Inland waters
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These data are input files for CAESAR-Lisflood (CL), a numerical hydrodynamic-landscape evolution model. These files were created to support coupled hydrodynamic-landscape evolution modelling to evaluate the geomorphological response of river channels affected by the 7th February 2021 ice-rock avalanche and debris flow in Chamoli District, Uttarakhand, India. They include 10 m digital elevation models (DEMs) of bed rock and land surface topography in a gridded (raster) format. They also include reanalysis-derived river discharge data generated by the GEOGloWS project at the following locations: Rontigad, Rishiganga, Dhauliganga, and Alaknanda. The configuration settings and parameters for CL modelling are also included. Full details about this dataset can be found at https://doi.org/10.5285/4cdd86b3-bf58-457d-b8cf-b57aed2d56d0
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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
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The data resource contains daily time-series of simulated streamflow, ground water levels and estimated demands, from humans, livestock and irrigation across the Narmada Basin, India. The data were generated using the Global Water Availability Assessment (GWAVA) Model 5. For the Upper Narmada, a baseline of 1970-2013 is presented along with a future time slice of 2028- 2060. For the whole Narmada, a baseline of 1981-2013 and future period of 2021-2099 is included. The data were produced to help predict how climate and land use change in the region would impact on future water security. The research was funded by NERC research grant NE/R000131/1 Full details about this dataset can be found at https://doi.org/10.5285/9fc7ab01-c622-46f1-a904-0bcd54073da3
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This is a set of six ASCII grids describing the peak flood event for six return periods (2-100 years) at each point of the river network in the state of Kerala, India. Estimates were derived in a similar way to the Flood Estimation Handbook* approach. The data is measured in cubic metres per second, and is given on an unprojected resolution of 15 arc-seconds per grid cell. This work was supported by the Natural Environment Research Council as part of the LAWIS programme delivering National Capability. * (Flood Estimation Handbook. Centre for Ecology & Hydrology, 1999, ISBN: 9781906698003) Full details about this dataset can be found at https://doi.org/10.5285/cba9f9db-4706-4f1e-aaf4-fd7769e00db0
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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
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Data on peat depth from >250 locations in the Pastaza-Marañón Basin, Amazonian Peru. The data were collected during a series of field campaigns in 2019 and 2020. These data, along with similar data collected under other projects, were used to train a predictive model of peat distribution. Locations of a small number of other sites are given without peat depth measurements (i.e. with NA in the column Peat_depth_cm); these sites relate to data reported elsewhere in the ‘Carbon Storage in Amazonian Peatlands’ data collection. Full details about this dataset can be found at https://doi.org/10.5285/ab13a06f-392f-4bc6-b1bf-06dd8b020307
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Data comprise reservoir inflows and release data (including spills), evaporation loss and optimised monthly rule curve ordinates (upper, lower and critical) for Pong and Bhakra reservoirs in Northern India. Also included in the rule curve data are associated reservoir rationing ratios that can be applied to gross demand when rationing is also indicated. Data contain monthly Inflows, net-evaporation loss and release (all in million cubic metres, i.e. x 10^6 m^3) as simulated by WEAP for the Pong and Bhakra reservoir for the baseline (1989 - 2008); mid-century (2032-2050) and end-century (2082-2100) periods. The future inflows were based on forcing the WEAP model of the basin with climate projections of the GFDL-CM3 CMIP model The data were collected by Heriot-Watt University under the Sustaining Himalayan Water Resources in a Changing Climate (SusHi-Wat) project funded by NERC. Full details about this dataset can be found at https://doi.org/10.5285/46135938-cc6c-44a0-b35b-f6e5f5dd1221
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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
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Aquatic carbon (dissolved inorganic carbon (DIC), dissolved organic carbon (DOC) and particulate organic carbon and the carbon isotopic composition of DIC) and nutrients (calcium, magnesium, potassium, sodium, total soluble phosphorus and silica) in rainfall fractions (rainwater, throughfall, stemflow and overland flow) were sampled in the Western Amazonian basin. The samples were collected towards the end of a wet season April - May 2012. Rainfall and throughfall samples were collected in plastic buckets. Stemflow samples were collected using stemflow collection systems. Overland samples were collected using a a plastic pipe cut lengthways directing flow into a plastic bucket. Established standard methods were used to analyse the DIC, DOC and nutrients. These methods are outlined in the lineage. The samples were taken to understand the nutrient and carbon delivery in rainwater as well as leaching from tree canopies, stems and from the soil surface. The data collection was carried out as part of the Natural Environment Research Council (NERC) funded Amazonica project (NE/F005482/1). Full details about this dataset can be found at https://doi.org/10.5285/59bdb8f6-fb1f-418f-a53c-394f6c68a334
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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