Abstract
Data on historical extreme events provides information not only for water resources planning and management but also for the design of disaster-prevention measures. However, most basins around the globe lack long-term hydro-meteorological information to derive the trend of hydrological extremes. This study aims to investigate a method to estimate maximum and minimum flow trends in basins with limited streamflow records. To carry out this study, data from the Allipén River watershed (Chile), the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological model at a daily time step, and an uncertainty analysis were used. Through a calibration using only five years of records, 21-year mean daily flow series were generated and the extreme values derived. To analyze the effect of the length of data availability, 2, 5, and 10 years of flows were eliminated from the analyses. The results show that in the case of 11 years of simulated flows, the annual maximum and minimum flow trends present greater uncertainty than in the cases of 16 and 19 years of simulated flows. Simulating 16 years, however, proved to properly simulate the observed long-term trends. Therefore, in data-scarce areas, the use of a hydrological model to simulate extreme mean daily flows and estimate long-term trends with at least 16 years of meteorological data could be a valid option.
Highlights
Water availability changes each year due to local, global, natural, and anthropogenic phenomena
The results show that in the case of 11 years of simulated flows, the annual maximum and minimum flow trends present greater uncertainty than in the cases of 16 and 19 years of simulated flows
High sensitivity of the results to variations in Figure 5 presents the results of the regional sensitivity analysis (RSA) in the calibration process focused on high and low flows parameters
Summary
Water availability changes each year due to local, global, natural, and anthropogenic phenomena. These changes and the constant increase in demand, be it for human consumption, irrigation, hydropower, or industrial use, require increasingly efficient water resources planning and management [1]. Despite scientific and technological progress, the population remains exposed to these events [4]; trend analysis of hydroclimatic variables has become the study focus for many researchers around the world [3,5,6]. To analyze the hydrological behavior in a watershed it is important to determine maximum and minimum flow trends; ascertaining the history of a basin can be a difficult task when the available hydrometeorological information is limited [14]. Most drainage basins around the globe are ungauged or data-scarce, either because a required variable has not been sampled at the required resolution or because it has not been observed during a period of interest [15]
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