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<p>The spatiotemporal patterns and intensity of monsoon rainfall have experienced notable changes in recent years, particularly across the high-altitude regions of India. Hydrological extremes in the Himalayas result from heavy rainfall beyond the traditional JJAS monsoon season. The lack of long-term hydrological and meteorological data in the Himalayan region constrains accurate hydrological assessments, hindering effective strategies for managing extreme hydrological events. In recent times, Gridded Remote Sensing Precipitation Products (RSPPs) have emerged as essential alternatives to ground-based rainfall data. However, no defined criteria exist for identifying a region-specific, better-suited global RSPP for hillslope hydrological analysis. This study proposes a novel monsoon-based index, such as the Monsoon Index (MI), to quantify the temporal distribution of the monsoon period in terms of its magnitude. Among the assessed RSPPs (PERSIANN-CDR, MSWEP, and GPCP 1dd), IMERG exhibits the strongest agreement with the observed Monsoon Index (MI) for 2000–2020, as reflected in its median MI value of 0.633, which closely matches the observed data. Its lowest average deviation (0.021), lowest error statistics (<i>RMSE</i> 0.048, <i>MAPE</i> 5.769), and highest <i>R²</i> (0.617) further confirm IMERG as the most suitable RSPP for the study area. An observed data-based optimized lumped hydrological model (i.e., HYSIM) was used to simulate daily runoff using the RSPPs dataset to assess their usability for runoff estimation. The higher <i>R²</i> (0.741), <i>NSE</i> (0.654), and lower <i>PBIAS</i> (0.000) and <i>RSR</i> (0.588) compared to the observed runoff confirm the efficacy of this RSPP for runoff estimation. Thus, region-specific MI-based RSPPs present a reliable and practical alternative for hydrological assessments in ungauged, high-altitude regions.</p> Graphical Abstract <p></p>

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Assessment of Remote Sensing Precipitation Products for Hydrological Analysis in an Ungauged Watershed

  • 期刊论文

  • 发表日期：

    2026年1月3日

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  • Dibyandu Roy,
  • J. Indu

摘要

The spatiotemporal patterns and intensity of monsoon rainfall have experienced notable changes in recent years, particularly across the high-altitude regions of India. Hydrological extremes in the Himalayas result from heavy rainfall beyond the traditional JJAS monsoon season. The lack of long-term hydrological and meteorological data in the Himalayan region constrains accurate hydrological assessments, hindering effective strategies for managing extreme hydrological events. In recent times, Gridded Remote Sensing Precipitation Products (RSPPs) have emerged as essential alternatives to ground-based rainfall data. However, no defined criteria exist for identifying a region-specific, better-suited global RSPP for hillslope hydrological analysis. This study proposes a novel monsoon-based index, such as the Monsoon Index (MI), to quantify the temporal distribution of the monsoon period in terms of its magnitude. Among the assessed RSPPs (PERSIANN-CDR, MSWEP, and GPCP 1dd), IMERG exhibits the strongest agreement with the observed Monsoon Index (MI) for 2000–2020, as reflected in its median MI value of 0.633, which closely matches the observed data. Its lowest average deviation (0.021), lowest error statistics (RMSE 0.048, MAPE 5.769), and highest R² (0.617) further confirm IMERG as the most suitable RSPP for the study area. An observed data-based optimized lumped hydrological model (i.e., HYSIM) was used to simulate daily runoff using the RSPPs dataset to assess their usability for runoff estimation. The higher R² (0.741), NSE (0.654), and lower PBIAS (0.000) and RSR (0.588) compared to the observed runoff confirm the efficacy of this RSPP for runoff estimation. Thus, region-specific MI-based RSPPs present a reliable and practical alternative for hydrological assessments in ungauged, high-altitude regions.

Graphical Abstract