Dr. Muñoz-Ortiz, Enrique

Para una adecuada gestión hídrica resulta necesario conocer tanto los caudales simulados por un modelo como la incertidumbre asociada con éstos. El presente estudio busca cuantificar la incertidumbre en los caudales simulados por un modelo hidrológico junto con la propagación de ésta hacia aguas abajo, producto de incertidumbre en las precipitaciones, para así definir potenciales mejoras en los resultados de un modelo hidrológico. Se calibró un modelo conceptual semidistribuido y se determinó la incertidumbre asociada con la estructura y parámetros, para luego cuantificar la incertidumbre relacionada con una variación porcentual de las precipitaciones en diferentes periodos del año. Como resultado se obtuvo que el efecto de propagación de la incertidumbre hacia aguas abajo es despreciable debido al aumento de la magnitud de los caudales simulados, y que la incertidumbre en las salidas del modelo depende de la incertidumbre en las precipitaciones sólo en invierno.

The use of unmanned aerial vehicles (UAVs) is steadily increasing due to their capacity to capture terrain elevation data with remarkable precision and cost-effectiveness. Nonetheless, their application for estimating water surface elevations and submerged terrain, such as channel bathymetry, remains constrained. Consequently, the development of a digital terrain model that relies on UAV data during low-water periods assumes a more extensive dry channel surface area, thus alleviating the information gap regarding submerged terrain. The objective of this brief report is to validate a hydraulic model for flood calculation. To this end, a 1D steady-state hydrological model of the Ñuble River based on a UAV survey in the low-water period of 2016 was constructed in HEC-RAS v.5.0.3 and compared to water surface elevation observations of the flood on 24 June 2023. The model tends to overestimate the flood, but the errors are considered tolerable for flood calculation (on average, a 10.6% depth error was obtained for a 30-year return period flood); therefore, the hydraulic model derived from remote sensing seems to be an effective alternative for the construction of hydraulic models for flood studies.

Understanding the groundwater storage and release (S-Q) process and its contribution to river flows is essential for different hydrological applications, especially in periods of water scarcity. The S-Q process can be characterized based on recession parameter b, which is the slope of the power–law relationship −dQ/dt = aQb of the recession flow analysis, where recession parameter b represents the linearity of the S-Q process. In various studies, it has been found that this parameter can present high variability, which has been associated with the approach or spatial variability of basin characteristics. However, the variability of parameter b and its relationship with geology and the behavior of groundwater storage over time (evolution over time) have not been sufficiently studied. The objective of this study is to analyze the variability of recession parameter b and its relationship with geological and morphological characteristics and climate variability at different time scales. To this end, 72 drainage basins located in south central Chile were examined via recession flow analysis, considering five different time scales (5 years, 10 years, 15 years, 20 years, and 25 years). In addition, to analyze spatial variability patterns and generate groups of basins with similar characteristics, a cluster analysis was carried out. Clusters were obtained using the principal component analysis (PCA) and K-means methods. The results show that in wet periods, the slope of recession parameter b tends to increase (fast drainage process), while in dry periods, the recession slope tends to decrease (slow drainage processes). In general, the results suggest that the variability of recession coefficient b indicates changes in S-Q behavior; therefore, it could be used as an indicator of the sensitivity of a basin to climate variability.

Due to population growth and expansion in the agricultural and industrial sectors, the demand for water has increased. However, water availability in some regions has decreased due to climate change trends and variability, necessitating innovative strategies and adaptation in water allocation to avoid conflicts among users in a hydrological system. This paper presents a resilience analysis and a conceptual hydrological modeling approach to evaluate the resilience capacity of a new water allocation rule in the Laja Lake basin in southern Chile. Resilience assessments included absorptive and adaptive capacities with four system states: resilient, susceptible, resistant, and vulnerable. A modeling approach was used considering the climate variability uncertainty and climate change trends of the Laja system. Characterization of adaptive and absorptive capacities showed that the Laja Lake basin moved from resistant to vulnerable. Hydrological modeling analyses showed that after a new water allocation agreement, the Laja Lake system is moving from vulnerable to susceptible, since the new rule has more adaptive alternatives to face climate variability. The new rule diminishes the possibilities of conflicts among users, ensuring the fulfillment of water needs for uses such as farming and ecosystem services such as landscaping, and allows for increased water allocation for energy in wet hydrological years.

Time-varying sensitivity analysis (TVSA) allows sensitivity in a moving window to be estimated and the time periods in which the specific components of a model can affect its performance to be identified. However, one of the disadvantages of TVSA is its high computational cost, as it estimates sensitivity in a moving window within an analyzed series, performing a series of repetitive calculations. In this article a function to implement a simple TVSA with a low computational cost using regional sensitivity analysis is presented. As an example of its application, an analysis of hydrological model results in daily, monthly, and annual time windows is carried out. The results show that the model allows the time sensitivity of a model with respect to its parameters to be detected, making it a suitable tool for the assessment of temporal variability of processes in models that include time series analysis. In addition, it is observed that the size of the moving window can influence the estimated sensitivity; therefore, analysis of different time windows is recommended.

Precipitation is the main input in the water balance of watersheds; therefore, correct estimates are necessary for water resources management and decision making. In south-central Chile there is a low density of precipitation gauges (~1 station/675 km2), most of which are located in low-altitude areas. The spatial distribution of precipitation is, therefore, not properly recorded. In this study an inverse modeling approach is used to estimate the extent to which precipitation amounts must be corrected. Using a lumped water balance model, a factor for correcting precipitation data is calculated for 41 watersheds located in south-central Chile. Then, based on a geo-statistical interpolation, a map for correcting the precipitation amounts is proposed and a validation of these corrections is achieved. The results show that in gently sloping areas, the precipitation records are more representative than in steep mountain areas. In addition, the higher the mountains, the less representative the precipitation records become.

The study aims to evaluate the applicability of the slurry-TXRF method for estimating background contents and ecological indices in a rapid and convenient way. For this reason, the agricultural soils of the Itata Valley were used as a case study, where 48 soil samples were collected and analyzed. This rapid, minimally sample-intensive, and simultaneous multi-element quantification technique presented high accuracy but lower precision (approx. 20% RSD) compared to the classic total reflection X-ray fluorescence and flame/graphite furnace atomic absorption spectrometry methods, which require sample digestion. Due to the analytical characteristics of Slurry-TXRF, it can be concluded that the lower precision is likely compensated for, and this method represents a valuable alternative for the rapid and efficient assessment of trace element contamination in agricultural soils. The regional median concentrations of Cr, Ni, Cu, Zn, and Cd in the Itata Valley surface soils were found to be 63.7, 9.57, 31.0, 41.1, and 0.56 mg kg−1, respectively, with corresponding upper limits of 47.6, 6.82, 17.0, 30.7, and 0.284 mg kg−1. The ecological indices, including the geoaccumulation index, contamination factor, enrichment factor, and degree of contamination, suggest moderate levels of contamination in the region.

Choosing a model that suitably represents the characteristics of a watershed to simulate low flows is crucial, especially in watersheds whose main source of baseflow generation depends on groundwater storage and release. The goal of this investigation is to study the performance and representativeness of storage-release process modeling, considering aspects such as the topography and geology of the modeled watershed through regional sensitivity analysis, in order to improve low-flow prediction. To this end, four groundwater storage-release structures in various watersheds with different geological (fractured and sedimentary rock) and topographic domains (steep and gentle slopes) were analyzed. The results suggest that the two-reservoir structure with three runoff responses is suitable (better) for simulating low flows in watersheds with fractured geological characteristics and rugged or steep topography. The results also indicate that a one-reservoir model can be adequate for predicting low flows in watersheds with a sedimentary influence or flat topography.

Three models for estimating the daily reference evapotranspiration ETo are evaluated in the agricultural zone of Chillán, Chile: Penman-Monteith FAO PMF, Prietsley-Taylor PT and Hargreaves-Samani HS. The daily ETo values estimated through these methodologies are compared with the daily values of ETo estimated from pan evaporation ETB data series obtainedfrom meteorological stations of the Universidad de Concepción Campus Chillán and INIA Quilamapu, both located within Chillán ’s city limits. The comparison and analysis were performed with data covering a span of 13 years (1996 - 2008). Results indicate that the HS method systemically underestimates ETo values, particularly during dry periods. Moreover, differences between the three methods quantified with Root Mean Squared Error RMSE and Relative Differences RD computed for different time periods (1, 3, 7 and 30 days) suggest that the PT method fits better the observations, being more adequate for the agricultural area of Chillán - weekly averages yield RMSE of 1.01 mm/day and RD of 32.8%.