Managing water scarcity in European and Chinese cropping systems

In “Soil and Tillage Research

Authors: M.López-Vicente, J.A.Gómez, G.Guzmán, J.Calero, R.García-Ruiz


Soil erosion plays an important role in C cycling at farm scale, especially in bare soil areas. In Mediterranean woody crops, temporary cover crops (CC) effectively reduce soil erosion and increase total and protected soil organic carbon (SOC) fractions. However, the effects of CC in olive groves on the preferential loss of organic carbon (Corg) fractions remains poorly understood. To address this issue, in four plots with seeded CC and two tilled plots (CT) in a Spanish olive grove, the unprotected and protected Corg fractions were measured in soil and sediments over the course of a hydrological year. The sediment/soil C enrichment ratios (ERSOC) were calculated, and results analysed considering the rainfall regimes of the site: dry (DS), heavy-rainy (HRS) and rainy (RS). Total, unprotected and protected Corg contents in the top 5 cm soil of CC plots were 46 %, 88.4 % and 28.5 %, respectively, higher than those of CT. 79.7 % and 70.3 % of the annual sediment yield (SY) was collected during December in CC and CT plots, respectively. Soil loss in CC plots ( = 9.2 Mg ha–1 yr–1) was significantly lower (−55.6 %) than that in CT plots. Despite that the average eroded Corg was higher in the CT ( = 222 kg C ha–1 yr–1) compared to CC ( = 148 kg C ha–1 yr–1) plots differences were not significant due to the higher Corg concentration in the sediment from CC plots. The highest proportion of eroded Corg (44%–45%) corresponded to the physically protected fraction. The highest ERSOC (1.99 and 2.04 for CC and CT, respectively) was recorded in DS whereas the lowest was in the RS (0.90) and HRS (0.96) seasons. The mean ERSOC were of 1.00 and 0.92 in the CC and CT plots, with no significant difference. The fact that most of the SY was recorded in one month, when CC plants were not fully developed, might explain the ERSOC at 1, and why their presence did not modify it. This study demonstrates that CC favours greater total, unprotected and protected Corg fractions in the topsoil, promoting soil C sequestration. The asynchrony between the periods of full development of the CC plants and those with the highest rainfall erosivity prevented any selectiveness of the eroded Corg. Thus, fast-growing CC plant species with short life-cycles are recommended, as well as adequate management to promote self-seeding avoiding soil disturbance for seeding in erosion prone seasons.
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In “Civil Engineering  Journal

Authors: Jakub Jeřábek, David Zumr


Catchment drainage area is a basic spatial unit in landscape hydrology within which the authorities estimate a water balance and manage water resources. The catchment drainage area is commonly delineated based on the surface topography, which is determined using a digital elevation model. Therefore, only a flow over the surface is implicitly considered. However, a substantial portion of the rainfall water infiltrates and percolates through the soil profile to the groundwater, where geological structures control the drainage area instead of the topography of the soil surface. The discrepancy between the surface topography-based and bedrock-based drainage area can cause large discrepancies in water balance calculation. It this paper we present an investigation of the subsurface media stratification in a headwater catchment in the central part of the Czech Republic using a geophysical survey method – electrical resistivity tomography (ERT). Results indicate that the complexity of the subsurface geological layers cannot be estimated solely from the land surface topography. Although shallow layers copy the shape of the surface, the deeper layers do not. This finding has a strong implication on the water transport regime since it suggests that the deep drainage may follow different pathways and flow in other directions then the water in shallow soil profile or shallow subsurface structures.
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In “Science of The Total Environment

Authors: J.M.Ramírez-Cuesta, M.Minacapilli, A.Motisi, S.Consoli, D.S.Intrigliolo, D.Vanella


The identification and recognition of the land processes are of vital importance for a proper management of the ecosystem functions and services. However, on-ground land uses/land covers (LULC) characterization is a time-consuming task, often limited to small land areas, which can be solved using remote sensing technologies. The objective of this work is to investigate how the different MODIS NDVI seasonal parameters responded to the main land processes observed in Europe in the 2000-2018 period; characterizing their temporal trend; and evaluating which one reflected better each specific land process. NDVI time-series were evaluated using TIMESAT software, which extracted eight seasonality parameters: amplitude, base value, length of season, maximum value, left and right derivative values and small and large integrated values. These parameters were correlated with the LULC changes derived from COoRdination of INformation on the Environment Land Cover (CLC) for assessing which parameter better characterized each land process. The temporal evolution of the maximum seasonal NDVI was the parameter that better characterized the occurrence of most of the land processes evaluated (afforestation, agriculturalization, degradation, land abandonment, land restoration, urbanization; R2 from 0.67-0.97). Large integrated value also presented significant relationships but they were restricted to two of the three evaluated periods. On the contrary, land processes involving CLC categories with similar NDVI patterns were not well captured with the proposed methodology. These results evidenced that this methodology could be combined with other classification methods for improving LULC identification accuracy or for identifying LULC processes in locations where no LULC maps are available. Such information can be used by policy-makers to draw LULC management actions associated with sustainable development goals. This is especially relevant for areas where food security is at stake and where terrestrial ecosystems are threatened by severe biodiversity loss.

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Authors: Barlin O.Olivares, JulioCalero, Juan C.Rey, Deyanira Lobo, Blanca B.Landa, José A.Gómez 


Soil morphological properties described in the field, such as texture, consistence or structure, provide a valuable tool for the evaluation of soil productivity potential. In this study, we developed a regression model between the soil morphological variables of banana plantations and a crop Productivity Index (PI) previously developed for the same areas in Venezuela. For this, we implemented categorical regression, an optimal scaling procedure in which the morphological variables are transformed into a numerical scale, and can thus be entered in a multiple regression analysis. The model was developed from data from six plantations growing “Gran Nain” bananas, each with two productivity levels (high and low), in two 4-ha experimental plots, one for each productivity level. Sixty-three A horizons in thirty-six soils were described using 15 field morphological variables on a nominal scale for structure type, texture and hue, and an ordinal scale for the rest (structure grade, structure size, wet and dry consistence, stickiness, plasticity, moist value, chroma, root abundance, root size, biological activity and reaction to HCl). The optimum model selected included biological activity, texture, dry consistence, reaction to HCl and structure type variables. These variables explained the PI with an R2 of 0.599, an expected prediction error (EPE) of 0.645 and a standard error (SE) of 0.135 using bootstrapping, and EPE of 0.662 with a SE of 0.236 using 10-fold cross validation. Our study showed how soil quality is clearly related to productivity on commercial banana plantations, and developed a way to correlate soil quality indicators to yield by using indicators based on easily measured soil morphological parameters. The methodology used in this study might be further expanded to other banana-producing areas to help identify the soils most suitable for its cultivation, thereby enhancing its environmental sustainability and profitability.

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In “The Vadose Zone Journal”

Authors: D. Tzohar, M. Moshelion, A. Ben-Gal


Plant root systems are exposed to spatial and temporal heterogeneity regarding water availability. In the long-term, compensation, increased uptake by roots in areas with favorable conditions in response to decreased uptake in areas under stress, is driven by root growth and distribution. In the short-term (hours–days), compensative processes are less understood. We hypothesized hydraulic compensation where local lowered water availability is accompanied by increased uptake from areas where water remains available. Our objective was to quantify instantaneous hydraulic root uptake under conditions of differential water availability. Tomato (Solanum lycopersicum L.) plants were grown in split-root weighing-drainage lysimeters in which each half of the roots could alternatively be exposed to short-term conditions of salinity. Uptake was quantified from each of the two root zone compartments. One-sided exposure to salinity immediately led to less uptake from the salt-affected compartment and increased uptake from the nontreated compartment. Compensation occurred at salinity, caused by NaCl solution of 4 dS m−1, that did not decrease uptake in plants with entire root systems exposed. At higher salinity, 6.44 dS m−1, transpiration decreased by ∼50% when the total root system was exposed. When only half of the roots were exposed, total uptake was maintained at levels of nonstressed plants with as much as 85% occurring from the nontreated compartment. The extent of compensation was not absolute and apparently a function of salinity, atmospheric demand, and duration of exposure. As long as there is no hydraulic restriction in other areas, temporary reduction in water availability in some parts of a tomato’s root zone will not affect plant-scale transpiration.


a Independent Researcher, Variability, Ashalim 85512, Israel
b Department of Applied Mathematics, Delft University of Technology, Mourik Broekmanweg 6, 2628 XE Delft, the Netherlands
c TerraVision Lab, Midreshet Ben-Gurion 8499000, Israel
d Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization, Gilat Research Center, Mobile post Negev 2, 85280, Israel
e Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, P.O. Box 15159, Rishon LeZion 7505101, Israel
f The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, The Robert H. Smith Faculty of Agriculture, Food & Environment, Rehovot 76100, Israel
g Department of Soil and Water Sciences, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, P.O. Box 12, Rehovot 7610001, Israel
h Department of Precision Agriculture, MIGAL Galilee Research Institute, Kiryat Shmona 11016, Israel
i Department of Agriculture and Oenology, Eastern R&D Center, Israel
j Department of Chemical Engineering, Ariel University, Ariel 40700, Israel

Computers and Electronics in Agriculture


Collection of accurate and representative data from agricultural fields is required for efficient crop management. Since growers have limited available resources, there is a need for advanced methods to select representative points within a field in order to best satisfy sampling or sensing objectives. The main purpose of this work was to develop a data-driven method for selecting locations across an agricultural field given observations of some covariates at every point in the field. These chosen locations should be representative of the distribution of the covariates in the entire population and represent the spatial variability in the field. They can then be used to sample an unknown target feature whose sampling is expensive and cannot be realistically done at the population scale.

An algorithm for determining these optimal sampling locations, namely the multifunctional matching (MFM) criterion, was based on matching of moments (functionals) between sample and population. The selected functionals in this study were standard deviation, mean, and Kendall’s tau. An additional algorithm defined the minimal number of observations that could represent the population according to a desired level of accuracy. The MFM was applied to datasets from two agricultural plots: a vineyard and a peach orchard. The data from the plots included measured values of slope, topographic wetness index, normalized difference vegetation index, and apparent soil electrical conductivity. The MFM algorithm selected the number of sampling points according to a representation accuracy of 90% and determined the optimal location of these points. The algorithm was validated against values of vine or tree water status measured as crop water stress index (CWSI). Algorithm performance was then compared to two other sampling methods: the conditioned Latin hypercube sampling (cLHS) model and a uniform random sample with spatial constraints. Comparison among sampling methods was based on measures of similarity between the target variable population distribution and the distribution of the selected sample.

MFM represented CWSI distribution better than the cLHS and the uniform random sampling, and the selected locations showed smaller deviations from the mean and standard deviation of the entire population. The MFM functioned better in the vineyard, where spatial variability was larger than in the orchard. In both plots, the spatial pattern of the selected samples captured the spatial variability of CWSI. MFM can be adjusted and applied using other moments/functionals and may be adopted by other disciplines, particularly in cases where small sample sizes are desired. View Full-Text

Keywords: Partially-observed data, Representative sampling given covariates, Two-phase study, Agricultural sampling, Spatial autocorrelation

1 The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Robert H. Smith Faculty of   Agriculture, Food & Environment, The Hebrew University of Jerusalem, Rehovot 76100, Israel
2 Agricultural Engineering, Agricultural Research Organization—Volcani Institute, P.O. Box 15159, Rishon LeZion 7505101, Israel
3 Department of Chemical Engineering, Ariel University, Ariel 40700, Israel
4 Eastern R & D Center, Department of Agriculture and Oenology, Ariel 40700, Israel
5 TerraVision Lab, Midreshet Ben-Gurion 8499000, Israel
6 Independent Researcher, Variability, Ashalim 85512, Israel
7 Gilat Research Center, Soil, Water and Environmental Sciences, Agricultural Research Organization—Volcani Institute, Mobile Post Negev 2 85280, Israel
*Author to whom correspondence should be addressed.
Academic Editor: Simona Consoli
Remote Sens. 202113(9), 1636;
Received: 21 March 2021 / Revised: 17 April 2021 / Accepted: 19 April 2021 / Published: 22 April 2021
Wine quality is the final outcome of the interactions within a vineyard between meteorological conditions, terrain and soil properties, plant physiology and numerous viticultural decisions, all of which are commonly summarized as the terroir effect. Associations between wine quality and a single soil or topographic factor are usually weak, but little information is available on the effect of terrain (elevation, aspect and slope) as a compound micro-terroir factor. We used the topographic wetness index (TWI) as a steady-state hydrologic and integrative measure to delineate management zones (MZs) within a vineyard and to study the interactions between vine vigor, water status and grape and wine quality. The study was conducted in a commercial 2.5-ha Vitis vinifera ‘Cabernet Sauvignon’ vineyard in Israel. Based on the TWI, the vineyard was divided into three MZs located along an elongate wadi that crosses the vineyard and bears water only in the rainy winter season. MZ1 was the most distant from the wadi and had low TWI values, MZ3 was closest to the wadi and had high TWI values. Remotely sensed crop water stress index (CWSI) was measured simultaneously with canopy cover (as determined by normalized difference vegetation index; NDVI) and with field measurements of midday stem water potential (Ψstem) and leaf area index (LAI) on several days during the growing seasons of 2017 and 2018. Vines in MZ1 had narrow trunk diameter and low LAI and canopy cover on most measurement days compared to the other two MZs. MZ1 vines also exhibited the highest water stress (highest CWSI and lowest Ψstem), lowest yield and highest wine quality. MZ3 vines showed higher LAI on most measurement days, lowest water deficit stress (Ψstem) during phenological stage I, highest yield and lowest wine quality. Yet, in stage III, MZ3 vines exhibited a similar water deficit stress (CWSI and Ψstem) as MZ2, suggesting that the relatively high vigor in MZ3 vines resulted in higher water deficit stress than expected towards the end of the season, possibly because of high water consumption over the course of the season. TWI and its classification into three MZs served as a reliable predictor for most of the attributes in the vineyard and for their dynamics within the season, and, thus, can be used as a key factor in delineation of MZs for irrigation. Yet, in-season remotely sensed monitoring is required to follow the vine dynamics to improve precision irrigation decisions. View Full-Text

A. Tallou 1, F. Aziz 2,A. J. Garcia 3, F. P. Salcedo 3, F. E. El Minaoui 1 & S. Amir 1

1 Polydisciplinary Laboratory of Research and development, Faculty of Sciences and Techniques, Sultan Moulay Slimane University of Beni Mellal, Beni Mellal, Morocco

2 Laboratory of Water, Biodiversity & Climate Change, Semlalia Faculty of Sciences, University Cadi Ayyad, B.P. 2390, 40000, Marrakech, Morocco

3 Department of Irrigation, CEBAS-CSIC, Campus Universitario de Espinardo, 30100, Murcia, Spain


International Journal of Environmental Science and Technology (2021)


Tomatoes (Solanum lycopersicum) plant were provided with bio-fertilizers issued from anaerobic digestion of olive mill wastewater without and with 1%, 5% of phosphate residues in mesophilic conditions for 25 days. 1% of raw substrates (OMW raw; OMW + 1%PR raw; olive mill wastewater + 5%phosphate residues raw; and phosphate residues) and digestates (olive mill wastewater digestate, olive mill wastewater + 1%phosphate residues digestate and olive mill wastewater + 5%phosphate residues digestate) was provided fortnightly to the plants. Reclaimed water from a wastewater treatment plant located in the study site was used for automatically controlled irrigation. It contained a low level of chemical fertilizers to compare tomato plant growth, leaf analysis, steam water potential, production yield and fruit quality results to plants fed with bio-fertilizers. Generally, parameters and results were progressively increased during the growing and harvesting stage, which refer to the essential elements that cover the plant’s needs. Plants fed with bio-fertilizers showed the most extended plant height (olive mill wastewater + 5% phosphate residues raw), and the best accumulation of essential elements in leaves (olive mill wastewater + 1% phosphate residues digestate and olive mill wastewater + 5%phosphate residues digestate). The maximum average fruit weight per treatment (35.5 g) was obtained when applying the digestates mixture of olive mill wastewater raw and olive mill wastewater + 5% phosphate residues. The maximum yield production per plant was obtained when applying phosphates residues. Bio-fertilizers (digestates) showed good performances, high fruit quality and perfect tomato yield production compared to the control plants. Results obtained during this study are considered promising regarding environmental framework. However, this study was done in a laboratory scale and needs to be applied in a large scale to provide more data on the effectiveness of the digestates application. It is also recommended to apply these bio-fertilizers on different crops and various soils for a better evaluation.

XunWua, YanqiXua, JianchuShia, QiangZuoa, TingZhanga, LichunWangb, XuzhangXueb, AlonBen-Galc

a College of Land Science and Technology, China Agricultural University; Key Laboratory of Plant-Soil Interactions, Ministry of Education; and Key Laboratory of Arable Land Conservation (North China), Ministry of Agriculture, Beijing 100193, China
b National Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China
c Soil, Water and Environmental Sciences, Agricultural Research Organization – Volcani Institute, Gilat Research Center, Mobile Post Negev 85280, Israel

Received 20 October 2020, Revised 4 March 2021, Accepted 7 March 2021, Available online 18 March 2021.


Stomatal conductance, closely related to water flow in the soil-plant-atmosphere continuum, is an important parameter in the Penman-Monteith (P-M) model for estimating evapotranspiration (ET). In this study, a novel soil water stress index ω, considering intrinsic soil-plant water relations, was introduced into the Jarvis empirical estimation model of stomatal conductance to improve the representation of the effect of soil water stress on stomatal conductance. The index ω accounted not only for current water availability by combing the effects of relative distribution of soil water to roots and nonlinear stomatal response, but also for the hysteresis effect of water stress by means of the inclusion of a recovery coefficient. Combined plant and soil-based measurements from a greenhouse experiment provided the basis for investigating the relationship between leaf stomatal conductance gs and root zone soil water stress represented by ω. The response of gs to root-weighted soil matric potential was found to be nonlinear. The relationship between gs and the extent of previous water stress (i.e. the water stress recovery coefficient curve) was generalized by a power function and was verified and confirmed using results obtained from the literature. The reliability of ω was tested by coupling it into the Jarvis model to estimate leaf (gs) and canopy (gc) stomatal conductance, and thereupon into the P-M model to estimate cumulative ET (CET) in the greenhouse experiment and two field experiments. The estimated gs, gc and CET agreed well with the measurements, with root mean squared error not more than 0.0006 m s−1, 0.0020 m s−1 and 8.2 mm, respectively, and determination coefficient (Nash-Sutcliffe efficiency coefficient) consistently greater than 65% (0.14). Therefore, ω should be feasible and reliable to delineate the response of stomatal physiological reaction to water stress, and hence helpful for accurate estimation of ET using Jarvis-based P-M models.

Computers and Electronics in Agriculture 2021,  182,  106038,

Partner publication (IAS-CSIC & UCO):

Tomás R. Tenreiroa Margarita García-Vilab José A. Gómeza José A. Jiménez-Bernia Elías Fereresab

aInstitute for Sustainable Agriculture (CSIC), 14004 Córdoba, Spain
bDepartment of Agronomy, University of Córdoba, 14014 Córdoba, Spain



The fraction of green canopy cover (CC) is an important feature commonly used to characterize crop growth and for calibration of crop and hydrological models. It is well accepted that there is a relation between CC and NDVI through linear or quadratic models, however a straight-forward empirical approach, to derive CC from NDVI observations, is still lacking. In this study, we conducted a meta-analysis of the NDVI-CC relationships with data collected from 19 different studies (N = 1397). Generic models are proposed here for 13 different agricultural crops, and the associated degree of uncertainty, together with the magnitude of error were quantified for each model (RMSE around 6–18% of CC). We observed that correlations are adequate for the majority of crops as