Presenting a Mathematical Model for Estimating the Deep Percolation Due to Irrigation

Transcription

1 International Journal of Hyraulic Engineering 2015, 4(1): DOI: /j.ijhe Presenting a Mathematical Moel for Estimating the Deep Percolation Due to Irrigation Kaveh Osta-Ali-Askari 1,*, Mohamma Shayanneja 2 1 PhD Stuent, Department of Water Engineering, Faculty of Civil Engineering, Najafaba Branch, Islamic Aza University, Najafaba, Iran 2 Associate Professor, Water Engineering Department, Isfahan University of Technology, Isfahan Province, Iran Abstract Infiltration is one of the most important factors of hyrology cycle. Deep percolation is the flowing of soil water by gravity below the effective epth of the root zone, that is an important factor in filling of grounwater an esign of subsurface rainage. Deep percolation can be etermine by taking fiel ata to estimate soil water epletion using water balance equation. This metho is very expensive an time consuming. The goal of this research was to quantify eep percolation ue to irrigation with using a mathematical moel. The input variables of this moel are the effective parameters on eep percolation such as, be slope, inflow rate an coefficients of soil infiltration. These variables were measure at 16 farms in Zayanehroo basin. Comparison between estimate an measure eep percolation showe that the moel s error percentage is 1.73%. Keywors Deep percolation, Infiltration, Moel, Soil properties 1. Introuction Generally, percolation is one of the components of the hyrology cycle. Water which ue to irrigation or rain percolates in pastures or farmlans, ivies into two parts. Part of it is preserve in the root region of pasture plants or crops which is use by plants. Another part leaves the root region which is calle eep percolation. In other wors, eep percolation is the soil water movement by the gravity force below the region of roots. Deep percolation plays a crucial role in stuies of artificial nutrition of pastures an catchment basins an esigning of rains. Stuies inicate that there are two methos available for estimating or measuring the eep percolation: 1. The water balance metho: In this metho percolation is measure through employing the relation p1, an measurement of soil humiity at the root region, evaporation an transpiration an also measurement of rain an irrigation epth. (1) In this equation, I inicates epth of irrigation water * Corresponing author: Kaveh.oaa2000@gmail.com (Kaveh Osta-Ali-Askari) Publishe online at Copyright 2015 Scientific & Acaemic Publishing. All Rights Reserve percolate into the soil, Re is epth of the percolate rain, ET stans for the evaporation an transpiration epth, DP is epth of the eep percolation water, n is the of soil layers in which humiity is measure, θ 1 an θ 2 stan for volumetric soil moisture at the beginning an at the en of the perio an i is the epth of the soil its layer. Philips et al (1) estimate the eep percolation in an irrigate alfalfa crop in south central Colorao using the water balance an base on publication ASCE NO. 70 (2) 2. Metho of concurrent measurement of moisture an soil suction at various epths. In this metho, first soil moisture an suction at ifferent soil epth is measure an the soil moisture slope is rawn. Then employing the Couric an Millington metho, presente by Bouwer an Jackson (3) capillary conuction is estimate. Intensity of eep percolation base on Darcy law, is compute from the prouct of capillary conuction an suction curve slope between the two specifie epths. Stentizer an Gassner (4) employe this metho for estimating the eep percolation. Although the above sai methos have provie goo results however, they are very time consuming an expensive. In this paper, a mathematical moel is presente for estimating the eep percolation base in some characteristics of the soil an total water percolate to the soil, an its precision in comparison with the measure rates has been stuie.

2 18 Mohamma Shayanneja et al.: Presenting a Mathematical Moel for Estimating the Deep Percolation Due to Irrigation 2. Materials an Methos 1. Introucing the stuie region stuies relevant to this research have been one in the Morghab sub-basin in the center of Zayanehroo basin. This sub-basin is ajacent to the Zarcheshme sub-basin in the south, Shurehagham sub-basin in the south west, Gavekhuni sub-basin in the east, Plasjan sub basin in the west an Khoshkroo an Arestan sub basin in the north. Surface area of this basin has been reporte to be ha, equal to 29% of the Zayanehroo basin. Climate of the Morghab sub-basin accoring to the Gucene classification inclues four areas base on which the Asgaran area is situate in the steppe climate, Tiran an other foothills are locate in the slight semi- esert climate an the en of the sub-basin incluing Rooshetin, Jarquyeh an Mahyar are situate in the esert climate. Water sources of Morghab sub-basin inclue subsurface sources like source, Qanat an Wells estimate to be about 2.2 billion m 3 an surface sources like Morghab River an Zayanehroo of about 1.4m 3. Total farmlans have been reporte to be ha from which ha are irrigate, 3139 ha are ry farming an ha are orchars an nurseries. Common irrigation methos of farmlans inclue sprinkler irrigation, furrow an flooing irrigation for water cultivation an basin irrigation for orchars. Table 1. Investigate fiel properties name an location Soil texture Crop type 1 Eslam aba in Najaf aba clay loam Wheat 2 Alvar in Asgaran silty clay Wheat 3 Chah go in Nasim aba sany loam Wheat 4 Yaghoot aba in Yaghoot aba clay loam Wheat 5 Ghajavarestan in Ghahab silty clay Wheat 6 Naeri in Jey an Ghahab silty loam Wheat 7 Zamani in Ghahab silty clay Wheat 8 Dashti Ahmai in South Braan silty clay loam Wheat 9 Vajareh in North Braan clay loam Barley 10 Janata ba in Najaf aba loam Alfalfa 11 Jafar aba in Karvan loam Clover 12 Ashtarjan in Falavarjan silty loam Alfalfa 13 Ghajavarestan in Ghahab silty clay Alfalfa 14 Vareh Kharboze in Ghahab silty clay Alfalfa 15 Mosayebi in Borkhar silty loam Corn 16 Dooghi in Jey an Ghahab silty loam Corn The rate of water consumption in the agriculture sector is reporte to be 2.6 billion m 3 24% of which is provie from sources of surface waters an the rest is obtaine of wells, Qanats an sources. Accoring to the performe agrology stuies about 45% of lars are locate in 5.2 unit, 10% in the 5.3 unit, 20% in the 4.1 unit, 10% in the 4.2 unit an remainer of the lans with agricultural application are locate in 4.3, 4.4, 3.1, 3.2, 8.1, 8.2, an 7 units. ata collection has been one from the farm which is at present water irrigate an has a meium to heavy soil texture. Stuy of farming situation in the Morghab area inicate that wheat is consiere as ominant autumn culture, rice an corn for summer culture an alfalfa for perennial culture. Thus, regaring the uner cultivation surfaces, 9 measurements in the wheat farms, 5 measurements for alfalfa an 2 measurements in the corn farms was performe. Specifications of the farms are presente in table Measurement of parameters effective on eep percolation from the 16 above sai farms, parameters effective on eep percolation were collecte as follows. A. Slope of the farm (s) B. Percolation Coefficients of the lewis-kostiakov equation explaine in relation 2: In this equation Z stans for epth of the percolate water, f 0 is velocity of final percolation of soil, accoring to m/min, t is percolation time in minutes, an k an a are coefficients the percolation equation. Final percolation velocity an percolation coefficients were etermine by fiel tests. C. Depth of the available moisture (epth of the water present in the soil which is easily available for the plant) which is compute from the equation (3); In this equation n stans for available moisture in meter, FC is volumetric percentage of soil moisture in fiel capacity, PWP is the volumetric percentage of moisture at the permanent willing point, is root epth in meter, an P is percentage of permissible moisture ischarge. FC an PWP values were etermine via fiel tests. D. Irrigation perio compute from the relation 4: In this relation tco inicates irrigation perio in minutes, g stans for epth of water entere to the farm in meter, A is surface area of the farm in square meter, an q is the inflow ischarge to the farm in m 3 /min. therefore through inclusion of the irrigation perio in the consiere mathematical moel, its three relevant parameters are inclue as well which are etermine through fiel measurements. 3. Measurement of eep percolation: In orer to measure eep percolation the following stages are performe: (2) (3) (4)

3 International Journal of Hyraulic Engineering 2015, 4(1): The progress-regress cure is rawn an then, the percolation time respite is compute from the ifference of progress an regress time. - Through insertion of percolation time of each point in the relation (2) epth of the percolate water for each point is calculate. - The eep percolation rate at each point is compute from the ifference of available moisture an epth of the percolate water at each point. In case the ifference result is negative, eep percolation is zero. Therefore, these volumes of the eep percolation water at the istance between two consecutive i an i + 1 point is compute accoring to figure (1) an via the relation (5): In which, W stans for with of the farm, X i istance between two consecutive points i an i + 1, n epth of the available moisture, an Z i+ 1 an Z i inicate i points respectively. Figure1. percolation situation at two consecutive points. An, finally, percentage of eep percolation is etermine employing relation (6). epth of the percolate water in i an + 1 (5) 3. Results Values of measure parameters for 16 farms are presente in table 2. In this table L stans for length of the farm. In orer to prepare a mathematical moel amongst the parameters effective on percolation, epenent variables were such ranomly selecte that maximum correlation coefficient an minimum error woul be obtaine. To o so/even some o the variables were combine. Finally, following final stuy, the most appropriate epenent variables in the moel were selecte as follows: 1. The farm slope (s) 2. n j ratio which in cases of full irrigation, this ratio will be the irrigation efficiency. 3. Irrigation perio ( t co ) through inclusion of which parameter base on relation (4), surface area of the farm an the flow ischarge woul be consiere. 4. Depth of the percolate water uring the irrigation perio, that by placing t co in relation (2) is obtaine as follows: Z = k +. t (7) co a. tco f0 co (6) Figure 1. The penetration situation in two consequent point

4 20 Mohamma Shayanneja et al.: Presenting a Mathematical Moel for Estimating the Deep Percolation Due to Irrigation a k Table 2. Measurement summery in investigate fiel s properties F0 (m/min) q (m3/min) S (m/m) L (m) W (m) n(m) g(m) DP% Figure 2. The comparison between measure an calculate eep percolation Table 3. properties for moel preparation S Zco (m) n g t co (min) DP% Through inclusion of this parameter, percolation coefficients will be taken into account as well.\table (2) summary of measurements in ifferent farms. Amongst information gathere on 16 farms, information on 10 farms were ranomly use for preparing the moel (accoring to table 2) an information of 6 farms was use for it confirmation. (8)

5 International Journal of Hyraulic Engineering 2015, 4(1): To confirm the moel an stuing its precision, the root of multiple square error (RMSE) was use as in relation (9): In which DP m is the measure eep penetration which has been compute using the above sai fiel measurements an relation (6); DP c is the eep penetration compute via relation (8) an N is the of farms. Comparison of measure eep penetration values an compute ones inicate that the moel has ha a suitable precision in estimating the eep penetration rate. The RMSE in this research is equal to 1.73 an also the compute correlation coefficient is equal to showing appropriate precision of the moel in estimating the eep penetration rate. Figure 2 epicts the moel's precision in estimating the rate of water penetration epth. 4. Discussion Regaring complexity of the penetration process, it is necessary to not that statistical methos are powerful tools for expressing the relationship between the factors influencing the penetration phenomenon which have been consiere in investigations of many of the researchers. Inclue are Mishra et al. (5) who employing the statistical relations, stuie the precision of 14 moels in estimating penetration in the soils with ifferent textures. (9) Their results, ue to ifferent fiel conitions an employment of ifferent penetration relations cannot be compare with our results. Meanwhile results obtaine of the above moel has shown that in soils with meium an heavy textures, instea of other time consuming an expensive methos using statistical moels achieve results with appropriate precision for estimating the eep percolation rate. REFERENCES [1] Philips, R.W Measuring eep percolation for an irrigate alfalfa crop in south central Colorao. A proposal project for the egree of master of water resources. University of Newmexico [2] Evapotranspiration an irrigation water requirement ASCE manual an Reports on Engineering Practice, 70. New York. [3] Bouwer, H & R.D Jackson Determinig soil properties. Agronomy series 17, American Society of Agronomy. Maison. Wisconsin [4] Stentizer, E. & L. Gassner In situ estimation of eep percolation in a ry area by concurrent measurements of soil water content an soil water potential. Geophysical Research Abstracts. 7: [5] Mishra, S.K., J.V. Tyagi & V.P. Singh Comparison of infiltration moels. Hyrol. Process. 17: