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Efficiency improvement in linear-move sprinkler systems through moderate runoff–runon control

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Abstract

Given the importance of achieving substantial water and operation savings, automated irrigation management has evolved toward integration of soil moisture measurements with simulation models. The main objective of this study was to develop a set of procedures to maximize irrigation efficiencies in linear-move irrigation systems. A system of field truth data collection and spatially distributed, physically based hydrological modeling was developed to evaluate the efficiencies of linear-move systems considering various naturally occurring boundary conditions and management options. Interactions among the irrigation flow depth, the evaporation conditions, the net infiltration depth and soil moisture uniformity, the irrigation turn duration and runoff–runon production were considered. Environments were of the semiarid Patagonian Monte at varying field slope and antecedent soil moisture. Plot experiments on infiltration and overland flow were used to calibrate a modified version of the CREST hydrological model adapted to the simulation of linear-move irrigation. Modeling results show that irrigation efficiencies can be improved by allowing runoff–runon to occur to an extent compatible with adequate soil moisture uniformity at the end of the irrigation turns. High efficiencies in both attaining effective infiltration depths and minimizing irrigation turn durations may be reached by adjusting the irrigation flow depth through the advance velocity of the irrigation system and/or inter-nozzle distances with due consideration to the antecedent soil moisture condition and the field slope.

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Abbreviations

BCMF:

Boundary conditions and management factors

CREST:

Coupled routing and excess storage

DDM:

Drainage (flow) direction map (8-cell convention)

DEM:

Digital elevation map

EM:

Evaporation flow map

FAM:

Flow accumulation factor (number of contributing upstream map cells)

GPS:

Global positioning system

IIM:

Irrigation intensity map

RRM:

Runoff–runon depth map

TDI:

Tension disk infiltrometer

θ i :

Soil moisture depth at location i (mm)

θ l,irr :

Soil moisture depth increase due to irrigation (mm)

θ v :

Soil moisture content (mm3/mm3)

\(\bar{\theta }_{l,a}\) :

Average antecedent soil moisture depth (mm)

\(\bar{\theta }_{v}\) :

Average volumetric soil moisture depth (mm3/mm3)

\(\bar{\theta }_{{l,{\text{end}}}}\) :

Average soil moisture depth at the end of irrigation turn (mm)

\(\bar{\theta }_{{l,{\text{irr}}}}\) :

Average soil moisture depth increase due to irrigation (mm)

σ RRF :

Standard deviation of runoff–runon factor

σ θv :

Standard deviation of volumetric soil moisture depth (mm3/mm3)

a, b, c :

Coefficients of infiltration function (mm/min)

A i :

Irrigated area (mm2)

CU:

Coefficient of uniformity (%)

DS:

Depressional storage area (%)

e a :

Irrigation application efficiency (mm/mm)

e t :

Irrigation turn duration efficiency (mm/min)

E v :

Evaporation flow (mm/min)

\(\bar{E}_{v}\) :

Average value of the EM (mm/min)

F :

Cumulative frequencies of θ v at various class values

I n,p :

Infiltration flow fed from runoff–runon flow and ponded water (mm/min)

I n,s :

Infiltration flow fed from sprinklers (mm/min)

I r,a :

Cumulative irrigation flow depth (mm)

Irr:

Irrigation flow (mm/min)

ITD:

Irrigation turn duration (min)

K sat :

Saturated hydraulic conductivity (mm/min)

ND:

Inter-nozzle distance (m)

NIC:

Number of irrigated cells in field digital map

NRR:

Number of cells where runoff–runon occur

pCoem :

Overland flow friction factor

pLeaOne :

Coefficient of non-depressional storage (100-DS)/100 (%)

RR:

Runoff–runon depth (mm)

RRF:

Runoff–runon factor

\(\overline{\text{RR}}\) :

Average value of the RRM (mm)

\(\overline{\text{RRF}}\) :

Average runoff–runon factor (all scenarios)

S :

Field main slope (%)

TWI:

Topographic Wetness Index

V :

Velocity of the linear-move irrigation system (m/min)

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Acknowledgments

The authors gratefully acknowledge financial support from Agencia Nacional de Investigaciones Científicas y Técnicas (ANPCyT) PICT 07-1738 and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) PIP 1142 0080 1002 01. J. Rossi was a doctoral CONICET Fellow at National Patagonic Center (2008-2014). An anonymous reviewer provided pertinent comments to the first version of this manuscript.

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  1. National Patagonic Centre, CONICET, Boulvd. Brown 2915, 9120, Puerto Madryn, Chubut, Argentina

    M. J. Rossi & J. O. Ares

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Correspondence to M. J. Rossi.

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Communicated by E. Fereres.

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Rossi, M.J., Ares, J.O. Efficiency improvement in linear-move sprinkler systems through moderate runoff–runon control. Irrig Sci 33, 205–219 (2015). https://doi.org/10.1007/s00271-015-0460-x

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