In Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for missing or data different from the requested variable, and (d) requesting the information once again if it is not correct. To tackle these setbacks, 318 rain gauges located in the Colombian Caribbean region were used to first evaluate whether or not the Gumbel distribution was indeed the most suitable by performing frequency analyses using three different distributions (Gumbel, Generalized Extreme Value (GEV), and Log-Pearson 3 (LP3)); secondly, to generate daily maximum isohyetal maps for return periods of 2, 5, 10, 20, 25, 50, and 100 years; and, lastly, to evaluate which interpolation method (IDW, spline, and ordinary kriging) works best in areas with a varying density of data points. GEV was most suitable in 47.2% of the rain gauges, while Gumbel, in spite of being widely used in Colombia, was only suitable in 34.3% of the cases. Regarding the interpolation method, better isohyetals were obtained with the IDW method. In general, the areal maximum daily rainfall estimated showed good agreement when compared to the true values.

This work proposes an approach to automatically adjust the curve number (CN) to account for changes in vegetation density. Precipitation–runoff pairs from the MOdel Parameter Estimation EXperiment (MOPEX) dataset were used to estimate monthly simulated CNs (CN_sim). Remotely sensed greenness fraction (GF) was used as a proxy for vegetation density. A relationship was established between CN_sim and GF values, and an adjustment factor was introduced. The coefficients of determination (R²) between the simulated and observed runoff when using the unadjusted and adjusted CNs were 0.63 and 0.80, respectively. Likewise, Nash-Sutcliffe coefficients of –0.17 and 0.67, and root mean square error (RMSE) of 5.22 and 2.75 were also obtained for the unadjusted and adjusted CNs, respectively. The results demonstrate how the adjustments compensate for the runoff overestimation when the standard CN (CN_std) is used, and also imply that the adjustment is crucial for improved hydrological modelling, particularly, for flood and flash flood monitoring and forecasting.

The 24-h maximum rainfall (P_24h-max) observations recorded at the synoptic weather station of Rafael Núñez airport (Cartagena de Indias, Colombia) were analyzed, and a linear increasing trend over time was identified. It was also noticed that the occurrence of the rainfall value (over the years of record) for a return period of 10 years under stationary conditions (148.1 mm) increased, which evidences a change in rainfall patterns. In these cases, the typical stationary frequency analysis is unable to capture such a change. So, in order to further evaluate rainfall observations, frequency analyses of P_24h-max for stationary and non-stationary conditions were carried out (by using the generalized extreme value distribution). The goodness-of-fit test of Akaike Information Criterion (AIC), with values of 753.3721 and 747.5103 for stationary and non-stationary conditions respectively, showed that the latter best depicts the increasing rainfall pattern. Values of rainfall were later estimated for different return periods (2, 5, 10, 25, 50, and 100 years) to quantify the increase (non-stationary versus stationary condition), which ranged 6% to 12% for return periods from 5 years to 100 years, and 44% for a 2-year return period. The effect of these findings were tested in the Gordo creek watershed by first calculating the resulting direct surface runoff (DSR) for various return periods, and then modeling the hydraulic behavior of the downstream area (composed of a 178.5-m creek’s reach and an existing box-culvert located at the watershed outlet) that undergoes flooding events every year. The resulting DSR increase oscillated between 8% and 19% for return periods from 5 to 100 years, and 77% for a 2-year return period when the non-stationary and stationary scenarios were compared. The results of this study shed light upon to the precautions that designers should take when selecting a design, based upon rainfall observed, as it may result in an underestimation of both the direct surface runoff and the size of the hydraulic structures for runoff and flood management throughout the city.

In ungauged watersheds, the estimation of the time of concentration (Tc) is always a challenging task due to the intrinsic uncertainty involved when making assumptions. Given that Tc is one of the main inputs in a hydrological analysis for the design of hydraulic structures for stormwater management, ten equations (including one proposed in several local studies) and two Tc methodologies (overland flow time plus channel flow time) were used to compute the Tc in fifteen urban ungauged watersheds, located in Cartagena de Indias (Colombia), with different area sizes and slopes to statistically assess their performance against the value obtained via the Natural Resources Conservation Service (NRCS) velocity method (assumed to be the true value). According to the Nash–Sutcliffe efficiency index, none of the equations proved to be reliable in all watersheds as only four equations predicted the Tc value in 53% of the cases. In addition, based on the percent bias, all equations tended to significantly over- or underestimate the Tc, which affects the quantification of the runoff volume necessary for, among others, the implementation of best management practices for watershed management (e.g., conventional and/or sustainable drainage system design), flood-prone area delineation and flood risk analyses, urban planning, and stream restoration.

In the Colombian Caribbean region, there are few studies that evaluated the behavior of one of the most commonly used variables in hydrological analyses: the maximum daily rainfall (P_max-24h). In this study, multiannual P_max-24h time series from 19 rain gauges, located within the department of Atlántico, were analyzed to (a) determine possible increasing/decreasing trends over time, (b) identify regions with homogeneous behavior of P_max-24h, (c) assess whether the time series are better suited under either a stationary or non-stationary frequency analysis, (d) generate isohyetal maps under stationary, non-stationary, and mixed conditions, and (e) evaluate the isohyetal maps by means of the calculation of areal rainfall (P_areal) in nine watersheds. In spite of the presence of both increasing and decreasing trends, only the Puerto Giraldo rain gauge showed a significant decreasing trend. Also, three regions (east, central, and west) with similar P_max-24h behavior were identified. According to the Akaike information criterion test, 79% of the rain gauges showed better fit under stationary conditions. Finally, statistical analysis revealed that, under stationary conditions, the errors in the calculation of P_areal were more frequent, while the magnitude of the errors was larger under non-stationary conditions, especially in the central–south region.