Operational Precise Irrigation for Cotton Cultivation through the Coupling of Meteorological and Crop Growth Models

To advance site-specific management of soil volumetric moisture content (VMC), this study analyzed the spatio-temporal evolution characteristics of soil VMC using the method of sequential Gaussian simulation (SGS) during the different growth stages of winter wheat. This was compared with data measured by time domain reflectometry (TDR) which is a well-established electromagnetic technique to measure soil VMC. The spatial autocorrelation coefficient of VMC indicated the strongest clustering of VMC in the tillering stage, and the least clustering of VMC in the harvest stage. A threshold of VMC in topsoil in the jointing stage of winter wheat was put forward. This threshold is 26, signifying that at a lower value, irrigation should be performed and irrigation efficiencies can be improved. Stable and sub-stable areas in the spatial variability maps of VMC were identified in the winter wheat jointing stage. Furthermore, the optimal irrigation stage was the early jointing stage, and irrigation was performed once as a guide. A loose-couple spatial model was constructed using the VMC in topsoil and the volume of water for irrigation. The VMC in the jointing stage of winter wheat was linked with efficient and water-saving irrigation.

Section: Introductionmentioning

confidence: 99%

Optimal Irrigation Mode and Spatio-Temporal Variability Characteristics of Soil Moisture Content in Different Growth Stages of Winter Wheat

Yang

Huang

Zhang

et al. 2018

“…Other DSS, such as ARTMO [44], simulate and estimate vegetation structure or radiative transfer from vegetal canopies, with no regards to irrigation scheduling and, therefore, they have to be used by experts in order to gather the information provided by these platforms and translate it into irrigation strategies to be applied in the field. Another example of DSS with a module for irrigation scheduling is FIGARO [46], which also uses AquaCrop for determining crop water requirements, and has been applied only to field crops such as cotton [47]. In summary, our approach is easier to use than current platforms because it is more intuitive and requires a lower number of parameters and inputs; moreover, it is easily adapted to a great number of crop species, as long as their crop coefficients are available, as exemplified for lettuce (herbaceous plant) and peach (woody perennial species) in the current manuscript.…”

Section: Discussionmentioning

confidence: 99%

A Novel ArcGIS Toolbox for Estimating Crop Water Demands by Integrating the Dual Crop Coefficient Approach with Multi-Satellite Imagery

Ramírez-Cuesta

Mirás-Avalos

Rubio-Asensio

et al. 2018

Advances in information and communication technologies facilitate the application of complex models for optimizing agricultural water management. This paper presents an easy-to-use tool for determining crop water demands using the dual crop coefficient approach and remote sensing imagery. The model was developed using Python as a programming language and integrated into an ArcGIS (geographic information system) toolbox. Inputs consist of images from satellites Landsat 7 and 8, and Sentinel 2A, along with data for defining crop, weather, soil type, and irrigation system. The tool produces a spatial distribution map of the crop evapotranspiration estimates, assuming no water stress, which allows quantifying the water demand and its variability within an agricultural field with a spatial resolution of either 10 m (for Sentinel) or 30 m (for Landsat). The model was validated by comparing the estimated basal crop coefficients (Kcb) of lettuce and peach during an irrigation season with those tabulated as a reference for these crops. Good agreements between Kcb derived from both methods were obtained with a root mean squared error ranging from 0.01 to 0.02 for both crops, although certain underestimations were observed resulting from the uneven crop development in the field (percent bias of −4.74% and −1.80% for lettuce and peach, respectively). The developed tool can be incorporated into commercial decision support systems for irrigation scheduling and other applications that account for the water balance in agro-ecosystems. This tool is freely available upon request to the corresponding author.

“…Sprinkler irrigation systems are dominating in PRDP, which can be substituted by the much more efficient drip irrigation systems. Moreover, for some crops such as cotton and corn which are cultivated in PRDP, deficit irrigation has been proved to be very effective for decreasing irrigation water consumption with a negligible loss on crop production [82,83].…”

Section: Projected Climate Change Impactsmentioning

confidence: 99%

Investigating the Effects of Agricultural Water Management in a Mediterranean Coastal Aquifer under Current and Projected Climate Conditions

Pisinaras¹,

Paraskevas²,

Παναγόπουλος³

2021

Coastal delta plains are areas with high agricultural potential for the Mediterranean region because of their high soil fertility, but they also constitute fragile systems in terms of water resources management because of the interaction of underlying aquifers with the sea. Such a case is the Pinios River delta plain located in central Greece, which also constitutes a significant ecosystem. Soil and Water Assessment Tool (SWAT) and SEAWAT models were combined in order to simulate the impact of current water resources management practices in main groundwater budget components and groundwater salinization of the shallow aquifer developed in the area. Moreover, potential climate change impact was investigated using climate data from Regional Climate Model for two projected periods (2021–2050 and 2071–2100) and two sea level rise scenarios (increase by 0.5 and 1 m). Modeling results are providing significant insight: although the contribution of the river to groundwater inflows is significant, direct groundwater recharge from precipitation was found to be higher, while capillary rise constitutes a major part of groundwater outflows from the aquifer. Moreover, during the simulation period, groundwater flow from the aquifer to the sea were found to be higher than the inflows of seawater to the aquifer. Regarding climate change impact assessment, the results indicate that the variability in groundwater recharge posed by the high variability of precipitation during the projected periods is increasing the aquifer’s deterioration potential of both its quantity and quality status, the latter expressed by the increased groundwater Cl− concentration. This evidence becomes more significant because of the limited groundwater storage capacity of the aquifer. Concerning sea level rise, it was found to be less significant in terms of groundwater salinization impact compared to the decrease in groundwater recharge and increase in crop water needs.