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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>RiBaSE: A Pilot for Testing the OGC Web Services Integration of Water-related Information and Models</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Lluís Pesquer Mayos</string-name>
          <email>l.pesquer@creaf.uab.cat</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Christoph Stasch</string-name>
          <email>c.stasch@52north.org</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Simon Jirka</string-name>
          <email>s.jirka@52north.org</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>David Arctur</string-name>
          <email>david.arctur@utexas.edu</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>52°North Initiative for Geospatial Open Source Software GmbH 48155 Münster</institution>
          ,
          <country country="DE">Germany</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>52°North Initiative for Geospatial Open Source Software GmbH 48155 Münster</institution>
          ,
          <country country="DE">Germany</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Center for Research in Water Resources, University of Texas at Austin 10100</institution>
          <addr-line>Burnet Rd Bldg 119, Austin, TX</addr-line>
          <country country="US">USA</country>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Grumets Research Group CREAF Edicifi C, Universitat Autònoma de Barcelona 08193 Bellaterra</institution>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff4">
          <label>4</label>
          <institution>Joan Masó Pau, Grumets Research Group CREAF Edicifi C, Universitat Autònoma de Barcelona Bellaterra</institution>
          ,
          <country country="ES">Spain</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>-The design of an interoperability experiment to demonstrate how current ICT-based tools and water data can work in combination with geospatial web services is presented. This solution is being tested in three transboundary river basins: Scheldt, Maritsa and Severn. The purpose of this experiment is to assess the effectiveness of OGC standards for describing status and dynamics of surface water in river basins, to demonstrate their applicability and finally to increase awareness of emerging hydrological standards as WaterML 2.0. Also, this pilot will help in identifying potential gaps in OGC standards in water domain applications, applied to a flooding scenario in present work.</p>
      </abstract>
      <kwd-group>
        <kwd>Interoperabilty</kwd>
        <kwd>WaterML</kwd>
        <kwd>flood modeling</kwd>
        <kwd>river basin management</kwd>
        <kwd>OGC</kwd>
        <kwd>WPS</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>INTRODUCTION</p>
      <p>There are several standardization committees and
international organizations relevant for water domain
Information Technology (IT) applications: International
Organization for Standardization (ISO), World Wide Web
Consortium (W3C), Institute of Electrical and Electronics
Engineers (IEEE), Organization for the Advancement of
Structured Information Standards (OASIS), Open Geospatial
Consortium (OGC), Internet Engineering Task Force (IETF),
etc. Related to the Infrastructure for Spatial Information in
Europe (INSPIRE), the OGC is one of the main players (with
the ISO TC211) providing standardized specifications of
spatial information and interoperability of the corresponding
spatial data services.</p>
      <p>
        The OGC is an international industry consortium of
companies, government agencies and universities participating
in a consensus process to develop publicly available interface
standards. Some successful examples of OGC standards for
general spatial purposes are, for example, the Web Map
Service (WMS) for providing interoperable pictorial maps
over the web and the Keyhole Markup Language (KML) as a
data format for virtual globes. On the other hand,
specializations of common OGC standards for the water
domain, such as WaterML 2.0, a model and exchange format
for water observations and metadata, are not yet as widely
used as the veteran WMS standard. Hence, supporting tools
such as an official WaterML validator are not yet available [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]
in the OGC compliance program [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ]. Notwithstanding, some
current efforts are progressing in this sector, e.g. the Sensor
Web Enablement (SWE), where the corresponding working
group develops standards to integrate sensors into the
Geospatial Web [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ]; and a second example is the WMO
Hydrology Domain Working Group that close collaborates
with the World Meteorological Organization (WMO)
Commission for Hydrology [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ]. Furthermore, the level of
interoperability that may be achieved using these standards in
different application scenarios and study areas has not yet
been fully evaluated, specifically the lack of interoperability
between information provided by sensors and the processing
services and alerts.
      </p>
      <p>European directives such as INSPIRE, the Water
Framework Directive (WFD), or the EU Floods Directive
(Directive 2007/60/EC), as well as agendas and roadmaps
include many recommendations in terms of harmonization,
standardization and interoperability goals. They indeed raise
very important challenges for progressing in these issues. In
particular, the water sector needs standards for:
•
•
•
•</p>
      <p>Exchange of geographic information at local, regional and
global levels.</p>
      <p>Transmission of hydrological information to different
agencies and organizations.</p>
      <p>Dissemination of hydrological forecasts between different
agencies and corresponding own methodologies.</p>
      <p>Alerting and Notification between data and
providers and decision makers.
model</p>
      <p>Flood modeling is a paradigmatic example in the water
domain where standardization can improve the IT
contributions to the society. The increasingly variable climate
has seen a rising number of extreme flood events in the last
decades. Floods are natural phenomena that cannot be fully
avoided, but through the right measures we can reduce their
likelihood and limit their impacts. Indeed, floods pose great
challenges to decision makers of the meteorological and
hydrological agencies and local communities. An
interoperable design of all related components in the area of
flood forecasting, warning, and emergency response will
contribute to the integrated flood management plans on
various administrative scales.</p>
      <p>In the context of the Horizon 2020 project WaterInnEU1
and coordinated by the OGC, an Interoperability Pilot, called
RiBaSE, is designed for testing:
• the adaptability of common spatial standards to water
applications
• the best suitable connection between them
• the specific characteristics for the engaging of the
WaterML 2.0 in a general geospatial framework.</p>
      <p>
        While there are many examples of data management and
modeling systems as separate tools in the water domain, fewer
examples of integrated systems are set up. The present work
follows the general trend towards standardization in both the
data and the modeling [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. This paper describes the overall
approach of this pilot, key standardization issues, and
corresponding solutions for a global interoperable workflow
for supporting decision makers in an inland flood risk
situation.
      </p>
    </sec>
    <sec id="sec-2">
      <title>II. INTEROPERABILTY PILOT DESIGN</title>
      <p>
        The present work aims to design a global approach for one
hydrological issue, an emergency flood scenario, integrating
all related processes in an interoperable way. Previous works
such as [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ] and [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ] have demonstrated the possibilities for the
integration of some hydrological applications with OGC
standards, however a complete interoperable workflow (from
the primary data sources, to final outputs, including all
processing models) still needs to be designed and developed.
      </p>
      <sec id="sec-2-1">
        <title>1 http://www.waterinneu.org</title>
        <p>The whole approach is shown in Figure 1 including the
services involved and the client interfaces. Essentially, the
monitoring of meteorological data and the hydrological gauges
provide input data to a flood prediction model. Depending on
countries and agencies, the data is provided in heterogeneous
structures and formats, e.g. as plain CSV files or in custom
XML formats. In order to ease the integration of different data
sources, the Observation &amp; Measurements (O&amp;M) standard
and its extension for WaterML 2.0 defines common models
and encodings for observation data. In case data inputs are not
yet provided in WaterML 2.0 or O&amp;M, a translator component
is needed that allows conversion of the data into the WaterML
2.0 structure for providing it via Sensor Observation Services
(SOS) or netCDF format in a Web Coverage Service (WCS).
The flood model (detailed in the next section) is encapsulated
in a Web Processing Service (WPS) allowing the execution of
it in Web-based infrastructures. The output of the model is
sent to a client for visualization purposes under a WMS and
the raw data can be downloaded via a WCS service or Web
Feature Service (WFS), which is transactional for a better
integration with WPS. These services are launched by the
WPS client that controls the status of the WPS and coordinates
its outputs and the following processes. At the end of this
workflow and, in case of a risk situation for a particular
location in a river basin, an alert notification will be sent.
Since there is not yet a common standard available for the
alerting functionality, new concepts such as encapsulating the
event engine in WPS are being elaborated and tested in the
pilot. In this architecture, the client applications enable
control, visualization and decision support based on the model
results, considering data and metadata.</p>
        <p>Short descriptions of the standards utilized in these
components are as follows (references to these standards are
given in Table 1):</p>
        <p>NetCDF – Network Common Data Form: It consists of a
standards suite that supports encoding of digital geospatial
information representing space/time-varying phenomena in a
binary file format.</p>
        <p>SAS – Sensor Alert Service: It is an event notification
service for determining the nature of offered alerts, the
protocols used, and the options to subscribe to specific alert
types.</p>
        <p>SOS – Sensor Observation Service: It defines a Web
Service interface which allows querying and receiving
observations, sensor metadata, as well as representations of
observed features.</p>
        <p>WaterML 2.0: It is a standard information model for the
representation of in-situ water observation data. In fact, it is a
specialization of a more generic standard: ISO/OGC
Observations &amp; Measurements. So far, WaterML 2.0 is
composed of three parts: Part 1: Time series; Part 2: Ratings,
Gauging and Sections; Part 3: Water Quality. This work
primarily uses Part 1.</p>
        <p>WCS – Web Coverage Service: It defines a standard
interface and operations that enable interoperable access to
geospatial grid coverage.</p>
        <p>WFS – Web Feature Service: It defines a Web interface
with operations for querying and editing vector geographic
features. The subtype WFS-T (transactional) allows creation,
deletion, and updating of features.</p>
        <p>
          WPS – Web Processing Service: It is a standardized
interface that defines a standardized Web-based access to
geoprocessing functionality, as well as rules for standardizing
the inputs and outputs (requests and responses) of geospatial
processing functionality. This is the main component for the
flood model and this solution has been successful for
geoprocessing in other water resource systems [
          <xref ref-type="bibr" rid="ref8">8</xref>
          ].
        </p>
        <p>The services considered in this workflow can be classified
by their main functionality as:
•
•
•
•</p>
        <p>Data exchanging: NetCDF and WaterML translator</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Modeling: WPS flood simulation</title>
      <p>Delivering: WCS (raster), WFS (vector), SAS (alerts)</p>
    </sec>
    <sec id="sec-4">
      <title>Visualization: WMS (maps)</title>
      <sec id="sec-4-1">
        <title>Acronym</title>
        <p>netCDF CF</p>
      </sec>
      <sec id="sec-4-2">
        <title>SAS draft</title>
        <p>SOS 2.0</p>
      </sec>
      <sec id="sec-4-3">
        <title>WaterML 2.0 WCS 2.0 WFS 2.0 WPS 1.0</title>
        <p>Standards Specifications
www.opengeospatial.org/standards/netcdf
www.opengeospatial.org/projects/initiativ
es/sasie
www.opengeospatial.org/standards/sos
www.opengeospatial.org/standards/water
ml
www.opengeospatial.org/standards/wcs
www.opengeospatial.org/standards/wfs
www.opengeospatial.org/standards/wps</p>
        <p>The general workflow that integrates all these components
in a flooding scenario is structured in four concrete
experiments:
Experiment #2: If the readings exceed a threshold,
start a WPS 2.0 execution with a hydrological model.
Experiment #3: Expose the results of the model using
geospatial services to download data suitable for
visualization.</p>
        <p>Experiment #4: Notify alerts to the relevant
emergency services using Sensor Notification
Services or similar. This might be more experimental,
since there is a lack of official standards. Current work
of the OGC Pub/Sub Standards Working Group can be
an alternative to take into consideration.</p>
        <p>Some recommendations for the suitable integration of the
four experiments into the whole workflow need to be
considered:</p>
        <p>
          Related to Experiment #1, the SOS can be used to query
O&amp;M data and metadata about sensors in a standardized way.
A specialization of the SOS for the water domain already
exists with the SOS Hydrology profile [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ]. Hence, the pilot
can evaluate the application of the SOS Hydrology profile.
The threshold for Experiment #2 is being recalculated for each
study region considering the statistics of the previous
executions.
        </p>
        <p>In Experiment. #3, input data (as well as output data) also
needs interfaces to be published over the web: stream gauge
data and a time series hydrograph (WMS) and gridded data
(WCS) are forms suitable for publishing the time series graph
and map data.</p>
        <p>For Experiment #4, various notifications are triggered
depending on the location, timing, and severity of the alert
situation.</p>
      </sec>
    </sec>
    <sec id="sec-5">
      <title>III. MODEL IMPLEMENTATION</title>
      <p>
        The model to predict and map inland flood inundation
areas is the core component of the RiBaSE architecture. This
architecture allows any execution model with a complete
description of all processes, options, variables and parameters
involved. This description allows a generic WPS implemented
solution and models from AutoRapid [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ], TauDEM2/HAND
[
        <xref ref-type="bibr" rid="ref11">11</xref>
        ] or r.inund.fluv (GRASS) [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ]. The WPS descriptions are
encapsulated in a XML file (example in Fig. 2) containing all
the necessary information for server execution.
      </p>
      <p>2 http://hydrology.usu.edu/taudem/taudem5/index.html</p>
      <p>This complete description is the key for the correct
interpretation and implementation of the main WPS operations
(shown in Figure 3):</p>
      <p>GetCapabilities: it describes the service and provides the
list of available processing functionality in the instance.
DescribeProcess: it is a full description of inputs and
outputs of a specific geoprocessing functionality, e.g.
parameter names, value types, what parameters are
optional or mandatory, default values, etc.</p>
      <p>Execute: it runs a process with the inputs provided and
returns the corresponding outputs</p>
      <p>For this pilot, the WPS is implemented on the server side
as a Common Gateway Interface (CGI). Thus it is enabled for
wrapping the selected hydrological model and guided by the
WPS configuration file. The WPS client instance implemented
is provided by 52°North3 (Figure 4).</p>
      <p>In order to test the present design, three transboundary
regions have been proposed: Scheldt, Maritsa and Severn.
Figure 5 shows a short geographical description for these
areas.</p>
      <p>The Scheldt flows through Wallonia, Flanders and the
Netherlands, and discharges in the North Sea at Flushing. This
makes it one of Europe’s most densely populated river basin
districts. The hydrological dataset has been downloaded from
the portal of the Flemish Water Management4 in WaterML 2.0
format.</p>
      <p>Maritsa is the largest river in Balkan Peninsula and flows
through Bulgaria, Greek and Turkey. A small subsample of
data for this study is provided by the East Aegean River Basin
in a CSV format.</p>
      <p>The Severn rises on the northeastern slopes of Plynlimon
(Wales) and flows to the Bristol Channel and the Atlantic</p>
      <sec id="sec-5-1">
        <title>3 http://52north.org</title>
      </sec>
      <sec id="sec-5-2">
        <title>4 www.waterinfo.be</title>
        <p>Ocean. It is the longest river in the United Kingdom. It is
2
about 354 km long and its drainage basin area is 11266 km .
The hydrological dataset is provided by the National River
Flow Archive (NRFA) through a SOS hosted in the Centre for
Ecology &amp; Hydrology (CEH)5 (Figure 6).</p>
        <p>
          In these three regions, the terrain is obtained from the
ASTER Global Digital Elevation Model 30 m spatial
resolution [
          <xref ref-type="bibr" rid="ref13">13</xref>
          ]. This resolution is enough for testing the
interoperability challenges in present experiment, but a finer
resolution would be needed for a more accurate
implementation. Other main auxiliary information, also
nontime dependent in this study, is the land use database:
CORINE Land Cover [
          <xref ref-type="bibr" rid="ref14">14</xref>
          ] (available for Bulgaria and Turkey,
but not for Greece in Maritsa). Since both data sets are not
dynamic, interoperability efforts are not strictly necessary.
They are prepared next to the server for some implemented
hydrological model or for identifying the affected areas.
        </p>
        <p>The three study regions cover a wide range of possibilities
of data and metadata availability coming from different
agencies and bodies, in terms of format, completeness,
accuracy and openness. This is a great challenge for the
interoperable goals of the present work and a robust test for
the four experiments mentioned previously.</p>
        <p>CONCLUSIONS</p>
        <p>The work presents the design, the methodology and the
requirements of the RiBaSE, an interoperability pilot that is
running within the WaterInnEU project. This design pursues
to achieve a complete integration of the specific thematic
standards, as WaterML, into more mature generic geospatial
standards (WMS, WFS, WCS, etc.). The proposed architecture
allows testing with different hydrological model
implementations in a WPS context. This integration of
services and the heterogeneity of three study regions represent
an interoperable effort for a more efficient emergency
management in a flooding scenario.</p>
        <p>Future works will aim to conduct the same architecture
with other flooding models and using finer (spatial and time)
resolution datasets and examine the expected improvements
on the accuracy of predictions.</p>
      </sec>
    </sec>
    <sec id="sec-6">
      <title>ACKNOWLEDGMENT</title>
      <p>This work is currently developing within the WaterInnEU
project (No 641821) that has received funding from the
European Union’s Horizon 2020 research and innovation
programme and it is also supported by Catalan Government
under Grant 2014SGR-149.</p>
    </sec>
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