M. Ghahremannejad; Saeid Boroomand Nasab; AbdAli Naseri; A. Sheini Dashtegol
Abstract
Introduction: Infiltration is the most important physical properties of agricultural soils. Infiltration families are general relationships that attempt to categorize the infiltration behavior of soils. Walker et al. (2006) discussed the assumptions and procedures used to develop the original NRCS families. ...
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Introduction: Infiltration is the most important physical properties of agricultural soils. Infiltration families are general relationships that attempt to categorize the infiltration behavior of soils. Walker et al. (2006) discussed the assumptions and procedures used to develop the original NRCS families. Those families categorize infiltration behavior according to their steady-intake rate and were developed largely from border irrigation data. As such, those families have been more widely adopted in border/basin irrigation analyses than in furrow studies. In 2004, NRCS decided to revise the families, largely with the goal of enhancing their applicability to furrow irrigation (Walker et al., 2006). In contrast with the original families, Walker et al. (2006) categorized infiltration based on the average rate during the first 6 h of opportunity time. The new families were developed from furrow infiltration measurements, and then adapted to border conditions. Those infiltration measurements were obtained under inflow rate, slope, cross section, and roughness conditions. Recognizing that these flow conditions affect flow depth and that flow depth affects infiltration in furrows, Walker et al. (2006) proposed procedures for adapting the parameters to new hydraulic conditions. Procedures are also provided for adapting the parameters to events late in the irrigation season. Another important aspect of the new families is the use of the Extended Kostiakov equation, which represents steady-state infiltration better than the Kostiakov formula employed by the original NRCS families. The procedures used to adapt the furrow infiltration parameters to different hydraulic conditions are empirical. From the available data, Walker et al. (2006) developed relationships for the reference parameter values (Kref, aref, and f0ref) and reference hydraulic conditions (discharge Qref and wetted perimeter1 WPref) as a function of Fn, the family value.
In this study the currency of revised SCS method to estimate infiltration parameters of furrow irrigation systems in Amirkabir sugar cane fields was evaluated. For this purpose, infiltration parameters and the cumulative 6 hours infiltration (z) for furrow irrigation systems of this region was estimated with revised SCS method and, then compared with field measurement of z. Then, general functions were developed to adjust the parameters to later flow irrigation conditions.
Materials and Methods: This research was carried out from January 2010 to December 2011. As one of the research fields of Sugarcane Research Center in Amir Kabir Sugarcane Planting and by Products Company of Khuzestan. The field work was conducted on one set of furrow irrigation. This set had three furrows1.8 m wide and 140 m long. The middle furrow of each set was used to take measurements, while the side furrows were used as buffering area. The intake family numbers in revised SCS method (Fn) based on the average infiltration rate during the first 6 h of irrigation. To determine the Fn, double ring experiment were performed before irrigation. Then revised SCS parameters and original SCS parameters were determined. By measuring inflow, outflow, and calculating surface water storage, the volume of infiltrated water was determined. The advance and recession times were recorded at 14 points at 10 m intervals along each furrow. Seven irrigation events were examined. Fiberglass flumes (WSC) type II was used at the beginning and the end of each furrow in the first set where inflow/outflow measurements were to be taken. Experiments were carried out in order to determine the final infiltration rate (f0) with the assumption of uniform soil infiltration characteristics. First, inflow and outflow of the furrow were measured at the beginning and the end of two Fiberglass WSC flumes. Then, when the flow reached a constant level, f0 was measured.
Results and Discussion: For evaluation of the results, four statistical indices: average prediction error of model (Er), distribution into 45° line (λ), determination coefficient (R2) and average relative error of model (Ea) were used. According to the results, revised SCS method overestimated infiltration value and it had an excessive error. Due to the high error of this technique, empirical formulas for reference parameters to this irrigation conditions was determined. The values of a, K, and F0 parameters were measured in field and correlated with the NRCS Family Number, Fn. Then, general functions were developed to adjust the parameters to later flow irrigation conditions. Review the accuracy of the presented functions showed that these functions with values of λ, R2 and Ea respectively 0.95, 0.91 and %4.5, has the best prediction of infiltration. The coefficient of irrigation condition factor (ICF) for the desired area was determined that the average numeric value equal to 0.82. According to the results of Walker et al. (2006), a typical later continuous intake can be estimated by ICF of 0.80. The average value of the 6 h intake rate (Fn) for the desired area is 0.46 and the average value of basic infiltration rate (f0) is 0.48 which is larger than Fn. This is consistent with the results of Walker et al. (2006).
Conclusion: Results of this study showed that the original SCS method has underestimated cumulative infiltration and revised SCS method with furrow irrigation equations has the overestimated cumulative infiltration. General functions were developed to adjust the parameters to later flow irrigation conditions. Review the accuracy of the presented functions showed that these functions have the best prediction of infiltration. The coefficient of irrigation condition factor (ICF) was also determined, (ICF= 0.82).
