Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach

Abstract

This study reviews soil water balance (SWB) model approaches to determine crop irrigation requirements and scheduling irrigation adopting the FAO56 method. The K c -ET o approach is discussed with consideration of baseline concepts namely standard vs. actual K c concepts, as well as single and dual K c approaches. Requirements for accurate SWB and appropriate parameterization and calibration are introduced. The one-step vs. the two-step computational approaches is discussed before the review of the FAO56 method to compute and partition crop evapotranspiration and related soil water balance. A brief review on transient state models is also included. Baseline information is concluded with a discussion on yields prediction and performance indicators related to water productivity. The study is continued with an overview on models development and use after publication of FAO24, essentially single K c models, followed by a review on models following FAO56, particularly adopting the dual K c approach. Features of dual K c modeling approaches are analyzed through a few applications of the SWB model SIMDualKc, mainly for derivation of basal and single K c , extending the basal K c approach to relay intercrop cultivation, assessing alternative planting dates, determining beneficial and nonbeneficial uses of water by an irrigated crop, and assessing the groundwater contribution to crop ET in the presence of a shallow water table. The review finally discusses the challenges placed to SWB modeling for real time irrigation scheduling, particularly the new modeling approaches for large scale multi-users application, use of cloud computing and adopting the internet of things (IoT), as well as an improved wireless association of modeling with soil and plant sensors. Further challenges refer to the use of remote sensing energy balance and vegetation indices to map K c , ET and crop water and irrigation requirements. Trends are expected to change research issues relative to SWB modeling, with traditional models mainly used for research while new, fastresponding and multi-users models based on cloud and IoT technologies will develop into applications to the farm practice. Likely, the K c -ET o will continue to be used, with ET o from gridded networks, re-analysis and other sources, and K c data available in real time from large databases and remote sensing.

Transpiration and Water Use of an Irrigated Traditional Olive Grove with Sap-Flow Observations and the FAO56 Dual Crop Coefficient Approach

“…A wide review on crop coefficients for trees and vines [14] has shown that the variability in K c values is large and much greater than the variability in K cb values, particularly by the end season, as well as in the initial and the late seasons, which results from rainfall events occurring during these periods. Aiming at ET partitioning [16], studies have been carried out based on soil evaporation, measured in mi-crolysimeters; actual crop transpiration, determined with sap flow sensors [5,17,18]; and/or actual crop evapotranspiration, obtained using eddy covariance techniques [4,19,20], as reviewed by Pereira et al [21]. A different approach that is currently used is remote sensing, namely, exploring the relationships between K cb act and a spectral vegetation index [22][23][24][25], which allows its use, together with ground data, in modeling [21].…”

“…Aiming at ET partitioning [16], studies have been carried out based on soil evaporation, measured in mi-crolysimeters; actual crop transpiration, determined with sap flow sensors [5,17,18]; and/or actual crop evapotranspiration, obtained using eddy covariance techniques [4,19,20], as reviewed by Pereira et al [21]. A different approach that is currently used is remote sensing, namely, exploring the relationships between K cb act and a spectral vegetation index [22][23][24][25], which allows its use, together with ground data, in modeling [21]. Properly calibrated models may be used to evaluate crop water requirements, to support proper irrigation management and to evaluate the impact of crops and management, even under the application of water deficit strategies.…”

“…However, models implement different structures and often do not apply the FAO K c -ET o approach, e.g., in the remote sensing-based two-source energy balance algorithm [19] and the transient model Hydrus-2D [26]. Further examples were recently reviewed [21]. Among the dual K c models, the SIMDualKc model [27,28] is used in the present study since it applies the FAO dual-K c approach, which is suitable for olive orchards [4,5] and other woody perennial crops, such as vineyards [29,30] and peach trees [7].…”

Improved Soil Moisture and Electrical Conductivity Prediction of Citrus Orchards Based on IoT Using Deep Bidirectional LSTM

“…Citrus cultivation in China has been intensified with the use of large-area orchards [4]; at the same time, drip irrigation is widely applied in citrus growing. Therefore, the decision-making and scheduling of the irrigation of citrus orchards have become important problems [5]. The traditional drip irrigation operation depends mainly on subjective experience to make decisions and schedules and lacks an objective reference [6].…”

Impacts of climate change and rising atmospheric CO2 on future projected reference evapotranspiration in Emilia-Romagna (Italy)

“…Evapotranspiration represents the simultaneous processes of transfer of water to the atmosphere by transpiration and evaporation in a soil-plant system (Allen et al 1998). In particular, reference evapotranspiration (ETo) is an important hydrological variable for irrigation water management and hydrological modeling (Immerzeel and Droogers 2008;Pereira et al 2020). Since the agricultural sector accounts for 70% of freshwater withdrawals (Kummu et al 2012) and around 90% of global freshwater consumption (Wada et al 2012), improved understanding of changes in evapotranspiration is essential for dependable projections of global freshwater availability under conditions of climate change.…”