In this study, to agroecological zoning of irrigated and rainfed wheat lands in the world, the first existing climatic and soil zones were analyzed, and were determined the frequency of production, cultivation area, and yield of each zone. Furthermore, the distribution map of climatic zones and soil was prepared. Afterward, by combining climatic zones and soil zones, agro-egological zones of irrigated wheat and rainfed lands of the world were obtained. Finally, the results obtained from agro-ecological zones were analyzed and the frequency percentage of each agro-ecological zone was calculated and the distribution map of agro-ecological zones was drawn.
2.1. GYGA Climate Map
In this map, climatic zones are separated based on the information of the following three variables (www.yieldgap.org/web/guest/cz-ted):
-
Growing degree days (GDD) with a base temperature of zero degrees Celsius
-
Temperature seasonality
-
Annual aridity index (AI)
Equation 1 is used to calculate the GDD:
Equation 1:\(GDD=\sum _{i}^{n}{t}_{i}\)
Where, GDD is the unit of temperature throughout the year in terms of day degrees; n, the number of days during the year, which is 365 days in normal years and 366 days in leap years; i, day of the year; ti, the average daily temperature on a day i. If the average daytime temperature of the year is below zero degrees Celsius, ti is considered zero for that day. Obviously, for a climatic zone, the higher GDD value indicates that the average temperature of that climatic zone is higher throughout the year.
The temperature seasonality is the standard deviation of average monthly temperatures that is obtained from Eq. 2:
Equation 2:\(\text{T}\text{e}\text{m}\text{p}\text{e}\text{r}\text{a}\text{t}\text{u}\text{r}\text{e} \text{S}\text{e}\text{a}\text{s}\text{o}\text{n}\text{a}\text{l}\text{i}\text{t}\text{y}=\sqrt{\sum _{m}^{12}\frac{{({t}_{m}-{t}_{avr})}^{2}}{12}}\)
Where, temperature seasonality is the coefficient of temperature fluctuations throughout the year; tm: the average temperature in the month m in degrees Celsius; tavr: the average temperature throughout the year in degrees Celsius. The larger seasonal temperature fluctuations coefficient for a climatic zone shows that temperature fluctuations are higher throughout the year in that climatic zone. In simpler terms, the difference between the coldest and warmest months of the year is greater.
The third index used for zoning by the extrapolation method of the Global Atlas of yield gap is an aridity index derived from Eq. 3:
Equation 3:\(AI=\frac{MAP}{MAE}\)
Where AI is annual aridity index; MAP: Average annual rainfall in millimeters; MAE: Average annual evaporation in millimeters. according to this equation, in a climatic zone, the smaller the amount of AI, the drier the zone.
To do zoning, first, all regions of the world were pixeled. The size of each pixel was 5 minutes (approximately 10 ˣ 10 km). A pixel was used in subsequent calculations in the case at least 0.5% of its area was covered by one of the important crops including corn, rice, wheat, sorghum, millet, barley, soybean, cassava, potatoes, sweet potatoes, bananas, peanuts, beans and Other legumes, sugar beets and sugarcane (www.yieldgap.org/web/guest/cz-ted).
For each pixel, the values of the variables described above are calculated. Then, zoning is done based on the classification that is done for each of these variables (Table 1) and the overlapping maps of these three variables. Ten classes for the GDD, ten classes for the annual aridity index, and three classes for the temperature seasonality have been created.
Table 1
Defined classes for each of the variables used in climate classification by the extrapolation method of the Global Atlas of yield gap.
GYGA code
|
GDD*
|
GYGA code
|
Aridity index**
|
GYGA code
|
Temperature seasonality***
|
1000
|
0-2670
|
0
|
0-0.2695
|
1
|
0-3.832
|
2000
|
2671–3169
|
100
|
0.2696–0.3893
|
2
|
3.833–8.355
|
3000
|
3170–3791
|
200
|
0.3894–0.4791
|
3
|
> 8.356
|
4000
|
3792–4829
|
300
|
0.4792–0.5689
|
|
|
5000
|
4830–5949
|
400
|
0.5690–0.6588
|
|
|
6000
|
5950–7111
|
500
|
0.6589–0.7785
|
|
|
7000
|
7112–8564
|
600
|
0.7786–0.8685
|
|
|
8000
|
8565–9311
|
700
|
0.8686 − 0.10181
|
|
|
9000
|
9312–9850
|
800
|
0.10182-12876
|
|
|
10000
|
> 9851
|
900
|
> 12877
|
|
|
* Calculation of the GDD based on the base temperature of zero degrees Celsius |
** Ratio of annual rainfall to annual evaporation potential |
*** The amount of standard deviation of the monthly temperature from the average annual temperature |
On this site, potential yield information is reported separately for climate codes for different countries. The weighted average potential yield for each of the climate codes (according to the area under cultivation in each climate code in each country) was calculated and generalized to other similar climate codes worldwide. In some climate codes where potential yield information was not available, the average potential yield in each temperature unit was calculated and their values were used as potential yield. For example, code 5903 does not have potential yield information, so the average potential yield was calculated for the climate code that had a temperature unit of 5000 (5003, 5103, 5203, etc.), and the value obtained was considered as the potential yield for the climate code 5903.
The map of GYGA is indicated in Fig. 1.
2.2. Soil zoning based on HC27
Soil information was obtained from IFPRI-Harvest Choice as indicated in Table 2 (Koo and Dimes, 2013). According to the GYGA protocol, soil types are chosen based on the coverage of the wheat growing area within the RWS buffer zone. A soil that covers at least 50% of the wheat growing area within the buffer zone is selected as dominant soil. If there is no dominant soil type within RWS, the soils with more than 10% coverage of wheat growing area within RWS are selected as dominant soils. The evaluation of HC27 for the situation in Iran with the SSM-iCrop2 model was reported by Nehbandani et al. (2020) and the results showed that the evaluation of this soil database is acceptable for Iran. This map was classified based on soil texture, three groups of clay, silt, and sand, based on soil depth, into three groups: deep, medium, and shallow, and based on fertility into three groups: high, medium, and low fertility (Table 2). Map of HC27 and distribution of the soil type was indicated in Fig. 2.
Table 2
Soil information in the world is based on IFPRI Harvest Choice (Koo and Dimes, 2013).
Soil #
|
Soil code
|
Depth (mm)
|
Albedo
|
Curve number
|
Drainage factor
|
Saturation limit (m3/m3)
|
Drained upper limit (m3/m3)
|
Lower limit (m3/m3)
|
1
|
HC1-Clay HF180
|
1800
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
2
|
HC2-Clay HF120
|
1200
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
3
|
HC3-Clay HF060
|
600
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
4
|
HC4-Clay MF180
|
1800
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
5
|
HC5-Clay MF120
|
1200
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
6
|
HC6-Clay MF060
|
600
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
7
|
HC7-Clay LF180
|
1800
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
8
|
HC8-Clay LF120
|
1200
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
9
|
HC9-Clay LF060
|
600
|
0.05
|
85
|
0.2
|
0.458
|
0.405
|
0.233
|
10
|
HC10-Loam HF180
|
1800
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
11
|
HC11-Loam HF120
|
1200
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
12
|
HC12-Loam HF060
|
600
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
13
|
HC13-Loam MF180
|
1800
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
14
|
HC14-Loam MF120
|
1200
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
15
|
HC15-Loam MF060
|
600
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
16
|
HC16-Loam LF180
|
1800
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
17
|
HC17-Loam LF120
|
1200
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
18
|
HC18-Loam LF060
|
600
|
0.10
|
75
|
0.5
|
0.41
|
0.307
|
0.180
|
19
|
HC19-Sand HF180
|
1800
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
20
|
HC20-Sand HF120
|
1200
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
21
|
HC21-Sand HF060
|
600
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
22
|
HC22-Sand MF180
|
1800
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
23
|
HC23-Sand MF120
|
1200
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
24
|
HC24-Sand MF060
|
600
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
25
|
HC25-Sand LF180
|
1800
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
26
|
HC26-Sand LF120
|
1200
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
27
|
HC27-Sand LF060
|
600
|
0.15
|
65
|
0.75
|
0.365
|
0.169
|
0.073
|
The number of each soil code is the deep of soil, HF, MF, and LF is high fertility, medium fertility, and low fertility respectively.
|