Irrigation management evaluation of multiple irrigation methods using performance indicators

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Two exponential relationships ([1] from the beginning to the midpoint of the field, [2] from the beginning to the endpoint of the field) were considered for the advance curve of surface irrigation water along a field. The constant coefficients of these advance relationships were determined using the least squares optimization method. These relationships were compared with the advanced relationships obtained by the Elliott and Walker method (EW) using the advanced data related to 14 irrigation events and using root mean square error deviation (dRMS) and Nash–Sutcliffe (NSE) indices. The results of this evaluation showed that the advanced relationships obtained from the method presented in this research (TR) have better accuracy, with average values of 7.05 min and 0.984 for dRMS and NSE, respectively. Then, using the TR method for deriving the advance relationships and using the volume balance method, the coefficients of the Kostiakov–Lewis infiltration relationship were determined. The infiltration relationships derived from the TR method were compared with the infiltration relationships obtained from the two‐point method of EW. The results of this investigation showed that the TR method predicts the average infiltration depth with an average absolute relative error of 6%, which is more accurate than that of EW.

Section: Introductionmentioning

confidence: 99%

Determining Kostiakov–Lewis infiltration coefficients using the water advance relationship and optimization

Panahi

Seyedzadeh

Bahrami

et al. 2023

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“…Designers and farmers, aware of the water advance velocity along the field for different flow rates, can choose the appropriate field length (within limitations) and/or the appropriate inflow to achieve a better distribution uniformity and greater application efficiency (Davis, 1961). The importance of the advance relationship is in estimating the infiltration depth to develop operational recommendations that can reduce deep percolation losses (Seyedzadeh, Panahi, & Maroufpoor, 2020; Seyedzadeh et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Subsurface shape factor for surface irrigation hydraulics

Seyedzadeh

Panahi

Maroufpoor

et al. 2022

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An improved analytic solution is presented to estimate soil water infiltration by surface irrigation methods through a more rigorous determination of the subsurface shape factor, as applied in volume‐balance models. Based on the results of this analysis and by averaging the shape factor of previously published equations, a new relationship is presented, with a maximum error of 0.036%. Also, the effect of these relationships on the empirical parameters for the Kostiakov–Lewis equation and the water infiltration depth were evaluated. Based on this evaluation, the relative error difference of the infiltration depth of the actual subsurface shape factor value and the new relationship was less than 0.01%. Given the high accuracy of the proposed methodology and the simplicity of its form, this relationship is recommended for use in practical work to predict surface irrigation hydraulic performance and irrigation application efficiency.

Water depth and cross‐sectional area relationships in sloping surface irrigation systems

Seyedzadeh,

Panahi,

Maroufpoor

2024

The equations governing variations in water depth and cross‐sectional area along a field are crucial for solving the Saint‐Venant equations and determining surface water volume via the volume balance method to determine other hydraulic parameters of surface irrigation systems. Various researchers have proposed different formulations for this equation based on varying assumptions. In many investigations, the flow depth profile has been assumed to be parallel to the furrow bottom or modelled as an elliptical relationship. This study explored four different forms of equation to analyse changes in the water depth profile and to refine its mathematical representation. The coefficients of these equations were derived as functions of the surface storage coefficient. Using field data, the surface storage coefficient values and, consequently, the coefficients of the proposed relationships were determined. The calculated values of the flow cross‐sectional area along the field and the water surface storage volume were compared with the measured values using the established relationships. The most accurate relationship for estimating the flow depth profile was identified through this analysis.