Generation of Daily Synthetic Precipitation Series: Analyses and Application in La Plata River Basin

Abstract

Precipitation analysis is embedded in a range of important hydrological studies for hydraulic works construction and maintenance. However, flaws and limitations in records are obstacles often encountered by researchers. One feasible solution for overcoming these obstacles is to generate synthetic series. The main objective of this work is to structure and validate a model for generating synthetic rainfall series at a daily scale. A parametric model has been constructed, where the occurrences are determined by a stochastic Markov process and the cumulative rainfall quantities are computed using a mixed exponential probability distribution. Since no previous studies using the proposed probability distribution in La Plata Basin were found in the literature, several significance tests and relevant criteria were applied, in order to verify the model accuracy. The approach was studied in 11 rainfall stations inside Parana and Uruguay rivers basins, located in Brazilian South and Southeast regions, obtaining good results. Additional analyses of the model performance related to extreme events and droughts are also present.

The CLARIS LPB database: constructing a long‐term daily hydro‐meteorological dataset for La Plata Basin, Southern South America

“…Several other works used daily surface minimum and maximum temperature and rainfall data observed at governmental and non‐governmental stations from Argentina, Brazil, Paraguay, and Uruguay, also compiled in CLARIS LPB database (Bettolli et al ., ,b; D'Orgeval et al ., ; Detzel & Mine, ; Renom et al ., ; Urcola et al ., ; Bettolli & Penalba, ; among others).…”

Earth Dam Construction Simulation Considering Stochastic Rainfall Impact

“…It is assumed that the evolution of the precipitation state depends only on its current state, the Markov property test has been conducted to validate the applicability of the Markov chain in modeling the daily rainfall sequence (Zhang et al, 2010). The daily precipitation amount was assumed to be independent and identically distributed (Verma et al, 2011;Detzel and Mine, 2011;Chen and Brissette, 2014b). To consider the seasonality features of precipitation, models are separately established for 12 calendar months (Li et al, 2014;Sonnadara and Jayewardene, 2015).…”

“…Considering the advantages of using fewer parameters to achieve satisfactory simulation results, the parametric distributions are the most widely used. For example, the exponential distribution (Gronewold et al., ), the gamma distribution (Mhanna and Bauwens, ), the Weibull distribution (Mudd et al., ), the skewed normal distribution (Lobo et al., ), and the mixed exponential distribution (Detzel and Mine, ) were used in modeling precipitation intensity. Moreover, the distribution of rainfall is usually not a normal distribution but has a right‐skewed trend.…”

Cumulative distribution function of daily rainfall in the Tocantins–Araguaia hydrographic region, Amazon, Brazil

“…The most efficient distributions were gamma and Weibull (Silva, Heldwein, Martins, Trentin, & Grimm, 2007). Detzel and Mine (2011b) observed that the use of mixed exponential distribution for modeling daily precipitation is suitable for the southern region of Brazil. In the case of the Amazon region, Paiva and Clarke (1997) adjusted the gamma distribution to the daily rainfall data in 402 rainfall gauge stations.…”