Prediction of the change trend of temperature and rainfall in the future period and its impact on desertification

Document Type : Research/Original/Regular Article

Authors

1 M.Sc. Student/ Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Tehran, Iran

2 Ph.D. of Combatting Desertification/ Department of Natural Resources Engineering, Faculty of Agriculture and Natural Resources, University of Hormozgan, Bandar Abbas, Iran

3 Ph.D. Student, Department of Arid and Mountainous Regions Reclamation/ Faculty of Natural Resources, University of Tehran, Tehran, Iran

4 Associate Professor/Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Tehran, Iran

Abstract

Introduction
Desertification is equivalent to land degradation in arid, semi-arid, and semi-humid arid regions affected by climate change and human activities. Recognition of climatic anomalies that are effective in aggravating desert conditions that cause climatic conditions to distance themselves from normal long-term conditions in a certain spatial and temporal range as a major factor or precondition for the intensification of human activities is essential. Climate change, has multiple effects on various ecosystems. Given the wide-ranging effects of climate change on desertification and economic and social issues, knowing how such changes occur in environmental planning will be very effective.
Materials and Methods
Investigating temperature and precipitation changes, as two main elements of the climate structure, in the statistical period 1989-2010 and predict these changes in the study periods 2011-2030, 2046-2065, and 2080-2099, in three decades 2020, 2050 and 2090 were performed at Baft Synoptic Station using LARS-WG micro-scale method. Baft City is located in the southwest of Kerman Province. Daily data of rainfall, temperature parameters, and sunshine duration during the period 1989-2010 were collected. A homogeneity test was performed. The LARS-WG model is a multivariate regression model for the production of climatic data by statistical micro-scale techniques according to a specific climate change scenario in the future. The monthly and seasonally results of the HadCM3 model were generated under the emission scenario of A2, A1B, and B1.
Results and Discussion
The highest increase in average daily temperature is related to scenario A2 in autumn, scenario A2 in spring and scenario A2 in summer. Comparison of seasonal temperature changes in the future also shows an increase in temperature in all seasons, especially spring and summer. The highest rainfall is related to the months of February in scenario A1B, March in scenario A2, January in scenario A1B and February in scenario A2, respectively, and only in July and December the precipitation decreased in all three scenarios. In the period 2046-2065, the highest increase in rainfall is related to January and February in scenario A1B, March in scenario B1, and January in scenario A2, respectively, and the least rainy month compared to the base period is December. In the period 2080-2099, the highest increase in rainfall is related to March in scenario A1B and scenario B1 and January in scenario A2, respectively, and the least rainy month compared to the base period is December.
Conclusion
The temperature will increase in all months as well as decrease rainfall in summer and increase it in autumn and winter. This increase in temperature and decrease in rainfall are among the factors aggravating desertification based on climate criteria. The findings can be used to estimate changes in water resources, agricultural crop yields, droughts and floods in the future.

Keywords

References

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Water and Soil Management and Modelling
Volume 1, Issue 1
March 2021
Pages 53-66

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History

  • Receive Date: 16 April 2021
  • Revise Date: 11 May 2021
  • Accept Date: 12 May 2021

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