The International Map of the World (IMW) series is no longer maintained, and printed copies of this map are no longer available. The Australian portion of the series consists of 49 maps. They were produced to an international specification using the R502 series at 1:250,000 scale as source material. Production commenced in 1926 and was completed in 1978. The maps were revised from time to time and the last reprint was undertaken in 2003. Each standard map sheet covers 4 degrees of latitude by 6 degrees of longitude and was produced using a Lambert Conformal Conic projection with 2 standard parallels. The series has recently been superseded by the 1:1 000 000 topographic map general reference.

I. Overview The Yellow River is the second longest river in our country. The problem of the Yellow River's sediment has attracted the attention of people all over the world. Based on the vector map of the 14 million rivers in China as a base map, the upper reaches of the Yellow River basin were cut out. The vector map of the river is a key element for extracting the boundary of the basin by using the topographic map, and it is also a key element for flood evolution and sediment evolution. Ⅱ. Data processing description Using the national vector map of the 14 million rivers as the data source, it is cut out by using the boundary of the upper reaches of the Yellow River. Ⅲ. Data content description The map is stored in ArcGIS, .shp files, including vector diagrams of the main and tributaries from the source area of the Yellow River to Toudaoguai. Ⅳ. Data usage description The vector map of the river is a key element for extracting the boundary of the watershed by using the topographic map, and it is also a key element for flood evolution and sediment evolution.

The International Map of the World (IMW) series is no longer maintained, and printed copies of this map are no longer available. The Australian portion of the series consists of 49 maps. They were produced to an international specification using the R502 series at 1:250,000 scale as source material. Production commenced in 1926 and was completed in 1978. The maps were revised from time to time and the last reprint was undertaken in 2003. Each standard map sheet covers 4 degrees of latitude by 6 degrees of longitude and was produced using a Lambert Conformal Conic projection with 2 standard parallels. The series has recently been superseded by the 1:1 000 000 topographic map general reference.

The International Map of the World (IMW) series is no longer maintained, and printed copies of this map are no longer available. The Australian portion of the series consists of 49 maps. They were produced to an international specification using the R502 series at 1:250,000 scale as source material. Production commenced in 1926 and was completed in 1978. The maps were revised from time to time and the last reprint was undertaken in 2003. Each standard map sheet covers 4 degrees of latitude by 6 degrees of longitude and was produced using a Lambert Conformal Conic projection with 2 standard parallels. The series has recently been superseded by the 1:1 000 000 topographic map general reference.

Seafloor geomorphology is the study of physical features on the seafloor. This layer represents the characterizations of geomorphic features and the zones within the ocean where they occur. The data for this layer are from the first map of seafloor geomorphology ever published; this map was published 2014 by GRID Arendal.“The new seafloor features map provides a foundation on which to build an understanding of the living and non-living resources of the ocean and to improve decision making on a range of global issues like food security, resource use and conservation.” - Dr. Peter Harris, the project leader and Managing Director of GRID-Arendal.Dataset SummaryThe geomorphic features in this layer were created by automated and manual processes over the course of many months. The source data for the process is a modified 30-arc second (~1 km) resolution version of SRTM30_PLUS global bathymetry produced in 2009. The following features and zones are included as sub-layers:FeaturesCanyons - Submarine canyons are defined as steep-walled, sinuous valleys with V-shaped cross sections, axes sloping outward as continuously as river-cut land canyons and relief comparable to even the largest of land canyons.Seamounts - Seamounts are a single or group of peaks, greater than 1,000 meters in relief above the sea floor, characteristically of conical form.Guyots - Guyots are isolated or a group of seamount having a comparatively smooth flat top. Also called tablemounts.Troughs - Troughs are long depressions of the sea floor characteristically flat bottomed and steep sided and normally shallower than a trench. In this study we found that troughs are also commonly open at one end (i.e. not defined by closed bathymetric contours) and their broad, flat floors may exhibit a continuous gradient. Troughs may originate from glacial erosion processes or have form through tectonic processes.Glacial Troughs - Glacial troughs are the largest of the shelf valleys at high latitudes incised by glacial erosion during the Pleistocene ice ages to form elongate troughs, typically trending across the continental shelf and extending inland as fjord complexes. Glacial troughs are characterized by depths of over 100 m (often exceeding 1,000 m depth) and are distinguished from shelf valleys by an over-deepened longitudinal profile that reaches a maximum depth inboard of the shelf break, thus creating a perched basin on the shelf with an associated sill.Trenches - Trenches are long narrow very deep asymmetrical depressions of the sea floor, with relatively steep sides. Trenches are generally distinguished from troughs by their “V” shape in cross section (in contrast with flat-bottomed troughs). Bridges - Bridge features are blocks of material that partially infill Trenches forming a “bridge”across the trench.Sills - Sills are a sea floor barrier of relatively shallow depth restricting water movement between basins. Thus every basin has a sill, over which fluid would escape if the basin were filled to overflowing. Shelf Valleys - Shelf valleys are greater than 10 km in length and greater than 10 m in depth overall with an elongate shape more than 4 times greater in length than width.Rift Valleys - Rift valleys are confined to the central axis of mid-ocean spreading ridges; they are elongate, local depressions flanked generally on both sides by ridges.Ridges - Ridges are isolated or a group of elongated narrow elevations of varying complexity with steep sides, often separating basin features. Ridges have greater than 1,000 meters of relief.Spreading Ridges - Spreading ridges are mid-oceanic mountain systems of global extent.Terraces - Terraces an isolated or a group of relatively flat horizontal or gently inclined surface(s), sometimes long and narrow, which is (are) bounded by a steeper ascending slope on one side and by a steeper descending slope on the opposite side. Fans - Fans are relatively smooth, fan-like, depositional featured normally sloping away from the outer termination of a canyon or canyon system. Fans overlay and comprise part of the continental rise and are located offshore from the base of the continental slope. Fans are inter-related with submarine canyons and sediment drift deposits; in cases where canyon axes extend across the rise, the canyon-channels may be flanked by sediment drift deposits, which have been grouped with fans in this study. Fans are defined in the present study by 100 m isobaths that form a concentric series exhibiting an expanding spacing in a seaward direction away from the base of the slope, sometimes clearly associated with a canyon mouth, but also comprising low-relief ridges between canyon-channels on the abyssal plain.Rises - Continental rises are areas with sediment thickness greater than 300 meters and the occurrence of a smooth sloping seabed as indicated by evenly-spaced, slope-parallel contours. In this study, the term “Rise” was restricted to features that abut continental margins and does not include the mid-ocean ridge.Plateaus - Plateaus are flat or nearly flat elevations of considerable areal extent, dropping off abruptly on one or more sides. TerrainMountains - Greater than 1,000 meters of local relief within ~25 kilometers.Hills - Between 300 and 1,000 meters of local relief within ~25 kilometers.Plains - Less than 300 meters of local relief within ~25 kilometers.Basins - Basins are depressions in the sea floor that are more or less equi-dimensional in plan, of variable extent, and are restricted to seafloor depressions defined by closed bathymetric contours.Escarpments - Escarpments are “an elongated, characteristically linear, steep slope separating horizontal or gently sloping sectors of the sea floor in non-shelf areas. Also abbreviated to scarp” (IHO, 2008). Escarpments, like basins, overlay other features (i.e. other individual features may be partly or wholly covered by escarpments). Thus features like the continental slope, seamounts, guyots, ridges and submarine canyons (for example) may be sub-classified in terms of their area of overlain escarpment.ZonesShelf - The zone adjacent to the continents or islands. Slope - The deepening seafloor from the edge of the shelf to the top of the continental rise.Abyss - Areas below the foot of the continental rise and includes all depths up to 6,000 meters.Hadal - Depths greater than 6,000 metersNote that the above definitions are brief summarizations of the definitions contained in Geomorphology of the Oceans.Esri staff edited several of the layers: Zones, Terrain, Basins, and Glacial Troughs to improve drawing performance. All of these edits were split polygon operations; no vertexes were moved, only at cut points were vertexes introduced. If these layers are downloaded, these edits can be removed by using the Dissolve tool, with all fields, including shape, and producing no multi-part polygons in the output.For metadata info, please see Bluehabitats.org.What can you do with this layer?This layer is based on a dynamic map service, which means there are several sub-layers of vector features that can be used for visualization and analysis throughout the ArcGIS Platform. This layer is not editable.This layer is part of a larger collection of Oceans layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about oceans layers and the Living Atlas of the World. To get started see the Living Atlas Discussion Group.

Note: This layer does not have clickable pop-ups at this time.Watersheds, also called drainage or catchment basins, are areas of land where precipitation drains into a common body of water such as a lake, river, or ocean. This includes precipitation from clouds like rain or snow, groundwater, and other bodies of water within the basin. Watersheds are powerful components of the natural landscape, and it is important to understand the factors that impact their condition. The size and shape of a drainage basin is determined by many features of its landscape. Often, the first that comes to mind is an area’s topography. The steepness of hills and mountains, along with the distance between a precipitation source and bodies of water, also determine how quickly it reaches its destination. Additionally, different soil types impact water movement, with some types (like sand) much more permeable than others (like clay). If the surface is too impermeable for precipitation to reach the soil in the first place, which is the case in developed areas covered by roofs and pavement, it forms runoff and reaches bodies of water without spending time as groundwater. Extremely large drainage areas are made of a number of tributary basins, which collect precipitation in streams and then deliver water to the major rivers. Watersheds can be made of any number of smaller drainage basins, which is called a river system.The elevated boundary between areas drained by different basins is called a divide, and a continental divide completely separates large river systems to different regions of a continent. In North and South America, the Great Continental Divide runs along the peaks of the Rocky Mountains and Andes, with water to the west running into the Pacific Ocean and to the east into the Atlantic. Another continental divide exists along the Himalayan Mountains in South Asia and continues along the coast of the Arabian Peninsula and eastern Africa, directing precipitation into the Indian Ocean. On the other side of this divide, to the north of the Himalayas, exists a feature called an endorheic basin—in these regions, precipitation never reaches an ocean, but is retained in a smaller body of water like a lake or inland sea.Knowing the extent of watersheds is important for both natural and sociopolitical reasons. Scientists interested in hydrology and ecology often study entire drainage basins because the majority of the precipitation, sediments, nutrients, and pollutants flowing through a watershed originated there, too. Many conservation efforts protect watersheds as holistic units as well, called watershed management, and some countries and states even have governing bodies for basins in their territory. In the field of geopolitics, the study of how international relations are influenced by geographical factors, watersheds can be the cause of conflict or of harmony through mutual governance and accountability.This map layer was created using a model that predicts water flow with elevation data. It separates one watershed into two, by predicting flow then using GIS to add additional information to the model such as catchment boundaries, lake shorelines, and rivers.Each time a divide is created, the model makes a new level—these levels are called hydrologic units. Hydrologic units break the globe up into regions, subregions, basins, subbasins, watersheds and sub watersheds. Each hydrologic unit has a unique code called a hierarchical hydrologic unit code (HUC). Regions, for example, have a two-digit code. An additional two digits are added for each subsequent scale until sub watersheds, which has twelve digits. Not all of the watersheds are clickable at this time. Check back as we add data for areas outside the United States.Watershed conservation is a very important part of keeping water clean and safe. The Nature Conservancy explains that there are a lot of ways to help protect your watersheds, like conserving water, disposing of waste and chemicals safely, or choosing to walk or bike instead of drive. Add the Protected Areas layer to the map to find the areas of your watershed that need special care.

Geomorphological map of the Sutlej and Yamuna fans, northwestern India. Grant abstract: India is the largest agricultural user of groundwater in the world. The last 40 years has seen a revolutionary shift from large-scale surface water management to widespread groundwater abstraction, particularly in the northwestern states of Punjab, Haryana and Rajasthan. As a result of this, northwestern India is now a hotspot of groundwater depletion, with 'the largest rate of groundwater loss in any comparable-sized region on Earth' (Tiwari et al., 2009). This unsustainable use of groundwater becomes even more challenging when set increasing demands from a burgeoning population and industrialisation, together with potential but poorly understood effects of climate-driven changes in the water cycle. There are a number of innovative socio-economic strategies that can address this issue, including enhanced recharge and subsurface water storage, but their implementation and success depend on solid regional understanding of the geology and hydrogeology of the aquifer systems, and of the patterns and rates of groundwater flow and recharge. What we know about regional groundwater resources comes largely from either low-resolution studies based on satellite data, or from local investigations; there has been no large-scale, cross-state integrated study of the groundwater system. Groundwater in northwestern India is thought to be largely hosted within buried, sandy former river channels, which extend from the Himalayas toward the southwest and are separated by fine-grained muds. Only a few channels are visible at the surface; most are buried and their existence must be inferred. Our approach is founded on the premise that we must first understand the geology and geometry of the aquifer system before we can hope to estimate the way it will respond to a complex set of future stresses. This means that we must be able to describe the locations, sizes, and characteristics of these channels as well as their age and three-dimensional pattern. Once these characteristics are determined, we can forecast the likely future behaviour of the system. In this proposal, we will provide, for the first time, a regional assessment of the aquifer system in northwestern India, along with models for its evolution under changes in the water cycle and in the way in which groundwater is used. Our project will combine expertise in sedimentology, stratigraphy, sediment routing and basin evolution, hydrology, and isotope geochemistry to understand the geological framework of the aquifer system, the ages of the groundwaters within it, and the ways in which groundwater levels are likely to evolve over the next 50 years. The outcomes of the proposal will include (1) a comprehensive data base that covers the northwestern Indian aquifer system, (2) much better understanding of regional sources, ages, and flow rates of groundwater, and (3) a suite of predictions for how the groundwater system will respond to a range of different future scenarios.

The Global River Topology (GRIT) is a vector-based, global river network that not only represents the tributary components of the global drainage network but also the distributary ones, including multi-thread rivers, canals and delta distributaries. It is also the first global hydrography (excl. Antarctica and Greenland) produced at 30m raster resolution. It is created by merging Landsat-based river mask (GRWL) with elevation-generated streams to ensure a homogeneous drainage density outside of the river mask (rivers narrower than approx. 30m). Crucially, it uses a new 30m digital terrain model (FABDEM, based on TanDEM-X) that shows greater accuracy over the traditionally used SRTM derivatives. After vectorisation and pruning, directionality is assigned by a combination of elevation, flow angle, heuristic and continuity approaches (based on RivGraph). The network topology (lines and nodes, upstream/downstream IDs) is available as layers and attribute information in the GeoPackage files (readable by QGIS/ArcMap/GDAL).

A map of GRIT segments labelled with OSM river names is available here: https://michelwortmann.com/research/gritv05-segments-river-names/

Regions

Vector files are provided in 7 regions with the following codes:

• AF - Africa
• AS - Asia (excl. Siberia)
• EU - Europe
• NA - North America
• SA - South America
• SI - Siberia
• SP - South Pacific/Australia

The domain polygons (GRITv04_domain_GLOBAL.gpkg.zip) provide 60 subcontinental catchment groups that are available as vector attributes. They allow for more fine-grained subsetting of data (e.g. with ogr2ogr --where and the domain attribute).

Vector files are provided both in the original equal-area Equal Earth Greenwich projection (EPSG:8857) as well as in geographic WGS84 coordinates (EPSG:4326).

Network segments

Lines between inlet, outlet, confluence and bifurcation nodes. Files have lines and nodes layers.

Attribute description of lines layer

Name	Data type	Description
cat	integer	domain internal feature ID
global_id	integer	global river segment ID, same as FID
catchment_id	integer	global catchment ID
upstream_node_id	integer	global segment node ID at upstream end of line
downstream_node_id	integer	global segment node ID at downstream end of line
upstream_line_ids	text	comma-separated list of global river segment IDs connecting at upstream end of line
downstream_line_ids	text	comma-separated list of global river segment IDs connecting at downstream end of line
direction_algorithm	float	code of RivGraph method used to set the direction of line
width_adjusted	float	median river width in m without accounting for width of segments connecting upstream/downstream
length_adjusted	float	segment length in m without accounting for width of segments connecting upstream/downstream in m
is_mainstem	integer	1 if widest segment of bifurcated flow or no bifurcation upstream, otherwise 0
strahler_order	integer	Strahler order of segment, can be used to route in topological order
length	float	segment length in m
azimuth	float	direction of line connecting upstream-downstream nodes in degrees from North
sinuousity	float	ratio of Euclidean distance between upstream-downstream nodes and line length, i.e. 1 meaning a perfectly straight line
drainage_area_in	float	drainage area at beginning of segment, partitioned by width at bifurcations, in km2
drainage_area_out	float	drainage area at end of segment, partitioned by width at bifurcations, in km2
drainage_area_mainstem_in	float	drainage area at beginning of segment, following the mainstem, in km2
drainage_area_mainstem_out	float	drainage area at end of segment, following the mainstem, in km2
bifurcation_balance_out	float	(drainage_area_out - drainage_area_mainstem_out) / max(drainage_area_out, drainage_area_mainstem_out), dimensionless ratio
grwl_overlap	float	fraction of the segment overlapping with the GRWL river mask
grwl_value	integer	dominant GRWL value of segment
name	text	river name from Openstreetmap where available, English preferred
name_local	text	river name from Openstreetmap where available, local name
n_bifurcations_upstream	integer	number of bifurcations upstream of segment
domain	text	catchment group ID, see domain index file

Attribute description of nodes layer

Name	Data type	Description
cat	integer	domain internal feature ID
global_id	integer	global river node ID, same as FID
catchment_id	integer	global catchment ID
upstream_line_ids	text	comma-separated list of global river segment IDs flowing into node
downstream_line_ids	text	comma-separated list of global river segment IDs flowing out of node
node_type	text	description of node, one of bifurcation, confluence, inlet, coastal_outlet, sink_outlet, grwl_change
grwl_value	integer	GRWL code at node
grwl_transition	text	GRWL codes of change at grwl_change nodes
cycle	integer	>0 if segment is part of an unresolved cycle, 0 otherwise
continuity_violated	integer	1 if flow continuity is violated, otherwise 0
drainage_area	float	drainage area, partitioned by width at bifurcations, in km2
drainage_area_mainstem	float	drainage area, following the mainstem, in km2
n_bifurcations_upstream	integer	number of bifurcations upstream of node
domain	text	catchment group, see domain index file

Network reaches

Segment lines split to not exceed 1km in length, i.e. these lines will be shorter than 1km and longer than 500m unless the segment is shorter. A simplified version with no vertices between nodes is also provided. Files have lines and nodes layers.

Attribute description of lines layer

Name	Data type	Description
cat	integer	domain internal feature ID
segment_id	integer	global segment ID of reach
global_id	integer	global river reach ID, same as FID
catchment_id	integer	global catchment ID
upstream_node_id	integer	global reach node ID at upstream end of line
downstream_node_id	integer	global reach node ID at downstream end of line
upstream_line_ids	text	comma-separated list of global river reach IDs connecting at upstream end of line
downstream_line_ids	text	comma-separated list of global river reach IDs connecting at downstream end of line
grwl_overlap	float	fraction of the reach overlapping with the GRWL river mask
grwl_value	integer	dominant GRWL value of node
grwl_width_median	float	median width of the GRWL river mask, meters
grwl_width_std	float	standard deviation of width of the GRWL river mask, meters
length	float	length of reach in meters
sinuousity	float	ratio of eucledian distance betwen upstream-downstream nodes and line length, i.e. 1 meaning a perfectly straight line
azimuth	float	direction of line connecting upstream-downstream nodes in degrees from North
domain	text	catchment group, see domain index file

Attribute description of nodes layer

Name	Data type	Description
cat	integer	domain internal feature ID
segment_node_id	integer	global ID of segment node at segment intersections, otherwise blank
n_segments	integer	number of segments attached to node
global_id	integer	global river reach node ID,

Awash river basin boundary is derived from the HydroBASINS product, which was obtained by delineating drainage basin boundaries from hydrologically corrected elevation data (WWF HydroSHEDS, Lehner et al. 2008; Lehner and Grill 2013) and supported by the topological concept of the Pfafstetter coding system (Verdin & Verdin 1999). Source: The HydroBASINS product has been developed on behalf of World Wildlife Fund US (WWF), with support and in collaboration with the EU BioFresh project, Berlin, Germany; the International Union for Conservation of Nature (IUCN), Cambridge, UK; and McGill University, Montreal, Canada. Major funding for this project was provided to WWF by Sealed Air Corporation; additional funding was provided by BioFresh and McGill University. Citations and acknowledgements of the HydroBASINS data should be made as follows: Lehner, B., Grill G. (2013): Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrological Processes, 27(15): 2171–2186. Data is available at www.hydrosheds.org.

A Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDET) This is a Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDET) developed by the Surface Dynamics and Modeling Lab at the University of Alabama that calculates flood depth using a flood extent layer and a digital elevation model. This research is made possible by the CyberSeed Program at the University of Alabama. Project name: WaterServ: A Cyberinfrastructure for Analysis, Visualization and Sharing of Hydrological Data. Please see the associated publications: 1. Peter, B.G., Cohen, S., Lucey, R., Munasinghe, D., Raney, A. and Brakenridge, G.R., 2020. Google Earth Engine Implementation of the Floodwater Depth Estimation Tool (FwDET-GEE) for rapid and large scale flood analysis. IEEE Geoscience and Remote Sensing Letters, 19, pp.1-5. https://ieeexplore.ieee.org/abstract/document/9242297 2. Cohen, S., Peter, B.G., Haag, A., Munasinghe, D., Moragoda, N., Narayanan, A. and May, S., 2022. Sensitivity of remote sensing floodwater depth calculation to boundary filtering and digital elevation model selections. Remote Sensing, 14(21), p.5313. https://github.com/csdms-contrib/fwdet 3. Cohen, S., A. Raney, D. Munasinghe, J.D. Loftis J, A. Molthan, J. Bell, L. Rogers, J. Galantowicz, G.R. Brakenridge7, A.J. Kettner, Y. Huang, Y. Tsang, (2019). The Floodwater Depth Estimation Tool (FwDET v2.0) for Improved Remote Sensing Analysis of Coastal Flooding. Natural Hazards and Earth System Sciences, 19, 2053–2065. https://doi.org/10.5194/nhess-19-2053-2019 4. Cohen, S., G. R. Brakenridge, A. Kettner, B. Bates, J. Nelson, R. McDonald, Y. Huang, D. Munasinghe, and J. Zhang (2018), Estimating Floodwater Depths from Flood Inundation Maps and Topography, Journal of the American Water Resources Association, 54 (4), 847–858. https://doi.org/10.1111/1752-1688.12609 Sample products and data availability: https://sdml.ua.edu/models/fwdet/ https://sdml.ua.edu/michigan-flood-may-2020/ https://cartoscience.users.earthengine.app/view/fwdet-gee-mi https://alabama.app.box.com/s/31p8pdh6ngwqnbcgzlhyk2gkbsd2elq0 GEE implementation output: fwdet_gee_brazos.tif ArcMap implementation output (see Cohen et al. 2019): fwdet_v2_brazos.tif iRIC validation layer (see Nelson et al. 2010): iric_brazos_hydraulic_model_validation.tif Brazos River inundation polygon access in GEE: var brazos = ee.FeatureCollection('users/cartoscience/FwDET-GEE-Public/Brazos_River_Inundation_2016') Nelson, J.M., Shimizu, Y., Takebayashi, H. and McDonald, R.R., 2010. The international river interface cooperative: public domain software for river modeling. In 2nd Joint Federal Interagency Conference, Las Vegas, June (Vol. 27). Google Earth Engine Code /* ---------------------------------------------------------------------------------------------------------------------- # FwDET-GEE calculates floodwater depth from a floodwater extent layer and a DEM Authors: Brad G. Peter, Sagy Cohen, Ronan Lucey, Dinuke Munasinghe, Austin Raney Emails: bpeter@ua.edu, sagy.cohen@ua.edu, ronan.m.lucey@nasa.gov, dsmunasinghe@crimson.ua.edu, aaraney@crimson.ua.edu Organizations: BP, SC, DM, AR - University of Alabama; RL - University of Alabama in Huntsville Last Modified: 10/08/2020 To cite this code use: Peter, Brad; Cohen, Sagy; Lucey, Ronan; Munasinghe, Dinuke; Raney, Austin, 2020, "A Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDET-GEE)", https://doi.org/10.7910/DVN/JQ4BCN, Harvard Dataverse, V2 ------------------------------------------------------------------------------------------------------------------------- This is a Google Earth Engine implementation of the Floodwater Depth Estimation Tool (FwDETv2.0) [1] developed by the Surface Dynamics and Modeling Lab at the University of Alabama that calculates flood depth using a flood extent layer and a digital elevation model. This research is made possible by the CyberSeed Program at the University of Alabama. Project name: WaterServ: A Cyberinfrastructure for Analysis, Visualization and Sharing of Hydrological Data. GitHub Repository (ArcMap and QGIS implementations): https://github.com/csdms-contrib/fwdet ------------------------------------------------------------------------------------------------------------------------- How to run this code with your flood extent GEE asset: User of this script will need to update path to flood extent (line 32 or 33) and select from the processing options. Available DEM options (1) are USGS/NED (U.S.) and USGS/SRTMGL1_003 (global). Other options include (2) running the elevation outlier filtering algorithm, (3) adding water body data to the inundation extent, (4) add a water body data layer uploaded by the user rather than using the JRC global surface water data, (5) masking out regular water body data, (6) masking out 0 m depths, (7) choosing whether or not to export, (8) exporting additional data layers, and (9) setting an export file name....

HD model parameter files

This dataset comprises global parameter data that are necessary to run the Hydrological Discharge (HD) model, which has been published on Zenodo. The HD model calculates the lateral transport of water over the land surface to simulate discharge into the oceans. The HD model parameter dataset comprises parameter fields at 0.5° global resolution and at 5 Min. resolution (global, Europe). Details for both resolutions are provided below.

Authors: Stefan Hagemann, Tobias Stacke
Copyright 2021: Institute of Coastal Systems - Analysis and Modelling, Helmholtz-Zentrum Hereon
License: under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0; https://creativecommons.org/licenses/)

HD model parameter file at 5 Min resolution: hdpara_vs5_0.nc

River directions and digital elevation data were provided by Bernhard Lehner (pers. comm., 2014) and were derived from the HydroSHEDS (Lehner et al., 2006) database and from the Hydro1K dataset for areas north of 60°N (https://lta.cr.usgs.gov/HYDRO1K).
For a number of rivers (most of them north of 60°N), flow directions and model orography were manually corrected based on available GIS data, such as from DIVA (https://www.diva-gis.org/gdata), CCM River and Catchment Database
(Vogt et al. 2007), SMHI (Swedish Meteorological and Hydrological Institute), NVE (Norges vassdrags- og energidirektorats), SYKE (Finnish Environment Institute).

This corrected dataset is referred to as HDvs5 in the following.
The HD model parameters for overland flow, base flow and river flow are generated as described in Hagemann and Dümenil (1998) and Hagemann et al. (2020). However, different to the HD model vs. 4 described in Hagemann et al. (2020), Vs5 utilizes inland water fractions from the ESA CCI Water Bodies Map v4.0 (Lamarche et al. 2017) and wetland fractions from the Global Lakes and Wetlands Database (Lehner and Döll 2004) instead of the previously used lake and wetlands fractions.

The HD parameter dataset contains 14 variables which are shortly described in the following table.

• FLAG | Land sea mask | -
• FDIR | Flow direction | - | defined as written below
• ALF_K | HD model parameter Overland flow k | d-1
• ALF_N | HD model parameter Overland flow n | -
• ARF_K | HD model parameter Riverflow k | d-1
• ARF_N | HD model parameter Riverflow n | -
• AGF_K | HD model parameter Baseflow flow k | d-1
• AREA | Grid cell area | m-2 | based on own computation
• FILNEW | River flow target indices for longitudes | -
• FIBNEW | River flow target indices for latitudes | -
• DISTANCE | Distance between gridboxes in flow direction | m
• RIVERLENGTH | Distance between gridbox and the river mouth (or final sink) | km
• CAT_AREA | Upstream catchment area of gridbox | km²
• CAT_ID | Catchment ID of gridbox | -

Flow directions in variable FDIR are defined as on the Num Pad of a PC keyboard:

• 7 8 9
• \ | /
• \|/
• 4--5--6
• /|\
• / | \
• 1 2 3

Special directions: 5 = Sink point, i.e. no outflow
0 = River mouth point in the ocean
-1 = Ocean point, but no river mouth

Forcing data masks file: masks_5min.nc

In the offline HD model version, this file is usually only used to obtain the grid information of the forcing data, i.e. of surface runoff and drainage (subsurface runoff). However, it contains four variables that are read in by the model, and that are actually used un coupled applications within the MPI-ESM. Even though these variables are not used in the HD model offline version, it was decided to keep them in order to allow future developments regarding the usage of these data and to keep some consistency with the HD model code implemented in MPI-ESM.

• ALAKE | Lake fraction within a grid box | Lamarche et al. 2017
• GLAC | Glacier fraction within a grid box | Hagemann 2002
• SLF | Land fraction within a grid box | Lamarche et al. 2017
• SLM | Land Sea Mask | Lamarche et al. 2017

For simplicity, the data provided at the HD model resolution. Hence, these masks can be used when the forcing data are interpolated to the HD model resolution before they are read during the model run.

This tar archive also include a subset of this global dataset for the European domain, hdpara_vs5_0_euro5min.nc.

HD model parameter file at 0.5° resolution: hdpara_vs1_10_ext.nc

In addition, a global 0.5° HD parameter file (hdpara_vs1_10_ext.nc) is included that is consistent to the parameter files used in previous offline and coupled applications of the HD model at 0.5° resolution (see, e.g. studies cited in Sect. 2.1 of Hagemann et al., 2020). Compared to previous versions, only some flow directions (mainly over Europe) have been updated for version 1.10. Except for DISTANCE and RIVERLENGTH, it comprises the same variables as for the 5 Min. version, but flow directions and parameters are generated as described in Hagemann and Dümenil (1998) and Hagemann and Dümenil Gates (2001). Here, the 0.5 degree mask file mask_05.nc comprises those masks that were utilized in the HD parameter generation. Only the land fraction is taken from Hagemann (2002) where the HD land sea mask indicates land.

References

• Hagemann, S., L. Dümenil (1998) A parameterization of the lateral waterflow for the global scale. Clim. Dyn. 14 (1), 17-31
• Hagemann, S., L. Dümenil Gates (2001) Validation of the hydrological cycle of ECMWF and NCEP reanalyses using the MPI hydrological discharge model, J. Geophys. Res. 106, 1503-1510
• Hagemann, S., 2002: An improved land surface parameter dataset for global and regional climate models, MPI Report No. 336, Max Planck Institute for Meteorology, Hamburg, Germany
• Hagemann, S., T. Stacke and H. Ho-Hagemann (2020) High resolution discharge simulations over Europe and the Baltic Sea catchment. Front. Earth Sci., 8:12. doi: 10.3389/feart.2020.00012.
• Lamarche, C., Santoro, M., Bontemps, S., d’Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O. (2017) Compilation and validation of SAR and optical data products for a complete and global map of inland/ocean water tailored to the climate modeling community. Remote Sensing, 9(1), p.36.
• Lehner, B., P. Döll (2004) Development and validation of a global database of lakes, reservoirs and wetlands.
• J. Hydrol., 296: 1-22, doi:10.1016/j.jhydrol.2004.03.028.
• Vogt, J.V. et al. (2007): A pan-European River and Catchment Database. European Commission - JRC, Luxembourg, (EUR 22920 EN) 120 pp.

This data set estimates large-scale wetland distributions and important wetland complexes, including areas of marsh, fen, peatland, and water (Lehner and Döll 2004). Large rivers are also included as wetlands (lotic wetlands); it is assumed that only a river with adjacent wetlands (floodplain) is wide enough to appear as a polygon on the coarse-scale source maps. Wetlands are a crucial part of natural infrastructure as they help protect water quality, hold excess flood water, stabilize shoreline, and help recharge groundwater (Beeson and Doyle 1995, Stuart and Edwards 2006). Limited by sources, the data set refers to lakes as permanent still-water bodies (lentic water bodies) without direct connection to the sea, including saline lakes and lagoons as lakes, while excluding intermittent or ephemeral water bodies. Lakes that are manmade are explicitly classified as reservoirs. The Global Lakes and Wetlands Database combines best available sources for lakes and wetlands on a global scale. This data set includes information on large lakes (area ≥ 50 km2) and reservoirs (storage capacity ≥ 0.5 km3), permanent open water bodies (surface area ≥ 0.1 km2), and maximum extent and types of wetlands.

Purpose of the Caribbean Ecoregional AssessmentThe Caribbean is one of the worlds epicenters of biological diversity and species endemism with literally thousands of plants and animals found nowhere else on earth. Conservation has proven a challenge in this large, diverse, and globally-important area one the Nature Conservancy is addressing through a strong on-the-ground presence led by country programs that have science-based conservation strategies. To address these problems and opportunities, The Nature Conservancy initiated a Regional Conservation Assessment for the Greater Caribbean Basin, designed to examine regional biodiversity and the associated threats and conservation opportunities. This follows a worldwide trend of recognizing the need to examine about and manage for the maintenance of functioning ecosystem processes and populations across appropriately large regions to help slow widespread environmental changes. To facilitate this approach, we have assembled, into a standard, seamless GIS database, the biological and socio-economic data necessary to analyze the regional-scale context of Caribbean biodiversity.We identified and mapped a range of coarse-filter targets that represent a full spectrum of terrestrial, freshwater and marine biodiversity using combinations of biophysical factors (such as climate, geology, major habitat type, elevation, depth etc.). Mapping Caribbean biodiversity provides the basis for conservation decision making. Coarse-filter mapping at the level of ecological communities, ecosystems and landscapes is an efficient method to represent all essential elements of biodiversity across the entire region. We assessed human impact in two ways: expert judgments and mapping of the relative intensity of human impacts. Local experts provided judgments on the condition of targets and this information is combined with maps of human activities in order to determine relative human impacts. Distribution of human activities is a critical factor in conservation and resource management. Not all human activities are threats to biodiversity and determining relative human impact and predicting ecological health is necessary for sound management. We suggest that by providing the latest analytical tools and comprehensive biodiversity and socio-economic data, we can assist conservation organizations, local communities and governments that are striving to meet their national or local conservation missions and leverage and enhance ongoing conservation efforts. These data and tools can be used to enable sound, pragmatic conservation decisions at-scale. In this way, this assessment will serve to enhance and unify ongoing local and national conservation efforts and provide a common vision of conservation success throughout the Greater Caribbean. We suggest that use of the data and tools can facilitate strategic partnerships amongst both local and regional organizations across the basin a key to achieving lasting results. We hope to put in place a long-term information system that promotes the protection of the regions irreplaceable terrestrial, freshwater, coastal and marine biodiversity. We have designed simple data management systems to promote long-term use and dynamic updates of the database. Information is archived in a standardized structure on a freely accessible spatial warehouse using simple, robust systems that are easily and accessible to partners and stakeholders. Standardization and open access promotes updateable archiving systems so that new information can be easily integrated and compared with existing information and also facilitations information sharing and collaboration.