K
K. P. Sudheer
Researcher at Indian Institute of Technology Madras
Publications - 118
Citations - 6824
K. P. Sudheer is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Artificial neural network & Hydrological modelling. The author has an hindex of 34, co-authored 105 publications receiving 5819 citations. Previous affiliations of K. P. Sudheer include Kerala State Council for Science, Technology and Environment & Indian Institute of Technology Delhi.
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Models for estimating evapotranspiration using artificial neural networks, and their physical interpretation
TL;DR: In this paper, an artificial neural network (ANN) technique was used to estimate evapotranspiration (ET) from limited climatic data, and the results indicated that even with limited input variables an ANN can estimate ET accurately.
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Explaining the internal behaviour of artificial neural network river flow models
K. P. Sudheer,Ashu Jain +1 more
TL;DR: A novel method of visualizing and understanding the internal functional behaviour of an artificial neural network (ANN) river flow model is presented, and it is anticipated that the current approach will initiate further research and make ANNs more useful to the hydrologic community.
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Development and verification of a non-linear disaggregation method (NL-DisTrad) to downscale MODIS land surface temperature to the spatial scale of Landsat thermal data to estimate evapotranspiration
TL;DR: In this paper, a nonlinear method (NL-DisTrad) was developed and tested to disaggregate satellite-derived estimates of land surface temperature of MODIS (Moderate Resolution Imaging Spectrometer) with a resolution of 960m to the scale of Landsat 7 ETM+ (Enhanced Thematic Mapper Plus) at 60m.
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Potential application of wavelet neural network ensemble to forecast streamflow for flood management
TL;DR: This paper presented and compared WNN and artificial neural network, both of which were combined with the ensemble method using block bootstrap sampling (BB), in terms of the forecast accuracy and precision at various lead-times on the Bow River, Alberta, Canada, suggesting that the WNN-BB is a robust modeling approach for streamflow forecasting and thus would aid in flood management.
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Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes
Subimal Ghosh,H. Vittal,Tarul Sharma,Subhankar Karmakar,K. S. Kasiviswanathan,Yeganantham Dhanesh,K. P. Sudheer,Sachin S. Gunthe +7 more
TL;DR: A significant decrease in the monsoon rainfall over major water surplus river basins in India is found, contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India.