It has been known that for the recent year the implementation of geographic information systems (GIS) is one of the tool to manage data. Among this, different software classified in principle as an open or proprietary source exists. For the monitoring center such a software is one of the main bases for the daily tasks that needs to be accomplished. The center has started to use different tools that combine the use of open source software and proprietary software to develop applications that are easily understood by people and offers easy access and transmission in real time. As an example, online land information system is operating in a decentralized manner with updated information since 2010. The information basically includes: flood risks status, landslide risk, droughts, tsunamis, earthquakes and volcanic eruptions.
Designing a system to manage and communicate information of the natural disasters situation in El Salvador
Earlier, the areas that elements and devices are needed within the natural hazards context in El Salvador has been described. Different experts in the fields involved in the monitoring center develop application to manage big data, and to generate product such as maps with different characteristics for different purposes (rainfall, soil moistures, landslide, geological characteristic). An application named WorkStation was develop to integrate the information from the Natural Hazards Monitoring Center and the Environmental Monitoring. The elements of the system are:
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Management and decision making: oriented to the high level decision makers.
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Workstation: groups formed by specialists and technicians responsible for the natural hazards monitoring.
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Information dissemination: services and tools to obtain information that are geared for the general public.
A system engineer works on the tasks of developing applications. His objectives are to improve the storage data structure by adding space capabilities, to design the user interface and to build the software [10]. Following a methodology lifting requirements, modifications to existing databases, interface design and coding are also required. Additionally, data structure design, user interface design and mobile interface design are of main importance. (See Fig. 4.Platform for data collection and storage).
As an outcome, the platform displays information as a country base map with different shapes to define the locations of the telemetric station network information in a graphical way. The internal process are set to display registered rainfall, river levels variations, landslide susceptibility, radar images and different other graph with the processed data. The information is updated on real time indicating rainfall amount variations, river fluctuations, rainfall radar images, landslides and flood susceptibility (see Fig. 5. Workstation System).
Mobile applications for the dissemination of information to the population
In the previous sections an application utilized mainly for the internal process in the monitoring center was described. However, the institution decided to share with the population specific information to maintain updated information and make faster response in different ways. A set of mobile applications created with information from early warning systems was developed to share information related to natural threats in the shortest time possible.
Weather hazard app
Weather Hazard mobile application is a real time flood and landslide warning system for El Salvador. It is an android application created in principle for global app development competition (GEO Appathon 2014) and to develop useful tools for Salvadoran users (see Fig. 6).
This product is a combination of both Global Earth Observation System of Systems (GEOSS) and MARN datasets. The data on the GEOSS portal, is an entry point to earth observation data from all over the world. The GEOSS portal is a large metadata base service containing resources of agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water as well as weather data. Furthermore, data coming from the reports of the users (citizen report) were also included in the app. The implementation characteristics include:
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Google App Engine: Google App Engine is a platform offered as a service (PaaS) that allows building and running applications on Google’s infrastructure.
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Weather Hazard uses App engine to store citizen reports and process WMS tiles to add transparency to tiles.
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Frontend: The App was developed using Eclipse ADT and Standard Android APIs + Google Maps API for Android V2. Main UI composed of a Tabbed Activity.
Warning message App. Alertas @MARN.SV V2.0 - android app
The warning message application is a push notifications app developed for Android devices. The application was created to disseminate notifications and alerts generated in the monitoring center of the Ministry of Environment and Natural Resources of El Salvador.
The notified information includes the ongoing monitoring state of the San Miguel volcano activity, susceptibility to landslides, hydrometeorological monitoring, air quality, and other information related to natural hazards [11, 12].
The application was originally designed as an internal communication tool within the monitoring center. However due to the characteristics of the information, is considered as a public interest tool. (See Fig. 7. “Alertas MARN” Plataform).
Dissemination if the volcanic activity. Monitoreo VSM
The original product is a web app designed for TV Screen (32”). It is a tool implemented in the monitoring center and the municipalities surrounding the volcano. (See Fig. 8. Volcano Monitoring. Original application)
To implement in mobile and Windows Store App, Bootstrap was used as CSS Framework (Grid system + some components). The rest of the code was reused from the existing App. The app was developed utilizing Apache Cordova.
Apache Cordova is a platform for building native mobile applications using HTML, CSS and JavaScript. Using this platforms represents an opportunity to take advantage of the written codes for the web to make available on mobile devices.
The application is maintaining informed by the people about the volcanic activity (San Miguel Volcano). They receive the information in real time. Besides, the warnings by the official institutions of national and local government are issued. (See Fig. 9. Volcano monitoring app for mobile.)
Agrometeorological data dissemination
MARN publishes bulletin about crop condition and agrometeorological information, including a map of estimated soil moisture. To share this information a web mapping application as well as an Android mobile application was developed [13].
The map is an estimation of the soil moisture. The soil moisture amount is a calculation done by agro climatic expert and GIS technicians. MARN facilitates the automation of the generation of this map as part of a new drought monitoring system.
The system architecture of MARN contains different elements related each other such as PosgreSQL + PostGIS Tabular and Spatial Data, Apache Web Server MapServer (for WMS), and R for Statistical Computing. (See Fig. 10. Agrometeorological application architecture. MARN Agrometeorología.)
The database is a compilation of different geographical points containing soil moisture information. The data is processed in R framework that executes a spatial Interpolation (ordinary kriging), reclassification, and calculates and stores the result in the geo-database (PostGIS). Once the data processing is done, the final results are presented in a web map developed using PHP, JavaScript + jQuery, and Google Maps API for JavaScript.
The mobile application displays agrometeorological monitoring information (see Fig. 11. Agrometeorological Mobil Application). The app allows to share pictures and comments from the citizen reporting the crops status. Additionally, other contents are available:
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Daily map soil moisture, updated daily at 11:00 am
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Map of soil moisture based on 10 days.
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Daily Record of rain in the rainfall network of El Salvador.
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Decadal agrometeorological report.
Automated system for acquisition and processing of satellite images in high definition (SAAPIS-HD)
The Automated System for Acquisition and Processing of Satellite Images in High Definition was developed to provide access to satellite images and HD resolution for meteorological products, storage raw data for future research and case studies, as well as to generate high quality images and meteorological products. In addition, improving accessibility to information for everyone in the area of meteorology is an advantage provided by this system.
SAAPIS-HD is a set of free programs, scripts and configurations synchronized to generate satellite imagery from the NOAA GOES-13 satellite. The system is based on software visualization and analysis of McIDAS-V data at version 1.3, set to run in Ubuntu 10.04 LTS Lucid Lynx system and controlled by scripts that run all processes [4].
The set of procedures consist on data acquisition, processing, product processing, storage and presentation. The processes are done through an html interface, Drupal content management system mounted on an Apache / MySQL server. (See Fig. 12. SAAPIS-HD data processing)
The system is able to generate images for the analysis of meteorological variables based on the NOAA GFS 0.5 degrees. Capable to generate images for the analysis of meteorological variables based on local data from the mesoscale model WRF. (See Fig. 13. SAAPIS-HD products).
These tasks seek to fulfill the performance of numerical operations using the data obtained from the satellite images. The library PyQGIS in QGIS to execute Python code could be a tool to accomplish tasks that require periodic calculations. The advantages are the processes automatization, simplicity in creating plugins in QuantumGIS and fulfill the specific needs of data analysis.
Automatic numerical modeling of mesoscale system with the weather research and forecast model - WRF (SMNM –WRF)
Weather Research Forecast Model (WRF) is a meteorological numerical model with Non-hydrostatic and mesoscale hydrostatic option. The model is utilized for operational as well as research purposes. The Automatic Numerical Modeling of Mesoscale System with the Weather Research and Forecast Model (SMNM –WRF) is a self-contained system, it does not need human intervention to run the weather research and forecast model. Running under Ubuntu 10.04 LTS Lucid Lynx system and using scripts, the WRF data is created by different institution related involved in the meteorological field.Footnote 3 [3].
The final stage of the model consist in generate imageries to be published and utilized for analysis processes. The data related to El Salvador is done by the meteorological area in the monitoring center:
The tool ARWPost tool produces images for the analysis of meteorological variables with GRADS software, these products are presented through an html interface using the Drupal (content management system) mounted on an Apache / MySQL server. (See Fig. 14. Maps produced by the SMNM -WRF.)
Central America Flash Flood Guidance (CAFFG)
Most of the previous tools described are related to sharing information for in a user friendly way for the population. In previous section, an application for the meteorological areas were presented. The next tool is related to the actions performed by the hydrological area implemented in the Central America Flash Flood Guidance (CAFFG). The CAFFG is an early warning system for floods developed by the Hydrologic Research Center (HRC) that allows Central American countries to forecast flash floods in small streams draining areas.
The CAFFG comprises three models: the soil moisture model [5] the threshold runoff model [2], and the flash flood guidance model [6]. The system provides images and text related to estimated and forecast precipitation products. The information comes in imagery and numerical data, it has been developed to work areas with 130 km2 with high resolution. (See Fig. 15. Composite Products. Central America Flash Flood Guidance - CAFFG)
The primary system product is the Flash Flood Guidance amount (FFG). FFG is the rainfall amount needed to cause bank full at the end of the basin. The users can leverage that information in their efforts for quality control and in their assessments to further apply the FFG data in their operational forecasting activities [8]. (See Fig. 16. CAFFG data management). The data generated by the system is handled primarily in the QGIS platform, for database adjustments and handle graphics in specific periods of time and locations. (See Fig. 17. Flash Flood Guidance variation between October 11 and 12, 2011).