Ecohydrological assessment of the water balance of the world's highest elevation tropical forest (Polylepis).

Polylepis trees grow at elevations above the continuous tree line (3000-5000 m a.s.l.) across the Andes. They tolerate extreme environmental conditions, making them sensitive bioindicators of global climate change. Therefore, investigating their ecohydrological role is key to understanding how the water cycle of Andean headwaters could be affected by predicted changes in environmental conditions, as well as ongoing Polylepis reforestation initiatives in the region. We estimate, for the first time, the annual water balance of a mature Polylepis forest (Polylepis reticulata) catchment (3780 m a.s.l.) located in the south Ecuadorian páramo using a unique set of field ecohydrological measurements including gross rainfall, throughfall, streamflow, and xylem sap flow in combination with the characterization of forest and soil features. We also compare the forest water balance with that of a tussock grass (Calamagrostis intermedia) catchment, the dominant páramo vegetation. Annual gross rainfall during the study period (April 2019-March 2020) was 1290.6 mm yr-1. Throughfall in the Polylepis forest represented 61.2 % of annual gross rainfall. Streamflow was the main component of the water balance of the forested site (59.6 %), while its change in soil water storage was negligible (<1 %). Forest evapotranspiration was 54.0 %, with evaporation from canopy interception (38.8 %) more than twice as high as transpiration (15.1 %). The error in the annual water balance of the Polylepis catchment was small (<15 %), providing confidence in the measurements and assumptions used to estimate its components. In comparison, streamflow and evapotranspiration at the grassland site accounted for 63.7 and 36.0 % of the water balance, respectively. Although evapotranspiration was larger in the forest catchment, its water yield was only marginally reduced (<4 %) in relation to the grassland catchment. The substantially higher soil organic matter content in the forest site (47.6 %) compared to the grassland site (31.8 %) suggests that even though Polylepis forests do not impair the hydrological function of high-Andean catchments, their presence contributes to carbon storage in the litter layer of the forest and the underlying soil. These findings provide key insights into the vegetation-water­carbon nexus in high Andean ecosystems, which can serve as a basis for future ecohydrological studies and improved management of páramo natural resources considering changes in land use and global climate.

Assessment of satellite-based water requirements for a drip-irrigated apple orchard in Mediterranean agroclimatic conditions.

Accurate assessment of evapotranspiration (ETa) and crop coefficient (Kc) is crucial for optimizing irrigation practices in water-scarce regions. While satellite-based surface energy balance models offer a promising solution, their application to sparse canopies like apple orchards requires specific validation. This study investigated the spatial and temporal dynamics of ETa and Kc in a drip-irrigated 'Pink Lady' apple orchard under Mediterranean conditions over three growing seasons (2012/13, 2013/14, 2014/15). The METRIC model, incorporating calibrated sub-models for leaf area index (LAI), surface roughness (Zom), and soil heat flux (G), was employed to estimate ETa and Kc. These estimates were validated against field-scale Eddy Covariance data. Results indicated that METRIC overpredicted Kc and ETa with errors less than 10 %. These findings highlight the potential of the calibrated METRIC model as a valuable decision-making tool for irrigation management in apple orchards.

The banana tree circle as a nature-based solution for sustainable greywater management: A new design model.

The banana tree circle (BTC) is a low-cost system for local greywater management, using a natural treatment and disposal process, providing additional resource recovery benefits. However, there are no standard design criteria for BTC that would allow for quality control of its efficiency and sustainability, and little is currently known about the full-scale performance of BTC. Based on the scoping literature review of 31 documents in the scientific database and eight documents from grey literature, a standard design model was proposed for the BTC technology based on the concept of water balance, greywater flows, rain, infiltration, and evapotranspiration. The first two steps of the BTC design were determining the areas required for infiltration and evapotranspiration. A cylindrical form trench, the soil percolation rate, and the hydraulic loading rate were considered for the infiltration area. The banana trees' evapotranspiration rate was taken into consideration for the evapotranspiration area. The proposed model was applied in a case study where we used a trench with 0.8 m depth and 1.5 m diameter. This study proposes a standard design criterion for the BTC based on environmental factors, and the scoping of the literature provides the basis for future studies to evaluate its environmental sustainability.

Multi-datasets to monitor and assess meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region.

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes.

Agricultural drought assessment in dry zones of Tolima, Colombia, using an approach based on water balance and vegetation water stress.

Soil water balance is an essential element to consider for the management of droughts and agricultural land use. It is important to evaluate the water consumption of a crop in each of its phenological phases and the status of water reserves during critical hydrologic periods. This study developed an agricultural drought index (Standardized Soil Moisture Deficit Index - SMODI) conceptualized with a water balance model considering the vegetation stress caused by soil moisture deficit. This contribution was based on meteorological information, soil moisture from satellite images, hydrophysical properties of the soil and crop evapotranspiration. Information from 61 weather stations located in the dry zone of Tolima was used for estimating the water balance. SMODI was compared with the most common drought indexes: Standardized Precipitation - Evapotranspiration Index (SPEI), the Palmer Self-Calibrated Drought Index (scPDSI), and other eleven macroclimatic indexes. Pearson's correlation coefficients (r), Tukey's test, and analysis of variance were applied to analyze the degree of association between SMODI and the contrasting indexes on a quarterly basis. SMODI considers factors influencing soil moisture distribution and retention and the water stress thresholds that plants have evolved to withstand during drought periods. Consequently, this integrated approach enhances the assessment of agricultural drought by relying on pertinent physical processes. SMODI identified extremely dry, severe, moderate and normal drought 5 %, 3 %, 20 % and 72 % respectively conditions in areas characterized by Entisols, Inceptisols, and Andisols, where rice and fruit crops and pasturelands are cultivated. The SMODI has a good correlation with macroclimatic indexes (0.70 < r < 0.74).

ENSO effects on the relationship between aerosols and evapotranspiration in the south of the Amazon biome.

The effects of the El Nino-Southern Oscillation (ENSO) events have local, regional, and global consequences for water regimes, causing floods or extreme drought events. Tropical forests are strongly affected by ENSO, and in the case of the Amazon, its territorial extension allows for a wide variation of these effects. The prolongation of drought events in the Amazon basin contributes to an increase in gas and aerosol particle emissions mainly caused by biomass burning, which in turn alter radiative fluxes and evapotranspiration rates, cyclically interfering with the hydrological regime. The ENSO effects on the interactions between aerosol particles and evapotranspiration is a critical aspect to be systematically investigated. Therefore, this study aimed to evaluate the ENSO effect on a site located on the southern portion of the Amazonian region. In addition to quantifying and testing possible differences between aerosols and evapotranspiration under different ENSO classes (El Niño, La Niña and Neutrality), this study also evaluated possible variations in evapotranspiration as a function of the aerosol load. A highly significant difference was found for air temperature, relative humidity and aerosol load between the El Niño and La Niña classes. For evapotranspiration, significant differences were found for the El Niño and La Niña classes and for El Niño and Neutrality classes. Under the Neutrality class, the aerosol load correlated significantly with evapotranspiration, explaining 20% of the phenomenon. Under the El Niño and La Niña classes, no significant linear correlation was found between aerosol load and evapotranspiration. However, the results showed that for the total data set, there is a positive and significant correlation between aerosol and evapotranspiration. It increases with a quadratic fit, i.e., the aerosol favors evapotranspiration rates up to a certain concentration threshold. The results obtained in this study can help to understand the effects of ENSO events on atmospheric conditions in the southern Amazon basin, in addition to elucidating the role of aerosols in feedback to the water cycle in the region.

Climate risk zoning for wheat crops in the southeastern region of Brazil.

BACKGROUND: Wheat (Triticum aestivum L.) is the second most consumed food in the world. One way to meet this demand is the expansion of wheat cultivation to the Brazilian Cerrado in the southeastern region. However, one of the major limitations is that there are few studies related to wheat climate risk zoning. Thus, this study aimed to determine the agroclimatic zoning of wheat by estimating the water needs satisfaction index (ISNA) in the southeastern region of Brazil. For this purpose, a 60-year historical series of meteorological data was used to calculate the potential evapotranspiration, crop evapotranspiration, and climatological water balance values. To define the agroclimatic zones of wheat and sowing date, the ISNA method was used. The data were analyzed using descriptive statistics to determine the variations. To obtain the agroclimatic zoning of wheat, the geostatistical method of kriging interpolation was used. RESULTS: The regions with the highest rainfall are the south of Minas Gerais and the coast of São Paulo. The sowing period directly impacts the development of the crop, the available water capacity and the ISNA values indicated the spring and summer had better cultivation conditions, and the best window for wheat cultivation is concentrated in the fall due to the limitation of biotic factors. CONCLUSION: In terms of altitude (>700 m), Minas Gerais has 39.4% of the area suitable for wheat cultivation. Thus, climatic variations within and between the states of the southeastern region should be considered for the positioning of wheat cultivars in these regions to obtain the maximum yield. © 2023 Society of Chemical Industry.

Comparison, validation and improvement of empirical soil moisture models for conditions in Colombia.

Modeling soil moisture as a function of meteorological data is necessary for agricultural applications, including irrigation scheduling. In this study, empirical water balance models and empirical compartment models are assessed for estimating soil moisture, for three locations in Colombia. The daily precipitation and average, maximum and minimum air temperatures are the input variables. In the water balance type models, the evapotranspiration term is based on the Hargreaves model, whereas the runoff and percolation terms are functions of precipitation and soil moisture. The models are calibrated using field data from each location. The main contributions compared to closely related studies are: i) the proposal of three models, formulated by combining an empirical water balance model with modifications in the precipitation, runoff, percolation and evapotranspiration terms, using functions recently proposed in the current literature and incorporating new modifications to these terms; ii) the assessment of the effect of model parameters on the fitting quality and determination of the parameters with higher effects; iii) the comparison of the proposed empirical models with recent empirical models from the literature in terms of the combination of fitting accuracy and number of parameters through the Akaike Information Criterion (AIC), and also the Nash-Sutcliffe (NS) coefficient and the root mean square error. The best models described soil moisture with an NS efficiency higher than 0.8. No single model achieved the highest performance for the three locations.

Predicting rainfall and irrigation requirements of corn in Ecuador.

This work is a case study whose objective is prediction of irrigation needs of corn crops in different regions of Ecuador; being this a fundamental basic food for the country's economy, as in the remaining countries of the Andean area. The proposed methodology seeks to help improving the quality of corn crop. Specifically, we propose the application of regression models, within the framework of Functional Data Analysis (FDA), to predict the amount of rainfall (scalar response variable) in the places with the highest production of corn in Ecuador, as a function of functional covariates such as temperature and wind speed. From the estimation of the amount of rainfall, effective precipitation is calculated. This is the fraction of water used by the crops, from which the value of real evapotranspiration or ETc is obtained and, more importantly, the irrigation requirements at each stage of the corn crop, for its adequate physiological development. Application of regression models based on functional basis, Functional Principal Components (FPC) or Functional Partial Least Squares (FPLS) for scalar response variable, allows us to use the information of variables such as wind speed and temperature (of functional nature) in a better way than using multivariate models, for predicting the amount of rainfall, obtaining, as a result, very explicative models, defined by a high goodness of fit (R2=0.97, with 6 significant parameters and an error of 0.14) and practical utility. The model has been also applied to North Peru regions, obtaining rainfall prediction errors between 9% and 22%. Thus, the geographical limitations of the model could be the Andean regions with similar climate. In addition, this study proposes the application of FDA exploratory analysis and FDA outlier detection techniques as a common and useful practice in the specific domain of rainfall prediction studies, prior to applying the regression models.

Remote sensing environmental indicators for monitoring spatial and temporal dynamics of weather and vegetation conditions: applications for Brazilian biomes.

The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale remote sensing environmental indicators in Brazilian biomes. MODIS MOD13Q1 reflectance product and gridded weather data for the year 2016 were used to demonstrate the suitability of the algorithm to monitor the dynamics of environmental remote sensing indicators along a year in the Brazilian biomes, Amazon, Caatinga, Cerrado, Pantanal, Atlantic Forest, and Pampa. Significant spatial and temporal variations in precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P-ET) and water productivity (WP = ET/BIO). The highest WB and WP differences were detected in the wettest biomes, Amazon, Atlantic Forest, and Pampa, when compared with the driest biome, Caatinga. Rainfall distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e., the ET to reference evapotranspiration (ET0) ratio. However, there was a gap between ETf and WB, which may be related to the time needed for recovering good soil moisture conditions after rainfalls. For some biomes, BIO related most to the levels of absorbed photosynthetically active radiation (Amazon and Atlantic Forest), while for others, BIO followed most the soil moisture levels, depicted by ETf (Caatinga, Cerrado, Pantanal, and Pampa). The large-scale modeling showed suitability for monitoring the water and vegetation conditions, making way to detect anomalies for specific periods along the year by using historical images and weather data, with strong potential to support public policies for management and conservation of natural resources and with possibilities for replication of the methods in other countries.

Influence of management practices on water-related grain yield determinants.

Adequate management of N supply, plant density, row spacing, and soil cover has proved useful for increasing grain yields and/or grain yield stability of rainfed crops over the years. We review the impact of these management practices on grain yield water-related determinants: seasonal crop evapotranspiration (ET) and water use efficiency for grain production per unit of evapotranspired water during the growing season (WUEG,ET,s). We highlight a large number of conflicting results for the impact of management on ET and expose the complexity of the ET response to environmental factors. We analyse the influence of management practices on WUEG,ET,s in terms of the three main processes controlling it: (i) the proportion of transpiration in ET (T/ET), (ii) transpiration efficiency for shoot biomass production (TEB), and (iii) the harvest index. We directly relate the impact of management practices on T/ET to their effect on crop light interception and provide evidence that management practices significantly influence TEB. To optimize WUEG,ET,s, management practices should favor soil water availability during critical periods for seed set, thereby improving the harvest index. The need to improve the performance of existing crop growth models for the prediction of water-related grain yield determinants under different management practices is also discussed.

Predicción de la evapotranspiración de referencia utilizando redes neuronales artificiales / Reference evapotranspiration prediction using Artificial Neural Networks

RESUMEN La evapotranspiración de referencia (ETo) es una variable hidrológica de gran importancia en el manejo del riego. Su estimación se realiza con la ecuación de Penman-Montieth (PM), que requiere de muchas variables meteorológicas, las cuales, a veces, no se encuentran disponibles. Dado que la ETo es una variable no lineal y compleja, en los últimos años han surgido métodos alternativos para su estimación, como las redes neuronales artificiales (RNA). El objetivo del presente trabajo fue estimar la evapotranspiración de referencia (ETo) usando la ecuación de Penman-Montieth, a fin de desarrollar modelos de redes neuronales artificiales (RNA) que permitan predecir la ETo en regiones con información climatológica limitada, y su vez comparar el desempeño de tres modelos de RNA: FFNN, ERNN y NARX. Se utilizó información diaria durante el periodo 1 de enero de 2007 al 31 de diciembre de 2018, de las estaciones meteorológicas ENP8 y ENP4 de la CDMX. Se realizó un análisis de correlación y el análisis de sensibilidad de Garson para estudiar 2 casos (red estática FFNN y redes dinámicas: ERNN y NARX) usando 3 modelos de RNA: 1) RNA con 6 entradas: radiación solar (Rad), temperatura máxima y mínima (Tmax, Tmin), humedad relativa máxima y mínima (HRmax, HRmin) y velocidad del viento (u); y 2) RNA con 2 entradas (Rad y Tmax). La variable de salida fue la ETo calculada con la ecuación de PM. En todos los casos, las 3 RNA fueron muy parecidas, la diferencia más notable es que las redes dinámicas (ERNN y NARX) requieren de menor número de iteraciones para llegar al desempeño óptimo. Las RNA entrenadas, únicamente con Rad y Tmax como entradas, fueron capaces de predecir la ETo en el largo plazo, durante 440 d, en otra estación meteorológica cercana (ENP4), con eficiencias mayores al 90 %.

ABSTRACT Reference evapotranspiration (ETo) is a hydrological variable of great importance in irrigation management. Its estimation is carried out with the Penman-Montieth (PM) equation that requires many meteorological variables and that are sometimes not available. Since ETo is a nonlinear and complex variable, in recent years alternative methods have emerged for its estimation, such as artificial neural networks (ANN). The objective of this work was to estimate the reference evapotranspiration (ETo) using the Penman-Montieth equation, in order to develop artificial neural network (ANN) models that allow ETo to be predicted in regions with limited climatological information, and in turn to compare the performance of three RNA models: FFNN, ERNN and NARX. Daily informtion was used during the January 1, 2007 to December 31, 2018 period, for the ENP8 and ENP4 meteorological stations in Mexico city. Based on the correlation analysis and the Garson sensitivity analysis, 2 cases were studied for the 3 ANN models: 1) ANN with 6 inputs: solar radiation (Rad), maximum and minimum temperature (Tmax, Tmin), maximum and minimum relative humidity (RHmax, RHmin), and wind speed (u), and 2) RNA with 2 inputs (Rad and Tmax). The output variable was the ETo, calculated with the PM equation. In all cases, the performance of the 3 ANNs was very similar. The most notable difference is that the dynamic networks (ERNN and NARX) require fewer iterations to achieve the optimum performance. ANNs trained only with radiation and maximum temperature as inputs were able to predict a long-term ETo for 440 at another nearby meteorological station (ENP4), with efficiencies greater than 90 %.

A preliminary experimental study simulating evapotranspiration process in TEvap tanks cultivated with different forages.

The evapotranspiration tank (TEvap) is a 'zero-discharge' ecotechnology for toilet water disposal. This work refers to a preliminary study to evaluate the influence of forages and the addition of a vertical soil strip on evapotranspiration (ET), electrical conductivity (EC) and pH in TEvap receiving fresh water. The factors studied were the forages and the soil strip, resulting in four treatments with three replications. Two plant growing seasons, cycle 1 and cycle 2, were monitored, during which the variables were measured every three and seven days, respectively. Weather variables were used to estimate the reference evapotranspiration and determine the TEvap coefficient (KTEvap). The accumulated ET for TEvap with Capiaçu was 27.93% and 45.89% greater than for TEvap cultivated with Tifton-85 during the first and second cycles, respectively. There were no significant differences in ET for TEvap with and without the soil strip. BRS Capiaçu also showed lower values for EC and pH. High values were obtained for KTEvap: 2.37 and 1.76 for TEvap cultivated with BRS Capiaçu and Tifton-85 grass, respectively. Considering the period of this study, the minimum area for 'zero-discharge' would be 5.70 m2 inhab-1 and 7.77 m2 inhab-1 by TEvap planted with BRS Capiaçu and Tifton-85 grass, respectively. Due to its greater capacity for evapotranspiration, it can be concluded that the BRS Capiaçu forage is suitable for a 'zero-discharge' constructed wetland systems. It is suggested that further, more-thorough studies be carried out to design a 'zero-discharge' TEvap, considering different weather conditions, crops and inlet toilet water.HIGHLIGHTS Evapotranspiration tank (TEvap) is a 'zero discharge' ecotechnology for disposing toilet water;A preliminary study was conducted to simulate the evapotranspiration in TEvap receiving fresh water;Two forages - Cynodon spp. (Tifton-85 grass) and Pennisetum spp. (BRS Capiaçu) - were cultivated in the tanks;5.70 m2 inhab-1 were estimated for evapotranspiration with BRS Capiaçu and 7.77 m2 inhab-1 with Tifton-85 grass.

Corrigendum: Impact of climate change and rubber (Hevea brasiliensis) plantation expansion on reference evapotranspiration in Xishuangbanna, Southwest China.

[This corrects the article DOI: 10.3389/fpls.2022.830519.].

Rootstocks Comparison in Grafted Watermelon under Water Deficit: Effects on the Fruit Quality and Yield.

Drought is widely recognized as one of the most significant agricultural constraints worldwide. A strategy to avoid the adverse effects of drought on crops is to cultivate high-yielding varieties by grafting them onto drought-tolerant rootstocks with a differentiated root system. Thus, the objective of this study was to evaluate fruit yield and quality, root system architecture, and water productivity of watermelon grafted onto Lagenaria siceraria rootstocks. To do so, a commercial watermelon cultivar "Santa Amelia" [Citrullus lanatus (Thunb.)] was grafted onto five L. siceraria rootstocks: 'Illapel', 'Osorno', 'BG-48', 'GC', and 'Philippines', which were grown under three irrigation treatments (100%, 75%, and 50% of evapotranspiration). The comparison of the L. siceraria rootstocks in the irrigation treatments demonstrated no significant effect on watermelon fruit quality parameters. The rootstocks 'Illapel', 'Osorno', and 'GC' significantly improved the fruit number and yield (total fruit weight) under water deficit. Similarly, 'Illapel', 'Osorno', and 'GC' consistently showed statistical differences for root system architecture traits compared to 'BG-48' and 'Philippines'. Based on these results, we concluded that the used L. siceraria rootstocks did not affect the fruit yield and quality of grafted watermelon under water deficit. This study may help adjust the amount of applied water for watermelon production where L. siceraria rootstocks are utilized.

Evaluating the contribution of satellite-derived evapotranspiration in the calibration of numerical groundwater models in remote zones using the EEFlux tool.

Assessment of groundwater resources is crucial for developing water management practices for its sustainable exploitation, both for current and future needs. Numerical models are useful tools for such purpose. However, the lack of continuous monitoring networks, mainly due to difficult access to some remote locations, poses a challenge in developing and calibrating groundwater models. Remote sensing offers an alternative for acquiring information on hydrological and climatic variables at multiple spatiotemporal scales that has the potential to strengthen groundwater modeling. The aim of this study is to develop a methodology that uses remote sensing products to support model calibration. With this aim, we used the Parameter Estimation software (PEST) to calibrate a hydrogeological model of an unexploited basin located in the arid Chilean Altiplano using observed groundwater levels and evapotranspiration (ET) derived from the Earth Engine Evapotranspiration Flux (EEFlux) tool as observations. Our results show that the best model calibration is achieved using both EEFlux-ET and heads as observations to calibrate the hydraulic properties (normalized root mean square error = 4.1 %). We analyzed the effect of EEFlux-ET on the calibration of these properties and found a direct effect on specific yield parameters, which regulate the fluctuations of the water table over time. Incorporating EEFlux-ET estimates in the calibration resulted in lower values of specific yield across the aquifer. Therefore, incorporating remotely sensed ET as observations in the calibration of the groundwater model contributes to a better simulation of the spatiotemporal head variations in the basin.

Ajuste del coeficiente basal de cultivo (Kcb) de frijol (Phaseolus vulgaris) mediante teledetección

Para realizar un manejo eficiente del agua en la agricultura es necesario conocer los requerimientos hídricos del cultivo, lo cual, se puede realizar de manera sencilla y rápida, con la ayuda de cámaras convencionales. En este estudio, se determinaron los requerimientos hídricos de un cultivo de frijol (variedad DIACOL CALIMA G4494), sembrado en CIAT, Palmira - Valle del Cauca, Colombia, mediante la estimación de la curva del coeficiente basal de cultivo (Kcb), derivada de la curva de fracción de cobertura vegetal (Fcv). Para determinar la curva de fracción de cobertura vegetal, se emplearon imágenes tomadas con una cámara digital en el espectro visible (RGB), a baja altura (menos de 3 m). Las necesidades hídricas del cultivo de frijol, se calcularon empleando los valores del coeficiente basal de cultivo derivados junto con la modelación FAO-56. Los resultados indican que la curva de Kcb ajustada por fotografía fue diferente a la curva estándar presentada en la publicación FAO-56 para frijol, mostrando, principalmente, diferencia en la duración de las etapas y los valores de Kcb, en estas etapas. En cuanto a las necesidades hídricas, al emplear la curva de Kcb ajustada por fotografías, se evidencia que el cultivo requiere más agua en las etapas media y final, para evitar estrés hídrico en las plantas.

To carry out efficient water management in agriculture, it is necessary to know the water requirements of the crop, which can be done easily and quickly with the help of conventional cameras. In this study, the water requirements of a bean crop (DIACOL CALIMA G4494 variety) planted in CIAT, Palmira - Valle del Cauca, Colombia, were determined by estimating the curve of the basal crop coefficient (Kcb) derived from the vegetation cover fraction curve (Fcv). To determine the vegetation cover fraction curve, images taken with a digital camera in the visible spectrum (RGB) at low height (less than 3m) were used. The water needs of the bean crop were calculated using the basal crop coefficient values derived together with the FAO-56 modelling. The results indicate that the Kcb curve adjusted by photography was different from the standard curve presented in the publication FAO-56 for beans, mainly showing a difference in the duration of the stages and the Kcb values in these stages. Regarding water needs, when using the Kcb curve adjusted by photographs, it is evident that the crop requires more water in the middle and final stages, to avoid water stress in the plants.

Random forest for spatialization of daily evapotranspiration (ET0) in watersheds in the Atlantic Forest.

The importance of daily data on reference evapotranspiration (ET0) has increased in recent years due to its relevance in planning and decision making regarding irrigated agriculture, water production, and forest restoration. Facing the scarcity of this information measured in loco, the study of interpolation methods capable of representing ET0 becomes important. Therefore, this study aimed to evaluate the adequacy of the Random Forest (RF) method in the spatialization of ET0 in the watersheds of the Mid-South region of the Espírito Santo State, located within the Atlantic Forest biome, Brazil. From this study, it was found that the RF method is the most suitable one for ET0 spatialization when compared to the Angular distance weighting (ADW) and the inverse distance weighting (IDW) techniques. Also, the spatializations carried out by this method were transformed into databases in a grid format and made available online. Furthermore, the RF database was also compared to other ET0 grid databases, and it was concluded that the RF database also carried out a better performance than the other ones.

Remote sensing-based assessment of land degradation and drought impacts over terrestrial ecosystems in Northeastern Brazil.

The spatio-temporal assessment of water and carbon fluxes in Brazil's Northeast region (NEB) allows for a better understanding of these surface flux patterns in areas with different vegetation physiognomies. The NEB is divided into four biomes: Amazon, Cerrado, Caatinga, and Atlantic Forest. Land degradation is a growing problem, particularly in susceptible areas of the Caatinga biome, such as the seasonally dry tropical forest. Furthermore, this region has experienced climatic impacts, such as severe droughts. Due to increasing human pressure, the Caatinga's natural land cover undergoes drastic changes, making it a region particularly vulnerable to desertification. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) estimates of evapotranspiration (ET) and gross primary production (GPP) were validated in two contrasting areas, dense Caatinga and sparse Caatinga, using eddy covariance (EC) data and then investigated their behavior over 21 years (2000-2021) for the NEB. MODIS products explained around 60% of the variations in ET and GPP, showing higher accuracy in dense Caatinga, while areas of sparse Caatinga presented the lowest GPP, indicating that land degradation has reduced the photosynthetic activity of the vegetation in this area. Based on the analysis of ET and GPP over 21 years, we observed a greater dependence of the sparse Caatinga on climate variability, demonstrating a stronger resilience of dense Caatinga to climate effects. In comparison with the other biomes of the NEB region, we found lower rates of ET and GPP in the Caatinga biome, with averages similar to the Sparse Caatinga. In comparison with the other biomes in the NEB region, we found the lowest averages of ET and GPP in the Caatinga biome, similar to values found in the sparse Caatinga. In forest areas, similar to the monitored DC, they allowed the Caatinga to behave closer to the other biomes present in the region.

Impact of Climate Change and Rubber (Hevea brasiliensis) Plantation Expansion on Reference Evapotranspiration in Xishuangbanna, Southwest China.

The expansion of rubber (Hevea brasiliensis) cultivation plantation over the past few decades has been significantly explosive in Xishuangbanna, southwest China. More and more evidences concerning the expansion of rubber plantations lead to the negative influence to local regional hydrology. It is vital to explore the impact of climate change and rubber (Hevea brasiliensis) plantation expansion on reference evapotranspiration (ET0) for the sustainable and efficient use of regional water resources. In this study, the spatiotemporal variation of ET0 as well as its relationship in rubber plantations area in Xishuangbanna from 1970-2017 were analyzed by using trend, correlation and contribution analysis. The results showed that the rubber plantation was 12,768 ha yr-1 from 1990 to 2017 in Xishuangbanna, and nearly 40.8% of new rubber plantations expanded above 900 m in altitude from 2000 to 2017. Sunshine duration and average relative humidity were the key meteorological factors that affect ET0 in Xishuangbanna, with the sensitivity coefficient of 0.51 and 0.35, respectively. The multiyear relative change of ET0 in Xishuangbanna was 9.18%, and the total contribution of major climate factors was 7.87% during 1970 and 2017. The average relative humidity in the plantation area decreases, which directly leads to the increase of ET0. The amount of ET0 change from 2000 to 2017 affected by climate change increased at 3.13 mm/10a, whereas it was 2.17 mm/10a affected by the expansion of rubber plantations by quantitative separation. ET0 was significantly affected by climate change but intensified by the expansion of rubber plantation.