Statistical downscaling of GRACE terrestrial water storage changes based on the Australian Water Outlook model.

The coarse spatial resolution of the Gravity Recovery and Climate Experiment (GRACE) dataset has limited its application in local water resource management and accounting. Despite efforts to improve GRACE spatial resolution, achieving high resolution downscaled grids that correspond to local hydrological behaviour and patterns is still limited. To overcome this issue, we propose a novel statistical downscaling approach to improve the spatial resolution of GRACE-terrestrial water storage changes (ΔTWS) using precipitation, evapotranspiration (ET), and runoff data from the Australian Water Outlook. These water budget components drive changes in the GRACE water column in much of the global land area. Here, the GRACE dataset is downscaled from the original resolution of 1.0° × 1.0° to 0.05° × 0.05° over a large hydro-geologic basin in northern Australia (the Cambrian Limestone Aquifer-CLA), capturing sub- grid heterogeneity in ΔTWS of the region. The downscaled results are validated using data from 12 in-situ groundwater monitoring stations and water budget estimates of the CLA's land water storage changes from April 2002 to June 2017. The change in water storage over time (ds/dt) estimated from the water budget model was weakly correlated (r = 0.34) with the downscaled GRACE ΔTWS. The weak relationship was attributed to the possible uncertainties inherent in the ET datasets used in the water budget, particularly during the summer months. Our proposed methodology provides an opportunity to improve freshwater reporting using GRACE and enhances the feasibility of downscaling efforts for other hydrological data to strengthen local-scale applications.

Estimation of groundwater storage loss for the Indian Ganga Basin using multiple lines of evidence.

We used remote sensing data, field observations and numerical groundwater modelling to investigate long-term groundwater storage losses in the regional aquifer of the Ganga Basin in India. This comprised trend analysis for groundwater level observations from 2851 monitoring bores, groundwater storage anomaly estimation using GRACE and Global Land Data Assimilation System (GLDAS) data sets and numerical modelling of long-term groundwater storage changes underpinned by over 50,000 groundwater level observations and uncertainty analysis. Three analyses based on different methods consistently informed that groundwater storage in the aquifer is declining at a significant rate. Groundwater level trend indicated storage loss in the range - 1.1 to - 3.3 cm year-1 (median - 2.6 cm year-1) while the modelling and GRACE storage anomaly methods indicated the storage loss in the range of - 2.1 to - 4.5 cm year-1 (median - 3.2 cm year-1) and - 1.0 to - 4.2 cm year-1 (median - 1.7 cm year-1) respectively. Probabilistic modelling analysis also indicated that the average groundwater storage is declining in all the major basin states, the highest declining trend being in the western states of Rajasthan, Haryana and Delhi. While smaller compared to the western states, average groundwater storage in states further towards east-Uttar Pradesh, Bihar and West Bengal within the basin are also declining. Time series of storage anomalies obtained from the three methods showed similar trends. Probabilistic storage analysis using the numerical model vetted by observed trend analysis and GRACE data provides the opportunity for predictive analysis of storage changes for future climate and other scenarios.

Numerical groundwater modelling for studying surface water-groundwater interaction and impact of reduced draft on groundwater resources in central Ganga basin.

Water resources in India's Indo-Gangetic plains are over-exploited and vulnerable to impacts of climate change. The unequal spatial and temporal variation of meteorological, hydrological and hydrogeological parameters has created additional challenges for field engineers and policy planners. The groundwater and surface water are extensively utilized in the middle Gangetic plain for agriculture. The primary purpose of this study is to understand the discharge and recharge processes of groundwater system using trend analysis, and surface water and groundwater interaction using groundwater modelling. A comprehensive hydrological, and hydrogeological data analysis was carried out and a numerical groundwater model was developed for Bhojpur district, Bihar, India covering 2395 km2 geographical area, located in central Ganga basin. The groundwater level data analyses for the year 2018 revealed that depth to water level varies from 3.0 to 9.0 meter below ground level (m bgl) in the study area. The M-K test showed no significant declining trend in the groundwater level in the study area. The groundwater modelling results revealed that groundwater head is higher in the southern part of the district and the groundwater flow direction is from south-west to north-east. The groundwater head fluctuation between the monsoon and the summer seasons was observed to be 2 m, it is also witnessed that groundwater is contributing more to rivers in the monsoon season in comparison with other seasons. Impact of reduction in pumping on groundwater heads was also investigated, considering a 10% reduction in groundwater withdrawal. The results indicated an overall head rise of 2 m in the southern part and 0.2-0.5 m in the middle and northern part of the district.