In this paper, we present Geo-MHYDAS, a landscape discretization tool that allows explicit representation of landscape features, particularly man-made ones, that are known to have a great impact on water and mass flows across the landscape. Well) Well HydroID = 2791ġ8 Raster Series Raster datasets indexed by timeĮach raster represents a continuous surface describing a variable for a given time over an area of interest 1991 1992 1993Īrc Hydro Groundwater Wells and Time series demoĢ5 Wells and 3D data 3D data is referenced along the wellįrom depth (top) – To depth (bottom) From ToĢ6 3D features (BorePoints and BoreLines)Ĭombining the well geometry (x, y) and the vertical measurements we can describe a set of 3D geometries (x, y, z) 146 128 -60 41 -81 750 -140 -217 -372 -433 Georgetown Fm.The representation of landscape variabilities by means of an adequate landscape discretization is of major importance in distributed hydrological modeling. In many cases collected and stored separately Store, visualize, and analyze in the same context Well in the Edwards Aquifer (state well ) Streamflow Gage at Comal Springs, New Braunfels TexasįeatureID of the time series = HydroID of the spatial feature (e.g. The Well location is defined as a 2D point in the Well feature class In the Arc Hydro model we only predefine a set of basic attributes Wells in the Edwards Aquifer

MODFLOW Analyst Import MODFLOW simulations Visualization Post-processing Build modelsġ1 Framework Surface water Groundwater Temporalġ2 Aquifer features An aquifer is defined by one or a set of polygon features Aquifer features can be grouped by HGUID Subsurface Analyst Borehole management Borehole visualization Cross-sections GeoVolumes 1 Arc Hydro GroundWater Data Model and ToolsĢ Company Background Software development Training ConsultingĮxtension to Arc Hydro, originally published in 2002 by David Maidment and ESRI Press Data model and tools are developed by Aquaveo in partnership with ESRIĦ Groundwater Analyst Wells Time Series Import Data

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