Extended Abstract
Introduction and Objective: Due to the limited number of meteorological stations especially in mountainous areas, the use of satellite data to extract rainfall is very important. On the other hand, the lack of spatial appropriate rainfall data is one of the major challenges in flood or drought prediction and timely warning in this case. One of the available solutions in this case is to measure rainfall from space.
Material and Methods: The aim of this study was to investigate the accuracy of rainfall data obtained from TRMM satellite images in Taleghan watershed on a monthly and annual time scale during the period 2010 to 2015. For this purpose, TRMM images with three-hour spatial resolution were received during the statistical period for the study area. Then using the sum of three hours rainfall, daily rainfall was estimated. In the following the adjustment coefficients were also presented to reduce the error of rainfall data, and finally the accuracy of satellite image data was compared with two common interpolation methods i.e. invers distance weighting and Kriging.
Results: The results of error indices showed that the rainfall of TRMM images is well correlated with the data of ground stations, especially Joestan station, but in some months, there is a problem of under-estimation and over-estimation. For this reason, correction coefficients were applied to solve this problem, which on average in most months; this coefficient was calculated less than one, which indicates the overestimation of TRMM image precipitation data. Examination of the corrected data showed that by applying the estimation coefficients, in addition to solving the overestimation problem, the error rate was also reduced and the Nash-Sutcliffe performance index was somewhat improved. The root mean square error (RMSE) at Garab station also decreased from 88 to 26 mm in annual rainfall time scale by applying the adjustment coefficients, which indicates an increase in data efficiency after the application of correction coefficients. The results of comparing the modified data with interpolation methods showed that in all error indices, the modified TRMM data is more efficient in estimating rainfall.
Conclusion: Overall, it can be said that rainfall from TRMM images can give satisfactory results if adjustment coefficients are applied, and in areas with a shortage of meteorological and data stations, it can be a reliable source of rainfall data.
Type of Study:
Research |
Subject:
سنجش از دور و سامانه های اطلاعات جغرافيايی Received: 2021/07/16 | Accepted: 2021/10/20