Aryal et al. (2025) Dynamics of Meteorological and Agricultural Drought in the Karnali River Basin, Nepal

Identification

• Journal: Land
• Year: 2025
• Date: 2025-11-17
• Authors: Kumar Aryal, Dhiraj Pradhananga, Deepak Aryal, Nir Y. Krakauer, Rajesh Sigdel
• DOI: 10.3390/land14112271

Research Groups

• Central Department of Hydrology and Meteorology, Tribhuvan University, Kathmandu, Nepal
• Department of Meteorology, Tri-Chandra Multiple Campus, Tribhuvan University, Kathmandu, Nepal
• The Small Earth Nepal, Kathmandu, Nepal
• Department of Civil Engineering, City College of New York, New York, USA
• Institute of Forestry, Hetauda Campus, Tribhuvan University, Hetauda, Nepal

Short Summary

This study provides a multidimensional drought analysis for the Karnali River Basin (Nepal) using 30 years of observational and satellite data, revealing a long-term greening trend despite a significant increase in meteorological drought severity, highlighting the complex interplay of climatic and anthropogenic factors.

Objective

• To compute and standardize the Standardized Precipitation Index (SPI), Soil Moisture Index (SMI), and Normalized Difference Vegetation Index (NDVI) for a general drought assessment.
• To determine inter-annual and seasonal variability and identify spatial drought hotspots.
• To determine the frequency, intensity, and category distributions of drought using standard thresholds.
• To create decision-supportive visual products for drought monitoring in the Karnali River Basin.

Study Configuration

• Spatial Scale: Karnali River Basin (KRB), western Nepal, covering approximately 42,457 square kilometers, with altitudes ranging from 142 meters to 7497 meters.
• Temporal Scale: 1995–2024 (30 years for precipitation and soil moisture), 2000–2024 (25 years for NDVI), analyzed on monthly, seasonal, and annual timescales.

Methodology and Data

• Models used:
  • Standardized Precipitation Index (SPI) for meteorological drought (3-month, 6-month, and 12-month accumulation periods).
  • Soil Moisture Index (SMI) for hydrological and agricultural drought.
  • Normalized Difference Vegetation Index (NDVI) for ecological drought.
  • Principal Component Analysis (PCA) to develop composite meteorological and agricultural drought indices.
  • Mann–Kendall test and Sen’s slope estimator for trend analysis.
  • Inverse Distance Weighting (IDW) for spatial interpolation of precipitation data.
• Data sources:
  • Daily precipitation data from 28 stations of the Nepal Department of Hydrology and Meteorology (DHM).
  • ERA5 reanalysis data for volumetric soil moisture (0–7 cm depth).
  • MODIS satellite instruments (MOD13Q1 product, 250 m resolution, 16-day composites) for NDVI.

Main Results

• The Normalized Difference Vegetation Index (NDVI) showed a consistent long-term greening trend, with an average increase of 12% from 2000 to 2024 (Sen slope of 0.0011 per year, p < 0.05).
• The annual average Soil Moisture Index (SMI) exhibited a slight, non-significant declining tendency of −0.0024 per year (p = 0.75), indicating overall stable medium-soil moisture conditions.
• The Standardized Precipitation Index (SPI) revealed a slight but significant increase in long-term meteorological drought severity (SPI12: −0.031 per year, p < 0.05), with mountainous regions identified as drought hotspots (frequency > 12% for SPI12).
• Vegetation responses (NDVI) lagged soil moisture anomalies (SMI) by approximately one month.
• Composite meteorological and agricultural drought indices were moderately correlated (Pearson r = 0.55). Meteorological droughts were highly volatile (52% normal conditions), while agricultural droughts evolved more slowly with greater permanence (64% normal conditions).

Contributions

• Provides a comprehensive, multi-dimensional drought analysis (meteorological, hydrological, ecological) for the Karnali River Basin, addressing a critical knowledge gap in the region.
• Introduces a novel approach for the KRB by developing composite meteorological and agricultural drought indices using Principal Component Analysis (PCA) from integrated multi-source datasets (ground observations, reanalysis, and satellite data).
• Offers a transferable methodological framework for assessing drought propagation in data-scarce, topographically complex, and monsoon-influenced basins globally.
• Highlights the complex interplay of a long-term greening trend with increasing meteorological drought severity, suggesting buffering effects from factors like irrigation, meltwater, and land-use changes.
• Generates actionable data and insights crucial for enhancing disaster preparedness, informing agricultural planning, and supporting adaptive water resource management strategies in climate-vulnerable mountain regions.

Funding

• University Grant Commission (UGC) under PhD Fellowship and Research Support, award no. PhD-81/82-S&T-11.

Citation

@article{Aryal2025Dynamics,
  author = {Aryal, Kumar and Pradhananga, Dhiraj and Aryal, Deepak and Krakauer, Nir Y. and Sigdel, Rajesh},
  title = {Dynamics of Meteorological and Agricultural Drought in the Karnali River Basin, Nepal},
  journal = {Land},
  year = {2025},
  doi = {10.3390/land14112271},
  url = {https://doi.org/10.3390/land14112271}
}