The Rijkswaterstaat historical time series data can be accessed via Waterbase. Waterbase is a mechanism that provides a web-service for a subset of the DONAR (in Dutch:Data Opslag NAtte Rijkswaterstaat) database that contains all historical data for all water-related Rijkswaterstaat affairs. MWTL is the name of the monitoring programme (in Dutch: Monitoring Waterstaatkundige Toestand des Lands Milieumeetnet rijkswateren) DONAR also contains grids, lines etc. For these non time series data see the links on Rijkswaterstaats waterdata_waterberichtgeving, this also includes Near Real Time (NRT) data in a geoviewer. NRT data feeds are available via www.rws.nl/rws/opendata. Much information on RIjkswaterstaat data is also present in the HelpDeskWater. Currently Rijkswaterstaat is working on updating the IT infrastructure to connect everything via an internal Data Distribution Layer.
The waterbase menu is in fact only a macro to construct a url that is subsequently called to download the data. Passing a command to a server via a url is a so-called web service. The web service urls to download the data can also be constructed without the macro, and be called directly from other programs, for instance by Matlab. The syntax for the waterbase urls is fairly simple. For instance, to download the water levels from Katwijk in in the 18th century you can use this url. This url consists of a base-url followed by ampersand(&)-separated keywords.
http://live.waterbase.nl/wboutput.cfm? loc=KATWK &wbwns=1|Waterhoogte+in+cm+t.o.v.+normaal+amsterdams+peil+in+oppervlaktewater &byear=1737&bmonth=01&bday=01 &eyear=1808&emonth=01&eday=01 &output=Tekst &whichform=2
The method to pass command via url keywords is the typical for web services, and has the same syntax-grammer same as the international OGC WMS and WCS standards used for grids. For time series there is no internationally accepted and implemented set of keywords yet (WFS and SOS will do). Ampersand-separated keywords are also used in the operational Matroos system of Rijkswaterstaat.
rws_waterbase_load.mand (ii) a python tool box. We recommend to choose the text files from Waterbase, and not the Excel files. The Excel files are not real (binary) Excel files, but are tab-delimited ascii files. This means that they do load well into Excel directly, but also that you cannot read them into Matlab with
rws_waterbase_get*.m. Together with the aforementioned function to parse the ascii files (
rws_waterbase_load.m), this forms a complete toolbox to work with MWTL data in Matlab.
rws_waterbase*.mtoolbox for Matlab. In addition, for use of the MWTL data in other analysis programs such as R and Python the
rws_waterbase*.mtoolbox is of no use. For both analysis languages, dedicated parse functions have to be programmed as well. Therefore, we extended the
rws_waterbase*.mtoolbox, so that it not only downloads the data in batch mode, but transforms the data to an internationally standardized format that can readily be used by R and python as well in addition to Matlab: netCDF-CF. This resulted in a complete workflow in Matlab that downloads Waterbase data automatically using the above mentioned web service urls, parses them into Matlab memory with
rws_waterbase_load.m, and uses
rws_waterbase2nc.mto save them as a netCDF-CF file , and adding preliminary Aquo meta-data. These netCDF files are made available on our open OPeNDAP server opendap.deltares.nl. We update this OpeNDAP server manually periodically. For easy querying, we harvest all meta-data, and cache that as a separate netCDF file called catalog.nc. We are planning to cache the meta-data also as a catalog.xml file, that can readily be ingested by meta-data servers such as geonetwork. As a final step we make an overview of all stations for one parameter in a kml file, aka known as Google Earth file. The Matlab script
rws_waterbase_all.mperforms this entire workflow. It is run periodically to update our OPeNDAP server and kml server (see Figure below).