Airsheds, watersheds and more – The flows that drive intra-extra-urban connections, and their implications for nature-based solutions (NBS)

This is the final version. Available on open access from Elsevier via the DOI in this recordCities are highly complex, inter-connected social-ecological systems, encompassing social, built and natural/semi-natural components. They interact with their surrounding extra-urban areas at varying scales, from peri-urban and rural to global. Space is a valuable commodity in cities. However, in most instances, city planners tend to think about interventions only within cities and rarely about the wider connected domains outside. Yet, considering the wider spatial context, including space outside of the city boundaries, may open up opportunities to achieve substantially greater benefit for city residents without sacrificing valuable space, leading to more sustainable city design for people and the environment. In this paper we discuss the intra-extra-urban flows which connect cities to their wider airsheds, watersheds, biosheds and resourcesheds, which in turn interact with their peoplesheds. For each domain, we illustrate the processes and the scales they operate at, and discuss the implications for optimum location of nature-based solutions (NBS) to address urban challenges. We suggest that integrating knowledge about these multiple sheds can inform holistic design of NBS to deliver greater benefit for city residents. This takes into account the synergies and multi-functional co-benefits which arise from a careful consideration of place and people, while minimising potential disbenefits and trade-offs

Seasonal glacier and snow loading in Svalbard recovered from geodetic observations

We processed time-series from seven Global Navigation Satellite System (GNSS) stations and one Very Long Baseline Interferometry (VLBI) station in Svalbard. The goal was to capture the seasonal vertical displacements caused by elastic response of variable mass load due to ice and snow accumulation. We found that estimates of the annual signal in different GNSS solutions disagree by more than 3 mm which makes geophysical interpretation of raw GNSS time-series problematic. To overcome this problem, we have used an enhanced Common Mode (CM) filtering technique. The time-series are differentiated by the time-series from remote station BJOS with known mass loading signals removed a priori. Using this technique, we have achieved a substantial reduction of the differences between the GNSS solutions. We have computed mass loading time-series from a regional Climatic Mass Balance (CMB) and snow model that provides the amount of water equivalent at a 1 km resolution with a time step of 7 d. We found that the entire vertical loading signal is present in data of two totally independent techniques at a statistically significant level of 95 per cent. This allowed us to conclude that the remaining errors in vertical signal derived from the CMB model are less than 0.2 mm at that significance level. Refining the land water storage loading model with a CMB model resulted in a reduction of the annual amplitude from 2.1 to 1.1 mm in the CM filtered time-series, while it had only a marginal impact on raw time-series. This provides a strong evidence that CM filtering is essential for revealing local periodic signals when a millimetre level of accuracy is required