Gridded land use map of Peninsular Malaysia with a resolution of approximate 25 meters for the year 2018. The map includes nine different classes: 1) non-paddy agriculture, 2) paddy fields, 3) rural residential, 4) urban residential, 5) commercial/institutional, 6) industrial/infrastructure, 7) roads, 8) urban and 9) others. The land use map was created as part of the project “Malaysia - Flood Impact Across Scales”. The project is funded under the Newton-Ungku Omar Fund ‘Understanding of the Impacts of Hydrometeorological Hazards in South East Asia’ call. The grant was jointly awarded by the Natural Environment Research Council and the MYPAIR Scheme under the Ministry of Higher Education of Malaysia. Full details about this dataset can be found at https://doi.org/10.5285/36df244e-11c8-44bc-aa9b-79427123c42c

This dataset contains high-resolution (5-minute) raw, atmospheric corrected and mean sea level adjusted water level data for 9 flood storage areas (FSAs) in the Littlestock Brook catchment (a tributary of the River Evenlode, Thames Basin) from 2018 to 2022. The dataset also includes the estimated 9 x FSA stored volume time-series, estimated using a depth-stored volume lookup table for each FSA, produced from a digital elevation model of each feature and a depth-area-volume toolset. The annual barometric pressure time-series used to correct water level is also provided. This dataset was collected by UKCEH as part of a hydrological monitoring programme for the Littlestock Brook Natural Flood Management scheme. This work was supported by the SPITFIRE NERC DTP (NE/L002531/1) and the SCENARIO NERC DTP (NE/L002566/1). Full details about this dataset can be found at https://doi.org/10.5285/cf70f798-442a-4775-963c-b6600023830f

This dataset includes neutron probe data measured across the Pontbren study catchment in mid-Wales, UK. Neutron probe access tubes were installed at various locations across the site and measurements taken between 2006-2009 as part of the Pontbren Catchment Study Land Use and Management Multi-Scale Experimental Programme. To estimate profile volumetric soil moisture content (cm3 cm-3), measurements were taken every 10 cm down the soil profile to a maximum depth of 120 cm below the soil surface. Raw neutron probe count data (16 second sampling time) are provided along with shield count (1 x 64 second sampling time) and water count (average 5 x 64 second sampling time) data. These data are provided in .txt files and have columns indicating the site and plot name along with a time stamp. Depth of observation is shown in the column headings of the data. Due to access tubes becoming water logged it was sometimes not possible to carry out measurements at the lower depths of some of the access tubes. Details of the dataset, monitoring locations and how to convert neutron probe counts to volumetric moisture content are provided in the supporting documentation.

This dataset is from an automatic weather station (AWS) located at the Pontbren study site in mid-Wales, UK. The AWS was installed at the Bowl study site, an area of improved grassland, between 2006-2010 as part of the Pontbren Catchment Study Land Use and Management Multi-Scale Experimental Programme. The parameters measured by the AWS were; incident radiation, wind speed and direction, soil and air temperature, relative humidity and net radiation. All sensors are sampled every one minute and provided in the form of daily and ten-minute averages. Data are provided in the form of .txt files and generally split into six-month blocks. Associated with each data point in the .txt file is a quality assurance code, QA code, in the adjacent column. Details of the dataset and the quality assurance coding system (Appendix A) are provided in the supporting documentation. Other measurements taken at the Bowl include monitoring runoff from an improved grassland field in the form of overland and drain flow, soil water tension, soil volumetric moisture content, groundwater height and precipitation.

This dataset includes data collected from the Bowl site located with the Pontbren study catchment in mid Wales, UK. The Bowl is an area of improved grassland and was instrumented between 2004 to 2010 and monitored as part of the Pontbren Catchment Study Land Use and Management Multi Scale Experimental Programme. Variables measured and included in this dataset are the drain flow from a field drain, overland flow runoff and soil water tension within the improved grassland hillslope. Other variables measured at the Bowl but not included in this dataset are: climatic data from an automatic weather station, precipitation, groundwater height, and soil moisture data (using a neutron probe); these other datasets are also available. Within this Pontbren Bowl study site folder are a series of sub-folders with different datasets all associated with the Bowl study site. The Bowl runoff folder includes all runoff data from the Bowl study site. Runoff from the Bowl in the form of overland and drain flow was monitored using a combination of tipping bucket and weir box monitoring systems. Flow is measured in litres/second (ls-1) and runoff data from the bowl was collected for the period end of 2004 to 2010. Differences in sampling time occurred throughout the monitoring period due to logger limitations. Changes in sampling time can be found by examining specific data files. Changes in the size of the bucket of the tipping bucket system also occurred during the monitoring period. It is considered that the weir boxes provide a more accurate prediction of the highest flows, however there are times when they are not operation. The Bowl tensiometers folder contains soil water tension (cm H2O) data collected from two transects with arrays of tensiometers measuring soil water tension at 10 cm, 30 cm and 50 cm depth. Soil water tension data for the Bowl study site exist for the period 2005-2009. Data are provided in the form of .txt files and generally split into 6 month blocks. Associated with each data point in the .txt file is a quality assurance code, QA code, in the adjacent column. Note that for the Bowl tensiometer data in the early years of monitoring data from both transects are provided in one file. From March 2008 onwards there is a reduction in the number of tensiometers installed and the data files are split. Files with BotQC in the title contain data from the lower array of tensiometers and files with TopQC in the title contain data from the array of tensiometers further up the hillslope of the Bowl study site. Details of the dataset and the quality assurance coding system are provided in the supporting documentation.

Simulated 15-min discharge time-series (1/10/2015-17/1/2016) for the River Kent at Sedgwick following a Natural Flood Management intervention of ‘Enhanced Hillslope Storage’ plus the baseline simulations are presented. To derive these data, the observed 15-minute discharge River Kent measured at the Environment Agency (EA) Sedgwick gauging station (https://nrfa.ceh.ac.uk/data/station/info/73005) through the 1 Oct 2015 to 17 Jan 2016 period were modelled using the latest version of Lancaster University’s Dynamic TOPMODEL (https://cran.r-project.org/web//packages/dynatop/index.html). The spatially distributed rainfall field used as input to TOPMODEL was derived from a new direction-dependent and topographically controlled interpolation using observed rainfall data for the Cumbrian Mountains (Page et al., 2022. Hydrological Processes 36: e14758, https://doi.org/10.1002/hyp.14758). Lack of perfect understanding of the hydrological processes routing rainfall for stream channels and then along stream channels to the Sedgwick gauge was represented by using a very wide range of model parameters applied randomly within 10,000 simulations. Using the approach detailed in Beven et al. (2022a. Hydrological Processes 36(10): e14703, https://doi.org/10.1002/hyp.14703), the resultant wide range of simulated discharge time-series was reduced by rejecting all but 67 simulations that passed the prescribed criteria. These 67 baseline simulations of observed behaviour through the +3 month period at Sedgwick are presented here. To represent the effect of adding surface storage distributed across this 209 sq km River Kent catchment, the Digital Elevation Model (DEM) used in the baseline simulations according to Hankin et al (2018. Technical report SC150005/R6. Environment Agency, Bristol. 77pp, https://www.gov.uk/flood-and-coastal-erosion-risk-management-research-reports/working-with-natural-processes-to-reduce-flood-risk) to represent bunds placed on hillslopes in rural areas. The bunds are a type of flood mitigation measure known as Natural Flood Management or NFM. These are known formally as ‘Enhanced Hillslope Storage’ or EHS features (Beven et al 2022b. Hydrological Processes 36: e14752, https://doi.org/10.1002/hyp.14752). The TOPMODEL parameter sets producing the 67 ‘acceptable’ baseline simulations were then re-run with the modified DEM. These results are also presented here. Full details about this dataset can be found at https://doi.org/10.5285/af081a90-b014-43f7-9399-c948a8b7672f

This dataset contains information about soil near-surface physical and hydrological properties, vegetation observations and land use & management information across the Thames catchment (UK). It was collected during the ‘Landwise' project's ‘Broad-scale field survey' which sampled 1836 location points across a total of 164 fields/land parcels. The aim of the survey was to quantify the impact of innovative land use and management on soil properties, with implications for natural flood management. The surveyed fields were selected to represent four broad land use and management classes (arable with and without grass in rotation, permanent grassland and broadleaf woodland) and five generalised soil/geology classes. Approximately eight fields were sampled for each of the twenty combinations of land use and soil/geology class. The sampled fields cover a range of traditional and innovative agricultural practices. Within each field/parcel, representative sampling locations were selected to cover the anticipated range of soil variability, including typical infield, untrafficked margins and trafficked headlands/tramlines etc. Sampling was undertaken once during the period 2018-2021. Samples were measured and analysed using a range of field and laboratory techniques (see Data Lineage). Point data include: 1. Survey point location (British National Grid coordinates) 2. Soil quantitative measurements (near-surface: 0 – 50 mm below ground level): dry bulk density, volumetric water content, organic matter, derived porosity, derived porosity accounting for variable organic matter, particle size distribution and texture classification 3. Vegetation quantitative measurements: maximum and minimum height 4. Soil qualitative measurements: hand texture classification, aggregate stability test slaking and dispersion results, hydrochloric acid test for calcareous soil, and for a subset of locations Visual Evaluation of Soil Structure (VESS) score 5. Observations (also classified into groups): soil surface condition (e.g. slaked/unslaked/capped/poached etc.), vegetation type Field contextual data include: 1. Land owner/manager responses to a land use and management questionnaire (primary data) including information on: crop types/rotation, cover crops, herbal leys, organic or conventional, organic amendments, lime additions, tillage, last ploughed, tramlines, buffer strips, field drainage, grass species, livestock, last grazed, stocking density, grazing weeks per year, stock out-wintering, mob or paddock grazing, woodland management, tree species, woodland age, path management, land use history, flooding history, waterlogging, water or sediment runoff 2. Classification of selected questionnaire free text responses into categories (derived secondary data) 3. General field observations (primary data) including: slope gradient and shape, surface form, surface water, surface condition (slaking, capped, ruts, wheelings, poaching etc.), soil erosion or deposition features As agreed with the survey participants, this dataset has been anonymised by removing location specific information, such as farm and field names, along with any other personally identifiable information. As also agreed, point data location coordinates have been degraded to the nearest 1 km grid point. The dataset was co-produced by the UK Centre for Ecology and Hydrology and Landwise Partners as part of the Landwise Natural Flood Management project, supported by the Natural Environment Research Council (Grant NE/R004668/1). The participation and assistance of the land owners and managers is gratefully acknowledged. Full details about this dataset can be found at https://doi.org/10.5285/9ab5285f-e9c4-4588-ba21-476e79e87668