Estimating soil available water capacity within a Mediterranean vineyard watershed using satellite imagery and crop model inversion

Alkassem, Mohamed; Buis, Samuel; Coulouma, Guillaume; Jacob, Frédéric; Lagacherie, Philippe; Prévot, Laurent

doi:10.1016/j.geoderma.2022.116081

Cited by 5 publications

(3 citation statements)

References 104 publications

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“…We observed increases in aboveground biomass (AGB) and yield (Yld) following the in ltration of upstream runoff, mainly for clay-loam (CL) soils and deeper soils. This observation is explained by (1) a larger soil available water capacity for CL and deeper soils, allowing for a greater storage of water in the root zone (Alkassem et al 2022;Cousin et al 2022) and (2) a soil conducive to root zone development in terms of depth (van Leeuwen 2022).…”

Section: In Uence Of Soil Texture and Depthmentioning

confidence: 99%

Impact of hydrological connectivity on rainfed annual crops in Mediterranean hilly landscapes: a numerical exploration

Dhouib,

Molénat,

Prévot

et al. 2024

Preprint

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Within hilly agricultural landscapes, topography induces lateral transfers of runoff water, so-called interplot hydrological connectivity. Runoff water generated in upstream plots can infiltrate downstream plots, thus influencing the water content in the root zone that drives crop functioning. As the impact of runoff on crop functioning in the context of Mediterranean rainfed annual crops has been understudied thus far, the current study aims to comprehensively investigate this effect. To quantify how the downstream infiltration of upstream runoff affects crop functioning, we conduct a numerical experiment using the AquaCrop crop model and consider two hydrologically connected plots. The experiment explores a range of upstream and downstream agro-pedo-climatic conditions: crop type, soil texture and depth, climate forcing, and the area of the upstream plot. The experiment relies on data collected over the last 25 years within the Kamech catchment, an environment research observatory in northeastern Tunisia. Overall, the results show that the downstream infiltration of upstream runoff has a positive impact on crop functioning in a moderate number of situations, ranging from 16% (wheat) to 33% (faba bean) as the average across aboveground biomass and yield. This positive impact is mostly found for soils with higher available water capacity and under semiarid and dry subhumid climate conditions, with a significant impact of rainfall intra-annual distribution in relation to crop phenology. These results need to be deepened by considering both a wider range of crops and future climate conditions, for which larger occurrences of semiarid climate conditions are expected.

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Section: In Uence Of Soil Texture and Depthmentioning

confidence: 99%

Impact of hydrological connectivity on rainfed annual crops in Mediterranean hilly landscapes: a numerical exploration

Dhouib,

Molénat,

Prévot

et al. 2024

Preprint

Self Cite

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“…Landsat and MODIS satellites are often used to monitor evapotranspirative processes in the vineyard and in general are useful for detecting water status [92][93][94]. Another satellite that is being used to conduct vineyard water stress prediction surveys is the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite [95]. Consisting of 15 bands with 15 m resolution, it is suitable for measuring soil properties, soil temperatures [96].…”

Section: Satellitementioning

confidence: 99%

Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review

Ferro

Catania

2023

Horticulturae

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The potential of precision viticulture has been highlighted since the first studies performed in the context of viticulture, but especially in the last decade there have been excellent results have been achieved in terms of innovation and simple application. The deployment of new sensors for vineyard monitoring is set to increase in the coming years, enabling large amounts of information to be obtained. However, the large number of sensors developed and the great amount of data that can be collected are not always easy to manage, as it requires cross-sectoral expertise. The preliminary section of the review presents the scenario of precision viticulture, highlighting its potential and possible applications. This review illustrates the types of sensors and their operating principles. Remote platforms such as satellites, unmanned aerial vehicles (UAV) and proximal platforms are also presented. Some supervised and unsupervised algorithms used for object-based image segmentation and classification (OBIA) are then discussed, as well as a description of some vegetation indices (VI) used in viticulture. Photogrammetric algorithms for 3D canopy modelling using dense point clouds are illustrated. Finally, some machine learning and deep learning algorithms are illustrated for processing and interpreting big data to understand the vineyard agronomic and physiological status. This review shows that to perform accurate vineyard surveys and evaluations, it is important to select the appropriate sensor or platform, so the algorithms used in post-processing depend on the type of data collected. Several aspects discussed are fundamental to the understanding and implementation of vineyard variability monitoring techniques. However, it is evident that in the future, artificial intelligence and new equipment will become increasingly relevant for the detection and management of spatial variability through an autonomous approach.

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“…Another way to obtain indirect information about the AWC is to assimilate RS data into vegetation functioning models (e.g., [279][280][281]). Fusion approaches have also been developed to combine local soil property measurements with RS data [282][283][284]. A recent review by Cousin et al [285] provides an insightful overview of the ways to estimate the AWC using RS data as covariates for DSM AWC prediction from field to regional scales.…”

Section: Land-cover and Vegetation Characteristicsmentioning

confidence: 99%

Remote Sensing Data for Digital Soil Mapping in French Research—A Review

et al. 2023

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Soils are at the crossroads of many existential issues that humanity is currently facing. Soils are a finite resource that is under threat, mainly due to human pressure. There is an urgent need to map and monitor them at field, regional, and global scales in order to improve their management and prevent their degradation. This remains a challenge due to the high and often complex spatial variability inherent to soils. Over the last four decades, major research efforts in the field of pedometrics have led to the development of methods allowing to capture the complex nature of soils. As a result, digital soil mapping (DSM) approaches have been developed for quantifying soils in space and time. DSM and monitoring have become operational thanks to the harmonization of soil databases, advances in spatial modeling and machine learning, and the increasing availability of spatiotemporal covariates, including the exponential increase in freely available remote sensing (RS) data. The latter boosted research in DSM, allowing the mapping of soils at high resolution and assessing the changes through time. We present a review of the main contributions and developments of French (inter)national research, which has a long history in both RS and DSM. Thanks to the French SPOT satellite constellation that started in the early 1980s, the French RS and soil research communities have pioneered DSM using remote sensing. This review describes the data, tools, and methods using RS imagery to support the spatial predictions of a wide range of soil properties and discusses their pros and cons. The review demonstrates that RS data are frequently used in soil mapping (i) by considering them as a substitute for analytical measurements, or (ii) by considering them as covariates related to the controlling factors of soil formation and evolution. It further highlights the great potential of RS imagery to improve DSM, and provides an overview of the main challenges and prospects related to digital soil mapping and future sensors. This opens up broad prospects for the use of RS for DSM and natural resource monitoring.

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Estimating soil available water capacity within a Mediterranean vineyard watershed using satellite imagery and crop model inversion

Cited by 5 publications

References 104 publications

Impact of hydrological connectivity on rainfed annual crops in Mediterranean hilly landscapes: a numerical exploration

Impact of hydrological connectivity on rainfed annual crops in Mediterranean hilly landscapes: a numerical exploration

Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review

Remote Sensing Data for Digital Soil Mapping in French Research—A Review

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