Publications

Choursi, SK; Erfanian, M; Abghari, H; Miryaghoubzadeh, M; Javan, K (2024). Enhancing drought monitoring through spatial downscaling: A geographically weighted regression approach using TRMM 3B43 precipitation in the Urmia Lake Basin. EARTH SCIENCE INFORMATICS.

Abstract
Efficient drought monitoring in the Urmia Lake basin (ULB) is imperative to protect its ecosystem, agriculture, and the livelihoods of local communities relying on its water resources, considering the lake's susceptibility to changes in water availability. This study presents a novel approach to address the pressing issue of precise drought monitoring in regions with limited and unevenly distributed weather stations. By utilizing Tropical Rainfall Measuring Mission (TRMM) satellite-derived data and a Geographically Weighted Regression (GWR) model, we have significantly refined the spatial resolution of TRMM-3B43 precipitation (5 km) compared with the original TRMM data (about 25 km). This innovative methodology, which uses the globally available MODIS data of Normalized Difference Vegetation Index (NDVI) and day-night difference in land surface temperature (LSTdn) as independent variables, achieves spatial downscaling, enhancing the spatial resolution to 5 km for the period 2001-2019. The downscaled precipitation data from three models (M1: GWR_NDVI, M2: GWR_LSTdn, and M3: GWR_NDVI-LSTdn) were applied for drought assessment based on the Standardized Precipitation Index (SPI) and modified Rainfall Anomaly Index (mRAI). The findings demonstrate that the M2 model is more accurate than the other models for spatial downscaling of TRMM 3B43 data, with reductions in RMSE and MAE values by 6.04 and 4.16 mm, respectively. Additionally, this downscaling model significantly improves KGE values from 0.56 to 0.92 while achieving the lowest percentage bias. Monthly downscaled TRMM data based on LST across 12 synoptic stations in the basin reveals enhanced accuracy post-downscaling. Spatial analysis of average monthly precipitation maps illustrates a descending rainfall trend from June to September, followed by an ascending trend from October, with peak rainfall in November and December, notably in the western and southwestern regions. This analysis of precipitation trends offers valuable insights into the spatial distribution of rainfall within the basin, revealing variations across regions crucial for effective water resource management. The concentration of higher precipitation levels in the western and southwestern sectors underscores the significance of targeted water conservation and storage efforts. Drought severity analysis unveiled persistent and escalating drought conditions, causing significant impacts across the basin. A comparative assessment of severity classes using SPI and mRAI indices at 12 synoptic stations demonstrated strong agreement. Drought occurrences were a near-annual affair, attaining severe levels during specific years, notably 2008, 2011, and 2019. Spatial analysis revealed widespread drought events affecting nearly half of the basin area, with a noticeable worsening in severity during critical years. This highlights the practical need for adopting drought mitigation strategies and water resources management.

DOI:
10.1007/s12145-024-01324-4

ISSN:
1865-0481