灌漑・排水システム工学

The increasing demand for sustainable irrigation solutions in arid regions such as the Quetta Valley Aquifer underscores the need for innovative water pumping technologies. This study evaluates the feasibility and performance of solar Photovoltaic (PV) water pumping systems for irrigation purposes in the WASA tube wells of the Quetta Valley Aquifer. By analyzing the efficiency, reliability and economic viability of solar PV systems compared to traditional diesel-powered pumps, this research aims to provide insights into the potential benefits and challenges of adopting solar technology. The findings highlight the effectiveness of solar PV systems in reducing operational costs and enhancing water accessibility while contributing to environmental sustainability. The study concludes that solar PV water pumping offers a promising alternative for sustainable irrigation in the region, with considerations for initial investment and system integration.

Expansive soils, known for their significant volume changes due to moisture fluctuations, pose challenges to the stability of soil slopes, particularly in arid and semi-arid regions. This study focuses on model testing to investigate the deformation characteristics of fissured expansive soil slopes subjected to various loading and irrigation conditions. Through laboratory experiments, we simulate real-world scenarios to assess how these soils respond to applied loads and changes in moisture content. The findings reveal critical insights into the effects of fissuring and moisture variation on soil deformation, contributing to a better understanding of slope stability in expansive soils. The results offer valuable data for developing design strategies and mitigation measures to address the challenges associated with expansive soil slopes.

The increasing variability in climate and water availability poses significant challenges to the resilience of irrigation systems. To ensure sustainable and effective irrigation practices, it is crucial to implement quantitative metrics that can accurately measure and enhance system resilience. This study explores the application of quantitative resilience measurement criteria in irrigation systems, focusing on metrics such as system flexibility, reliability and adaptability. By employing data-driven approaches and performance indicators, this research aims to provide a comprehensive framework for assessing and improving the resilience of irrigation infrastructure. The study highlights the benefits of using quantitative metrics to identify vulnerabilities, optimize resource management and enhance overall system performance. The findings offer valuable insights for policymakers, engineers and agricultural practitioners seeking to build more robust and adaptive irrigation systems in the face of evolving environmental conditions.

The study aimed to assess the viability of utilizing canopy temperature-based Crop Water Stress Index (CWSI) for irrigation scheduling in wheat crop (Triticum Aestivum L.). Field experiments were carried out for the 2021-2022 and 2022-2023 cropping periods at the irrigation laboratory of the Civil Engineering Department at the Indian Institute of Technology Roorkee, Roorkee, India. The experimental field was divided into six plots, each subjected to different irrigation treatments based on the depletion of Total Available Soil Water (TASW) within the crop's root zone. These irrigation treatments maintained varying levels of Water Depletion in the Soil (WDS) of TASW, encompassing 10%, 25%, 35% and 50%, as well as fully irrigated (non-stressed) and extremely dry (fully stressed) conditions. Multiple regression analyses between meteorological and crop parameters were conducted to establish a baseline. The CWSI was subsequently calculated for various levels of WDS of TASW using an empirical method. It was found that the irrigation treatment corresponding to 50% WDS, with a mean CWSI of 0.36, resulted in optimal yield and maximum water use efficiency. The findings of the study suggest that the established CWSI value can effectively identify stress levels and serve as a valuable tool for scheduling irrigation in wheat crop.