Reference evapotranspiration (ET₀) is the first step in calculating crop irrigation demand, and numerous methods have been proposed to estimate this parameter. FAO-56 Penman–Monteith (PM) is the only standard method for defining and calculating ET₀. However, it requires radiation, air temperature, atmospheric humidity, and wind speed data, limiting its application in regions where these data are unavailable; therefore, new alternatives are required. This study compared the accuracy of ET₀ calculated with the Blaney–Criddle (BC) and Hargreaves–Samani (HS) methods versus PM using information from an automated weather station (AWS) and the NASA-POWER platform (NP) for different periods. The information collected corresponds to Module XII of the Lagunera Region Irrigation District 017, a semi-arid region in the North of Mexico. The HS method underestimated the reference evapotranspiration (ET₀) by 5.5% compared to the PM method considering the total ET₀ of the study period (26 February to 9 August 2021) and yielded the best fit in the different evaluation periods (daily, 5-day mean, and 5-day cumulative); the latter showed the best values of inferential parameters. The information about maximum and minimum temperatures from the NP platform was suitable for estimating ET₀ using the HS equation. This data source is a suitable alternative, particularly in semi-arid regions with limited climatological data from weather stations.

Assessing the impact of climate change is essential for developing water resource management plans, especially in areas facing severe issues regarding ecosystem service degradation. This study assessed the effects of climate change on the hydrological balance using the SWAT (Soil and Water Assessment Tool) hydrological model in the Mixteco River Basin (MRB), Oaxaca, Mexico. Temperature and precipitation were predicted with the projections of global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6); the bias was corrected using CMhyd software, and then the best performing GCM was selected for use in the SWAT model. According to the GCM MPI-ESM1-2-LR, precipitation might decrease by between 83.71 mm and 225.83 mm, while temperature might increase by between 2.57 °C and 4.77 °C, causing a greater atmospheric evaporation demand that might modify the hydrological balance of the MRB. Water yield might decrease by 47.40% and 61.01% under the climate scenarios SP245 and SSP585, respectively. Therefore, adaptation and mitigation measures are needed to offset the adverse impact of climate change in the MRB.

La eficiencia del uso de nitrógeno en la agricultura es muy baja, provocando problemas ambientales y baja productividad de los cultivos, por lo que conocer la distribución espacial y temporal de variables biofísicas que estimen su crecimiento, como la fracción de cobertura vegetal (FCV), y el contenido de nitrógeno del dosel (CND) aportará información valiosa para mejorar esta condición. El uso de imágenes satelitales de libre acceso, como las imágenes del satélite Sentinel-2 (S‑2), puede facilitar esta tarea. Con base en lo anterior, se realizó un estudio en seis parcelas de maíz, cultivadas por productores de la zona de Texcoco de Mora, Estado de México, cuyo primer objetivo fue investigar la relación entre índices espectrales, estimados a partir de la reflectancia, medida con un radiómetro multiespectral a nivel de superficie y de imágenes S-2; con la FCV, estimada mediante fotografías digitales a través de la aplicación para celulares Canopeo. El segundo objetivo fue obtener un modelo lineal para estimar el CND a partir del análisis de diferentes índices espectrales. Se generaron dos modelos para estimar la FCV, a partir de la información radiométrica a nivel de superficie, la validación de estos arrojó un valor alto de R2 = 0.92 y un CME = 7.3% entre datos de FCV medidos y estimados; sin embargo, en el caso de los datos estimados con imágenes S-2 se obtuvieron valores más bajos de R2 = 0.67 y CME = 17.6%, lo cual se atribuyó a un posible efecto de la atmósfera, ya que el periodo de estudio coincidió con la temporada de lluvias. Finalmente, en el caso del CND, los mejores resultados se obtuvieron con el modelo generado a partir del ClGreen, con el cual se obtuvo un R2 de 0.91 y un CME de 0.63 g m-2, al comparar el CND medido con relación al estimado.

The Mixteco River basin is located in the state of Oaxaca, Mexico and comprises a total area of 6 559.20 km2, which shows a strong degradation of its natural resources, derived mainly from anthropic actions associated with poor management of its natural resources. Thus, the goal of this research is to evaluate the runof f behavior with the SWAT (Soil and Water Assessment Tool) model in the Mixteco River basin using the soil spatial distribution from INEGI (Instituto Nacional de Estadística y Geografía) and that obtained through technique of DSM (Digital Soil Mapping) technique. The modeling with INEGI (ModINEGI) corresponds to the soil map of the series II scale 1:250 000, and the modeling with DSM (ModDSM) was obtained from the environmental covariates. The SWAT model performance evaluation indicators during the calibration phase were R2 = 0.88 and NSE = 0.87 for ModDSM and R2 = 0.85 and NSE = 0.85 for ModINEGI. However, during the validation period, the ModDSM results (R2 = 0.83 and NSE = 0.81) were better than those of ModINEGI (R2 = 0.83 and NSE = 0.61). Therefore, the results indicate that the spatial variation of the soil types obtained through the DSM technique in combination with the vegetation cover and the distribution of slopes at the basin level, allow the SWAT model to simulate the adequate surface runof f behavior.

Reference evapotranspiration (ET0) is the first step in calculating crop irrigation demand, and numerous methods have been proposed to estimate this parameter. FAO-56 Penman-Monteith (PM) is the only standard method for defining and calculating ET0. However, it requires radiation, air temperature, atmospheric humidity, and wind speed data, limiting its application in regions where these data are unavailable; therefore, new alternatives are required. This study compared the accuracy of ET0 calculated with the Blaney-Criddle (BC) and Hargreaves-Samani (HS) methods versus PM using information from an automated weather station (AWS) and the NASA-POWER platform (NP) for different periods of time. The information collected corresponding at Module XII of the Lagunera Region Irrigation District 017, a semi-arid region in the North of Mexico. The HS method underestimated by 5.5 % the reference evapotranspiration (ET0) compared to the PM method during the period from March to August, and yielded the best fit in the different evaluation periods: daily, average, and 5-day cumulative; the latter showed the best values of inferential parameters. The information about maximum and minimum temperatures from the NP platform was suitable for estimating ET0 using the HS equation. This data source is a timely alternative, particularly in semi-arid regions where no data from weather stations are available.