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Regional Sustainability >

2024 , Vol. 5 >Issue 3: 100156

DOI: https://doi.org/10.1016/j.regsus.2024.100156

Full Length Article

Assessing the impact of climate change on agricultural production in central Afghanistan

  • Homayoon RAOUFI a, b ,
  • Hamidreza JAFARI , a, * ,
  • Wakil Ahmad SARHADI c ,
  • Esmail SALEHI a
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  • aDepartment of Environmental Planning, Management and Health, Safety, and Environment, Faculty of Environment, University of Tehran, Tehran, 14174-66191, Iran
  • bFaculty of Agriculture, University of Kunduz, Kunduz, 3502, Afghanistan
  • cFaculty of Agriculture, University of Kabul, Kabul, 1001, Afghanistan
* E-mail address: (Hamidreza JAFARI).

Received date: 2023-11-08

  Revised date: 2024-05-01

  Accepted date: 2024-08-19

  Online published: 2025-08-14

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Abstract

Afghanistan has faced extreme climatic crises such as drought, rising temperature, and scarce precipitation, and these crises will likely worsen in the future. Reduction in crop yield can affect food security in Afghanistan, where the majority of population and economy are completely dependent on agriculture. This study assessed the interaction between climate change and crop yield in Kabul of Afghanistan during the reference (1990-2020) and future (2025-2100) periods. Climate data (1990-2020) were collected from four meteorological stations and three local organizations, and wheat yield data (1990-2020) were acquired from the United States Agriculture Department. Data during the reference period (1990-2020) were used for the validation and calibration of the statistical downscaling models such as the Statistical Downscaling Model (SDSM) and Long Ashton Research Station Weather Generator (LARS-WG). Furthermore, the auto-regression model was used for trend analysis. The results showed that an increase in the average annual temperature of 2.15°C, 2.89°C, and 4.13°C will lead to a reduction in the wheat yield of 9.14%, 10.20%, and 12.00% under Representative Concentration Pathway (RCP)2.6, RCP4.5, and RCP8.5 during the future period (2025-2100), respectively. Moreover, an increase in the annual maximum temperature of 1.79°C, 2.48°C, and 3.74°C also causes a significant reduction in the wheat yield of 2.60%, 3.60%, and 10.50% under RCP2.6, RCP4.5, and RCP8.5, respectively. Furthermore, an increase in the annual minimum temperature of 2.98°C, 2.23°C, and 4.30°C can result in an increase in the wheat yield of 6.50%, 4.80%, and 9.30% under RCP2.6, RCP4.5, and RCP8.5, respectively. According to the SDSM, the decrease of the average monthly precipitation of 4.34%, 4.10%, and 5.13% results in a decrease in the wheat yield of 2.60%, 2.36%, and 3.18% under RCP2.6, RCP4.5, and RCP8.5, respectively. This study suggests that adaptation strategies can be applied to minimize the consequences of climate change on agricultural production.

Key words： Climate change; Wheat yield; Food security; Representative; Concentration; Pathway (RCP); Afghanistan

Cite this article

Homayoon RAOUFI , Hamidreza JAFARI , Wakil Ahmad SARHADI , Esmail SALEHI . Assessing the impact of climate change on agricultural production in central Afghanistan[J]. Regional Sustainability, 2024 , 5(3) : 100156 . DOI: 10.1016/j.regsus.2024.100156

1. Introduction

Climate change is one of the most important drivers affecting agricultural production in the world. It has negative impacts on various key sectors, including water, energy, agriculture, food security, and human livelihoods (Junjua et al., 2010; Farooq et al., 2023). The adverse consequences of climate change on agricultural production and food security have been warned by many regional and global studies (Sarwary et al., 2023). Climate change increases vulnerability of developing countries (Intergovernmental Panel on Climate Change (IPCC), 2014). According to the Climate Change Conference (COP 27) held in Egypt in November 2022, Afghanistan is one of the countries most affected by climatic disasters (ICMPD, 2023). In addition, the majority of population (more than 80.00%) and economy of this country were completely dependent on agricultural production (Gay et al., 2006; Aich et al., 2017; NEPA, 2018; Tiwari et al., 2020), and agricultural sector provided more than 30.00% of the gross domestic product (GDP) in 2020 (World Bank, 2021). Sustainable agricultural and economic systems are needed against climatic disasters to meet a growing population, rising demand, and extreme weather events. A sustainable agricultural system can be achieved through investment, infrastructure development, and irrigation system building (World Bank, 2014), whereas, over the past decades, little attention and investment were conducted for the growth and development of the agricultural system. Therefore, climatic disasters such as droughts affected more than two-thirds (1.05×107 persons) of population during 2018-2019, and 1.35×107 persons were facing crisis or worse levels of food insecurity in Afghanistan (FAO, 2019). Climatic disasters such as extreme temperatures, floods, droughts, earthquakes, and reduced precipitation have proved to be the biggest humanitarian challenges in the country. In addition, low socioeconomic development level in the country and rising levels of insecurity made individuals extremely vulnerable to climatic disasters.
An increase in the average temperature of 1.50°C by 2050 would have significant impacts on agricultural production, water resources, ecosystems, food security, health, and energy productio. Arunrat et al. (2022) indicated that rising temperature has a negative effect on wheat yield, while rising precipitation and atmospheric CO2 concentration have a positive effect on wheat yield. Haris et al. (2013) reported that an increase in atmospheric CO2 concentration caused an increase in wheat yield with a lower quality of grain. Naikwade (2022) reported that India’s wheat yield would decline by 6.00%-23.00% by 2050 and 15.00%-25.00% by 2080 due to climate change. An increase in temperature negatively affects wheat yield (Ortiz et al., 2008), while an increase in precipitation benefits wheat yield. Ahmed et al. (2022) found that an increase in temperature of 0.00°C-5.00°C results in a decline in wheat yield. Reduction of wheat yield in response to the increase of 1.00°C in temperature has been proved by several studies, e.g., You et al. (2009) discovered a reduction in wheat yield of 3.00%-10.00%, Gupta and Nair (2012) reported a reduction in wheat yield of 2.00%-4.00%, Zhao et al. (2017) reported a reduction in wheat yield of 6.00%, Sonkar et al. (2019) reported a reduction in wheat yield of 4.00%-9.00%, and Daloz et al. (2021) reported a reduction in wheat yield of 1.00%-8.00%. An increase in temperature by 1.00°C above the threshold (>30.00°C) decreased grain filling in irrigated wheat by 0.30%-0.58% (Liu et al., 2016). Under several climate change scenarios, a significant reduction in the simulated yield of irrigated wheat has been reported by Hussain et al. (2020) due to an increase in crop evapotranspiration (Osman et al., 2022). In the majority of agricultural countries, a decrease in wheat yield is anticipated due to the negative effects of climate change on plant cultivation processes like physiological processes, crop evapotranspiration, and water use efficiency (Zhao et al., 2017; Paymard et al., 2019; Arunrat et al., 2022; Subedi et al., 2023). The crop irrigation requirements have increased in response to climate change, including increased temperature and decreased precipitation and humidity.
In the last years, wheat yield significantly declined because of the extreme vulnerability and the higher susceptibility of the crop production systems and low adaptive capacity to the impacts of severe climatic events (severe temperature, little precipitation, and droughts) (Aich et al., 2017; UNDP, 2019). According to the Ministry of Agriculture, Irrigation, and Livestock, Afghanistan needs to produce about 7.0×106 t of wheat to achieve self-sufficiency by 2022 (Sharma et al., 2015), but wheat yield fails to fulfill the internal demand of about 2.0×106 t. Farmers are the first line that would be seriously affected by climate change. They are directly dependent on climatic-sensitive resources like wheat yield, making them more vulnerable to climate change. Despite climate change has negative consequences on the economy and livelihoods, a few studies have examined the impacts of climate change on crop yield (Aich et al., 2017; NEPA, 2018; Sarwary et al., 2023). Thus, the trend of climate change and its impact on cereal crops such as wheat need to be investigated. The impact of climate change on wheat yield was conducted by calculating and comparing temperature and precipitation during the reference (1990-2020) and future (2025-2100) periods under Representative Concentration Pathway (RCP)2.6, RCP4.5, and RCP8.5, which were used in a wide range by climatic projection models in accordance of the IPCC report (IPCC, 2014). The objective of this study is to analyze the impact of climate change (temperature and precipitation variation) on wheat yield in central Afghanistan. To reduce climatic disasters, sustaining agricultural system is necessary. A sustainable agricultural system can be supported by adaptation strategies, including cultivation practice, field management, cultivating seed selection, ecological conservation, and water resources management.

2. Materials and methods

2.1. Study area

This study was conducted in Kabul (34°33′19′′N and 69°12′27′′E), central Afghanistan. It covered a total area of about 4655.25 km2, with the average elevation of 1959 m a.s.l. The average annual temperature was 14.99°C and the average annual precipitation was 269.00 mm during 1990-2020 in the study area. The driest month was June, with precipitation of 1.00 mm. Most precipitation took place in March, with an average of 88.00 mm. July was the hottest month of the whole year with an average temperature of 23.20°C. The lowest temperature of the whole year was -2.90°C, which occurs in January. Cereal crops cover a large cultivation area, but wheat is the first important crop cultivated in a wide range, with 61.30% of the total cropped area cultivation (Sarwary et al., 2023). Wheat is cultivated during October-November and harvested during June-July of the next year (UNDP, 2019). Table 1 shows the geographical and climatic characteristics of four meteorological stations in Kabul selected to obtain daily observation temperature and precipitation data.
Table 1 Geographical and climatic characteristics of four Meteorological stations in the study area.
Station name Latitude Longitude Average elevation
(m a.s.l.)		 Average precipitation (mm/a) Average temperature (°C/a)
Karizmir 34°38′20′′N 69°03′70′′E′′ 1905 392.00 12.90
Kabul-airport 34°33′39′′N 69°12′38′′E 1791 197.00 14.10
Qargha 34°33′10′′N 69°01′55′′E 1970 360.38 12.60
Shakardara 34°40′51′′N 69°01′00′′E 2168 411.38 10.16

2.2. Data sources

The observed daily climatic data for temperature and precipitation during 1990-2020 were collected from Kabul’s meteorological stations including Karizmir, Kabul-airport, Qargha, and Shakardara. Moreover, we used three local organizational databases including Afghanistan Meteorological Department (2022), Ministry of Agriculture, Irrigation, and Livestock (2022), and Ministry of Energy and Water (2022) to supplement the missing data. Furthermore, projections of temperature and precipitation were calculated from the General Circulation Models (GCMs) from the Fifth Assessment Report (AR5) of the IPCC, which is available in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The projections of temperature and precipitation were applied for screening future predictor variables (Zhou et al., 2017; Munawar et al., 2022). The data from the GCMs were downscaled by the Statistical Downscaling Model (SDSM) and the Long Ashton Research Station Weather Generator (LARS-WG) model, and then they were used to project temperature and precipitation during the future period (2025-2100) using the Canadian Earth System Model (CanEsm2) from the Canadian Center for Climate Modeling and Analysis, Canada (https://climate-scenarios.canada.ca/pred-canesm2). Three scenarios including RCP2.6, RCP4.5, and RCP8.5 were used to estimate the change trends of temperature and precipitation during the future period (IPCC, 2014). The SDSM is a decision support tool that employs multiple linear regression techniques, to interpret the relationships between the GCM simulation data and observed climatic data. The LARS-WG model is a stochastic weather generator that produces climate scenarios based on global climate models for assessing the impact of climate change (Semenov and Barrow, 2022). The model of LARS-WG was applied to produce synthetic time series data using the GCM simulation data and observed climatic data during the reference and future periods (Baghanam et al., 2020). Trend analysis was conducted by regression, which is a statistical method to estimate the long-term temperature and precipitation patterns (Radhakrishnan et al., 2017; Mudelsee, 2019). The bias correction method was also used to avoid ambiguities, errors, and biases in the results, and it was also used to correct the errors and biases between the GCM simulation data and the observed climatic data during the reference period (1990-2020) (Gurara et al., 2021; Jha et al., 2021; Munawar et al., 2022). Data from the reference period (1990-2020) were used for the validation and calibration of the SDSM and the LARS-WG. Moreover, wheat yield data (1990-2020) were acquired from the United States Department of Agriculture (2023).

2.3. Model specification

Each crop needs certain conditions, such as optimum temperature, adequate sunshine, soil moisture, atmospheric humidity, and enough minerals, for survival, growth, and development (Ali et al., 2017). Wheat yield depended on many input variables, which can be categorized into climatic and non-climatic variables. The effects of climatic and non-climatic variables on wheat yield were calculated by the auto-regression model. The method provides detailed results and allows for isolating the effects of individual variables. Empirical analysis has been done using EViews 12 (Micro Software Company, Redmond, the United States). The equation of wheat yield can be expressed as follows:
Wheat yield=f(climatic variables, non-climatic variables),
where wheat yield is the dependent variable; f is the function; and climatic and non-climatic variables are the independent variables. Climate change was measured through temperature and precipitation change trends. Non-climatic variables include fertilizers, labor force, machinery, tactics, and field management (Shafiq et al., 2021). The functional form of Equation 1 can be formally written as an auto-regression model.
An auto-regression model was applied to estimate the effects of climatic and non-climatic variables on wheat yield for each period as follows:
Yt=C+C1x1t+C2x2t+C3x3t+C4x4t+εt,
where Yt is the wheat yield in year t (kg/hm2); C is the intercept; C1-C4 represent the changes of independent variables; x1 is the average annual temperature (°C); x2 is the average annual precipitation (mm); x3 is the fertilizer (kg/hm2); x4 is the cultivated area (hm2); and εt indicates the error term in year t. In this study, non-climatic variables are supposed to be stable, but climatic variables are variable, which can be stated as follows:
Yit=C+C1Maxit+C2Minit+C3Preit+σit,
where Yit is the yield of crop i (here, it is wheat) in year t (kg/hm2); Maxit is the average monthly maximum temperature during cropping season for crop i in year t (°C); Minit is the average monthly minimum temperature during cropping season for crop i in year t (°C); Preit is the average monthly precipitation (mm) during cropping season for crop i in year t; and σit is the random error term for crop i in year t (Junjua et al., 2010; Ali et al., 2017; Shafiq et al., 2021).

3. Results

3.1. Temperature variation trend and its impact on wheat yield

Monthly temperature during the reference (1990-2020) and future (2025-2100) periods are presented in Table 2. From Table 2 we can see that the monthly maximum and minimum temperatures.
Table 2 Monthly minimum and maximum temperatures, and monthly precipitation during the reference (1990-2020) and future (2025-2100) periods.
Month Reference period (1990-2020) Future period (2025-2100)
RCP2.6 RCP4.5 RCP8.5
Tmin (°C) Tmax (°C) P (mm) Tmin (°C) Tmax (°C) P (mm) Tmin (°C) Tmax (°C) P (mm) Tmin (°C) Tmax (°C) P (mm)
January -0.20 10.20 28.20 2.40 12.30 28.70 3.40 13.30 35.10 4.90 14.30 42.70
February 1.20 12.10 52.20 4.80 14.90 35.20 6.10 16.10 35.80 7.50 17.00 39.80
March 5.60 17.30 57.70 9.50 20.00 37.60 10.40 20.70 45.80 11.90 22.10 51.90
April 8.20 20.90 46.60 12.20 24.60 41.80 12.80 25.50 30.60 14.30 27.00 46.90
May 11.50 25.10 23.70 14.60 28.10 20.80 15.00 28.90 24.30 16.30 30.20 30.30
June 14.60 29.40 3.20 16.90 32.10 3.90 17.40 32.90 3.50 18.60 34.00 6.90
July 16.70 32.10 3.40 18.50 33.30 1.90 19.30 33.90 2.00 20.40 35.10 3.20
August 16.10 31.50 6.00 17.40 32.80 3.50 18.40 33.20 5.50 19.70 34.50 3.70
September 13.20 27.80 3.90 14.30 28.40 28.00 15.20 28.90 23.00 16.70 30.60 21.00
October 9.20 22.30 7.40 10.90 22.90 25.20 11.80 23.50 23.20 13.30 25.10 28.30
November 4.90 16.00 21.20 6.60 16.80 19.90 7.40 17.50 19.80 9.00 18.80 20.00
December 2.00 12.10 15.30 3.70 13.30 36.30 4.40 14.20 33.60 5.90 15.20 38.20
Average 8.60 21.40 269.00 11.00 23.30 282.70 11.80 24.00 282.10 13.20 25.30 332.90

Note: Tmin, minimum temperature; Tmax, maximum temperature; P, precipitation; RCP, Representative Concentration Pathway.

Due to the various impacts of the annual maximum and minimum temperatures on wheat yield, both positively and negatively, the annual maximum and minimum temperatures were also calculated separately (Fig. 1).
Fig. 1. Average annual temperature (a), annual maximum temperature (b), and annual minimum temperature (c) during the reference (1990-2020) and future (2025-2100) periods under RCP2.6, RCP4.5, and RCP8.5. RCP, Representative Concentration Pathway.
The impact of the average annual temperature on wheat yield was predicted to be negative. The average annual temperature was expected to increase by 2.15°C, 2.89°C, and 4.13°C during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively. Due to the increase of the average annual temperature, the average wheat yield would decrese by 9.14%, 10.20%, and 12.00% under RCP2.6, RCP4.5, and RCP8.5, respectively (Table 3). The annual maximum temperature was predicted to increase by 1.79°C, 2.48°C, and 3.74°C during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively. Under RCP2.6, RCP4.5, and RCP8.5, the average wheat yield would reduce by 2.60%, 3.60%, and 5.45%, respectively, because of the increase of the annual maximum temperature (Table 4).
Table 3 Impact of the average annual temperature change on wheat yield under three scenarios.
Year RCP2.6 RCP4.5 RCP8.5
Average annual temperature change (°C) Wheat yield
change (%)		 Average annual
temperature change (°C)		 Wheat yield
change (%)		 Average annual
temperature change (°C)		 Wheat yield
change (%)
2025 1.23 -7.80 1.59 -8.30 1.95 -8.80
2030 1.18 -7.73 1.32 -7.90 1.68 -8.50
2040 1.44 -8.11 1.49 -8.20 1.85 -8.70
2050 2.41 -9.51 2.78 -10.00 3.53 -11.10
2060 2.40 -9.50 2.82 -10.10 3.59 -11.20
2070 1.88 -8.74 3.19 -10.60 4.66 -12.80
2080 2.54 -9.70 3.82 -11.60 5.37 -13.80
2090 3.10 -10.51 4.45 -12.50 7.24 -16.50
2100 3.18 -10.63 4.54 -12.60 7.31 -16.60
Average 2.15 -9.14 2.89 -10.20 4.13 -12.00
Table 4 Impact of the annual maximum temperature change on wheat yield under three scenarios.
Year RCP2.6 RCP4.5 RCP8.5
Annual maximum
temperature change (°C )		 Wheat yield
change (%)		 Annual maximum
temperature change (°C )		 Wheat yield
change (%)		 Annual maximum
temperature change (°C)		 Wheat yield
change (%)
2025 0.93 -1.35 1.09 -1.58 2.19 -3.18
2030 1.22 -1.77 1.08 -1.57 1.34 -1.94
2040 1.19 -1.73 1.26 -1.83 1.54 -2.23
2050 2.18 -3.16 2.55 -3.70 3.25 -4.72
2060 1.81 -2.63 2.23 -3.24 2.94 -4.27
2070 2.23 -3.24 3.59 -5.21 4.99 -7.24
2080 1.60 -2.32 2.95 -4.28 4.46 -6.47
2090 2.11 -3.06 3.42 -4.96 6.17 -8.95
2100 2.90 -4.21 4.22 -6.12 6.93 -10.05
Average 1.79 -2.60 2.48 -3.60 3.74 -5.45
The average annual minimum temperature was predicted to increase by 2.98°C, 2.23°C, and 4.30°C during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively (Table 5). Due to the increase of the average annual minimum temperature, the average wheat yield would increase by 6.50%, 4.80%, and 9.30% under RCP2.6, RCP4.5, and RCP8.5, respectively (Table 5).
Table 5 Impact of the annual minimum temperature change on wheat yield under three scenarios.
Year RCP2.6 RCP4.5 RCP8.5
Annual minimum temperature change (°C) Wheat yield
change (%)		 Annual minimum temperature change (°C) Wheat yield
change (%)		 Annual minimum temperature change (°C) Wheat yield
change (%)
2025 1.14 2.50 0.90 2.00 1.72 3.70
2030 1.56 3.40 1.14 2.50 2.01 4.40
2040 1.72 3.70 1.69 3.70 2.16 4.70
2050 3.01 6.50 2.64 5.70 3.81 8.30
2060 3.41 7.40 2.99 6.50 4.23 9.20
2070 3.20 6.90 1.94 4.20 4.76 10.30
2080 4.06 8.80 2.84 6.20 5.65 12.30
2090 4.12 8.90 2.74 5.90 6.96 15.10
2100 4.62 10.00 3.22 7.00 7.45 16.20
Average 2.98 6.50 2.23 4.80 4.30 9.30

3.2. Precipitation variation trend and its impact on wheat yield

Precipitation is crucial for the land areas that are suitable for wheat cropping. Central Afghanistan will likely experience increased weather events, including heat stress, prolonged dry periods, and low precipitation during the cropping season. The monthly precipitation are increasing during the future period (2025-2100), based on the reference period (1990-2020). The average annual precipitation was 269.00 mm during 1990-2020, but it would increase to 282.70, 282.10, and 332.90 mm during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively (Table 2). Moreover, from Table 2 we can see that the average monthly precipitation will decrease during February-May (growing months). However, the projected average monthly precipitation would increase during the future period (2025-2100), but the seasonal precipitation shows a decreasing trend in spring and an increasing trend in autumn. The average monthly precipitation between February and May would reduce by 44.09, 43.47, and 7.48 mm under RCP2.6, RCP4.5, and RCP8.5, respectively (Fig. 2).
Fig. 2. Average monthly precipitation during the reference (1990-2020) and future (2025-2100) periods under RCP2.6, RCP4.5, and RCP8.5.
The average monthly precipitation change and its impact on wheat yield during growing months are presented in Table 6. The decrease of the average monthly precipitation would negatively affect wheat yield during April-June. The LARS-WG model indicated that a decrease in the average monthly precipitation of 5.14%, 6.13%, and 4.88% would result in a reduction in the wheat yield of 3.12%, 3.87%, and 2.92% during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively (Table 6). According to the SDSM, the average monthly precipitation will decrease by 4.34%, 4.10%, and 5.13%, resulting in a reduction inin the wheat yield of 2.60%, 2.36%, and 3.18% under RCP2.6, RCP4.5, and RCP8.5, respectively.
Table 6 Impact of the average monthly precipitation change on wheat yield under three scenarios.
Variable change LARS-WG model SDSM
RCP2.6 RCP4.5 RCP8.5 RCP2.6 RCP4.5 RCP8.5
Average monthly precipitation change (%) -5.14 -6.13 -4.88 -4.34 -4.10 -5.13
Wheat yield change (%) -3.12 -3.78 -2.92 -2.60 -2.36 -3.18

Note: LARS-WG model, Long Ashton Research Station Weather Generator model; SDSM, Statistical Downscaling Model.

4. Discussion

Crop yield was controlled by several climatic and non-climatic variables. Climatic variables, including temperature and precipitation, directly and indirectly affect the growth and development of crops. The present study predicted a systematic increase in the average, maximum, and minimum temperatures during the future period (2025-2100) based on the reference period (1990-2020). The average monthly maximum temperature would increase to 23.30°C, 24.00°C, and 25.30°C during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively, concerning the average monthly maximum temperature of 21.40°C during the reference period (1990-2020) (Table 2). The average monthly minimum temperature would also increase to 11.00°C, 11.80°C, and 13.20°C during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively, with respect to the average monthly minimum temperature of 8.60°C during the reference period (1990-2020) (Table 2). The average annual temperature would increase by 2.15°C, 2.89°C, and 4.13°C during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively. Furthermore, the annual maximum temperature would increase by 1.79°C, 2.48°C, and 3.74°C under RCP2.6, RCP4.5, and RCP8.5, respectively. Moreover, the annual minimum temperature would increase by 2.98°C, 2.23°C, and 4.30°C during the future period (2025-2100) under RCP2.6, RCP4.5 and RCP8.5, respectively. The average annual temperature has increased by 1.50°C during 1900-2017 (World Bank, 2021). The average annual temperature was projected to increase by 3.50°C and 7.00°C until 2050 under RCP4.5 and RCP8.5, respectively (NEPA, 2018). Sarwary et al. (2023) found that the average annual temperature would increase by 1.70°C and 2.30°C until 2050 under RCP4.5 and RCP8.5. Moreover, FAO (2016) discovered that the average annual temperature would rise by 2.00°C and 6.50°C by 2100 under RCP4.5 and RCP8.5, respectively. The average annual temperature was projected to rise by 2.70°C and 5.50°C up to 2100 under RCP4.5 and RCP8.5 in Afghanistan, respectively (World Bank, 2021), respectively, relative to the reference period (1990-2020). The increase of temperature was projected to occur most rapidly in spring and summer at higher altitudes (central highlands and Hindu Kush) (NEPA, 2018). Moreover, the global average temperature will increase by 0.30°C-1.70°C under RCP2.6, 1.10°C-2.60°C under RCP4.5, and 2.60°C-4.80°C under RCP8.5 between 1986-2005 and 2081-2100 (IPCC, 2014). Sarwary et al. (2023) revealed that the global average temperature was expected to increase by 1.40°C-5.80°C by 2100.
Our findings revealed that the increase of temperature (the average annual temperature and annual maximum temperature) impacts wheat yield because of heat and drought stress. In contrast, an increase in the minimum temperature has a positive impact on wheat yield. An increase in the annual minimum temperature by 2.98°C, 2.23°C, and 4.30°C would increase the wheat yield by 6.50%, 4.80%, and 9.80% under RCP2.6, RCP4.5, and RCP8.5, respectively. We considered that every 1.00°C increase in the annual minimum temperature will lead to an increase of about 2.16% in wheat yield. The positive impact of an increase in the annual minimum temperature in arid and semi-arid regions was reported by Haris et al. (2013), Ali et al. (2017), Shakoor et al. (2018), and Saei et al. (2019). In addition, Haris et al. (2013) reported that crop yields would increase by nearly 2.00% when the minimum temperatures increased by 3.00°C.
In Afghanistan, as the increase of the maximum temperature, the average wheat yield would decrease by 2.60%, 3.60%, and 5.45% during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively, based on the reference period (1990-2020). Every 1.00°C rise in the average annual and maximum temperatures would lead to a decline in the wheat yield of 3.56% and 1.45%, respectively, by 2100. Sarwary et al. (2023) projected a reduction in the average crop yield of 271 kg/hm2 with a 1.00°C increase in the average annual temperature in Afghanistan. Shafiq et al. (2021) reported that crop yield would decrease by 0.89% with an 1.00°C increase in the average annual temperature. Moreover, on a global scale, wheat yield would decrease by 3.10%-8.90% with a 1.00°C rise in global temperature (Zhao et al., 2017). For every 1.00°C increase in temperature, global wheat yield was predicted to decline by 4.10%-6.40% (Morgounove et al., 2018). Hussain et al. (2020) reported that a 1.00°C increase in temperature would decrease the wheat yield by 6.00%-9.00% in arid and semi-arid regions. The negative impact of an increase in the average temperature on crop yield was reported by Hanif et al. (2010), Ashfaq et al. (2011), Haris et al. (2013), Zeb et al. (2013), Shakoor et al. (2018), Shafiq et al. (2021), Zhang et al. (2021), and Gul et al. (2022). Extreme high and low temperatures negatively affect the physiological and photosynthetic processes of plants. Change in crop life cycles is one of the most significant effects of climate change on crop (Wang et al., 2015). Moreover, a shorter grain-filling period, smaller and lighter grains, lower crop yields (lower grain quality and quantity), and lower protein levels occur on plants due to higher temperatures (Adams et al., 1998; Rezaei et al., 2008). Higher temperatures during emergence, tillering, or grain-filling stages, can significantly impact crop yield, particularly in water shortage (Bouras et al., 2019). The previous studies have some differences with the results of this study, which might be the different models used (NEPA, 2018; Jawid, 2020; Sarwary et al., 2023). Hassan et al. (2013) claimed that the different results arose from the differences in their downscaling strategy and basic concepts.
This study found the decreases in the average monthly precipitation during the growing months of wheat by the SDSM and LARS-WG model. However, the models respectively simulated an increasing and a decreasing trend in the average monthly precipitation during the future period under three scenarios. Still, a decrease in the average monthly precipitation was forecasted to occur during the growing months (Fig. 2; Table 6). Specifically, results indicated that the average monthly precipitation will decrease in February, March, and April and increase in September, October, December, and January. There are no significant changes in the average monthly precipitation in May, July, August, and November during the future period (2025-2100) compared with the reference period (1990-2020) (Fig. 2). Jawid (2020) predicted an 8.00% increase in the average monthly precipitation for the Parallel Climate Model and a 2.00% decrease in the average monthly precipitation for the Canadian Climate Center Model by 2100. The decrease of the average monthly precipitation during the growing months, greatly affects crop yield. Spring precipitation was projected to decrease by more than 5.00% in the central region of Afghanistan during 2021-2050 (FAO, 2016). The average monthly precipitation decreased by about 10.00% during 1951-2010 (World Bank, 2021). NEPA (2018) reported that the average monthly precipitation during March-May decreases by 5.00%-10.00% in the central region of Afghanistan, whereas it increases between October and December during 2006-2050. Future projections shows that the average monthly precipitation would change in a range from -1.60% to -3.80% during 2021-2050 (Sarwary et al., 2023). A decrease in spring precipitation would directly affect crop growth and development in the central region of Afghanistan (FAO, 2016). This study revealed that a decrease in the average monthly precipitation by 1.00% results in a decrease in wheat yield by about 0.60%. Khan et al. (1988) found that an increase in the average monthly precipitation by 1.00 mm leads to an increase in crop yield of about 0.29%.
An increase in the average annual temperature and a decrease in the average monthly precipitation lead to the increase of drought stress on crop growth and development. Droughts affected 70.00% of the total population during 1980-2008, cereal production decreased by 43.00% in 2004, and wheat production declined by 8.00%-9.00% during 2004-2011 (FAO, 2019). This study showed that Afghanistan faces significant drought issues, which directly impact the livelihoods and economy in its central region (World Bank, 2021). The crop yield reduced by 50.00% during the drought period between 2017 and 2018 (World Bank, 2021). It was noted that wheat yield would reduce by 20.90% and 28.11% during 2021-2050 under RCP4.5 and RCP8.5, respectively (Sarwary et al., 2023). World Bank (2021) noted that crop yield in the irrigated area could reduce by 30.00% in years of water scarcity, and these effects are major on livelihoods.
Reduced precipitation may increase the crop water requirements during the growing months. Water availability for crops during the growing months is very important to complete the phenological process (Sharma et al., 2015). Many variables, including temperature, precipitation, radiation, wind speed, sunlight exposure, and relative humidity, controll crop water conditions and affect crop water requirements (UNDP, 2019; Khan et al., 2021; Kambale et al., 2023). Water crisis is a key factor that limits crop yield by affecting the development of root system, physiological processes (such as photosynthesis and respiration), stomatal closure, grain quality, and crop yield during the growing months in arid and semi-arid regions (Zhong and Shangguan, 2014; Bello et al., 2022; Antoniuk et al., 2023). Without essential infrastructure and system adaptation, many people would be seriously impacted by climate change (IPCC, 2014). There are some mitigation and adaptation strategies for minimizing the climate change effect on crop yield, especially in the case of wheat yield, such as the use of tolerance varieties, and science-based farm management, time management (sowing date), fertilizer management, environmental management, and ecological pest management.

5. Conclusions and recommendations

This study explored climate change during the reference (1990-2020) and future (2025-2100) periods in central Afghanistan. The new risk of climate change may impact wheat yield in central Afghanistan. Most importantly, the average annual temperature will have alarming imapct on wheat yield in the coming decades. The results showed that an increase in the average annual temperature by 2.15°C, 2.89°C, and 4.13°C would reduce the average wheat yield by 9.14%, 10.20%, and 12.00% during the future period (2025-2100) under RCP2.6, RCP4.5, and RCP8.5, respectively. Moreover, an increase in the annual maximum temperature by 1.79°C, 2.48°C, and 3.74°C also causes a significant reduction in the average wheat yield by 2.60%, 3.60%, and 10.5% under RCP2.6, RCP4.5, and RCP8.5, respectively. Furthermore, an increase in the annual minimum temperature by 2.98°C, 2.23°C, and 4.30°C will lead to an increase in the average wheat yield by 6.50%, 4.80%, and 9.30% under RCP2.6, RCP4.5, and RCP8.5, respectively. According to the SDSM, the decrease of the average monthly precipitation by 4.34%, 4.10%, and 5.13% would lead to a reduction in the average wheat yield by 2.60%, 2.36%, and 3.18% under RCP2.6, RCP4.5, and RCP8.5, respectively. Meanwhile, the LARS-WG model indicated that a decrease in the average monthly precipitation by 5.14%, 6.13%, and 4.88% would reduce the average wheat yield by 3.12%, 3.87%, and 2.92% under RCP2.6, RCP4.5, and RCP8.5, respectively.
However, this study highlights the impacts of temperature and precipitation on wheat yield, but other climatic variables are not evaluated. It needs more research to evaluate the impacts of other climatic variables such as wind speed, radiation, sunshine, and humidity on crop yield. Moreover, studying more sustainable adaptation strategies and identifying crop varieties that have more adaptation capacity against climatic disasters will support reducing the impact of climate change. The study of crop water requirements can help better understand the impact of climate change on crop yield. Finally, we suggest the research on the impact of climate change on crop yield extending to other economic crops in Afghanistan as well.

Author contribution statement

Homayoon RAOUFI: conceptualization, methodology, formal analysis, writing original draft, and writing - review & editing; Hamidreza JAFARI: conceptualization and writing - review & editing; Wakil Ahmad SARHADI: conceptualization and writing - review & editing; and Esmail SALEHI: conceptualization and writing - review & editing. All authors approved the manuscript.

Declaration of conflict interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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