Evapotranspiration, gross primary productivity and water use efficiency over a high-density olive orchard using ground and satellite based data

Global warming has resulted in increases in the intensity, frequency, and duration of drought in most land areas at the regional and global scales. Nevertheless, comprehensive understanding of how water use efficiency (WUE), gross primary production (GPP), and actual evapotranspiration (AET)-induced water losses respond to exceptional drought and whether the responses are influenced by drought severity (DS) is still limited. Herein, we assess the fluctuation in the standardized precipitation evapotranspiration index (SPEI) over the Middle East from 1982 to 2017 to detect the drought events and further examine standardized anomalies of GPP, WUE, and AET responses to multiyear exceptional droughts, which are separated into five groups designed to characterize the severity of extreme drought. The intensification of the five drought events (based on its DS) increased the WUE, decreased the GPP and AET from D5 to D1, where both the positive and negative variance among the DS group was statistically significant. The results showed that the positive values of standardized WUE with the corresponding values of the negative GPP and AET were dominant (44.3% of the study area), where the AET values decreased more than the GPP, and the WUE fluctuation in this region is mostly controlled by physical processes, i.e., evaporation. Drought’s consequences on ecosystem carbon-water interactions ranged significantly among eco-system types due to the unique hydrothermal conditions of each biome. Our study indicates that forthcoming droughts, along with heightened climate variability, pose increased risks to semi-arid and sub-humid ecosystems, potentially leading to biome restructuring, starting with low-productivity, water-sensitive grasslands. Our assessment of WUE enhances understanding of water-carbon cycle linkages and aids in projecting ecosystem responses to climate change.

Section: Response Of Gpp and Wue To Drought Across Different Climate ...mentioning

confidence: 99%

Response of Ecosystem Carbon–Water Fluxes to Extreme Drought in West Asia

Alsafadi,

Bashir,

Mohammed

et al. 2024

“…The value of ε max (gC/MJ) is specific to each land cover and even to each species [45], with variations also depending on the geographical area. In this case, a value of 3 g/MJ was used for xeric shrublands, which is similar to the values for woody cover in semi-arid zones [46,47], and a value of 2 g/MJ was used for swamps, since the dominant species can be an intermediate value between grasslands [48] and annual crops [49].…”

Section: ε Estimationmentioning

confidence: 99%

Validation of Gross Primary Production Estimated by Remote Sensing for the Ecosystems of Doñana National Park through Improvements in Light Use Efficiency Estimation

Gómez-Giráldez,

Cristóbal,

Nieto

et al. 2024

Doñana National Park is located in the southwest of the Iberian Peninsula, where water scarcity is recurrent, together with a high heterogeneity in species and ecosystems. Monitoring carbon assimilation is essential to improve knowledge of global change in natural vegetation cover. In this work, a light use efficiency (LUE) model was applied to estimate gross primary production (GPP) in two ecosystems of Doñana, xeric shrub (drought resistant) and seasonal marsh (with grasslands dependent on water hydroperiod) and validated with in situ data from eddy covariance (EC) towers installed in both ecosystems. The model was applied in two ways: (1) using the fraction of absorbed photosynthetically active radiation (FAPAR) from Sentinel-2 and meteorological data from reanalysis (ERA5), and (2) using Sentinel-2 FAPAR, reanalysis solar radiation (ERA5) and the Sentinel-2 land surface water index (LSWI). In both cases and for both ecosystems, the error values are acceptable (below 1 gC/m2) and in both ecosystems the model using the LSWI gave better results (R2 of 0.8 in marshes and 0.51 in xeric shrubs). The results also show a greater influence of the water status of the system than of the meteorological variables in this area.

“…Providing non-destructive methodologies with high spatial, radiometric and temporal resolutions, RS allows the characterization and monitoring of spatiotemporal variability for multidimensional purposes [9][10][11][12][13]. Over the past few decades, RS technology has played a crucial role in the development of new agricultural applications, focusing primarily on monitoring vegetation cover [14][15][16], assessing crop vigor conditions [17][18][19], estimating nutrient and water status [20][21][22], determining crop evapotranspiration (ET c ) [23][24][25], identifying and managing invasive plants [26][27][28], detecting and monitoring pest/diseases [29][30][31] and forecasting crop yields [32][33][34]. The effectiveness of RS applications in agriculture depends on several fundamental factors, including the choice of sensing platform, which can be a satellite, aircraft, unmanned aerial vehicle (UAV) or terrestrial platform; the segment of the electromagnetic spectrum used; the number and range of spectral bands; spatial, temporal and radiometric resolutions; and the energy source (passive or active sensors) [9].…”

Section: Introductionmentioning

confidence: 99%

Advancements in Remote Sensing Imagery Applications for Precision Management in Olive Growing: A Systematic Review

Marques,

Pádua,

Sousa

et al. 2024

This systematic review explores the role of remote sensing technology in addressing the requirements of sustainable olive growing, set against the backdrop of growing global food demands and contemporary environmental constraints in agriculture. The critical analysis presented in this document assesses different remote sensing platforms (satellites, manned aircraft vehicles, unmanned aerial vehicles and terrestrial equipment) and sensors (RGB, multispectral, thermal, hyperspectral and LiDAR), emphasizing their strategic selection based on specific study aims and geographical scales. Focusing on olive growing, particularly prominent in the Mediterranean region, this article analyzes the diverse applications of remote sensing, including the management of inventory and irrigation; detection/monitoring of diseases and phenology; and estimation of crucial parameters regarding biophysical parameters, water stress indicators, crop evapotranspiration and yield. Through a global perspective and insights from studies conducted in diverse olive-growing regions, this review underscores the potential benefits of remote sensing in shaping and improving sustainable agricultural practices, mitigating environmental impacts and ensuring the economic viability of olive trees.