Winter Potato Water Footprint Response to Climate Change in Egypt

Abdel-Hameed, Amal Mohamed; Abuarab, Mohamed E.; Al‐Ansari, Nadhir; Mehawed, H.; Kassem, Mohamed A.; He, Hongming; Gyasi‐Agyei, Yeboah; Mokhtar, Ali

doi:10.3390/atmos13071052

Cited by 6 publications

(3 citation statements)

References 67 publications

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“…So as an alternative, we therefore opted for the use of satellite data from NASA's Power Data Access Viewer platform(https://power.larc.nasa.gov/) which has data over a period of 36 years (1985-2021), covering the entirety of our study area and containing all the variables allowing the calculation of the SPI: Temperature, total precipitation, wind speed, wind direction, surface pressure, relative humidity, cloud amount, soil moisture, Top-Of-Atmosphere Shortwave Downward Irradiance and all sky and All Sky Surface Shortwave Downward Irradiance. In addition to this, its use is reported in several works [28], [29], [30] to quote only those.…”

Section: B Datamentioning

confidence: 99%

Drought Forecasting in Alibori Department in Benin using the Standardized Precipitation Index and Machine Learning Approaches

VODOUNON¹,

SOUDE²,

MAMADOU³

2022

IJACSA

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Drought forecasting provides an early warning for the effective management of water resources to avoid or mitigate drought damage. In this study, the prediction of droughts is carried out in the department of Alibori in Benin republic using the standardized precipitation index (SPI) where two Machine Learning approaches were used to set up the drought prediction models which were Random Forest (RF) and Extreme Gradient Boosting (XGBOOST). The performance of these models was reported using metrics such as: coefficient of determination (R 2 ), root mean square error (RMSE), mean square error (MSE), and root mean absolute error (MAE). The results revealed that XGBOOST models gave better prediction performance for SPI 3, 6, 12 with coefficients of determination of 0.89, 0.83 and 0.99, respectively. The square root mean square error (RMSE) of the models gives 0.29, 0.40 and 0.07, respectively. This work demonstrated the potential of artificial intelligence approaches in the prediction of droughts in the Republic of Benin.

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Section: B Datamentioning

confidence: 99%

Drought Forecasting in Alibori Department in Benin using the Standardized Precipitation Index and Machine Learning Approaches

VODOUNON¹,

SOUDE²,

MAMADOU³

2022

IJACSA

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“…High spatial and temporal variability are the main aspects of the observed precipitation trends in the Mediterranean region, but the simulation of meteorological data using climate models reveals decreasing trends for precipitation in the coming years [1,2]. The Mediterranean region, due to its specific morphological, climatic, and atmospheric conditions, is classified as a moderate-and high-emitting region, revealing a strong response to global climate variability [3][4][5]. Moreover, its periods of low rainfall coincide with periods of high temperatures and high water demand, which further complicates the situation [6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Application of the Standardized Precipitation Index (SPI) in the Eastern Mediterranean

Tsesmelis

Leveidioti

Karavitis

et al. 2023

Climate

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The ever-increasing need for water, the alteration in the climate, and its observed changes over recent years have triggered a lot of research studies associated with the phenomenon of drought. Within the wider geographical region of the Mediterranean, the relevant scientific subject seems to be of great interest, since it is undoubtedly related to a number of severe socio-economic consequences. This present effort focuses on the evolution of this particular phenomenon over time, within the borders of nine different countries in the Eastern Mediterranean (Athens, Greece—Europe; Constantinople, Turkey—Asia; Nicosia, Cyprus—Europe; Jerusalem, Israel—Asia; Amman, Jordan—Asia; Damascus, Syria—Asia; Beirut, Lebanon—Asia; Cairo, Egypt—Africa; and Tripoli Libya—Africa). By applying the Standard Precipitation Index (SPI), examining precipitation data at the month level (January 1901 to December 2020), and utilizing the Inverse Distance Weighted (IDW) method, the spatio–temporal variability of drought events in the Eastern Mediterranean area was studied. In Jerusalem, long-term droughts presented a higher than usual volume, in accordance with applying the 12- and 24-month SPI, starting from the mid-20th century. Similarly, the region of Damascus presented a similar pattern to those in Beirut, Amman, and Jerusalem. An upward trend in the frequency of extreme drought events was observed for the last thirty years. The same trend seems to be true in terms of the duration of dry periods. Drought events have also been observed in the central, southern, and eastern regions of Turkey. A downward trend was observed in Cairo based on a trend analysis of its monthly precipitation.

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“…Although many studies have estimated the water footprint for agricultural crops and virtual water trade for Egypt [26][27][28], none of them focused on identifying virtual trade between Egypt and the EU and the main driving factors behind changes in VW outflows. With over 25% of Egypt's trade, the EU is the nation's most significant trading partner.…”

Section: Introductionmentioning

confidence: 99%

Decomposition Analysis of Virtual Water Outflows for Major Egyptian Exporting Crops to the European Union

2023

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International trade can spur economic growth, but it can also deplete the water resources needed to produce traded goods. This is crucial for Egypt as a lower-middle income country where boosting agricultural exports is encouraged to promote the sustainable agriculture development strategy. The objective of this paper was to quantify Egypt’s virtual water flows contributing to agricultural trade with one of its main trading partners, the European Union. We considered calculating virtual water of exports since 2001 as it represents Egypt-EU’s implementation of the association agreement. We focused on the five governorates of the Nile Delta. These governorates are major producers of the five major crops exported to the European Union. This study used long-term trade trends, and changes in crop composition to analyze the implications for virtual water outflows and economic water use efficiency. By decomposing the virtual water of exports, we were able to identify the trend of virtual water outflows and the factors affecting this trend. From both an economic and water perspective, our results suggest that adopting a policy aimed at saving water resources at the national level and focusing on high-yield exports at the international level will promote the development agenda of Egypt.

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Winter Potato Water Footprint Response to Climate Change in Egypt

Cited by 6 publications

References 67 publications

Drought Forecasting in Alibori Department in Benin using the Standardized Precipitation Index and Machine Learning Approaches

Drought Forecasting in Alibori Department in Benin using the Standardized Precipitation Index and Machine Learning Approaches

Spatiotemporal Application of the Standardized Precipitation Index (SPI) in the Eastern Mediterranean

Decomposition Analysis of Virtual Water Outflows for Major Egyptian Exporting Crops to the European Union

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