Dr. Carlos Bautista-Capetillo

Science and Technology of Water, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

Guest Editor for a Special Issue on decision-relevant hydroc...

Dr. Carlos Bautista-Capetillo

Science and Technology of Water, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

Guest Editor for a Special Issue on decision-relevant hydroc...

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Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2011 in Landscape and Urban Planning

Journal Article

Irrigation performance in private urban landscapes: A study case in Zaragoza (Spain)

Raquel Salvador

Carlos Bautista-Capetillo

Enrique Playán

17 February 2009 in Irrigation Science

Journal Article

A photographic method for drop characterization in agricultural sprinklers

Raquel Salvador

Carlos Bautista-Capetillo

Javier Burguete

Nery Zapata

A. Serreta

Enrique Playán

3 March 2020 in Sustainability

Journal Article

Spatio-Temporal Response of Vegetation Indices to Rainfall and Temperature in A Semiarid Region

Edith Olmos Trujillo

Julián González-Trinidad

Hugo Júnez Ferreira

Anuard Pacheco-Guerrero

Carlos Bautista-Capetillo

Carlos Eric Galván-Tejada

In this research, vegetation indices (VIs) were analyzed as indicators of the spatio-temporal variation of vegetation in a semi-arid region. For a better understanding of this dynamic, interactions between vegetation and climate should be studied more widely. To this end, the following methodology was proposed: (1) acquire the NDVI, EVI, SAVI, MSAVI, and NDMI by classification of vegetation and land cover categories in a monthly period from 2014 to 2018; (2) perform a geostatistical analysis of rainfall and temperature; and (3) assess the application of ordinary and uncertainty least squares linear regression models to experimental data from the response of vegetation indices to climatic variables through the BiDASys (bivariate data analysis system) program. The proposed methodology was tested in a semi-arid region of Zacatecas, Mexico. It was found that besides the high values in the indices that indicate good health, the climatic variables that have an impact on the study area should be considered given the close relationship with the vegetation. A better correlation of the NDMI and EVI with rainfall and temperature was found, and similarly, the relationship between VIs and climatic factors showed a general time lag effect. This methodology can be considered in management and conservation plans of natural ecosystems, in the context of climate change and sustainable development policies.

2 August 2017 in Water

Journal Article

Identifying Groundwater Recharge Sites through Environmental Stable Isotopes in an Alluvial Aquifer

Julián González-Trinidad

Anuard Pacheco-Guerrero

Hugo Júnez Ferreira

Carlos Bautista-Capetillo

Arturo Hernández-Antonio

Environmental isotope tracers have been a useful tool in providing new insights into hydrologic processes. In Mexico, there have been several studies reporting different values for

δ^{18} O

and

δ^{2} H

for certain geographical areas. The objective of this study is to achieve the isotopic characterization of rainfall and groundwater and to report the comprehensive understanding of groundwater flow processes around and within the Calera aquifer and, consequently, its potential recharge sites. The samples used for the stable isotope analysis (

δ^{18} O, δ^{2} H

) were measured using a GV-Isoprime isotope-ratio mass spectrometer at the Isotopy Laboratory of the Water Center for Latin America and the Caribbean. The

δ D

of precipitation ranged between −110.20‰ and 10.11‰, with a mean of −55.67‰

\pm

27.81‰. The

δ^{18} O

ranged between −17.80‰ and 2.74‰, with a mean of −9.44‰

\pm

4.74‰. The

δ D

of groundwater ranged between −81.92‰ and −36.45‰, with a mean of −66.05‰

\pm

8.58‰. The

δ^{18} O

ranged between −18.26‰ and −8.84‰, with a mean of −12.35‰

\pm

2.12‰. The local meteoric water line of the Zacatecas state is

δ D = - 2.03 + 5.68 δ^{18} O

. The groundwater samples were clustered into four groups. The clustering of the samples led to the finding that streamflows play a significant role in the hydrological balance as a source of local recharge to the aquifer.

30 July 2022 in Water

Journal Article

Effects of the Digital Elevation Model and Hydrological Processing Algorithms on the Geomorphological Parameterization

Sandra Dávila-Hernández

Julián González-Trinidad

Hugo Júnez Ferreira

Carlos Bautista-Capetillo

HÁ

Heriberto Morales De Ávila

Enrique Alejandro Lopez Baltazar

Hydrological cycle research requires a detailed analysis of the involved parameters to understand watershed behavior comprehensively. In recent decades, both Geographic Information Systems (GIS) and Digital Elevation Models (DEMs) were implemented and took a substantial role in watershed geomorphological parameterization; however, the variability of these instruments remains a challenge, together with high-resolution DEMs being unavailable, requiring digital processing to improve resolution. This research aims to merge DEMs and evaluate GIS geoprocessing algorithms to determine drainage networks and the geomorphological parametrization of a semiarid watershed. DEMs with resolutions of 1.5, 5, 12.5, and 30 m, the Jenson/Domingue (J/D) and Wang/Liu (W/L) fill algorithms; and D8, D, KRA, and MFD flow routing algorithms were used. One of the research findings proved that the divergences of the drainage networks are mainly attributed to filling algorithms and not flow routing algorithms; the shifts between the networks obtained in the processes reach horizontal distances up to 300 m. Since the water movement within the watershed depends on geomorphological characteristics, it is suggested that DEM-based hydrological studies specify both the resolution and the algorithms used in the parametrization to validate the rigidity of the research, improving estimate areas of high hydrological risk.

15 June 2022 in Applied Sciences

Journal Article

Convolutional Neural Network for Measurement of Suspended Solids and Turbidity

Daniela Lopez-Betancur

Ivan Moreno

Carlos Guerrero-Mendez

Tonatiuh Saucedo Anaya

Efrén González-Ramírez

Julián González-Trinidad

The great potential of the convolutional neural networks (CNNs) provides novel and alternative ways to monitor important parameters with high accuracy. In this study, we developed a soft sensor model for dynamic processes based on a CNN for the measurement of suspended solids and turbidity from a single image of the liquid sample to be measured by using a commercial smartphone camera (Android or IOS system) and light-emitting diode (LED) illumination. For this, an image dataset of liquid samples illuminated with white, red, green, and blue LED light was taken and used to train a CNN and fit a multiple linear regression (MLR) by using different color lighting, we evaluated which color gives more accurate information about the concentration of suspended particles in the sample. We implemented a pre-trained AlexNet model, and an MLR to estimate total suspended solids (TSS), and turbidity values in liquid samples based on suspended particles. The proposed technique obtained high goodness of fit (

R^{2}

= 0.99). The best performance was achieved using white light, with an accuracy of 98.24% and 97.20% for TSS and turbidity, respectively, with an operational range of 0–800

{mgL}^{- 1}

, and 0–306 NTU. This system was designed for aquaculture environments and tested with both commercial fish feed and paprika. This motivates further research with different aquatic environments such as river water, domestic and industrial wastewater, and potable water, among others.

About Me

Professor and researcher at the Autonomous University of Zacatecas (Mexico), he has built an academic career that integrates higher education teaching, research, editorial service, and university leadership in the fields of water resources and agricultural water management. His work is grounded in civil and hydraulic engineering perspectives while maintaining a strong interest in how technical solutions can be translated into practical improvements for irrigated agriculture, especially in water-limited, semi-arid environments, where efficiency gains can have clear implications for productivity, resilience, and long-term sustainability. He has taught at the undergraduate, master’s, and doctoral levels, contributing to the formation of engineers and researchers working on water and environmental challenges. His teaching portfolio spans foundational and applied areas that commonly define training in water engineering and hydroclimatology, including Hydraulics, Surface Hydrology, Design and Operation of Hydraulic Infrastructure, Soil–Plant–Atmosphere Water Relations, Meteorology, and Climatology. Alongside this teaching activity, he has supervised more than 70 theses across different degree levels, guiding students through research problems that connect theory, field data, and engineering decision-making. This sustained supervision reflects a long-term commitment to research training and to the development of new professional and scientific capacities in water-related disciplines

Dr. Carlos Bautista-Capetillo

Dr. Carlos Bautista-Capetillo

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