A decrease in water resources, as well as changing environmental conditions, calls for efficient irrigation-water management in cotton-production systems. Cotton (Gossypium sp.) is an important cash crop in many countries, and it is used more than any other fiber in the world. With water shortages occurring more frequently nowadays, researchers have developed many approaches for irrigation-water management to optimize yield and water-use efficiency. This review covers different irrigation methods and their effects on cotton yield. The review first considers the cotton crop coefficient (Kc) and shows that the FAO-56 values are not appropriate for all regions, hence local Kc values need to be determined. Second, cotton water use and evapotranspiration are reviewed. Cotton is sensitive to limited water, especially during the flowering stage, and irrigation scheduling should match the crop evapotranspiration. Water use depends upon location, climatic conditions, and irrigation methods and regimes. Third, cotton water-use efficiency is reviewed, and it varies widely depending upon location, irrigation method, and cotton variety. Fourth, the effect of different irrigation methods on cotton yield and yield components is reviewed. Although yields and physiological measurements, such as photosynthetic rate, usually decrease with water stress for most crops, cotton has proven to be drought resistant and deficit irrigation can serve as an effective management practice. Fifth, the effect of plant density on cotton yield and yield components is reviewed. Yield is decreased at high and low plant populations, and an optimum population must be determined for each location. Finally, the timing of irrigation termination (IT) is reviewed. Early IT can conserve water but may not result in maximum yields, while late IT can induce yield losses due to increased damage from pests. Extra water applied with late IT may adversely affect the yield and its quality and eventually compromise the profitability of the cotton production system. The optimum time for IT needs to be determined for each geographic location. The review compiles water-management studies dealing with cotton production in different parts of the world, and it provides information for sustainable cotton production.

Irrigation scheduling is crucial to effectively manage water resources and optimize profitability of an irrigated operation. Tools that can be customized to a field’s characteristics can greatly facilitate irrigation scheduling decisions. Soil moisture sensors and the evapotranspiration (ET)-based KanSched are two of the tools that could be implemented in an irrigated farm. Focusing on the installation of soil moisture sensors, demonstration set-ups were established at the Southwest Research-Extension Center plots in Garden City, Kansas, and in a producer’s field, each with three types of moisture sensors at different depths. Among others, this project validates the importance of moisture sensors being installed as early as possible in a representative location with good soil-sensor contact. The moisture sensors, at the least, help in determining when irrigation water should be applied or scheduled. Furthermore, in implementing an irrigation schedule, the irrigation manager considers the irrigation system capacity, the amount that can be efficiently applied, the soil intake rate, and other relevant factors.

The Ogallala Aquifer underlies 45 million ha, providing water for approximately 1.9 million people and supporting the robust agriculture economy of the US Great Plains region. The Ogallala Aquifer has experienced severe depletion, particularly in the Southern Plains states. This paper presents policy innovations that promote adoption of irrigation technology, and management innovations. Innovation in Kansas water policy has had the dual effects of increasing the authority of the state to regulate water while also providing more flexibility and increasing local input to water management and regulation. Technology innovations have focused on improved timing and placement of water. Management innovations include soil water monitoring, irrigation scheduling, soil health management and drought-tolerant varieties, crops, and cropping systems. The most noted success has been in the collective action which implemented a Local Enhanced Management Area (LEMA), which demonstrated that reduced water pumping resulted in low to no groundwater depletion while maintaining net income. Even more encouraging is the fact that irrigators who have participated in the LEMA or other conservation programs have conserved even more water than their goals. Innovative policy along with creative local–state–federal and private–public partnerships are advancing irrigation technology and management. Flexibility through multi-year allocations, banking of water not used in a given year, and shifting water across multiple water rights or uses on a farm are promising avenues to engage irrigators toward more sustainable irrigation in the Ogallala region.

Utilizing degraded quality waters such as saline water as irrigation water with proper management methods such as leaching application is a potential answer to water scarcity in agricultural systems. Leaching application requires understanding the relationship between the amount of irrigation water and its quality with the dynamic of salts in the soil. The HYDRUS-1D model can simulate the dynamic of soil salinity under saline water irrigation conditions. However, these simulations are subject to uncertainty. A study was conducted to assess the uncertainty of the HYDRUS-1D model parameters and outputs to simulate the dynamic of salts under saline water irrigation conditions using the Markov Chain Monte Carlo (MCMC) based Metropolis-Hastings algorithm in the R-Studio environment. Results indicated a low level of uncertainty in parameters related to the advection term (water movement simulation) and water stress reduction function for root water uptake in the solute transport process. However, a higher level of uncertainty was detected for dispersivity and diffusivity parameters, possibly because of the study’s scale or some error in initial or boundary conditions. The model output (predictive) uncertainty showed a high uncertainty in dry periods compared to wet periods (under irrigation or rainfall). The uncertainty in model parameters was the primary source of total uncertainty in model predictions. The implementation of the Metropolis-Hastings algorithm for the HYDRUS-1D was able to conveniently estimate the residual water content (θ_r) value for the water simulation processes. The model’s performance in simulating soil water content and soil water electrical conductivity (ECsw) was good when tested with the 50% quantile of the posterior distribution of the parameters. Uncertainty assessment in this study revealed the effectiveness of the Metropolis-Hastings algorithm in exploring uncertainty aspects of the HYDRUS-1D model for reproducing soil salinity dynamics under saline water irrigation at a field scale.

The current status of water resources in the U.S. Central High Plains necessitates adopting water conservation practices to move toward a sustainable agricultural economy. Identifying proper irrigation scheduling techniques is a conservative practice to maintain the sustainability of the agricultural systems. However, conducting field experiments is time and money consuming. Thus, the utilization of crop models, such as AquaCrop, could be a convenient alternative to field experiments. The FAO AquaCrop model was calibrated and validated for simulating forage sorghum yield response to various deficit irrigation conditions in a semi-arid region. Afterwards, the model was used to investigate the efficiency of the pre-season and in-season irrigation scheduling scenarios. In this study, the soil water status at the planting time was considered as the indicator of the pre-season irrigation level. Therefore, the pre-season irrigation scenarios were arranged as the replenishment of soil water deficiency at the time of planting at up to 30, 50, and 100% of the soil’s total available water for the first 60 cm of soil depth and the same replenishment levels for the entire crop root zone (150 cm soil depth). Then, AquaCrop long-term (37 years) simulations of forage sorghum biomass and irrigation water use efficiency reactions to three levels of maximum allowable depletion (MAD) (40, 55, and 70%) were compared to three fixed irrigation interval (4, 6, and 10 days) scenarios by considering six pre-season irrigation conditions (36 scenarios). The scenarios analysis found the 10-day irrigation interval and the MAD levels of 55% and 70% to be the most efficient irrigation scheduling strategies if combined with pre-season irrigation that brought the crop root zone (0–150 cm soil depth) to field capacity. Moreover, the 40% MAD application was the least efficient strategy. This study’s outputs can be a baseline for establishing forage sorghum irrigation scheduling in the U.S. Central High Plains. However, exploring the interactions of irrigation scheduling strategies with other irrigation and agronomic practices, such as salinity management and fertilizer application, is highly recommended.