Smart Irrigation System

About

Summary SCORRES is developing a robust, efficient, affordable and smart irrigation system to help tackle the food, water, energy trilemma. The system combines a highly localised weather forecast with local know-how on irrigation needs and soil conditions, to produce a ‘right time, right volume’ approach to micro-irrigation. The test system has increased crop yields, reduced labour and composting requirements and reduced water & energy consumption, leading to improved utilisation of power, increased grid stability and potential higher farmer revenues. Project Status The system is currently being tested in one farm in the Indian state of Tamil Nadu. At present, farm conditions are being monitored using a range of sensors, but SCORRES is using machine-learning to reduce reliance on physical sensors, thereby increasing farm performance through a low-cost, packaged intervention. To date, early results for a range of 8 vegetable crops that have been automatically drip irrigated as opposed to manually drip irrigated suggest: 82% reduction in water use and a corresponding reduction in the energy used in pumping  100% increase in crop yield (increase in fruit size and faster growing cycle) Other benefits are a reduction in labour required and potential saving in compost. Nutrition testing of the crops and the soil is ongoing to ensure nutritional value is not compromised. As this is an Innovate UK funded research project, the data is being analysed and verified by Heriot Watt University. The system is currently at Technology readiness level 6. The consortium has won further funding to develop a detailed, costed precision irrigation system specification for a candidate segment of the Indian Farming Sector. The consortium is actively seeking funding to expand this roll out in India and also to China. Description 54% of India faces extremely high water stress and the Indian agricultural sector accounts for 90% of annual fresh water withdrawal, 15% of the total diesel use and 18% of the total electricity use. Farmer incomes are highly volatile due to both crop yield and price. This is leading to a crisis of indebtedness among the Indian agrarian population. These problems are not unique to India.  Existing state of the art irrigation control systems in India are typically either manual in operation or rely on time clocks which have a lack of monitoring oversight. The increasing access to electricity and digital services in India is opening up opportunities for control systems that utilise cloud based computational approaches. The smart irrrigation system being developed by SCORRES seeks to utilise the opportunities arising for cloud based control systems to help ensure the ongoing sustainability of Indian farming. At the trial farm in Tamil Nadu, existing manual irrigation systems have been replaced with precision irrigation systems. Currently, a number of inputs including a highly accurate local weather forecast, soil moisture measurements, farmer know-how, evapotranspiration modelling and grid outage information is being used to make continual adaptive control decisions to optimise irrigation schedules across a range of crops and soil conditions. Initially, irrigation schedules based on the famer know how for all the crops being grown (lady’s fingers, lettuce, basil, basella, pumpkin, corn, rocket and long beans) and the soil condition has been scheduled on the cloud. This schedule is refined during the cropping process to take into account forecast and actual rain fall and soil moisture using a water balance model developed by the team. Also, as power outages are a common occurrence at the trial farm and throughout India, the control process is aware of these outages and adapts the cloud schedule as required. For each crop cycle there is a test and control bed so that results can be verified. Over the next couple of months, the consortium will validate water, energy and crop data for the control and test beds for all the crops. The Crop data includes nutritional information, crop yield and crop cycle time. Initial results are highly encouraging. As this system is still at the pre commercialisation stage, measuring hardware has been used throughout the farm to verify results and inform the irrigation optimisation process. Machine learning is being used to reduce the reliance on hardware requirements for the micro irrigation system thus reducing the cost of the system. Workshops have been ongoing to get feedback on the system from Indian farmers. The modelling approach used in SCORRES along with the field trail outputs is informing business models for the commercialisation of the system, which take into account State and National regulatory circumstances and local issues associated with (for instance) access to capital and affordability and also potential for use in other agricultural areas eg grain production. Innovative Aspect Firstly, the system uses a novel weather forecasting technique which involves machine learning algorithms to optimise existing weather data and provide highly accurate localised weather information which informs the irrigation model. The accuracy of this forecasting method was proved in the FP7 research project ORIGIN and provided the longitude and latitude is known can easily be customised for different locations. Similarly the control method for the irrigation process uses machine learning to optimise the irrigation to give the crop the correct amount of water as and when required. This removes the need for costly hardware and creates a more affordable cloud based solution for smart irrigation.  The results show that water use can be significantly reduced and therefore water pumping can also be reduced. Politically, there is a desire to move away from diesel pumping and move towards solar pumping. Reducing pumping demands significantly helps with the affordability of solar pumps as system sizes and costs can be lowered. Therefore, the consortium working with local farmers have been able to explore financially viable, innovative, business models appropriate to local communities to create a more sustainable irrigation process. It is envisaged that three classes of system can be developed to match economic conditions: a) automated versions of irrigation controls incorporating feedback from soil moisture probes b) an automated irrigation control system that is not reliant on crop bed feedback and c) a product that offers forecasted irrigation requirements via text message. Benefits For the range of 8 vegetable crops trialed, the irrigation requirements have reduced from 5.1 litre/day/m2 of cultivated area to 0.9 litre/day/m2 of cultivated area. If this water is being pumped by a diesel pump then the diesel required has reduced from 0.158 litres/m2 of cultivated area / annum to 0.029 litres/m2 of cultivated area / annum. In the case of solar pumping (based on a 2hp pump) then the solar array requirement has reduced from 471Wh/m2/annum to 87Wh/m2/annum and reduced the peak requirement from 1.3W/m2 of cultivated area to .25W/m2 of cultivated area. Also, crop yields increased by 100% - this was a combination of crop cycle times being reduced so more crops could be planted in a given time and also increased plant size. India produces 14% of the world’s vegetables on approximately 9.5 million ha and (approx. 6million ha currently irrigated according to State of Indian Agricultural report 2015/16) and yield is lower than that for developed countries so the scope for water and energy savings and increase in crop yields is vast. In somewhere like India, where almost 600 million people are at high risk of surface water supply disruption, the ability to reduce water use in irrigation for vegetable cultivation by 82% is very significant. Agriculture is also accountable for 15% and 18% of total diesel and electricity use in India. Water and energy consumption for agriculture and a growing population present multiple challenges to the country’s energy, water and food security. Therefore the ability to use precision irrigation to reduce both water and energy demands and increase crop yields in the agricultural sector is hugely beneficial. The affordable and robust precision irrigation systems being developed through this project reduce water, energy, labour and compost input and increase yield whilst keeping the system affordable for the user. This will benefit farmers through increased incomes and create a more resource efficient and sustainable future for the agricultural sector. Worldwide irrigated agriculture is the largest water user, therefore, the technology being developed could bring similar benefits throughout the world.