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Agricultural Water Management

A section of Agriculture (ISSN 2077-0472).

Section Information

The role of managing water—irrigation and rain—to sustain food production for an increasing world population and with changing environmental conditions, while preserving our natural resources, is a task confronting agriculturalists from many disciplines. Water quantity and quality is the common denominator that links every aspect of crop production, from sowing to harvest, and is key to developing best management practices that increase water and nutrient use efficiency.

The Section “Agricultural Water Management” will publish scientific contributions that advance our knowledge on the broad subject of water as it affects the many facets of agricultural production. Given the wide-ranging scope of water, we welcome original interdisciplinary research and review articles on irrigation technology (hardware and software), scheduling, and application methods to improve water and nutrient use efficiency. Furthermore, articles that address technologies for harvesting rain, quality of irrigation water, the relation between water use and crop yield, application of simulation models to cropping systems, and water conservation are encouraged. We invite articles that describe studies on spatial and temporal statistics and risk analysis to short- or long-term experiments that explore the management of water in agricultural production, and how the relationship between inputs and outputs is influenced by the water management of cropping systems.

Keywords

irrigation (hardware and software); scheduling, deficit–irrigation; irrigation water application methods; soil sensors to measure water; plant sensors to measure canopy temperature, water and CO₂ fluxes; use of recycled water; rain harvesting; quantity and quality of water; water and nutrient use efficiency; dryland production (semiarid) and rainfed production (humid); crop water use; water and energy balance; urban, turfgrass, orchard water use; agronomy; soil science; meteorology; plant stress physiology; remote sensing; hydrology; computer science (artificial intelligence and simulation models); statistics (temporal; spatial; data analytics); economics (risk analysis; food security, best management practices)