Water is considered as a powerful indicator of ecological sustainability and economic prosperity. Efficient use of water resources in agriculture is very much essential for sustaining agricultural productivity, ensuring food security, and promoting socio-economic development. However, water management in agricultural sector is facing numerous challenges. Conventional irrigation methods are associated with wastage of water and therefore, often require significant energy inputs for water conveyance, pumping, and distribution. In flood irrigation, there is substantial loss of water through surface runoff, evaporation and deep percolation beyond the root zone.
Similarly, in furrow irrigation also, there is wastage of water due to inefficient water distribution, evaporation, and runoff. Soil degradation through various mechanisms, including soil erosion, salinization, and waterlogging are also associated with conventional irrigation methods. To address these challenges, a transition is necessary towardsmore efficient, sustainable and climate smart irrigation practices. There has been considerable advancement in irrigation technologies which aim to enhance water use efficiency, minimize wastage and optimize crop yields while reducing the environmental footprint of irrigation practices.
Precision Irrigation
Precision irrigation is an advanced approach to water management in agriculture that utilizes the technology to apply need-based and accurate amount of water to a plant at an appropriate time and location. In precision irrigation, water is applied in variable rate; generally regulated by the inputs of sensors which help in reducing water losses and thereby conserving water resources and minimizing environmental impact.
Precision irrigation can also improve nutrient uptake by delivering nutrients directly to the root zone of plants, reducing leaching and run off. A precision irrigation system needs accurate in situ spatial and temporal real -time information on soil, crop, and weather conditions. Currently, several soil and plant-based sensors and automatic weather stations are available which can provide reliable information of required soil, crop, and weather parameters.
After collection of data, it is required to analyse and interpret the data and there are several multidimensional model / simulation software / tools are available that can forecast crop response to different applications. Precision irrigation system can be integrated with advanced irrigation planning and application systems with sensing, simulation and control systems. This involves the use of real-time automation and control of the system. Precision irrigation has the potential to revolutionize water management in agriculture, offering a sustainable solution to the challenges of water scarcity, climate change, and food security.
Automation in irrigation
Automation in irrigation systems plays a crucial role in updating irrigation practices and can replace manual irrigation. With the help of technology, an automated system monitors and regulates various aspects of operation like irrigation scheduling, delivery and distribution which enable farmers to achieve precise and targeted water application, resulting in improved crop yields, water savings, and resource management.
An important component of automated irrigation system is the use of sensors to monitor soil moisture status, weather condition and crop water requirement in real time which provide data for irrigation decision and management strategies based on the environmental conditions. Flow and distribution of water within irrigation systems is controlled with the help of automated valves and pumps for scheduling and adjusting water delivery rates to match crop water demand and minimize losses.
Recent advancement in automation in irrigation enables remote monitoring and control of irrigation operation, predictive analytic and automated decision-making processes. This system focuses on system integration, connectivity and intelligence through the use of Internet of Thing (IoT) technologies, cloud computing, and artificial intelligence (AI) algorithms which solve the problems of over- and under-irrigation based on crops and weather scenarios. One of the key advantages of IoT-based irrigation systems is their ability to collect and analyse large volumes of data from multiple sources, including soil moisture sensors, weather stations, crop sensors, and satellite imagery.
Weather-based Irrigation Scheduling
Weather-based irrigation scheduling relies on weather data such as solar radiation, temperature, humidity and wind speed to estimate crop water demand and calculate the amount of water needed to replenish soil moisture levels. In this approach, estimation of reference evapo-transpiration which is the evapotranspiration from a reference surface (ETo) under standard weather condition is required.
The reference surface is a hypothetical grass reference crop with an assumed crop height of 0.12 m, a fixed surface resistance of 70 s m-1 and an albedo of 0.23. The reference surface closely resembles an extensive surface of green, well-watered grass of uniform height, actively growing and completely shading the ground (FAO Irrigation and Drainage Paper No. 56). The FAO Penman-Monteith method is recommended as the sole standard method for computation of the reference evapotranspiration.
This method relies on weather data such as solar radiation, temperature, humidity and wind speed to estimate crop water demand and calculate the amount of water needed to replenish soil moisture levels. By combining ETo with crop coefficients (Kc ) that reflect crop-specific water requirements, farmers can estimate evapo-transpiration of crop (ETc) and determine irrigation needs based on the difference between ETc and rainfall.
Different tools and techniques can be used to get real time weather information, calculation of evapo-transpiration and irrigation recommendations for optimizing irrigation water management strategies. Irrigation scheduling based on the weather information can also be integrated with soil moisture sensor, remote monitoring system and automated irrigation system for higher efficiency and precision in irrigation. Recently, weather forecasting models and machine learning algorithms are also utilized to anticipate weather pattern, predict water demand of the crop and regulate scheduling of irrigation accordingly.
Micro-irrigation
Drip irrigation is an innovative methods of irrigation by which water can be supplied directly into the root zone. Drip irrigation systemis more efficient than other surface irrigation method which helps inincreasing crop yield and water use efficiency and also helps in water saving. Unlike traditional surface irrigation methods, drip irrigation delivers water precisely where it is needed, minimizing evaporation, runoff, and soil erosion (Santoshet al., 2022).
There is an increase in crop yields and reduction in the cost of fertilisers, pesticides and power for irrigation when using this method of irrigation. Drip irrigation systems consist of a water source, a distribution network, and emitters or drippers that release water near the plant roots. In case of subsurface drip irrigation (SDI), emitters are buried below the soil surface and water is delivered directly to the root zone of plants. As the emitters are placed underground, sub surface drip irrigation system minimizes water losses due to evaporation and surface runoff and also reduces the risk of weed growth and damage to irrigation equipment.
Conclusion
Advanced irrigation technologies are no longer a choice but a necessity for sustainable agricultural development. Precision irrigation is an advanced approach to apply need-based and accurate amount of water at right time and location. It integrates advanced irrigation planning and application systems which involves the use of real-time automation and control of the system. Irrigation scheduling based on the weather information can be integrated with soil moisture sensor and automated irrigation system for higher efficiency and precision in irrigation.By embracing these advances, we can achieve a balance between agricultural productivity and environmental sustainability.
References:
Writer Dr. Chinmoy Kumar Sarma is the Chief Scientist, Assam Agriculture University, Jorhat, Assam, India
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