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Papers on “water scarcity agriculture irrigation efficiency”

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1. Water Scarcity and Irrigation Efficiency in Egypt

   Rehab Osman, Emanuele Ferrari, Scott McDonald · 2016 · Water Economics and Policy · 43 cites

   This study provides quantitative assessments of the impacts of efficiency enhancement for different types of irrigation water under water scarcity conditions. It employs a single country CGE (STAGE 2) model calibrated to an extended version of a recently constructed SAM for Egypt 2008/09. The SAM segments the agricultural accounts by season and by irrigation scheme, including Nile- and groundwater-dependent as well as rain-fed agricultural activities. The simulations show that Egypt should manage potential reductions in the supply of Nile water with more efficient irrigation practices which increase the productivity of Nile water, groundwater and irrigated land. The results suggest a more am

2. Addressing water scarcity in agricultural irrigation: By exploring alternative water resources for sustainable irrigated agriculture

   A. Elmahdi · 2024 · Irrigation and Drainage · 37 cites

   This review paper addresses challenges in the water sector, particularly in irrigated agriculture, aiming to propose solutions for meeting irrigation demands while promoting global food security and sustainable development, notably SDG 6. Structured around three facets: empowering farmers, strengthening conventional sources of irrigation water and harnessing non‐conventional water resources, it emphasizes the significance of exploring blue water resources due to precipitation variability. Many irrigation systems operate below efficiency, offering productivity enhancement opportunities. Water management in agriculture spans various levels, involving farmers as key stakeholders. In addition to

3. Water and Energy Scarcity for Agriculture: Is Irrigation Modernization the Answer?

   Aftab Ahmad, Shahbaz Khan · 2017 · Irrigation and Drainage · 33 cites

4. Energy-Efficient Smart Irrigation Technologies: A Pathway to Water and Energy Sustainability in Agriculture

   U. Daraz, Štefan Bojnec, Younas Khan · 2025 · Agriculture · 28 cites

   The agricultural sector faces challenges such as water scarcity, energy inefficiency, and declining productivity, particularly in arid regions. Traditional irrigation methods contribute to resource depletion and environmental impacts. Solar-powered smart irrigation systems integrate precision irrigation with renewable energy, improving water use and productivity. In Pakistan, where agriculture contributes 19% of gross domestic product and employs 40% of the workforce, these challenges are severe, especially in water-scarce areas like the Cholistan Desert. This study examines the impact of solar-powered smart irrigation on agricultural productivity, water conservation, and energy efficiency i

5. Evaluating the Effect of Deficit Irrigation on Yield and Water Use Efficiency of Drip Irrigation Cotton under Film in Xinjiang Based on Meta-Analysis

   Qi Xu, Xiaomei Dong, Weixiong Huang, et al. · 2024 · Plants · 21 cites

   Water scarcity constrains the sustainable development of Chinese agriculture, and deficit irrigation as a new irrigation technology can effectively alleviate the problems of water scarcity and water use inefficiency in agriculture. In this study, the drip irrigation cotton field under film in Xinjiang was taken as the research object. Meta-analysis and machine learning were used to quantitatively analyze the effects of different farm management practices, climate, and soil conditions on cotton yield and water use efficiency under deficit irrigation, to investigate the importance of the effects of different factors on cotton yield and water use efficiency, and to formulate appropriate optimiz

6. Irrigation efficiency and water withdrawal in US agriculture

   Haoying Wang · 2019 · Water Policy · 14 cites

   AbstractTo meet future food demand and sustainability requirements of society, the agriculture sector faces challenges in both the institutional dimension and the technological dimension. One of the main concerns regarding the current agricultural production pattern is the tremendous amount of water it requires to maintain and boost output. With a changing climate and increasing demand from civil uses, promoting both water allocation efficiency and water application efficiency becomes the focus of policy design. The unintended consequences of water policies, however, have led to extensive debates. This study addresses the key question of whether irrigation efficiency improvement leads to red

7. A Review on Optimizing Water Management in Agriculture through Smart Irrigation Systems and Machine Learning

   Zaid Belarbi, Yacine El Younoussi · 2025 · E3S Web of Conferences · 9 cites

   Optimizing irrigation water usage is crucial for sustainable agriculture, especially in the context of increasing water scarcity and climate variability. Accurate estimation of evapotranspiration (ET), a key component in determining water requirements for crops, is essential for effective irrigation management. Traditional methods of measuring and estimating ET, such as eddy-covariance systems and lysimeters, provide valuable data but often face limitations in scalability, cost, and complexity. Recent advancements in machine learning (ML) offer promising alternatives to enhance the precision and efficiency of ET estimation and smart irrigation systems. This review explores the integration of

8. Optimizing Water Resource Management in Agriculture Using AI-Powered Solar Irrigation Systems

   M. B. Akanbi, K. J. Adedotun, A. K. Raji, et al. · 2025 · Journal of Science Innovation and Technology Research · 8 cites

   Water resource management is a critical challenge in modern agriculture, particularly in regions with erratic rainfall and increasing water scarcity. This study explores the implementation of AI-powered solar irrigation systems as a sustainable solution for optimizing water usage while enhancing agricultural productivity. The system integrates machine learning algorithms, IoT-based soil moisture sensors, and real-time weather forecasting to automate irrigation processes and ensure efficient water distribution. By continuously analyzing soil moisture levels, weather conditions, and crop water requirements, the AI model dynamically adjusts irrigation schedules, minimizing water wastage and max