Regionalization of Rainfall Using RCDA Cluster Ensemble Algorithm in India

Abstract

The magnitude and frequency of precipitation is of great significance in the field of hydrologic and hydraulic design and has wide applications in varied areas. However, the availability of precipitation data is limited to a few areas, where the rain gauges are successfully and efficiently installed. The magnitude and frequency of precipitation in ungauged sites can be assessed by grouping areas with similar characteristics. The procedure of grouping of areas having similar behaviour is termed as Regionalization. In this paper, RCDA cluster ensemble algorithm is employed to identify the homogeneous regions of rainfall in India. Cluster ensemble methods are commonly used to enhance the quality of clustering by combining multiple clustering schemes to produce a more robust scheme delivering similar homogeneous regions. The goal is to identify, analyse and describe hydrologically similar regions using RCDA cluster ensemble algorithm. RCDA cluster ensemble algorithm, which is based on discriminant analysis. The algorithm takes H base clustering schemes each with K clusters, obtained by any clustering method, as input and constructs discriminant function for each one of them. Subsequently, all the data tuples are predicted using H discriminant functions for cluster membership. Tuples with consistent predictions are assigned to the clusters, while tuples with inconsistent predictions are analyzed further and either assigned to clusters or declared as noise. RCDA algorithm has been compared with Best of K-means and Clue cluster ensemble of R software using traditional clustering quality measures. Further, domain knowledge based comparison has also been performed. All the results are encouraging and indicate better regionalization of the rainfall in different parts of India.

Precipitation Regionalization Using Self-Organizing Maps for Mumbai City, India

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Evaluation of GPM IMERG Performance Over the Lake Titicaca Basin at Different Time Scales

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Regionalization of Maximum Daily Rain in Moquegua Perú

“…El análisis de la precipitación diaria es un tema de gran interés, puesto que las precipitaciones torrenciales son uno de los mayores riesgos ambientales, así se ha investigado la concentración temporal a esta escala de tiempo (Benhamrouche & Martín Vide, 2011). La magnitud y la frecuencia de precipitación es de gran importancia en el diseño en hidrología e hidráulica, pero la disponibilidad de datos de precipitación están limitados a pocas zonas donde se ha instalado estaciones meteorológicas exitosamente y eficientemente, por ello en zonas sin estaciones la precipitación puede evaluarse por agrupar zonas con características similares (Ahuja & Dhanya, 2012). Se desarrolló una formula empírica IDF (intensidad duración frecuencia) para estimar la intensidad de precipitación para cualquier duración y para cualquier período de retorno con mínimo esfuerzo, para ello se han utilizado datos de precipitación diaria (Rashid et al, 2013).…”