RIVERA SALAZAR, DIEGO ANDRÉS
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RIVERA SALAZAR, DIEGO ANDRÉS
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diegorivera@udd.cl
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25822747600

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Generation of soil maps permeability. Case study in two cantons of Loja province, Ecuador

2023 , Jorge Andrés Espinosa Marín , RIVERA SALAZAR, DIEGO ANDRÉS , Renato Haro Prado

The generation of permeability maps is based on the analysis and interpretation of geology, environmental morphology, land use, and slope, which enables the selection of sampling areas with similar characteristics. The method represents the integration of the physical characteristics of the study area and then determines the infiltration capacity differences in the most representative geopedologic units. In determining the basic data, minidisc infiltrometers were used to perform seventy-two infiltration tests in different types of soils with varying organic matter content, texture, soil structure, and vegetation cover, which showed the spatial variability that exists in two cantons of Loja province, Ecuador. In addition, it was observed that the infiltration rate depended mainly on the content of the organic matter in the soil and is consistent with information collected on permeability worldwide. In this study, generated pedotransfer function (FTP) coefficient of determination R2 0.78, the determination of the coefficient indicates a satisfactory estimate of the permeability with the variables that were analyzed; in addition, the methodology for assessing the permeability was suitable for the conditions of this investigation. For this reason, the method described here should be tested in other areas of the country with a greater number of field trials and with more variable contents of organic matter and soil textural classes.

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Force Measurement with a Strain Gauge Subjected to Pure Bending in the Fluid–Wall Interaction of Open Water Channels

2022 , Luis Santana , RIVERA SALAZAR, DIEGO ANDRÉS , Eric Forcael

An experimental method to measure forces of small magnitude with a strain gauge as a force sensor in the fluid–wall interaction of open water channels is presented. Six uniaxial strain gauges were employed for this purpose, which were embedded across the entire sensing area and subjected to pure bending, employing two-point bending tests. Sixteen two-point bending tests were performed to determine the existence of a direct relationship between the load and the instrument signal. Furthermore, a regression analysis was used to estimate the parameters of the model. A data acquisition system was developed to register the behavior of the strain gauge relative to the lateral displacement induced by the loading nose of the universal testing machine. The results showed a significant linear relationship between the load and the instrumental signal, provided that the strain gauge was embedded between 30% and 45% of the central axis in the sensing area of the sensor (R2 > 0.99). Thus, the proposed sensor can be employed to measure forces of small magnitude. Additionally, the linear relationship between the load and the instrumental signal can be used as a calibration equation, provided that the strain gauge is embedded close to the central axis of the sensing area.

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A satellite-based ex post analysis of water management in a blueberry orchard

2020 , Eduardo Holzapfel , Mario Lillo-Saavedra , RIVERA SALAZAR, DIEGO ANDRÉS , Viviana Gavilán , Angel García-Pedrero , Consuelo Gonzalo-Martín

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Corrigendum to “Forest Hydrology in Chile; paste, present, and future” [J. Hydrol. 616 (2023)]

2023 , Francisco Balocchi , Mauricio Galleguillos , RIVERA SALAZAR, DIEGO ANDRÉS , Alejandra Stehr , Jose Luis Arumi , Roberto Pizarro , Pablo Garcia-Chevesich , Andrés Iroumé , Juan J. Armesto , Pedro Hervé-Fernández , Carlos Oyarzún , Pilar Barria , Christian Little , Gabriel Mancilla , Santiago Yépez , Rolando Rodriguez , Don A. White , Richard P. Silberstein , Daniel G. Neary , Pablo Ramírez de Arellano

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Effects of the number of drip laterals on yield and quality of apples grown in two soil types

2021 , F. Lecaros-Arellano , E. Holzapfel , E. Fereres , RIVERA SALAZAR, DIEGO ANDRÉS , N. Muñoz , J. Jara

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Neutral Sugar Content and Composition as a Sensitive Indicator of Fire Severity in the Andisols of an Araucaria–Nothofagus Forest in Southern Chile

2021 , Yessica Rivas , Jorge Retamal-Salgado , Heike Knicker , Francisco Matus , RIVERA SALAZAR, DIEGO ANDRÉS

Wildfire induces soil alterations that have a long-term impact on soil organic matter (SOM) quality. We postulated that after different fire severities, the neutral sugars in soils can be used as an indicator of soil organic matter quality after fire. The aim of this study was to determine the contribution of neutral sugar, bulk and occluded particulate organic matter (oPOM) affected by wildfire, at different soil depths in an Araucaria–Nothofagus Forest, four years post-after fire. The concentration and composition of the neutral sugars in the soils clearly comprised the major fraction in the unburned soil. Medium- and high-severity fires caused a drastic reduction in soil sugars in the bulk soil as well as in the oPOM fractions. The 13C-CPMAS NMR spectroscopy analysis revealed a high contribution of recalcitrant carbon to the decomposition such as aryl–C and aryl–O derived from charred material, whereas the abundance of O–alkyl C and alkyl C functional groups were decreased. The neutral sugars (Galactose+Mannose/Xilose+Arabinose) revealed a major microbial origin in fire affected areas as the ratio was >2. Therefore. Therefore, we suggest that the neutral sugar content of soil should be used for monitoring both short- and long-term changes in SOM altered by fires.

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Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS

2020 , Mathias Kuschel-Otárola , Niels Schütze , Eduardo Holzapfel , GODOY FAUNDEZ, ALEX ORIEL , Oleksandr Mialyk , RIVERA SALAZAR, DIEGO ANDRÉS

We propose a methodology to estimate the yield response factor (i.e., the slope of the water-yield function) under local conditions for a given crop, weather, sowing date, and management at each growth stage using AquaCrop-OS. The methodology was applied to three crops (maize, sugar beet, and wheat) and four soil types (clay loam, loam, silty clay loam, and silty loam), considering three levels of bulk density: low, medium, and high. Yields are estimated for different weather and management scenarios using a problem-specific algorithm for optimal irrigation scheduling with limited water supply (GET-OPTIS). Our results show a good agreement between benchmarking (mathematical approach) and benchmark (estimated by AquaCrop-OS) using the Normalised Root Mean Square Error (NRMSE), allowing us to estimate reliable yield response factors ( K y ) under local conditions and to dispose of the typical simple mathematical approach, which estimates the yield reduction as a result of water scarcity at each growth stage.

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Simulation of Water-Use Efficiency of Crops under Different Irrigation Strategies

2020 , Mathias Kuschel-Otárola , RIVERA SALAZAR, DIEGO ANDRÉS , Eduardo Holzapfel , Niels Schütze , Patricio Neumann , GODOY FAUNDEZ, ALEX ORIEL

Irrigation management is a key factor in attaining optimal yields, as different irrigation strategies lead to different yields even when using the same amount of water or under the same weather conditions. Our research aimed to simulate the water-use efficiency (WUE) of crops considering different irrigation strategies in the Central Valley of Chile. By means of AquaCrop-OS, we simulated expected yields for combinations of crops (maize, sugar beet, wheat), soil (clay loam, loam, silty clay loam, and silty loam), and bulk density. Thus, we tested four watering strategies: rainfed, soil moisture-based irrigation, irrigation with a fixed interval every 1, 3, 5, and 7 days, and an algorithm for optimal irrigation scheduling under water supply constraints (GET-OPTIS). The results showed that an efficient irrigation strategy must account for soil and crop characteristics. Among the tested strategies, GET-OPTIS led to the best performance for crop yield, water use, water-use efficiency, and profit, followed by the soil moisture-based strategy. Thus, soil type has an important influence on the yield and performance of different irrigation strategies, as it provides a significant storage and buffer for plants, making it possible to produce “more crop per drop”. This work can serve as a methodological guide for simulating the water-use efficiency of crops and can be used alongside evidence from the field.

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Comparing Methods for the Regionalization of Intensity−Duration−Frequency (IDF) Curve Parameters in Sparsely-Gauged and Ungauged Areas of Central Chile

2023 , Claudia Sangüesa , Roberto Pizarro , Ben Ingram , Alfredo Ibáñez , RIVERA SALAZAR, DIEGO ANDRÉS , Pablo García-Chevesich , Juan Pino , Felipe Pérez , Francisco Balocchi , Francisco Peña

Estimating intensity−duration−frequency (IDF) curves requires local historical information of precipitation intensity. When such information is unavailable, as in areas without rain gauges, it is necessary to consider other methods to estimate curve parameters. In this study, three methods were explored to estimate IDF curves in ungauged areas: Kriging (KG), Inverse Distance Weighting (IDW), and Storm Index (SI). To test the viability of these methods, historical data collected from 31 rain gauges distributed in central Chile, 35° S to 38° S, are used. As a result of the reduced number of rain gauges to evaluate the performance of each method, we used LOOCV (Leaving One Out Cross Validation). The results indicate that KG was limited due to the sparse distribution of rain gauges in central Chile. SI (a linear scaling method) showed the smallest prediction error in all of the ungauged locations, and outperformed both KG and IDW. However, the SI method does not provide estimates of uncertainty, as is possible with KG. The simplicity of SI renders it a viable method for extrapolating IDF curves to locations without data in the central zone of Chile.

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Early Estimation of Tomato Yield by Decision Tree Ensembles

2022 , Mario Lillo-Saavedra , Alberto Espinoza-Salgado , Angel García-Pedrero , Camilo Souto , Eduardo Holzapfel , Consuelo Gonzalo-Martín , Marcelo Somos-Valenzuela , RIVERA SALAZAR, DIEGO ANDRÉS

Crop yield forecasting allows farmers to make decisions in advance to improve farm management and logistics during and after harvest. In this sense, crop yield potential maps are an asset for farmers making decisions about farm management and planning. Although scientific efforts have been made to determine crop yields from in situ information and through remote sensing, most studies are limited to evaluating data from a single date just before harvest. This has a direct negative impact on the quality and predictability of these estimates, especially for logistics. This study proposes a methodology for the early prediction of tomato yield using decision tree ensembles, vegetation spectral indices, and shape factors from images captured by multispectral sensors on board an unmanned aerial vehicle (UAV) during different phenological stages of crop development. With the predictive model developed and based on the collection of training characteristics for 6 weeks before harvest, the tomato yield was estimated for a 0.4 ha plot, obtaining an error rate of 9.28%.

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