Agro-ecological zoning for cultivation of Alfalfa (Medicago sativa L.) using RS and GIS

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1 Scientia Agriculturae E-ISSN: X / P-ISSN: DOI: /PSCP.SA Sci. Agri. 9 (2), 2015: PSCI Publications Agro-ecological zoning for cultivation of Alfalfa (Medicago sativa L.) using RS and GIS Abbas Taati *, Fereydoon Sarmadian, Amin Mousavi, Asghar Rahmani Department of Soil Science Engineering, University of Tehran, P, O, Box: 4111, Karaj , I, R, Iran *Corresponding Author taatyabbas@yahoo.com Paper Information A B S T R A C T Agro-ecological zoning is one of the effective tools for identifying land Received: 9 October, 2014 resources and assign them to the best and most profitable forms of land productivity. In this study for Agro-ecological zoning of hectares of Accepted: 24 December, 2014 Qazvin province land in Iran, satellite imagery and Geographical Information System (GIS) were used. After Agro-climatic zoning (based Published: 20 February, 2015 on maps of isohyet, isothermal and length of growth period) and Agroedaphic zoning (based on maps of soil, slope and land use) 43 Agroecological Citation zoning were achieved. Then climate, soil and topographic characteristics of any zone were compared with Alfalfa requirements and Taati A, Sarmadian F, Mousavi A, Rahmani A land suitability classes were determined using parametric (square root) Agro-ecological zoning for cultivation of Alfalfa method. The results showed that studied area is highly suitable for Alfalfa (Medicago sativa L.) using RS and GIS. Scientia cultivation based on climate requirements. In addition, soil depth and Agriculturae, 9 (2), Retrieved from gravel percentage in the Northern part also salinity, alkalinity, lack of (DOI: organic material and gypsum are major limiting factors in the Southern /PSCP.SA ) part of area. Potential yield of Alfalfa was calculated by using FAO method and kg per hectare was calculated. Also land production potential in each of the zones was determined. This loss of yield in compared to potential yield is due to the impact of limiting factors that by using proper management actions such as adding organic material to soil, land drainage and leaching can increase crop yield PSCI Publisher All rights reserved. Key words: FAO, land use, potential yield, satellite images, square root, suitability classes Introduction Population growth and improve of life standards let to more food requirement so this issue result in think about new strategies for better land use and more crop production by human. Today there is no precise information about suitable land for cultivation of important crops and in the other side variety in the weather, soil and topography result in different Agroecological conditions that these conditions may be highly suitable, moderately and unsuitable for some crops (Ghaffari et al., 2012). so to achieve high production understanding limitations and capability of these areas is necessary. So can state that more food supply and other environmental resources with regard to protect biological resources for futures just could achieved by change in consume pattern and land usage. Sustainable agriculture is very useful method that can help human to achieve food safety. One applied method to achieve sustainable agriculture is land evaluation that able to solve these problems. So evaluation and management of land and soil have dispersible importance and need for applied program for efficient use of land is growing up (Teka and Haftu, 2012). Agro-ecological zoning is one of the land evaluations that used in this research and can use as pattern for better land evaluation, planning and management of land resources. FAO in1997 has described Agro-ecological zoning like that: Agroecological zoning as an evaluation unit, includes a relatively large area that base on classification, climate, soil, topography, land use and growth period requirements is homogeneous for the same desired crops. Agro-ecological zoning maps are indispensable tools for agriculture planning. In these maps play any key component role as single homogeneous complex and determine agricultural potential and its limitations to decision-makers and Agriculture planners (FAO, 1997). AEZ classify any area based on its abilities in terms of land potential and land capability. Due to the capabilities of GIS and remote sensing, using and integration of these systems by creating a set of databases in different layers and finally use of available models in the co-evaluation of layers, makes an important help to the Agro-ecological zoning (Maji et al., 1998; Walke et al., 2012). Agro-ecological zoning was applied in different countries for different purposes. For example can mention studies in Egypt by using GIS and RS in the agro-ecological zoning (Ismail, 2012). In Indonesia, Kandari et al (2013) performed Agro-ecological

2 zoning and land evaluation for maize cultivation by using GIS and used the FAO methods to determine land suitability classes. To sustainable development of agriculture in arid regions of Indonesia, land proportionality evaluation by using Agroecological method for different crops, an study was performed by Anasiru et al (2013). 12 units of land were obtained through overlapping layers of geology, geomorphology, topography and applied land use map. The results showed that 0.9%, 23% and 68% of land located in classes S1, S2 and S3 and N, respectively. This research was performed to Agro-ecological zoning a part of Qazvin plain land in Iran for cultivation of Alfalfa, Providing a comprehensive database of land resources properties for planning and organizing of optimal land use, Land suitability evaluation in each of the Agro-ecological zones by using parametric method (square root), Calculation of Alfalfa potential yeild and land production potential in each of the Agroecological zones and finally create a database in the GIS environment in order to extract the zoning maps of each soil profile. Material and methods Study area The study area is located in the Qazvin plain land in Iran, which covers an area of ha; between latitudes of 36 00' and 36 11' N and between longitudes of 50 16' and 50 20' E. The climate of the area is semi-arid with a mean annual rainfall of 258 mm and minimum and maximum relative humidity of 52 and 82%, respectively. The mean annual temperature is 14.1 C. The minimum and maximum altitude of the region are 1141 m and 1488 m, respectively.the soil moisture and temperature regimes of the region are Weak Aridic and Thermic, respectively (Soil Survey Staff, 2014). Common agricultures in the region include fall growth of irrigated barley, wheat, maize and alfalfa. The agriculture in the area uses traditional to semi-mechanized techniques and equipment (Taati et al., 2014). Soil sampling and Laboratory analysis After preliminary studies of topographic maps (1:25000), using GPS, studying location was appointed. 214 soil samples were collected from different horizons of 61 soil profiles located in the region (Taati et al., 2014). Physical and chemical properties of the sieved soil samples (<2mm) were determined after being air dried (Darvishi Foshtomi et al., 2011). Particle size analysis by hydrometer method, Organic Carbon (OC) was determined using Walkley-Black method (Nelson and Sommers, 1982), Electrical conductivity (EC) and ph were determined in a saturation extract of soil using conductivity meter and ph meter, respectively, CaCO 3 content was determined using Calcimetry method, gypsum content was determined using Acetone method and CEC (cation exchange capacity in cmol c kg -1 soil) determined by the method of Bower (Sparks et al., 1996; Keshavarzi et al., 2010). Total nitrogen and available phosphorus were determined by Kjeldahl and Olsen method, respectively. Isohyet map In order to prepare the Isohyet map, because in the studied area the number of meteorological stations were limiting, Isohyet map supplied by the Directorate General of Qazvin weather. This means that in order to prepare isohyet map the normal average annual rainfall precipitation data from 60 different meteorological stations (Synoptic and Climatology) inside and outside the province in a 27-year period ( ) were used. And for interpolation, IDW method in ArcMap software was used. Finally, Isohyet map area obtained, and then the raster map was converted to vector and was used as a layer in the zoning. Isothermal map For obtain isothermal map, the regression equation between annual mean temperature and height were used. Tmean = H R 2 = [1] In this equation Tmean is the annual average temperature and H is the height. And finally by entry the digital elevation model (DEM) with a spatial resolution of 10 m, the map area isotherm was obtained. Then Rastery map was converted to the vector map. Length of growing period map In this study for obtain length of growing period map, at the first evapotranspiration potential during for four weather stations (NIRUGAH, BAGH KOUSAR, QAZVIN and BOYIN ZAHRA) obtained by Cropwat software and as well as Growth period was calculated for these stations. According to the FAO, the growth period in the each zone includes a period of year that agricultural production because of sufficient moisture and lack of thermal limits is possible and growth period in each area is period that weather temperature is more than 6.5 ºC and precipitation more than half of evaporation and transpiration potential in addition to the number of days needed to deplete 100 mm of stored water in the soil after the rainfall (FAO, 1996). One of the calculating methods of growth period referred here is a linear method. In this method the ten days climate data and the consecutive decades to demarcate the period are used. If we consider two consecutive decades that the amount of rainfall 94

3 are P1 and P2 and evapotranspiration potential values for the first and second decades are E1 and E2; Beginning of growth period and rainfall end can be obtained by the following equation: t = integer [(P1 1/2E1) 10 ] (P1 P2+1/2E2 1/2E1) t is the time in days that starts from the middle of the first decade. In the equation [2] If the rules are true, start of the growth period (the rainfall) will be: P 2 > 1/2E2, P1 < 1/2E1 And if the rules are true, the end of the rainfall will be: P1 > 1/2E1, P2 < 1/2E2 Beginning and end of the wet period obtain by the following equation: t = integer [(P1 E1) 10] [3] (P1 P2+E2 E1) t is the time in days that starts from the middle of the first decade. In the equation [3] If P1 < E1, P2 > E2 the beginning of period is wet and if P1 > E1, P2 < E2; the end of the growth period is wet. End of growth period End of growth period achieved by adding the number of days in which 100 mm of soil water is evaporated to end of the rainfall period. After obtaining growth period for these stations, maps of the area growth period were obtained based on stations location and isothermal and isohyet lines. The Soil Map For soil mapping, by using interpretation of aerial images 1/40000 area and also the IRS images as auxiliary data as well as according to field studies, morphological properties of 61 soil profiles and doing physical and chemical needed testes on the soil samples, soil families were determined and finally the soil map was prepared. the map slope was obtained by using digital elevation model (DEM) in the ArcMap. Land use map To prepare a land use map of area, the Landsat 7 ETM + sensor images related to year 2011 with 30 m spatial resolution was used. These images are located on the satellite path 165 and row 35, which have been acquired from After processing the satellite images, land use map by support vector machine algorithm in the software environment ENVI4.3 was extracted (Mountrakis et al., 2011; Otukei and Blaschke, 2010; Huang et al., 2002). Agro ecological zoning map Agro ecological zoning map of the studied area was obtained by combination of Agro- climatic and Agro- edephic zoning maps and using the Union function in GIS environment. Land suitability evaluation In order to Land suitability evaluation in Agro-ecological zoning, conformity of the land characteristics in each defined zoning with Alfalfa growing requirements was done and the final class of land was measured. In this study the parametric method (square root) reported by (Sys et al., 1991) was applied for determining land suitability classes. In this method, a quantitative rating assigned to each characteristics of land. If the property is quite favorable for the desired crop, it will be assigned number 100 as maximum degree. If that characteristic has limitations, the lower grade will be assigned. In the square root equation [4] is used to obtain the land index. I = Rmin A 100 B 100 [4] Where: I = Land Index, A, B, C,... = degrees assigned to each of the land characteristics, Rmin = characteristic with minimal degree. Then the land suitability class was determined by using (Table 1). Table 1. Land suitability classes based on Land Index in the parametric method (square root) ) Sys et al., 1991(. Suitability classes Index Highlysuitable(S1) Moderatelysuitable(S2) Marginallysuitable(S3) Unsuitable(N) 0-25 [2] 95

4 Radiation-Thermal Crop Production Potential (RPP) The radiation-thermal crop production potential is the maximum production that a high-yielding variety at a specific location can achieve under optimal conditions being free of stresses of water, nutrients,pests and diseases, and on a constraintfree soil. The RPP value is given by the following equation [5]: RPP = 0.36bgm KLAI Hi/[ 1 L Ct] [5] Where: bgm is the maximum gross biomass production rate, KLAI the maximum growth rate ratio (KLAI=0.35LAI- 0.03LAI 2 ), Hi the harvest index, L the length of crop cycle and Ct the respiration coefficient [Ct = C30( t t 2 ), where t is the mean daily temperature and C30 takes the value of for non-legumes or of for legumes (Sys et al., 1991; Ye and Van Ranst, 2002). The maximum gross biomass production rate can be calculated from the sum of the maximum gross biomass production rate on overcast days and the maximum gross biomass production rate on clear days: bgm = f. bo + (1 f). bc [6] Where: f is the fraction of the daytime that the sky is overcast, f =1-n/N, bo and bc are function of latitude and time of the year. Their values can be found from tables (Van Ranst, 1991). But such values are only valid at light saturation (Pm)of 20 kg CH 2 O.ha -1.hr -1. The following corrections have to be made when Pm is different from 20 kg CH 2 O.ha -1.hr -1 : or bgm = f bo. ( y) + (1 f) bc. ( y) when Pm > 20 [7] bgm = f bo. ( y) + (1 f) bc. (1 0.01y) when Pm < 20 [8] Where: is the difference (%) to the value of 20 kg CH 2 O.ha -1.hr -1. Y=(pm-20)* Results and discussion After overlapping desired maps in the GIS, the studied area was defined and separate into 43 Agro-ecological zones. (Fig. 1) shows desired area Agro-ecological zoning map. In this map, the Agro-ecological zoning was shown with the letters A to AO. In this map, the Y-zone with hectares is the biggest zone with 10.88% of the area. And Z-zone with hectares is the lowest zone that includes the 0.45% of the area. The results of climate evaluation Results of climatic evaluation for Alfalfa cultivation showed that in totally the climate do not make serious limitations for growth and climate suitability class is Highly suitable (S1). Figure 1. Agro-ecological zoning map of the study area. Land suitability evaluation results (Fig. 2) shows Agro-ecological zoning map for Alfalfa by using parametric method (square root) and Land suitability classes in each zone are shown in (Table 2). (Fig. 3) also shows the area of each land suitability classes. 96

5 Figure 2. Agro-ecological zoning map for Alfalfa using parametric methodes (square root). Table 2. Land suitability classes in each Agro-ecological zones for Alfalfa. Agro-ecological zones Land index Suitability classes A S3s* B S1 C S1 D S2nf E S2nf F S2nf G S3ns H S3ns I S3ns J S3ns K S3ns L S2s M S2s N N O N P S2ns Q S2sf R S2s S S3s T S3s U S3s V S2s W N X S1 Y S1 Z S3ns AA S3ns AB S3s AC S1 AD S2s AE S2s AF S2s AG S1 AH S2s AI S1 AJ S1 AK S1 AL S3s AM S3s AN S2s AO S2s *n, s and f represent the salinity and alkalinity limitations, physical properties of soil and fertility 97

6 LPP(kg/ha)l Sci. Agri. 9 (2), 2015: Area (ha) S1 S2 S3 N NS Suitability Classes Figure 3.The area of each land suitability classes for Alfalfa. According to the data available in (Table. 2) and (Fig. 3), nearly 5216 hectares of the total area of the region belong to class S1, and 5779, 4128, 870, and 625 hectares to classes S2, S3, N, and NS (unstudied), respectively. Soils with an average texture, an optimum depth (greater than 100 cm), and well drainage are known as suitable zones for cultivation of Alfalfa. These properties can be observed in the following zones: B, C, X, Y, AC, AG, AI, AJ, and AK, which leads to highly suitable (S1) classes in these zones. In zone Q, the main limiting factor refers to the physical properties and soil fertility. In zones V, AD, AE, AF, and AO, the amount of gravel is away from the optimum value (with 0-15 percent difference), which results in the determination of class S2 in these zones. Zones O, N, and W are positioned class N. The main limitation factors in zone W are the high gravel percentage and the soil depth. In addition, in zones O and N, salinity and alkalinity, lack of organic material and gypsum of the soil are considered as the major limitations. Cultivation of Alfalfa in these zones decreases the potential yield from 60% to 100%. In zones G, H, I, J, K, Z, and AA, salinity and alkalinity of the soil as well as the existence of high amounts of gypsum are the main limiting factors. The optimum amount of gypsum for cultivation of alfalfa is from 0 to 4 percent, and the higher the amount of gypsum is, the more critical the suitability class will be, and as a result, the product yield will be decreased (Navidi, 2011). In zones S, T, U, AB, AL, and AM, the low depth of soil and the existence of gravel on the soil surface lead to the determination of class S3 in these zones.in a similar study, Jafarzadeh et al. (2006) studied the qualitative land suitability evaluation for cultivating alfalfa in Tabriz. They applied simple limitation method, limitation method regarding number and intensity of limitation, and parametric methods (storie and square root) to specify the suitability classes. Their results demonstrated that the most important factors that restrict the growth in the region include soil fertility properties (organic carbon), texture, gravel, and soil ph. Radiation-Thermal Production Potential (RPP) By using the FAO method that previously described, Radiation-Thermal Production Potential of Alfalfa were obtained tons per hectare. As well as land production potential (LPP), was calculated for Alfalfa by using result Indices from square root method in each zones (Tang et al., 1992). The results are shown in (Fig. 4) A B D E G I J L N O P Q R S U V W X Z AB AC AD AE AG AH AI AL AN Zones Figure 4. Land Production Potential in each zones for Alfalfa. 98

7 Alfalfa yield was predicted between and kg per hectare by using the square root method. The lowest yield is observed in zones O and N, and the highest yield can be obtained in zone AC. The crop yield depends on land related limiting factors and suitable using better done based on yield in any Agra-ecologic zoning. This decline in yield in any of the Agro-ecological zones, due to effect of limiting factors including limitations related to soil physical properties such as soil depth and gravel percentage in the northern part of the area and as well as salinity and alkalinity land, lack of organic material and gypsum in southern region. Behzad et al (2009) in the khuzestan Province also showed that the most limiting factors of the land suitability, in Alfalfa productions included physical characteristics such as soil texture, soil depth and lime content. Central parts of area, which includes zones B, X, Y, AC,AI have high potential for the Alfalfa production and Alfalfa cultivation should be priority in this area. In zones with the lower with proper management practices such as adding organic material to the soil, drainage, lands leaching, crop rotation, use of salinity resistant cultivars and modern methods of irrigation can increase water use efficiency. Conclusion The main aim of this study was Agro-ecological zoning part of Qazvin province land in Iran as an indispensable tools for agricultural planning. By overlay Agro-climatic and Agro-edaphic zoning maps, 43 Agro-ecological maps were obtained. Land suitability and land production potential evaluation was performed in each zone for Alfalfa based on parametric method (square root). The results showed that climatic properties do not create significant limitations for Alfalfa cultivation. 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