Drought assessment in Kabul River basin using machine learnings

Authors

  • UZAIR KHAN Department of Civil Engineering, University of Engineering and Technology, Peshawar, Pakistan
  • ALAMGIR KHALIL Department of Civil Engineering, University of Engineering and Technology, Peshawar, Pakistan
  • SHABIR JAN Department of Civil Engineering, University of Engineering and Technology, Peshawar, Pakistan

DOI:

https://doi.org/10.54386/jam.v26i3.2674

Keywords:

Drought prediction, Climate change, Machine learning, Kabul River Basin, Standardised Precipitation Evapotranspiration Index (SPEI)

Abstract

Droughts significantly impact water resources and agriculture, leading to economic losses and potential human fatalities. This study aims to predict droughts by analysing changes in the Standardised Precipitation Evapotranspiration Index (SPEI) for the Kabul River basin using data from 1981 to 2022. The research is divided into three phases: calculating SPEI, splitting the dataset into training (80%) and testing (20%) subsets, and evaluating model performance. Various machine learning algorithms, including XGBoost, Decision tree, AdaBoost, and KNN, were employed alongside different climatic variables. The models were assessed using statistical metrics such as R², RMSE, MAE, MSE for regression, and confusion matrix, accuracy, precision, recall, F1 score, ROC AUC, and Log loss for classification. Results showed strong performance, with R² values of 0.97, 0.86, 0.92, and 0.96 for XGBoost, KNN, Decision tree, and AdaBoost, respectively. SPEI demonstrated significant potential for drought forecasting, and spatial distribution mapping revealed persistent moderate drought occurrences.

References

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Published

01-09-2024

How to Cite

KHAN, U., KHALIL, A., & JAN, S. (2024). Drought assessment in Kabul River basin using machine learnings. Journal of Agrometeorology, 26(3), 349–355. https://doi.org/10.54386/jam.v26i3.2674

Issue

Vol. 26 No. 3 (2024): September

Section

Research Paper

Categories

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Copyright (c) 2024 UZAIR KHAN, ALAMGIR KHALIL, SHABIR JAN

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