These catchment boundaries define upland catchments and subcatchments at the headwaters of rivers Upper Hafren (Severn) and Upper Gwy (Wye). They identify the area of study of the Plynlimon research catchment project.

A modelled dataset derived from a range of national datasets, describing the distribution of woody linear feature boundaries in Great Britain. The dataset presents linear features which have a high likelihood of being a woody linear feature. The dataset was created by a predictive model developed at the Centre for Ecology & Hydrology, Lancaster in 2016. Full details about this dataset can be found at https://doi.org/10.5285/d7da6cb9-104b-4dbc-b709-c1f7ba94fb16

This dataset consists of soil data for 64 field sites on paired farm sites, with 29 variables measured for soil texture and structural condition, aggregate stability, organic matter content, soil shear strength, fuel consumption, work rate, infiltration rate, water quality and hydrological condition (HOST) data. The study is part of the NERC Rural Economy and Land Use (RELU) programme. A move to organic farming can have significant effects on wildlife, soil and water quality, as well as changing the ways in which food is supplied, the economics of farm business and indeed the attitudes of farmers themselves. Two key questions were addressed in the SCALE project: what causes organic farms to be arranged in clusters at local, regional and national scales, rather than be spread more evenly throughout the landscape; and how do the ecological, hydrological, socio-economic and cultural impacts of organic farming vary due to neighbourhood effects at a variety of scales. The research was undertaken in 2006-2007 in two study sites: one in the English Midlands, and one in southern England. Both are sites in which organic farming has a 'strong' local presence, which we defined as 10 per cent or more organically managed land within a 10 km radius. Potential organic farms were identified through membership lists of organic farmers provided by two certification bodies (the Soil Association and the Organic Farmers and Growers). Most who were currently farming (i.e. their listing was not out of date) agreed to participate. Conventional farms were identified through telephone listings. Respondents' farms ranged in size from 40 to 3000 acres, with the majority farming between 100 and 1000 acres. Most were mixed crop-livestock farmers, with dairy most common in the southern site, and beef and/or sheep mixed with arable in the Midlands. In total, 48 farms were studied, of which 21 were organic farmers. No respondent had converted from organic to conventional production, whereas 17 had converted from conventional to organic farming. Twelve of the conventional farmers defined themselves as practicing low input agriculture. Farmer interview data from this study are available at the UK Data Archive under study number 6761 (see online resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

This dataset contains a national-scale geodatabase of stream network and river catchment characteristics in the Philippines. It presents detailed information on 128 medium- to large-sized catchments (catchment area > 250 km2). The quantitative descriptions provide context for enabling geomorphologically-informed sustainable river management. The geodatabase provides a baseline understanding of fundamental topographic characteristics in support of varied geomorphological, hydrological and geohazard susceptibility applications. Data sets include: 1) GIS shapefiles with river catchment properties; 2) GIS shapefiles with stream network properties; 3) spreadsheets containing morphometric and topographic characteristics (n = 91); 4) example MATLAB code and topographic data to replicate the analysis for a selected catchment. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312/1. Full details about this dataset can be found at https://doi.org/10.5285/49ae11ec-e4e5-4e4a-b091-976d18c4ee3e