Web-Based GIS and Desktop Open Source GIS Software: An Emerging Innovative Approach for Water Resources Management

The main objective of the WSM300 project is the development of a methodology which guides and supports an improved water resources management on the level of small watersheds (up to 300 km²). The developed methodology is to be implemented into a software based tool within the framework of a generic Decision Support System (DSS). (Leichtfuss 2003, Schröter 2004). Core of the DSS is a "decision matrix", which has been implemented as a web based application (www.wsm300.de). The management objectives are represented by the indicators labeling the rows. They will be the result of a discussion of the objectives and problems in the specific sub-basin, which is supported by the catalogue of indicators. The matrix, once the labels are defined, serves as a plot for the planning process, defining clearly which objectives have to be considered and which indicator-values have to be calculated. The DSS further includes a concept and tools for the combination of existing software components and supports the processing of model-outputs to indicator-values. Filled with the indicator-values, the matrix allows a comparison of the scenarios and provides a good basis for a decision. If desired, multi-criteria decision aid methods can further help find the optimal scenario and mediate between stakeholders. As a co-product of the web-based DSS, the "River-Information-System" was established informing the public about the newest developments in their catchment.

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Development and implementation of an Integrated Water Resources Management System (IWRMS)

Advances in Science and Research ◽

10.5194/asr-7-83-2011 ◽

2011 ◽

Vol 7 (1) ◽

pp. 83-90 ◽

Cited By ~ 3

Author(s):

W.-A. Flügel ◽

C. Busch

Keyword(s):

Decision Support ◽

Water Resources ◽

River Basin ◽

Water Resources Management ◽

Management System ◽

Integrated Water Resources Management ◽

Time Saving ◽

Web Based ◽

Resources Management ◽

Different Types

Abstract. One of the innovative objectives in the EC project BRAHMATWINN was the development of a stakeholder oriented Integrated Water Resources Management System (IWRMS). The toolset integrates the findings of the project and presents it in a user friendly way for decision support in sustainable integrated water resources management (IWRM) in river basins. IWRMS is a framework, which integrates different types of basin information and which supports the development of IWRM options for climate change mitigation. It is based on the River Basin Information System (RBIS) data models and delivers a graphical user interface for stakeholders. A special interface was developed for the integration of the enhanced DANUBIA model input and the NetSyMod model with its Mulino decision support system (mulino mDss) component. The web based IWRMS contains and combines different types of data and methods to provide river basin data and information for decision support. IWRMS is based on a three tier software framework which uses (i) html/javascript at the client tier, (ii) PHP programming language to realize the application tier, and (iii) a postgresql/postgis database tier to manage and storage all data, except the DANUBIA modelling raw data, which are file based and registered in the database tier. All three tiers can reside on one or different computers and are adapted to the local hardware infrastructure. IWRMS as well as RBIS are based on Open Source Software (OSS) components and flexible and time saving access to that database is guaranteed by web-based interfaces for data visualization and retrieval. The IWRMS is accessible via the BRAHMATWINN homepage: http://www.brahmatwinn.uni-jena.de and a user manual for the RBIS is available for download as well.

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Web-based decision support system in regional water resources management

Proceedings of the 11th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing on International Conference on Computer Systems and Technologies - CompSysTech '10 ◽

10.1145/1839379.1839436 ◽

2010 ◽

Cited By ~ 1

Author(s):

Rossen Iliev ◽

Leoneed Kirilov ◽

Emil Bournaski

Keyword(s):

Decision Support ◽

Water Resources ◽

Decision Support System ◽

Water Resources Management ◽

Support System ◽

Web Based ◽

Resources Management ◽

Regional Water

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Operational river discharge forecasting in poorly gauged basins: the Kavango River Basin case study

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-11071-2014 ◽

2014 ◽

Vol 11 (10) ◽

pp. 11071-11108

Author(s):

P. Bauer-Gottwein ◽

I. H. Jensen ◽

R. Guzinski ◽

G. K. T. Bredtoft ◽

S. Hansen ◽

...

Keyword(s):

Water Resources ◽

Data Assimilation ◽

Open Source ◽

Water Resources Management ◽

Open Source Software ◽

River Discharge ◽

Lead Times ◽

Probabilistic Forecasting ◽

Resources Management ◽

Probabilistic Forecasts

Abstract. Operational probabilistic forecasts of river discharge are essential for effective water resources management. Many studies have addressed this topic using different approaches ranging from purely statistical black-box approaches to physically-based and distributed modelling schemes employing data assimilation techniques. However, few studies have attempted to develop operational probabilistic forecasting approaches for large and poorly gauged river basins. This study is funded by the European Space Agency under the TIGER-NET project. The objective of TIGER-NET is to develop open-source software tools to support integrated water resources management in Africa and to facilitate the use of satellite earth observation data in water management. We present an operational probabilistic forecasting approach which uses public-domain climate forcing data and a hydrologic–hydrodynamic model which is entirely based on open-source software. Data assimilation techniques are used to inform the forecasts with the latest available observations. Forecasts are produced in real time for lead times of 0 to 7 days. The operational probabilistic forecasts are evaluated using a selection of performance statistics and indicators. The forecasting system delivers competitive forecasts for the Kavango River, which are reliable and sharp. Results indicate that the value of the forecasts is greatest for intermediate lead times between 4 and 7 days.

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Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study

Hydrology and Earth System Sciences ◽

10.5194/hess-19-1469-2015 ◽

2015 ◽

Vol 19 (3) ◽

pp. 1469-1485 ◽

Cited By ~ 10

Author(s):

P. Bauer-Gottwein ◽

I. H. Jensen ◽

R. Guzinski ◽

G. K. T. Bredtoft ◽

S. Hansen ◽

...

Keyword(s):

Water Resources ◽

Data Assimilation ◽

Open Source ◽

Water Resources Management ◽

Open Source Software ◽

River Discharge ◽

Lead Times ◽

Probabilistic Forecasting ◽

Resources Management ◽

Probabilistic Forecasts

Abstract. Operational probabilistic forecasts of river discharge are essential for effective water resources management. Many studies have addressed this topic using different approaches ranging from purely statistical black-box approaches to physically based and distributed modeling schemes employing data assimilation techniques. However, few studies have attempted to develop operational probabilistic forecasting approaches for large and poorly gauged river basins. The objective of this study is to develop open-source software tools to support hydrologic forecasting and integrated water resources management in Africa. We present an operational probabilistic forecasting approach which uses public-domain climate forcing data and a hydrologic–hydrodynamic model which is entirely based on open-source software. Data assimilation techniques are used to inform the forecasts with the latest available observations. Forecasts are produced in real time for lead times of 0–7 days. The operational probabilistic forecasts are evaluated using a selection of performance statistics and indicators and the performance is compared to persistence and climatology benchmarks. The forecasting system delivers useful forecasts for the Kavango River, which are reliable and sharp. Results indicate that the value of the forecasts is greatest for intermediate lead times between 4 and 7 days.

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