, accurate estimations of evapotranspiration (ET) at proper spatial–temporal scales are critical to understand the crop water demand and uptake and to enable optimal irrigation scheduling. Remote sensing (RS)-based ET estimation has been adopted as a method for large-scale applications when the detailed spatial representation of ET is required. This research aimed to estimate instantaneous ET using very-high-resolution (VHR) multispectral and thermal imagery (GSD < 8 cm) collected using a single flight of a UAV over a high-density peach orchard with a discontinuous canopy. The energy balance component estimation was based on the high-resolution mapping of evapotranspiration (HRMET) model. A tree-by-tree ET map was produced using the canopy surface temperature and the leaf area index (LAI) resampled at the corresponding scale via a systematic feature segmentation method based on pure canopy extraction. Results showed a strong linear relationship between the estimated ET and the leaf transpiration (n = 42) measured using a gas exchange sensor, with a coefficient of determination (R2) of 0.89. Daily ET (5.5 mm d−1) derived from the instantaneous ET map was comparable with daily crop ET (6.4 mm d−1) determined by the meteorological approach over the study site. The proposed approach has important implications for mapping tree-by-tree ET over horticultural fields using VHR imagery. [ABSTRACT FROM AUTHOR]

• The study proposes and uses a new modelling framework for quantifying blue water scarcity. • This study reconstructs various water uses in India using census datasets. • Blue water scarcity is quantified in India at State and monthly scales. • More than 60% of the population in India faces severe water stress every year. • Groundwater abstraction in Gujarat, Rajasthan and Tamil Nadu exceeds the groundwater recharge. Sustainable water use and water scarcity are major concerns in developing countries such as India. Rapidly growing population along with increasing economic and technological development in India have resulted in increased water use leading to severe water scarcity. The present study aims to quantify and assess sustainable water use and water scarcity in India. A data-intensive approach is employed at a State spatial resolution and monthly temporal scales during the period 1991–1999. The Water Stress Index (WSI), which is defined as the ratio of total water use to available water, is used as a measure of blue water scarcity. The total available water includes surface water and groundwater while the total water uses include irrigation, industrial, domestic and environmental uses. A Community Land Model (CLM 4.0) developed by the National Centre for Atmospheric Research (NCAR), is used to quantify the total available water in India. Water uses in India are reconstructed using a census-based statistical database while the environmental water demand is modelled following the hydrology-based approach, which allocates environmental flows as a proportion of the available water, with seasonally defined environmental flow thresholds. Further, the excess water component, defined as the amount of water remaining after meeting the demands at each time step, is incorporated into the modelling framework by adding it to the available water pool. The study estimates that 60% of the population in India faces severe water stress during the analysis period, and is more predominant in the States of Rajasthan, Gujarat, Uttar Pradesh and Maharashtra. Moreover, non-renewable groundwater abstraction, which is defined as the amount of groundwater abstraction more than the groundwater recharge, is also quantified. This study identifies severe groundwater depletion in the north-western parts of India, consistent with the current estimates from GRACE satellite observations. [ABSTRACT FROM AUTHOR]