價格：免費
更新日期：2018-08-31
檔案大小：2.1M
目前版本：1.0
版本需求：Android 4.0.3 以上版本
官方網站：https://www.linkedin.com/in/hamed-zamanisabzi-02670130/
Email：ndilekli@gmail.com
Concept by Hamed Zamani Sabzi, execution by Naci Dilekli. This utility is an online application to optimally set the required irrigation schedules for different crops considering the geographical coordinates of a farm and the utilized irrigation techniques such as surface irrigation, sprinkler, or drip irrigation. In this utility, the forecasted climatic information is integrated with the physical information of the soil and crop types (field capacity, soil type, root zone of the crop, Management Allowable Deficit, Gravimetric Soil Moisture Content; (θm), Bulk Density (ρb), Density of the particle (ρp), Volume of the sample (Vb), Volumetric Soil Moisture Content (θv)=θm*ρb, , soil moisture content, evaporation rate, and …) to optimally find the required irrigation schedules. Our integrated toolbox guarantees to minimize the total irrigation loss through deep percolation and maximizing the irrigation efficiency. In this system by integrating the forecasted climatic variables and remotely measured data on physical characteristics of the soil and cultivated crops, the required volume of water for irrigation is minimized. The developed system totally works automatically and online by a minimum level of required aids. The system is a complicated system but easy to operate and control by personal mobiles. The calculation processes are based on the conceptual algorithm of volume balance method. All the data are measured and integrated online and remotely measured data.
We provide the following example in order to describe the process of the developed mobile-based application to optimize the irrigation scheduling. To measure the soil moisture content, we can follow two ways: either measure the soil moisture content through physical sampling within different time periods or using installed sensors through different depths of the root zone of the cultivated crop. Here, in order to simplify the process, we assume that we take tow samples in two different time periods.