The practice of alternate wetting and drying (AWD), a water-saving technology in lowland crop production systems, can be greatly facilitated using wireless water level sensors. However, these sensors generally work under clear water conditions. The sensitivity of these sensors to turbidity is important for accurate water level measurement and appropriate irrigation scheduling. This study evaluated the performance of a high-end water level sensor of the submersible pressure transducer type under various turbidity levels. The performance tests were performed in the laboratory using water samples collected from a typical lowland rice production system under various levels of turbidity replicated three times with clear water as control. The readings of the sensors were compared with manual readings for each turbidity level in all replications. Results showed that the measured water level depth generally increases with increasing turbidity for each voltage level. The linear regression or calibration equation developed for each turbidity level proved to be adequate as evidenced by a relatively low RMSE of less than 1 mV. Results of ANOVA suggest that turbidity significantly affects the accuracy of the water level sensor (p <.001). A unified calibration equation (R2=0.9985 and RMSE=1.971 mV) was developed to account for the effect of turbidity up to 4300 FAU on the water level measurements. Results of this study can be used to improve the accuracy of water level monitoring in irrigated lowland crop production systems employing alternate wetting and drying technology to further increase irrigation efficiencies and augment water savings particularly during the dry season or under water-scarce conditions for a more sustainable crop production.

The use of wireless sensors for real-time monitoring of field water level would greatly facilitate the application of alternate wetting and drying (AWD), an irrigation water management technique proven to result to significant water savings and reduced methane emissions in lowland rice production systems. However, most of the commercially available wireless sensors are generally costly. This study developed a low-cost wireless sensor that can perform real-time monitoring of water depth and surface temperature in lowland rice fields under an AWD irrigation regime. The sensor is composed mainly of an ultrasonic depth sensor, a waterproof temperature sensor, a humidity sensor, and a Wi-Fi-enabled microcontroller enclosed in a PVC cap that can be mounted in AWD pipes. The sensor was tested under laboratory, pseudo-field conditions and actual field conditions. Results showed a relatively high degree of agreement between sensor and manual measurements of water depth under all testing conditions, with the error ranging from only 5.2% to 6.6% and RMSE of 5.0 mm to 13.5 mm. The performance of the low-cost sensor also proved to be comparable with that of the high-end sensor, exhibiting practically similar measurement accuracy and higher precision. The wireless sensor developed in this study can provide a low-cost alternative to the high-cost and high-end sensors and other commercially available counterparts for efficient irrigation water management in lowland crop production systems during water-scarce conditions induced by climate change and climate variability.

This study developed a real-time web-and WSN-based information system for efficient irrigation water management and automation of drip-irrigated upland crop and intermittently-irrigated lowland crop production systems. The web-based system uses Flutter and DART to accommodate multiple end user platforms, while the WSN-based system uses state-of-the-art hardware and sensors for real-time monitoring of soil moisture, water level and weather conditions. The sensors are wirelessly connected in a low-power mesh network that sends data to a central server. The sensor readings are uploaded to the web application via MQTT, which generates charts and graphs for data analysis. The sensor readings compared well with measurements from conventional instruments. The system in this study provides a sustainable solution for improving irrigation efficiencies under both upland and lowland crop production systems, in minimizing water losses and in improving the overall agricultural crop productivity.

The evolution of smart phones has necessitated the development of mobile applications designed to perform a wide variety of functions. In the field of agriculture, mobile applications are currently used to monitor environmental parameters such as ambient temperature, humidity, soil moisture, water level, among others. A mobile application intended to monitor irrigation-related parameters and to control solenoid valves for irrigation automation was developed in this study. The mobile application was written using Flutter software development kit, and the Dart programming language. The mobile application communicates with the cloud server using a REST API written in JavaScript. The data acquired from the cloud server are presented as the current sensor reading and graphs. On the other hand, the mobile application controls the solenoid valves by sending designated bytes of data to the cloud server. The mobile application developed in this study was designed to be integrated with both low-cost sensors and the Smartmesh IP sensors to enable real-time monitoring and data visualization, and facilitate irrigation scheduling and manual irrigation control. The mobile application developed in this study may be used for efficient irrigation water management of upland crop production systems and for agricultural modernization in the Philippines and other developing countries.