Assessing the impact of global climate changes on irrigated wheat yields and water requirements in a semi-arid environment of Morocco

Bouras, Elhoussaine; Jarlan, Lionel; Khabba, Saïd; Er-Raki, Salah; Dezetter, Alain; Fathallah, Sghir; Tramblay, Yves

doi:10.1038/s41598-019-55251-2

Cited by 91 publications

(64 citation statements)

References 86 publications

(110 reference statements)

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“…According to Bouras et al (2019), the reduction of the cycle can reach 30 % at mid-century under the RCP8.5 scenario for wheat in the study region. Similar results were obtained with the ISBA-A-gs model (Calvet et al, 1998) when studying the impact of climate change on Mediterranean crops (Garrigues et al, 2015). It is also interesting to note that if the water demand for seasonal crops is reduced with the crop cycle duration, the yield may also be affected by extreme temperatures (Hatfield and Prueger, 2015) so that the trend might be affected in order to reach the production objective.…”

Section: Discussionsupporting

confidence: 72%

Projection of irrigation water demand based on the simulation of synthetic crop coefficients and climate change

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Fakir

Jarlan

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. In the context of major changes (climate, demography, economy, etc.), the southern Mediterranean area faces serious challenges with intrinsically low, irregular, and continuously decreasing water resources. In some regions, the proper growth both in terms of cropping density and surface area of irrigated areas is so significant that it needs to be included in future scenarios. A method for estimating the future evolution of irrigation water requirements is proposed and tested in the Tensift watershed, Morocco. Monthly synthetic crop coefficients (Kc) of the different irrigated areas were obtained from a time series of remote sensing observations. An empirical model using the synthetic Kc and rainfall was developed and fitted to the actual data for each of the different irrigated areas within the study area. The model consists of a system of equations that takes into account the monthly trend of Kc, the impact of yearly rainfall, and the saturation of Kc due to the presence of tree crops. The impact of precipitation change is included in the Kc estimate and the water budget. The anthropogenic impact is included in the equations for Kc. The impact of temperature change is only included in the reference evapotranspiration, with no impact on the Kc cycle. The model appears to be reliable with an average r2 of 0.69 for the observation period (2000–2016). However, different subsampling tests of the number of calibration years showed that the performance is degraded when the size of the training dataset is reduced. When subsampling the training dataset to one-third of the 16 available years, r2 was reduced to 0.45. This score has been interpreted as the level of reliability that could be expected for two time periods after the full training years (thus near to 2050). The model has been used to reinterpret a local water management plan and to incorporate two downscaled climate change scenarios (RCP4.5 and RCP8.5). The examination of irrigation water requirements until 2050 revealed that the difference between the two climate scenarios was very small (< 2 %), while the two agricultural scenarios were strongly contrasted both spatially and in terms of their impact on water resources. The approach is generic and can be refined by incorporating irrigation efficiencies.

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Section: Discussionsupporting

confidence: 72%

Projection of irrigation water demand based on the simulation of synthetic crop coefficients and climate change

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Fakir

Jarlan

et al. 2021

Hydrol. Earth Syst. Sci.

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“…Table 2 provides the average cropped areas, ratio between cropped area and total province area in percentage, average total production and average yields during the study period, coefficient of variation (standard deviation divided by the average, in percentage), cumulative total rainfall, and average air temperature during the crop season. Cereal yields are low compared with potential yields in all provinces, which can reach 7.5 to 8.0 t.ha −1 in rainfed areas when adequate technologies and practices are used [86,87]. This low yield is attributed to water stress, heat stress and poor soil, as well as to traditional agricultural practices that may lead to inappropriate crop rotation, insufficient nitrogen and fertilization and late sowing [88,89].…”

Section: Yield Datamentioning

confidence: 99%

Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco

et al. 2020

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In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000–2017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.

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“…The low impact of RCP scenarios could also be explained by the fact that the potential decrease in the annual crop growth cycle duration associated with temperature rise is not represented. According to (Bouras et al, 2019), the reduction of the cycle can reach 30% at mid-century under RCP8.5 scenario for wheat in the study region. Similar results were obtained with the ISBA A-gs model (Calvet et al, 1998) when studying the impact of climate change on Mediterranean crops (Garrigues et al, 2015).…”

Section: Discussionmentioning

confidence: 94%

Projection of irrigation water demand based on the simulation of synthetic crop coefficients and climate change

Page¹,

Fakir²,

Jarlan³

et al. 2020

Preprint

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Abstract. In a context of major changes (climate, demography, economy, etc.), the Southern Mediterranean area faces serious challenges with intrinsically low, irregular and continuously decreasing water resources. In some regions, the proper dynamic of irrigated areas is very important so that it is needed to include it in future scenarios. A method for estimating the future evolution of irrigation water requirements is proposed and tested in the Tensift watershed, Morocco. Monthly synthetic crop coefficients (Kc) of the different irrigated areas were obtained from a time series of remote sensing observations. An empirical model using the synthetic Kc and rainfall was developed and fitted to the actual data. The model appears to be reliable with an average r2 of 0.69 for the observation period (2000–2016). The sub sampling tests suggested that a loss of performance (r2 = 0.45) is to be expected for two time periods after the observations (2050). This flexible system of equations has been used to reinterpret a local water management plan and to incorporate two downscaled climate change scenarios (RCP4.5 and RCP8.5). The examination of irrigation water requirements until 2050 revealed that the difference between the two climate scenarios was very small (

show abstract

Assessing the impact of global climate changes on irrigated wheat yields and water requirements in a semi-arid environment of Morocco

Cited by 91 publications

References 86 publications

Projection of irrigation water demand based on the simulation of synthetic crop coefficients and climate change

Projection of irrigation water demand based on the simulation of synthetic crop coefficients and climate change

Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco

Projection of irrigation water demand based on the simulation of synthetic crop coefficients and climate change

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