The purpose of this study was to analyse the methods of automation, intelligent distribution, and consumption of water in Central Asian irrigation systems using the example of the Kyrgyz Republic. The study considered the use of sensor networks for monitoring water data by Wzzard LRPv and John Deere Operations Centre. The study analysed the work of AquaCrop software for modelling water balance and irrigation optimisation and the use of drones for monitoring the state of water resources and land plots, including Da-Jiang Innovations Phantom 4 RealTime Kinematic and P4 Multispectral drones. An analysis of the effectiveness of each method revealed considerable water conservation and improved water distribution performance. For the sensor networks, the level of water use in the irrigation system was 85% – with a supply of 1,000 m3 , losses amounted to 150 m3 . For the software, the water use efficiency was determined to be 70%, considering that the total volume of water supplied was 1,000 m3 and the factual volume of water retained in the root zone of plants was 700 m3 . The efficiency of using drones reached 90%, which meant that out of 500 m3 of water filled into the drones for spraying, 450 m3 were evenly distributed, while losses due to evaporation and spraying inaccuracies amounted to 50 cubic metres. The study analysed the capabilities of the Demand Driven Distribution water distribution management system revealed a 25% reduction in pump energy consumption, a 15% reduction in water leaks and a 50% reduction in pipe damage. An analysis of the capabilities of the Siemens Water Leak Finder system revealed that artificial intelligence algorithms accurately detected even minor water leaks of 0.2 litres per second, reducing resource losses by up to 50%. The analysis of the performance characteristics of the Rain Bird controller and the CropX platform revealed an increase in water consumption efficiency and water conservation in Central Asia, which was a major step towards the sustainable development of the agricultural sector in the region
Bаtykova et al. (Thu,) studied this question.