The Gangetic Plain is a large fertile area at the foot of the Himalayas, covering most of northern India. Home to around 400 million inhabitants, it is one of the most densely inhabited regions in South-East Asia. With its fertile soils, monsoon precipitation and vast groundwater aquifers, the plains have been at the heart of the Indian agricultural revolution. Over the last 4 decades, the introduction of new fertilisers and crops, and the construction of large-scale irrigation systems have been major drivers of socio-economic development in the region. These practices have, however, also led to severe groundwater decline and strains on other water resources. Changing feedbacks of water and energy between the land-surface and atmosphere may have even altered the local climate system. A strong economic development is expected to continue these trends in the near future and future climate change is also expected to increase the pressure on local water resources systems. Identifying the major causes of observed historical changes in water availability and predicting the future impact of local water management strategies under climate change are particularly challenging, yet indispensable for the sustainable management of water resources. For example: assessing the sustainability of groundwater aquifers requires knowledge of global climate influences, but also of the influence of land-use, abstractions and soil moisture dynamics; furthermore, the unprecedented scale of land-use changes and increased irrigation are expected to have influenced local climate through feedbacks of water and energy. In order to unravel and quantify the impact of different drivers of change, a fully integrated analysis of the major water fluxes in the Gangetic Plain is needed. This study would be the first to analyse changes in the main water fluxes and feedbacks of the Gangetic Plain in a fully integrated modelling set-up. The approach will enable the separation of the impact of local and regional land use change from that of global climate drivers. We will develop a custom-built coupled hydrological model for the region using available groundwater and surface water modelling toolboxes. This model will be calibrated and tested using a variety of different sources of information, from local measurements, satellite observations and global climate (reanalysis) datasets. Subsequently, we will run the model with different land-use and water extraction scenarios. This will allow us to quantify the impact of land-use change and extraction on the main hydrological fluxes and water resources. At the same time, the hydrological model will generate high-resolution data about soil moisture changes resulting from historical land-use, as well as different hypothetical scenarios. By feeding these scenarios into a global climate model, we will study the potential feedbacks of large-scale changes in soil moisture on the Indian monsoon system. A pair of state-of-the-art global climate models will be used: the UK MetOffice Unified Model (MetUM) and the NCAR Community Atmosphere Model (CAM4). In a final step, the superimposed impact of climate change will be assessed and future predictions of water availability will be generated. For this purpose, we will use the new CMIP5 ensemble of climate models. Using a statistical approach, these models will be downscaled to a level useful for application over the Gangetic Plains. The integrated hydrological model can then be run with these future climate projections to assess the impact of future climate change on regional and local water availability. Two local case studies will address the usefulness of such projections and their uncertainties in a local ecosystem-oriented management setting.

For many decades plant phenotyping has been used to help us understand the biological mechanisms that underpin plant growth and health. Measuring plants lets us seek out new crops that are higher yielding, or more resilient in the face of a changing climate or evolving diseases. Roots, the unseen and often overlooked part of plants, play a pivotal role in the development of strong and robust crops. Root systems extract water and nutrients from the surrounding soil, and a high performing root system can transform the performance of the plant above ground. There has been a great deal of research on the automatic measurement of root architectures - the arrangement of root systems in soil or substrate. Teams including those at the University of Nottingham, UK, the University of Saskatchewan, CA, and the Donald Danforth Plant Science Centre, USA, have developed techniques to acquire images of 2D and 3D root architecture and computer vision and AI software to measure these images quickly and automatically. The study of root anatomy - the organisation of cells within a root - has proven a more challenging task1. Microscopy and other similar images of roots are often very high resolution, and there may be many thousands of cells within even a small area. Many existing solutions have focused on 2D segmentation, but like root architecture, root anatomy is an inherently 3D challenge. Our ability to understand the biological mechanisms and benefits of root anatomy will always be limited until we can reliably and quickly phenotype these dense tissue structures. This project will push forward the technology that underpins high-resolution segmentation of 3D root anatomy by leveraging the imaging facilities at Nottingham, and the world-leading plant phenotyping and AI expertise at Nottingham, Saskatchewan, and the Donald Danforth Plant Science Centre. Nottingham houses modern imaging facilities at the Hounsfield Facility: a Laser Ablation Tomograph (LAT), and new micro-computed X-Ray tomography (µCT) platforms that collect 3D data at high throughput and resolution. Nottingham has also undertaken important work in 2D segmentation of root anatomy, which will provide a foundation for the 3D segmentation methods developed here. Researchers at the University of Saskatchewan are experts in working with large datasets, using AI to detect objects in 2D, and objects and events in video sequences. Their expertise will allow us to identify important biological features as we traverse through the 3D stack, combining these features with the existing 2D segmentations into a detailed 3D map of the root tissue. Researchers at the Donald Danforth Plant Science Center have expertise in plant phenotyping and 3D imaging, and low-cost devices. Their image data captured on the same species as those at Nottingham will provide important cross-platform image variability, letting us train generalisable models that work for the whole community. By working on common crop varieties important to the economies of the UK, Canada and the US, the AI solutions will be more general and more robust than those developed by a single lab working alone. Gaining a better understanding root anatomy will drive forward bioscience research, letting us better understand how root adaptations affect water and nutrient uptake. All trained models and the final segmentations will be shared with our partners in North America and released into the wider research community.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

At near-noon local times, at locations in the high arctic near 80 degrees North and South, the magnetic fields which originate in the conducting core of our planet extend upwards and are magnetically connected to the dayside magnetopause. This subsolar magnetopause is the point where the magnetic field of the Earth first touches the highly supersonic solar wind flow, and the interplanetary magnetic field of solar origin which is embedded in it. This creates the magnetospheric cusps, which are the primary entry points for energy of solar wind origin into the regions of space controlled by the terrestrial magnetic field, and the atmospheric regions which underlie them. This energy transfer occurs through a process called magnetic reconnection. As such, this crucial region of near-Earth space is fundamental to understanding the flow of energy, mass and momentum throughout the Earth's magnetosphere, ionosphere and upper atmosphere, and hence in our understanding of "space weather". The magnetospheric cusps are longstanding areas of research interest, but their highly variable nature, in both space and time, makes them a highly challenging region to fully understand. Here we describe a multi-instrument research programme based around an exciting new NASA space mission, TRACERS, due for launch in late 2022, on which the proposal PI is a named collaborator. The TRACERS programme relies on coordination with ground-based instrumentation. Of particular interest for TRACERS is the Svalbard region, an area of the high arctic uniquely well instrumented with, for example, numerous optical instruments and the NERC-funded EISCAT Svalbard radar. Around northern winter solstice Svalbard is in darkness at noon, and for ~10 days the moon is below the horizon. Such conditions offer a unique opportunity for multi-instrument cusp experiments involving cusp auroral optical observations. Our multi-instrument research programme requires the construction and deployment of a new state-of-the art digital imaging radar system, the Hankasalmi auroral imaging radar system (HAIRS). HAIRS will look northwards from Hankasalmi in Finland, having a field of view centred over the Svalbard region, revealing the ionospheric cusp region electrodynamics at high spatial and temporal resolution over a ~1 million square kilometre region of the ionosphere. In this programme, low earth orbit measurements of energetic ions precipitating from the cusp region taken by the twin TRACERS spacecraft will provide measurements of the temporal and spatial structuring of the cusp reconnection processes. Magnetically conjugate measurements of the footprint of the reconnection line from HAIRS and associated ground-based instrumentation, will measure the length and the location of the reconnection line. HAIRS will provide an analysis of the boundary motion, and of the convection velocities detected near the boundary, allowing a calculation of the reconnection rate mapped down to the ionosphere. Such a combination of instrumentation will provide an unprecedented opportunity to understand the temporal and spatial behaviour of cusp reconnection and its role in controlling terrestrial space weather. Outside of the science programme described here, HAIRS will offer vital complementary datasets to support the upcoming NERC-funded EISCAT 3D radar system at lower latitudes in Scandinavia, coming on stream in 2021 which will also lie in the HAIRS field of view. HAIRS will also directly complement the Solar wind Magnetosphere Ionosphere Link Explorer (SMILE), launching in 2023, a joint mission between the European Space Agency (ESA) and the Chinese Academy of Sciences (CAS). The innovative SMILE wide-field Soft X-ray Imager (SXI), provided by the UK Space Agency and other European institutions, will obtain unique measurements of the regions where the solar wind impacts the magnetosphere, regions which are directly magnetically connected to the area under study in this programme.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.