|RFx ID :||25265097|
|Tender Name :||High-Resolution Digital River Network for Northland|
|Reference # :||21/24|
|Open Date :||Friday, 17 December 2021 5:00 PM (Pacific/Auckland UTC+13:00)|
|Close Date :||Tuesday, 1 February 2022 11:30 PM (Pacific/Auckland UTC+13:00)|
|Tender Type :||Request for Quotations (RFQ)|
|Tender Coverage :||Sole Agency [?]|
|Exemption Reason :||None|
|Required Pre-qualifications :||None|
|Alternate Physical Delivery Address :|
|Alternate Physical Fax Number :|
Council uses the existing national scale river network model River Environment Classification (REC) for the purpose of regional modelling. However, REC is coarse (spatial scale) and often erroneous in several parts of our region, particularly in the coastal area and at higher altitudes with complex topographical terrain. Council recently developed a regional Overland Flow Path (OLF) layer and a Hydro-Enforced Digital Elevation Model (HE-DEM) for flood modelling purposes. However, for the purpose of natural resources accounting and implementation of the National Policy Statement for Freshwater Management (NPS-FM), additional datasets are required.
In that perspective Council wants a regional Digital River Network (DRN) model (covering the geographical extend of Northland region) developed from the most recent high-resolution LiDAR dataset and/or LiDAR derivatives, which will represent the detailed flow path for most of the waterways in our region including the smaller watercourses. The new DRN will also improve council’s hydrological and water quality models and will assist in correctly delineating the capture zones for surface water bodies.
The resulting product will be an organisation-wide authoritative geospatial layer and therefore, an asset for the council. The output from this project will improve the accuracy of existing models and provide useful tools for implementing land management mitigation measures at farm scale.
Success will be measured based on the accuracy of the outputs (at a catchment level) from the new DRN compared to the existing REC model.