Hydrological modeling is an important tool for water resources management, providing a feasible solution to represent the main hydrological processes and predict future streamflow regimes. The literature presents a set of hydrological models commonly used to represent the rainfall-runoff process in watersheds with different meteorological and geomorphological characteristics. The response of such models could differ significantly for a single precipitation event, given the uncertainties associated with the input data, parameters, and model structure. In this way, a correct hydrological representation of a watershed should include the evaluation of different hydrological models. This study explores the use and performance of five hydrological models to represent daily streamflow regimes at six hydropower plants located in the Tocantins river basin (Brazil). The adopted models include the GR4J, HYMOD, HBV, SMAP, and MGB-IPH. The evaluation of each model was elaborated considering the calibration (2014–2019) and validation period (2005–2010) using observed data of precipitation and climatological variables. Deterministic metrics and statistical tests were used to measure the performance of each model. For the calibration stage, results show that all models achieved a satisfactory performance with NSE values greater than 0.6. For the validation stage, only the MGB-IPH model present a good performance with NSE values greater than 0.7. A bias correction procedure were applied to correct the simulated data of conceptual models. However, the statistical tests exposed that only the MGB-IPH model could preserve the main statistical properties of the observed data. Thus, this study discusses and presents some limitations of the lumped model to represent daily streamflows in large-scale river basins (>50,000 km${}^2$).

This article presents the results of analyzing the use of dispersed storage tanks as a low impact development (LID) alternative to mitigate the flash flood risk in consolidated urban watersheds in Barranquilla, Colombia. Fieldwork, rainfall and flow rate monitoring, and numerical modeling were conducted to evaluate different scenarios combining storage tank capacity, two types of storage operations, and different locations by land use and watershed sectoring. These results showed that it is possible to reduce significantly the peak flow with small-capacity tanks distributed in the urban watershed with hydraulic structures that divide the discharge during the peak-flow time interval. By storing 3–17% of the runoff volume, equivalent to a dispersed storage capacity from 4 to 19 mm rainfall, it is possible to reduce the peak flow from 25 to 75%. These results demonstrate the advantages of using low impact development for stormwater management in consolidated cities with limited space, if regulatory p...

The assessment of seasonal streamflow forecasting is essential for appropriate water resource management. A suitable seasonal forecasting system requires the evaluation of both numerical weather prediction (NWP) and hydrological models to represent the atmospheric and hydrological processes and conditions in a specific region. In this paper, we evaluated the ECMWF-SEAS5 precipitation product with four hydrological models to represent seasonal streamflow forecasts performed at hydropower plants in the Legal Amazon region. The adopted models included GR4J, HYMOD, HBV, and SMAP, which were calibrated on a daily scale for the period from 2014 to 2019 and validated for the period from 2005 to 2013. The seasonal streamflow forecasts were obtained for the period from 2017 to 2019 by considering a daily scale streamflow simulation comprising an ensemble with 51 members of forecasts, starting on the first day of every month up to 7 months ahead. For each forecast, the corresponding monthly streamflow time series was estimated. A post-processing procedure based on the adjustment of an autoregressive model for the residuals was applied to correct the bias of seasonal streamflow forecasts. Hence, for the calibration and validation period, the results show that the HBV model provides better results to represent the hydrological conditions at each hydropower plant, presenting NSE and NSElog values greater than 0.8 and 0.9, respectively, during the calibration stage. However, the SMAP model achieves a better performance with NSE values of up to 0.5 for the raw forecasts. In addition, the bias correction displayed a significant improvement in the forecasts for all hydrological models, specifically for the representation of streamflow during dry periods, significantly reducing the variability of the residuals.

This article shows the design and development of a reactive early warning model as part of a reactive early warning system for urban flash flood management in the city of Barranquilla, Colombia. The system is divided into four components: (i) measuring equipment with rainfall and flow rate gauges, datalogging and transmission, (ii) a system for database processing and a web interface, (iii) a numerical rainfall-runoff model in PCSWMM calibrated and validated, and (iv) a reactive early warning model for determining the hazard level, and for making decisions of alertness along the main streets. Twelve (12) rainfall gauges were installed in the city, covering around 150 Km². The numerical model in PCSWMM was calibrated and validated with rainfall and flow rate data measured in a typical subcatchment of the city. A time of concentration equation was developed from the characteristics of the subcatchment such as slope and length. A pilot urban watershed was selected to test the system, from which hazard alerts every minute with forecasting of up to 40 minutes ahead on the lower parts of the watershed were determined. That time may allow people to make prompt decisions regarding their mobility over the city and reducing accidents caused by flash floods.