For the Bislak River, the Philippines, this dataset contains: (i) topography and orthoimagery in 2019 and 2020; (ii) Digital Elevation Models (DEMs) of Difference; (iii) predicted depth, velocity and shear stress from HEC-RAS two-dimensional hydraulic model simulations for 10, 50 and 100 year return period flood scenarios; and (iv) calculated bedload transport for 10, 50 and 100 year return period flood scenarios. Shear stress predictions were combined with median (D50) grain size observations to compute bedload transport rates for four different river patterns (meandering, wandering, braided, deltaic). For the 50 year return period flood event, bedload transport rates were also calculated for the D16 and D84 grain size. Geomorphic change detection was used to identify geomorphic change which took place between 2014-2019 and 2019-2020. All geospatial data are in WGS 1984 UTM Zone 51N. This data was created as part of a numerical, two-dimensional hydraulic modelling investigation to predict patterns of flood inundation and bedload transport for the Bislak River Philippines under different flood scenarios (10-, 50- 100-year flood events). Full details about this dataset can be found at https://doi.org/10.5285/5b29d98e-28b6-4ca7-89b3-57174d6b404a

This dataset contains river (fluvial) and surface water (pluvial) flooding maps for the central highlands of Vietnam and surrounding provinces. Flood depth is estimated at 30m horizontal grid spacing for 10 return periods, ranging from the 1 in 5 year to the 1 in 1000 year return period flood. These maps are of relevance to planners and policy makers to estimate which areas of most at risk of flooding and can contribute towards policy such as the sustainable development goals. Full details about this dataset can be found at https://doi.org/10.5285/74e4e6ec-a119-4dc7-8ada-9513252b1b60

This dataset comprises multiple baseline and future ensembles of hydrological model estimates of monthly mean and annual maximum river flows (m3s-1) on a 0. 0.008333° × 0. 0.008333° grid (approximate grid of 1 km × 1 km) across Peninsular Malaysia. Specifically, these are provided for historical (1971 to 2005) and projected future (2006 to 2099) periods, for 3 Representative Concentration Pathways (RCPs). This dataset is the output from the Hydrological Modelling Framework for Malaysia, or “HMF-Malaysia” model. The projected future hydrology simulations are provided for CORDEX-SEA (Coordinated Regional Downscaling Experiment – South East Asia) three RCPs (RCP2.6, RCP4.5 and RCP8.5) assuming (i) current artificial influences (CAI) such as water transfers and diversions and (ii) planned future artificial influences (FAI). This dataset is an output from the hydrological modelling study from the Malaysia - Flood Impacts Across Scales (FIAS) project. Full details about this dataset can be found at https://doi.org/10.5285/9b70bebe-189c-4ae8-9aee-1bb1db7b1ad5

This dataset contains fluvial flood maps of the present day 1 in 20 year return period, and corresponding flood extents for 3 SSP (Shared Socioeconomic Pathway)/RCP(Representative Concentration Pathway) scenarios for the future (2070-2100). Change in flood return periods are estimated using CMIP6 projections and subsequently used to extract flood maps from a global flood model. Full details about this dataset can be found at https://doi.org/10.5285/0d5d69ae-7f50-40ee-a0c9-2522de138f27

This dataset contains maximum water depth and maximum water velocity for 12 different Glacial Lake outburst floods (GLOFs) scenarios of the Tsho Rolpa Lake, Nepal. Also included is the water depth of dam breach flow and discharge of dam breach flow under each scenario. The GLOFs scenarios were created using a simple dam breach model. A high-performance hydrodynamic model was then used to simulate the resulting flood hydrodynamics. Full details about this dataset can be found at https://doi.org/10.5285/f4292d99-de93-4a28-a821-b2a6a826df4c

The datasets contain maps of the total change in topography along the river Liang (Philippines) after the Typhoon Mangkhut event in September 2018. The maps have been generated using multi-phase mass model r.avaflow to simulate the change in channel and landscape. Full details about this dataset can be found at https://doi.org/10.5285/5d17ff4b-fc98-47e5-9d61-956b17254681

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 data set covers high resolution (30-min frequency) water quality and dissolved carbon data from a peatland river in Southwest Scotland (5.8 km2), part of the Whitelee Wind Farm complex. The data set covers approx. 2.5 years including two full hydrological years and 261 individual flood events between 23/05/2012 and 16/12/2014. Carbon data was measured using a Scan Spectrolyser – a field deployable UV-Vis light spectrometer. Full details about this dataset can be found at https://doi.org/10.5285/4c591c29-01c9-493b-806e-7253e2682376

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

The data are dynamic response characteristics (DRCs) produced by modelling the rainfall-runoff behaviour of a series of micro-basins installed by the NERC Q-NFM project largely in Cumbria (UK) and ranging in scale from 0.0071 to 2.7329 sq. km. Specifically, the rainfall to discharge response of these basins has been modelled with the RIV algorithm of the CAPTAIN Toolbox (Taylor et al., 2007 doi.org/10.1016/j.envsoft.2006.03.002). The resultant modelled characteristics of the rainfall-discharge dynamics are presented on an event-by-event basis. Full details about this dataset can be found at https://doi.org/10.5285/ea641367-dc35-4695-97b8-63f7d6fa9105