Various types of rainfall characteristic have different rainfall drop size distributions (DSDs). DSDs that are measured by radar have a fundamental influence on parameters of the Z-R relationship; using a climatological Z-R relationship to estimate radar rainfall can lead to bias in radar rainfall estimates. This paper attempts to remove the source of bias in radar rainfall estimates due to an uncertain Z-R relationship by applying a local bias adjustment factor to a region that has the same climatological rainfall characteristic. Recorded historical daily rainfall data from 188 uniformly distributed rain gauges located under the radar umbrella and its vicinity were used for describing the climatological spatial pattern of rainfall in the study area based on kriging approaches. It was found that a simple kriging technique with the isotropic Bessel-J semivariogram model was the best method to classify climatological patterns of rainfall characteristic of the study area and therefore it has been used for identifying local bias correction areas of the proposed hourly local bias (HLB) correction method. Performances of different bias correction methods with various levels of complexity were evaluated from 500 of the calibrated and cross-validated gauges of the validated data set, selected randomly. These methods include mean field bias correction (MFB), hourly mean field bias correction (HMFB), hourly range dependent mean field bias correction (HRMFB), and HLB correction. Forty-four rainfall events recorded during 2003-2005 from the S-band Pimai radar located in Nakhon-Ratchasima Province, Thailand, and 50 automatic rain gauges were used in this study. The results of this study showed that, on average, the proposed HLB method could improve accuracy of radar rainfall estimates by 16.7%, 14.3%, 2.8%, 0.4% for the calibrated gauges, and by 11.8%, 10.2%, 9.4%, 4.1% for the cross-validated gauges when compared to non-bias corrected, MFB, HMFB, and HRMFB methods, respectively.

In 2022, Thailand was subjected to extensive flooding all over the country in both urban and rural areas, which caused tremendous losses. Better design and construction of infrastructures for timely and sufficient drainage can help mitigate the problems. This requires accurate intensity–duration–frequency (IDF) relationships at or near the problem areas. To obtain an IDF curve, a continuous rain record from an automatic gauge of the area is needed. Some automatic rain-gauge stations are scattered all over the country and are much fewer in number than the daily-reading rain-gauge stations. By applying a simple scaling theory, we can construct IDF curves from the daily rain records. The 37 automatic stations distributed the scaling exponent over the country. Gumbel location and scale parameters, from 30-year rainfall records, were determined. These three parameters were mapped throughout the country and are ready to be used for creating an IDF curve at any location in the country. We verified these parameters to generate IDF curves for three sites in different regions and found very good agreements. The majority of the errors were less than 15%.

Due to climate change, many research studies have derived the updated extreme precipitation intensity–duration–frequency relationship (IDF curve) from forecasted sub-hourly rainfall intensity time series, which is one of the most important tools for the planning and designing of hydraulic infrastructures. In this study, the IDF curves (1990–2016) of the six regions and procedures are used in accordance with those of the Royal Irrigation Department (RID)’s study (1950–1988). Each set of IDF relationships consists of 81 intensity values which are the combination of nine durations and nine return periods. The intensity ratios of this study and RID are compared. A greater-than-1 ratio indicates extreme intensity increment from the past to the present. Considering 81 ratios for each region, the number of greater-than-1 ratios for the North, Northeast, Central, East, West, and South regions are 8, 2, 31, 34, 6, and 7, respectively. These ratio numbers are far below 81 which means that the majority of extreme rainfall intensities do not increase from the past to the present. The study found that using accurate historical sub-hourly rainfall time series to create a set of IDF curves would be more reliable than using forecasted rainfall modeling.