Border irrigation performance with distance-based cut-off

A Method for Determining the Discharge of Closed-End Furrow Irrigation Based on the Representative Value of Manning’s Roughness and Field Mean Infiltration Parameters Estimated Using the PTF at Regional Scale

“…The simulated values of the advance time and performance indicators had a slight influence when the various Manning's roughness values (0.041, 0.075, and 0.175) were adopted (Figure 4), indicating that the advance trajectory and performance indicators of closed-end furrow irrigation were not sensitive to variations of Manning's roughness. This result was similar to the results of Smith et al [2], Salahou et al [5], and Nie et al [19]. These findings indicate that the Manning roughness of maize field can be used as a representative value (i.e., 0.075, 50% of the cumulative frequency of all experimental sites) to simulate the advance trajectory and irrigation performance of a closed-end furrow.…”

“…Because of the short length of the fields in northern China, which are mostly shorter than 200 m [41]-the maximum length of the furrow irrigation in this study was 130 m, as evident in Table 1-and a fairly short opportunity time (maximum opportunity time was 66 min), it was generally difficult to achieve stable infiltration, while estimation of the basic infiltration rate was challenging. Various studies have demonstrated that the Kostiakov equation achieves a high degree of precision in describing the soil infiltration process of surface irrigation [5,[42][43][44][45]. Therefore, the Kostiakov equation was adopted to characterize the infiltration process of furrow irrigation; which can be written as:…”

“…Advanced simulation models of surface irrigation have been proven to be effective for evaluating system design and management, and for improving irrigation performance. Manning's roughness and field mean infiltration parameters are essential input parameters for surface irrigation simulation models [3][4][5][6]. Therefore, it is vital to obtain realistic estimates of Manning's roughness and field mean infiltration parameters.…”

Strategies to Cope with Risks of Uncertain Water Supply in Spate Irrigation Systems

“…The objective of the scenario analysis was to optimize the practical field layout configuration and operation practice, as one method for reducing flood risk due to flow variability in GAS. The measured data used for the evaluation and calibration analysis were: field dimensions (8,400×500 m), daily inflow hydrographs, observed advance and recession curves, field slope (13.8 cm/km), observed average inflow rate (2,270 l/s), cutoff time Tco (600 hrs), soil type (silty clay) and estimated Manning roughness (n= 0.08), which is within the basic recommended range of the field roughness conditions 0.06 to 0.09 (Bautista et al, 2009a, Salahou et al, 2018, Zhang et al, 2006. Three strategies were investigated: 1-time management, 2-field design and time management, and 3-field design and flow management.…”

“…With limited literature on spate irrigation, field water management was described in terms of water rights and rules, field structures, field distribution systems and size of command area , Komakech et al, 2011, Van Steenbergen, 1997, Koppen et al, 2007. Previous studies on field design and optimization focused on conventional irrigation systems with a fixed predetermined supply and application time (Bautista et al, 2009b, Zerihun et al, 2005, Salahou et al, 2018, Adamala et al, 2014, Anwar et al, 2016, Bo et al, 2012 while research on field design in spate irrigation characterized by water supply variability is uncommon. Moreover, research on optimizing field dimensions and cut-off times (Tco) for a range of unpredictable inflow volumes under the complex conditions encountered in spate irrigation are lacking.…”