PANI: An App for Dynamic Irrigation Scheduling

Abstract

Large tracts of land in the delta region of Bangladesh are left fallow or are cultivated with low input crops during the dry winter months. Surface water based irrigation opens up new opportunities for sustainable intensification by enabling the production of a high yielding crop. Irrigation in Bangladesh is still managed in a very traditional manner without considering scientific data on soil and weather which increase cost of farming and also lower productivity. Farmers usually depends on their past experience. In a traditional way, they forecast the weather as well as the moisture of the land. So the process the irrigation depends more on their guess. The simulation model has been integrated into a smart phone app called PANI (Program for Advanced Numerical Irrigation). PANI runs on a daily time step and uses forecasted weather data to predict irrigation needs one week in advance. I used the calibration of the Blainy-Criddle Equation so that only forecasted daily maximum and minimum temperatures are required. PANI addresses the needs of the irrigation service provider as well as of the farmer. Both will receive the field data, informing them as to whether a field needs to be irrigated or not. Since the water balance of PANI is based on the SVM algorithm, it can be used under most conditions, as long as weather and ground cover data are available.