Water Quality

Williams, Richard J.; Neal, Colin; Jarvie, H. J.; Johnson, Andrew C.; Whitehead, Paul; Bowes, Mike; Jenkins, Alan

doi:10.1002/9781119074304.ch8

Cited by 2 publications

(1 citation statement)

References 191 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Europe (Dumont et al, 2012;Johnson et al, 2015;Williams et al, 2015), China (Lui et al, 2015) and India (Rickards et al, 2020) and a successful pilot study within the Upper Cauvery Catchment (Horan et al, 2021a), makes it suitable for application in southern India. The GWAVA model has been updated to better represent small-scale runoff harvesting interventions (Horan et al, 2021b), groundwater abstraction, artificial recharge, and regulated dam releases (Horan et al, 2021c).…”

Section: Model Selectionmentioning

confidence: 99%

An Investigation into the Suitability of Gauge-Corrected Remotely Sensed Rainfall Datasets for Hydrological Modelling in the Western Ghats

HORAN,

Smithers,

Clark

et al. 2024

Preprint

View full text Add to dashboard Cite

An accurate spatial and temporal representation of rainfall is essential for hydrological assessments and water resources management. Rainfall is monitored in India’s mountainous Western Ghats region via in-situ rainfall gauging stations maintained by the Indian Meteorological Department (IMD). However, the network is sparse, and significant periods of data are missing. Furthermore, the IMD gridded rainfall dataset is known to underestimate the depth of rainfall at the high altitudes within this region. In this study, rainfall estimated by the IMD grids and from remote sensing using the CHIRPS (0.25- and 0.05- degree), MSWEP and PERSIANN datasets are compared to the IMD in-situ gauged rainfall within the Western Ghats using a point-to-pixel analysis. The GWAVA model is utilised to determine the effect of the selected rainfall input datasets on representing wider water resources. It was found that the average ensemble provided the best representation of the in-situ gauged and catchment rainfall and a better representation than the IMD grids. It remains critical for water resources management to ensure that in-situ rainfall gauging networks are maintained. In-situ data sources of high confidence remain important for the continuous development and ground-truthing of different rainfall datasets.

show abstract