The extreme rainfall event during June 2013 in the Western Himalayas caused widespread flash floods, which triggered landslides, a lake-outburst, and debris flow. For the hydrological study of such an unexpected extreme event, it is essential to have reliable and accurate rainfall predictions based on satellite observations. The mountainous state of Uttarakhand is covered by complex topography, and this state has few, unevenly distributed, rain gauge networks. This unique study was conducted to evaluate three satellite based rainfall products (i.e., TMPA-3B42, Global Satellite Mapping of Precipitation (GSMaP), and NOAA CPC Morphing Technique (CMORPH)) against the observed rain gauge-based India Meteorological Department (IMD) gridded dataset for this rainfall episode. The results from this comprehensive study confirmed that the magnitude of precipitation and peak rainfall intensity were underestimated in TMPA-3B42 and CMORPH against gauge-based IMD data, while GSMaP showed dual trends with under- and over-predictions. From the results of the statistical approach on the determination of error statistic metrics (MAE (mean absolute error), NRMSE (normalized root mean square error), PBIAS (percent bias), and NSE (Nash-Sutcliffe efficiency)) of respective satellite products, it was revealed that TMPA-3B42 predictions were more relevant and accurate compared to predictions from the other two satellite products for this major event. The TMPA-3B42-based rainfall was negatively biased by 18%. Despite these caveats, this study concludes that TMPA-3B42 rainfall was useful for monitoring extreme rainfall event in the region, where rain-gauges are sparse.

Planning and managing water resources necessitate the utilization of hydrologic models. However, the calibration of these models poses a significant challenge due to the high degree of parameter uncertainty, which has global implications. Moreover, regions with high seasonal variation in precipitation exhibit strong heteroskedasticity, further complicating the calibration process. This study aims to determine an optimized calibration approach and parameter optimizations by integrating two sensitivity methods with two optimization techniques. The methodology was demonstrated in the sub-basins of the Bay of Plenty, New Zealand, using the SWAT hydrological model. The performance indices of the calibrated models were analyzed, revealing striking similarities between GLUE and SUFI-2 approaches. Although GLUE marginally outperformed SUFI-2 in terms of the fit indices, indicating better model accuracy, SUFI-2 demonstrated less uncertainty, making it a more stable option. Among the parameters, the initial SCS curve number for moisture condition II, baseflow factor, groundwater delay, groundwater revap coefficient, soil evaporation compensation factor, Manning's coefficient value for the main channel, and effective hydraulic conductivity in the main channel were identified as the most sensitive. These findings provide critical insights into hydrological modeling, supporting the development of policies not only in the Bay of Plenty but also in similar regions.

Hydrological components in a river basin can get adversely affected by climate change in coming future. Manipur River basin lies in the extreme northeast region of India nestled in the lesser Himalayan ranges and it is under severe pressure from anthropogenic and natural factors. Basin is un-gauged as it lies in remote location and suffering from large data scarcity. This paper explores the impact of climate change towards understanding the inter-relationships between various complex hydrological factors in the river basin. An integrated approach is applied by coupling Soil and Water Assessment Hydrological Model and Hadley Center Coupled Model based on temperature, rainfall and geospatial data. Future representative concentration pathways 2.6, 4.5 and 8.5 scenarios for 2050s and 2090s decades were used to evaluate the effects of climatic changes on hydrological parameters. Both annual mean temperature and annual precipitation is predicted to be increased by 2.07oC and 62% under RCP 8.5 by the end of 21st century. This study highlights that change in meteorological parameters will lead to significant change in the hydrological regime of the basin. Runoff, actual evapotranspiration and water yield are expected to be increased by 40.96 m3/s, 52.2% and 86.8% respectively under RCP 8.5. This study shows that water yield and evapotranspiration will be most affected by increase in precipitation and temperature in the upper and middle sub-basins. Different region within the basin is likely to be affected by frequent landslides and flood in coming decades.