Automated Weather Stations for Disaster Risk Management, Watershed Management and Future Payment for Environmental Services

AUTHOR/S: Lourdes R. Simpol, Jenith L. Banluta, Josef Rene Villanueva

DATE COMPLETED: February 14, 2014



             The Automated Weather Station (AWS) Project of the Ateneo de Davao University aims to contribute in the increasing of adaptive capacities of communities. This can be done through data collection and analysis of data for future forecasting and modelling.

            The long term over-all objective of the research is to create models and forecasts on climate patterns and changes of the city and its nearby communities which can be used as management tools in the future in terms of disaster risk reduction and climate change adaptation.

               The data that will be collected from the study could be used for risk management and planning tools for watershed management and can be basis for future payment for environmental services proposals.

                There are four main components to consider in the design of the Automatic Weather Station. First, an AWS should contain a series of automated sensors installed in close combination, but not affecting each other, directly connected to a central processing unit (CPU) (Part I, Chapter 1, WMO 2010: WMO Guide to Meteorological Instruments and Methods of Observation). Second it must include a CPU to facilitate data acquisition and conversion into a suitable format, proper processing of data for checking and correction, the temporary storage of processed data, and their transmission to a central server. Third, it should include peripheral equipment such as a robust and stable power supply providing sufficient power to the various parts of the station, a real-time clock ensuring precise sequencing of operation, and back-up memory storage for needed redundancy.

               Topographical description of the city was also taken into account in the identification of the meteorological stations’ locations. Topography pertains to the arrangement of the natural and physical features of an area. According to World Meteorological Organization (WMO) standards, the location should be as flat as possible with minimum obstruction so as not to impede ventilation at the site. Areas of homogeneity,  non-homogeneity and areas of transition were roughly estimated using geographical information system (GIS) tools alongside with the identification of the watersheds and elevations of the city. 

               Lastly for site description process, community partners must be identified within the location for the sustainability of the installed devices. These community partners may be a local government unit (LGU), non-government organizations (NGOs), colleges and universities, privately owned land or industries. A well-founded ground support plays as crucial part in the operation of the system in the long run; therefore the commitment of a community partner is imperative.

               A complete AWS prototype was installed at the Ateneo de Davao University Rooftop near the Energy and Meteorology Laboratory for field testing. These are some of the problems encountered during the field testing:

a. Intermittent sending of data

              There have been instances when the AWS stops sending data for a certain period of time, then resumes sending at a later random time. Two possible sources of the problem are identified: (1) a program bug which causes it to stop its normal operation; and (2) electrical noise coming from the mechanical relay in the RG-11 optical rain gauge.

             For the first possible source of the problem, a software solution has been added to the microcontroller firmware. A watchdog timer, which is an independent sector of the microcontroller, is used to monitor the important parts of the program. The watchdog time is set to 8 seconds, meaning that if the watchdog timer is not reset by a heartbeat signal within the allotted time, it will force the microcontroller to restart and execute the program from the beginning. With this, if the microcontroller freezes (or hangs), the watchdog automatically force a reset to resume normal operation. 

              For the second possible source of the problem, a controlled test was done for confirmation. When the microcontroller approaches its sending time, a rain event was simulated by continuously pouring water on the rain gauge. This was done several times to see its effect or whether it would cause the AWS to freeze. However, no effect was noticed, which then rules out electrical noise from the mechanical relay as a source of the problem. 

b. GSM network reliability

             During the testing of the AWS, the SIM card used for the GSM module for the data transmission is a Sun Cellular prepaid SIM. This is primarily because it is cheaper compared to SIM cards from other networks. However, there have been instances when data sent by the AWS were not received on time. And once the data are received they come in all at the same time. A possible explanation would be the network congestion due to the large number of SMS users for Sun Cellular. Also, reliability and availability becomes more an issue when the AWS is deployed in far areas which are not covered by the Sun Cellular network. 

c. Possible need for an independent power source

             For most of the testing of the AWS prototype, a DC power adapter was used. This provided a stable a source of power for the AWS, thus ensuring continuous operation. However, for deployment in areas which have no access to electricity, an alternative source of power may be considered. The most practical source would be solar  power. An initial test was done using a 20-W solar panel tied to a simple charge-control circuit to charge a readily available 7Ah sealed lead-acid battery. However, initial observations show that since the battery used is not a deep-cycle type, it cannot efficiently provide power when it is under-voltage. A possible solution would be to use Lithium-Polymer batteries or Silicon batteries which are more expensive, but are deep-cycle types. 

              The developed prototype can now be massed produced and can be ready for deployment to identified areas. Stakeholders have to be met for proper care and maintenance in the future of this infrastructure. This type of endeavor on increasing the adaptive capacity of the people can only work not only when the physical infrastructure ( the automated weather station instrument) will be in place but also the social infrastructure (LGU, community or organization that will take care of the instrument).

Request for Full Article (Please fill in the needed details. We will promptly respond to your request thru your e-mail.)

[contact-form-7 404 "Not Found"]