Abstract
ABSTRACT As an alternative to Gap filling in monthly average rainfall series, we attempted to present a methodology for the generation of series only with the observed data available in the rainfall stations present in the study area and its surroundings. For this, a computational tool was developed with a GIS approach, using scripts in the Python language, to automate the study steps. Two calculation alternatives for the mean precipitation, variable Thiessen polygons or variable inverse distance weights (IDW), were considered. Random gaps were imposed from a series of data without gaps allowing us to evaluate the presented methodology. The results of the series calculated according to this methodology were compared to two methods of Gap filling. The behavior of the series was evaluated through the analysis of position and dispersion measurements as well as the temporal behavior by the evaluation of the correlograms and periodograms. The results are found to be satisfactory, which demonstrates the equivalence of the proposal with results found with the gap filling methods under the tested conditions. The differences found between the series were small, which was reflected in the Nash-Sutcliffe Indexes. There were no significant differences between the calculation alternatives by Thiessen polygons or IDW weights.
Highlights
Rainfall, characterized by its spatial and temporal variation, is one of the most important data for hydrological studies.Hydrological monitoring, capable of promoting sufficient reliable data, is a preponderant part of a water resources information system, and it is a previous and fundamental step without which one cannot effectively execute the managing of these resources.Pluviometers traditionally physically measure the amount of precipitation in a determined space and, generally, provide data to a small area
To gap filling in monthly average rainfall series in a hydrographic basin we propose to carry this out in a automatized manner by means of geoprocessing tools
For the analysis of the average rainfall series by the alternative methodology, without gap filling, these series were compared to the ones obtained from the series originated from data without gaps and to the ones obtained from data with gap filling by the Regional Weighting Method
Summary
Pluviometers traditionally physically measure the amount of precipitation in a determined space and, generally, provide data to a small area. These rainfall measurements are used in rain-flow models (JAYAKRISHNAN; SRINIVASAN; ARNOLD, 2004). Given the difficulties found in the monitoring of rainfall, gaps can be expected in the historical series. These gaps are due to problems such as the lack of an observer, mistakes in the register mechanisms, loss of notes and data or in the transcription of the registers made by operators and closure of observations points. For most applications exists the need of continuous series analysis, demanding gap filling (STRECK et al, 2009; BERTONI; TUCCI, 2013)
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