Daily rainfall erosivity as an indicator for natural disasters: assessment in mountainous regions of southeastern Brazil

Natural Hazards - Rainfall erosivity is defined as the rainfall potential to cause erosion. Its concept is based on the kinetic energy of rainfall, rainfall intensity, and maximum rainfall...     

Potential of the LASH model for water resources management in data-scarce basins: a case study of the Fragata River basin,southern Brazil

ABSTRACT

The objective of this study was to evaluate, based on a data-scarce basin in southern Brazil, the potential of the Lavras Simulation of Hydrology (LASH) model for estimating daily streamflows, annual streamflow indicators and the flow–duration curve. It was also used to simulate the different runoff components and their consistency with the basin physiographical characteristics. The statistical measures indicated that LASH can be considered suitable according to widely used classifications and when compared with other studies involving hydrological models. LASH also showed satisfactory results for annual indicators, especially for maximum and average annual streamflows, as well as for the flow–duration curve. It was found that the model was consistent with the basin characteristics when simulating runoff components. The results obtained in this study allowed us to conclude that the LASH model has the potential to aid practitioners in water resources management of basins with scarce data and similar soil and land-use conditions.

Editor A. Castellarin; Associate editor Y. Gyasi-Agyei     

Artificial intelligence for identifying hydrologically homogeneous regions: A state‐of‐the‐art regional flood frequency analysis

Due to the severity related to extreme flood events, recent efforts have focused on the development of reliable methods for design flood estimation. Historical streamflow series correspond to the most reliable information source for such estimation; however, they have temporal and spatial limitations that may be minimized by means of regional flood frequency analysis (RFFA). Several studies have emphasized that the identification of hydrologically homogeneous regions is the most important and challenging step in an RFFA. This study aims to identify state‐of‐the‐art clustering techniques (e.g., K ‐means, partition around medoids, fuzzy C‐means, K ‐harmonic means, and genetic K ‐means) with potential to form hydrologically homogeneous regions for flood regionalization in Southern Brazil. The applicability of some probability density function, such as generalized extreme value, generalized logistic, generalized normal, and Pearson type 3, was evaluated based on the regions formed. Among all the 15 possible combinations of the aforementioned clustering techniques and the Euclidian, Mahalanobis, and Manhattan distance measures, the five best were selected. Several watersheds' physiographic and climatological attributes were chosen to derive multiple regression equations for all the combinations. The accuracy of the equations was quantified with respect to adjusted coefficient of determination, root mean square error, and Nash–Sutcliffe coefficient, whereas, a cross‐validation procedure was applied to check their reliability. It was concluded that reliable results were obtained when using robust clustering techniques based on fuzzy logic (e.g., K ‐harmonic means), which have not been commonly used in RFFA. Furthermore, the probability density functions were capable of representing the regional annual maximum streamflows. Drainage area, main river length, and mean altitude of the watershed were the most recurrent attributes for modelling of mean annual maximum streamflow. Finally, an integration of all the five best combinations stands out as a robust, reliable, and simple tool for estimation of design floods.     

Capability of LISEM to estimate flood hydrographs in a watershed with predominance of long-duration rainfall events

Natural Hazards - Process-based hydrological models are of great importance to understand hydrological processes and support decision making. The LImburg Soil Erosion Model (LISEM) requires...