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Modeling the Effects of Spatial Variability of Irrigation Parameters on Border Irrigation Performance at a Field Scale

1,2,3, 4, 4, 4,* and 1,2,3,*
1
Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
2
Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
3
Institute of Water-Saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling 712100, China
4
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resource and Hydropower Research, Beijing 100038, China
*
Authors to whom correspondence should be addressed.
Water 2018, 10(12), 1770; https://doi.org/10.3390/w10121770
Received: 19 October 2018 / Revised: 22 November 2018 / Accepted: 26 November 2018 / Published: 1 December 2018
(This article belongs to the Special Issue Advances in Hydrogeology: Trend, Model, Methodology and Concepts)
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Abstract

The interaction between surface and subsurface water flows plays an important role in surface irrigation systems. This interaction can effectively be simulated by the physical-based models, which have been developed on the basis of the numerical solutions to the Saint-Venant and Richards’ equations. Meanwhile, the spatial variability of field physical properties (such as soil properties, surface micro-topography, and unit discharge) affects the interaction between surface and subsurface water flows and decreases the accuracy of simulating surface irrigation events at large scales. In this study, a new numerical methodology is developed based on the physical-based model of surface irrigation and the Monte Carlo simulation method to improve the modeling accuracy of surface irrigation performance at a field scale. In the proposed numerical methodology, soil properties, unit discharge, surface micro-topography, roughness, border length, and the cutoff time for the unit discharge are used as the stochastic parameters of the physical-based model, while field slope is assumed as the constant value because of the same field tillage and management conditions at a field scale. Monte Carlo simulation is used to obtain the stochastic parameter sample combinations of the physical-based model to represent the spatial variability of field physical properties. The updated stochastic simulation model of surface micro-topography, which is developed to model the spatial distribution of surface elevation differences (SED), is used to obtain the surface micro-topography samples at a field scale. Compared with the distributed-parameter modelling methodology and the field experimental data, the proposed numerical methodology presents the better simulation performance. View Full-Text
Keywords: field scale; border irrigation; spatial variability; Monte Carlo; numerical simulation field scale; border irrigation; spatial variability; Monte Carlo; numerical simulation
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Dong, Q.; Zhang, S.; Bai, M.; Xu, D.; Feng, H. Modeling the Effects of Spatial Variability of Irrigation Parameters on Border Irrigation Performance at a Field Scale. Water 2018, 10, 1770.

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