The dataset contains measurements of CO2 efflux from streams, springs, reservoirs and ponds in the Houzhai catchment, a typical karst catchment in the karst region of SW China. Data were obtained via direct, field-based measurements during monthly campaigns conducted between January 2016 and February 2017. Also included are water chemistry parameters (water temperature, pH, dissolved oxygen, electronic conductivity, concentration of dissolved inorganic carbon (DIC) and isotopic composition of dissolved inorganic carbon (δ13C-DIC)) and flow velocity (determined prior to in-situ flux measurements). The data were collected under the NERC-funded project: Addressing a significant knowledge gap in fluvial system atmospheric CO2 efflux: the contribution from karst landscapes (NE/N002806/1). Full details about this dataset can be found at https://doi.org/10.5285/22706f2d-2070-425f-b570-d73089359b35

[This dataset is embargoed until September 30, 2027]. This data comprises key hydraulic and photosynthetic traits, nutrient concentration and plant structure for savanna species (trees, shrubs, grasses and herbaceous) of the Cerrado, collected in the Chapada dos Veadeiros National Park (PNCV; 14°05' S, 47°40' W), located in the central plateau region of Brazil in 2021. These data were collected throughout May-September 2021 on 19 woody species across 11 botanical families, and for 20 monocot species across 6 botanical families, including grasses, herbs and Velloziaceae. 32 plant functional traits were measured on the 19 woody species, and 17 plant functional traits were measured on the 20 monocot species. Trait collections followed standardised published methodologies. The aim of this data was to assess the functional trait space occupied by Cerrado species and whether they differed according to vegetation type, and whether certain species or plants from certain environments were more or less resistant to drought stress. This research was supported by Natural Environment Research Council (Grant: NE/S000011/1). Full details about this dataset can be found at https://doi.org/10.5285/e8cff3f4-60e5-46cf-a4d0-0f7ecf222ae4

[This dataset is embargoed until December 31, 2026]. This dataset comprises 25 traits related to plant hydraulic function and wood anatomy for 38 individual trees of five dipterocarp species from a site in Borneo. Traits were measured at multiple positions along each tree: at the bottom and the top of the trunk, then at 3 positions along a lower, a middle, and an upper branch in the crown of the tree - so 12 measurement points per tree for the traits. The trees that were measured ranged in height from 7.7 to 71 m in height. These data were all collected following standardised methodologies for each trait sampled and they were all collected during one very large field campaign which took place during 2022. Following this anatomy samples and data were processed. The aim of this data set was to test whether tree height alters the water transport system of trees to make them more vulnerable to the impacts of drought. Full details about this dataset can be found at https://doi.org/10.5285/6ecfd160-4740-491e-a8b3-8cbb3a4c8701

This dataset contains laboratory measurements of peat depth, horizontal saturated hydraulic conductivity, dry bulk density, and the degree of peat humification (von Post scale) for degrading palsas at Rensjön palsa mire, Norrbotten, Sweden. Full details about this dataset can be found at https://doi.org/10.5285/5d0f211e-d391-4861-8f12-e04a65108ae7

A range of hydraulics data including stages and discharges were collected for the River and Leat at Boxford between 01/04/2008 and 30/09/2014. The River Lambourn is a tributary of the River Thames, the principal river in the south-east of England. The CEH River Lambourn Observatory comprises a 600 m reach of river and 24 acres of associated water meadows at Boxford, Berkshire. Data include: 1. River flow gauging using Electro-magnetic Current Meter (ECM); 2. Leat flow gauging using Electro-magnetic Current Meter (ECM); 3. River flow gauging using Acoustic Doppler Current Profiler (ADCP); 4. River stage boards readings (eleven Stage boards); 5. Leat stage boards readings (six Stage boards); 6. River stage at water quality station (WQS) using Druck PDCR 1830 Submersible Pressure Transducer; 7. River stage at four stilling wells using SWS Technology Mini-Diver® Non-Vented Level Sensors with a built-in internal data logger (four locations); 8. Time series river discharges at Boxford which are calculated from the relationship obtained between discharge measurements taken monthly at Boxford using ADCP and total river discharges at Shaw gauging station; 9. Time series of the Leat discharges which are calculated from the relationship obtained between discharge measurements taken mo Full details about this dataset can be found at https://doi.org/10.5285/4ed6f721-b23b-454e-b185-02ba54d551f0

The dataset contains CO2 efflux, hydraulic and water chemistry data from six field sites which vary in location, size and catchment characteristics. Measurements were made at: i) two sites in the UK - the River Kelvin (335 km2, semi-urban catchment) and Drumtee water (9.6 km2, peat dominated catchment); ii) four sites in the Peruvian Amazon - Main Trail (5 km2, seasonally active stream in a rainforest catchment), New Colpita stream (7 km2, perennial stream in a rainforest catchment), La Torre river (2000 km2, rainforest catchment) and Tambopata river (14 000 km2, rainforest catchment with some small scale agriculture and gold mining). CO2 efflux was measured at all sites on each sampling occasion alongside a range of other parameters to enable investigation into the controls on CO2 efflux. Parameters measured include flow velocity and water depth (from which other hydraulic parameters can be calculated), DIC concentration and pH (from which pCO2 can be calculated) and water temperature. Sampling was carried out over several years, thus capturing a range of seasons and flow conditions, and at all sites, measurement locations were chosen to ensure that a range of flow intensities were included. Full details about this dataset can be found at https://doi.org/10.5285/02d5cea7-10aa-4591-938a-a41e1c5bc207

This dataset contains information about surface and sub-surface hydraulic and hydrological soil properties across the Thames (UK) catchment. Soil dry bulk density, estimated soil porosity, soil moisture and soil moisture retention (to 100 cm suction) were determined through laboratory analysis of soil samples collected at five depths between the surface and 100 cm below ground level (where possible). Surface soil infiltration rates were measured, and soil saturated hydraulic conductivity was calculated at 25 cm and 45 cm depths (where possible). Field scale point data were collected at seven sites in the Thames Catchment, with three sub-groups of sites under different land use and management practices. The first land management group included three arable fields in the Cotswolds, Gloucestershire, on shallow soils over Limestone with no grass in rotation, herbal leys in rotation or rye and clover in rotation. The second group included two arable fields in near Wantage, Oxfordshire, on free draining loamy soils over chalk with conventional management or controlled traffic. The final group included a permanent grassland and broadleaf woodland on slowly permeable soil over mudstone near Oxford, Oxfordshire. Data were collected in representative infield areas; trafficked areas (e.g. tramlines or animal tracks), and untrafficked margins. Samples and measurements were taken between April 2021 and October 2021, with repeats taken before and after harvest. Soil samples were collected using Eijkelkamp 07.53.SC sample ring kit with closed ring holder and the Edelman auger and Stony auger when required. Infiltration measurements were taken using Mini Disk Infiltrometers. Soil saturated hydraulic conductivity was measured using Guelph permeameters. Soil bulk density and porosity were calculated using oven drying methods. Soil moisture retention was calculated using an Eijelkamp Sandbox. This dataset was collected by UKCEH as part of the 'Land management in lowland catchments for integrated flood risk reduction' (LANDWISE) project. LANDWISE seeks to examine how land use and management can be used to reduce the risk of flooding for communities. LANDWISE is one of three projects comprising the Natural Environment Research Council Natural Flood Management Research Programme. The work was supported by the Natural Environment Research Council Grant NE/R004668/1. Full details about this dataset can be found at https://doi.org/10.5285/a32f775b-34dd-4f31-aafa-f88450eb7a90