corn yield by as much as 34% relative to the expected yield. The study found that, during some years, excessive rainfall reduced U.S. In a new study, an interdisciplinary team from the University of Illinois linked crop insurance, climate, soil, and corn yield data from 1981 through 2016. Thus, too much rain can be as dangerous as drought for agriculture: 'Data from the past three decades suggest that excessive rainfall can affect crop yield as much as excessive heat and drought.

landslides, which can threaten human life, disrupt transport and communications.ДЄs shown in the latest studies, excessive rainfall can affect crop productivity in various ways, including direct physical damage, delayed planting and harvesting, restricted root growth, oxygen deficiency, and nutrient loss.

damage to buildings and infrastructure,.

flooding, including risk to human life,.However, excessive rainfalls can lead to numerous hazards, for example : Primarily, I focused on excessive rainfall effects on agriculture in this project. To contribute to the solution to forfend and avert excessive rainfall instigated problems like agricultural productivity loss, I contemplated this project as a starting point. As 2020 passes, more than thirty-five incidents that caused the loss of crops and livestock due to heavy and violent rainfalls are recorded in my region. Meanwhile, other regions suffer from drought. Unfortunately, these days unexpected and excessive rainfalls occur more frequently and became relatively common due to climate change in some areas. Step 5.3: Evaluating the model and making predictions on the rainfall intensityД®specially in 2020, instant heavy and violent rainfalls have caused detrimental effects on greenhouses and crop yields in my country.Step 5.2: Training the model (ANN) on the rainfall intensity classes.Step 5.1: Visualizing and scaling (normalizing) the weather data.Step 5: Building an Artificial Neural Network (ANN) with TensorFlow.Step 4.2: Creating the weather data set for more than three months.Step 4.1: Reading and sending weather data with SIM808 (GPRS.

Step 4: Reading and sending weather data with ESP8266 (WiFi.Step 3.1: Setting up the web application on Raspberry Pi (or any server.Step 3: Developing a web application in PHP to append weather data to the spreadsheet.Step 2.2: Creating a spreadsheet on Google Sheets.Step 2.1: Getting credentials to use the Google Sheets API.Step 2: Collecting weather data on Google Sheets.Step 1: Assembling the weather station kit with an anemometer, wind vane, and rain bucket.

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