Managing water scarcity in European and Chinese cropping systems
Agricultural Water Management 2021, 248, 106774


Partner Publication (ARO & CAU):

JianchuShiabc XunWudMoZhangabc XiaoyuWangabc QiangZuoabc XiaoguangWue HongfeiZhange AlonBen-Galf


aCollege of Land Science and Technology, China Agricultural University, Beijing 100193, China

bKey Laboratory of Plant-Soil Interactions, Ministry of Education, Beijing 100193, China

cKey Laboratory of Arable Land Conservation (North China), Ministry of Agriculture, Beijing 100193, China

dCollege of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China

eLand Management Center of Inner Mongolia Autonomous Region, Hohhot 010020, China

fSoil, Water and Environmental Sciences, Agricultural Research Organization, Gilat Research Center, Mobile post Negev 85280, Israel


  • A coupled soil water transport and crop growth model is established and validated.
  • Relationships between irrigation scheduling and results are numerically quantified.
  • Numerical simulation is reliable for optimizing smart irrigation schedule.
  • Regulated deficit irrigation is superior in improving water use efficiency.
  • Irrigation scheduling is optimized according to actual water conditions.



Knowledge-driven “smart” irrigation proposes to achieve explicitly targeted crop yield and/or irrigation water use efficiency (WUE). A coupled crop growth and soil water transport model was established and applied to schedule irrigation for drip-irrigated and film-mulched maize through numerical simulation. By designing various scenarios with either a constant or variable threshold of plant water deficit index (PWDI) to initiate irrigation, the quantitative relationship between PWDI threshold and the corresponding yield and WUE was investigated with acceptable errors between the measured and simulated values (R2 > 0.85). The model allowed determination of PWDI thresholds designed to reach specific combinations of yield and WUE to consider actual conditions such as availability and cost of water resources. Regulated deficit irrigation with a variable threshold, considering variability of physiological response to water stress, was superior to a constant PWDI threshold in improving WUE. A constant PWDI threshold of 0.54 and 45 threshold combinations among various growth stages were suggested to obtain same relative values of yield and WUE. Numerical simulation has the potential to provide reliable dynamic information regarding soil water and crop growth, necessary for smart irrigation scheduling, due to its ability in integrating the effects of environmental conditions and economic considerations and, as such, should be further studied to enhance simulation accuracy and subsequently to optimize irrigation scheduling under complex situations.

José A.Gómeza, Ana Sánchez Monteroa, Gema Guzmána, María-AuxiliadoraSorianob

aInstitute for Sustainable Agriculture, CSIC, Cordoba, Spain
bAgronomy Department, University of Cordoba, Cordoba, Spain

Received 15 December 2020, Revised 15 January 2021, Accepted 19 January 2021, Available online 25 January 2021.


This manuscript presents a questionnaire-based study aimed to provide a detailed analysis on the different soil management carried out by olive farmers in two representative olive-growing areas in southern Spain (Cordoba and Estepa), their perceptions on cover crop use and the possible influence of the different types of farms and farmers’ typologies on these perceptions. Our results show a relatively large variability of soil management, with fourteen options, as a result of a combination of different alternatives for bare soil and cover crops with the use or not of pruning residues, but with a great similarity between both areas. The results indicate a high adoption of soil conservation measures in the two study areas, with 63% of farmers using cover crops and 80% a mulch of pruning residues, higher than that reported in previous studies in Southern Spain, and a trend of lower use of these techniques by less experienced and younger farmers. This high penetration of soil conservation measures resulted in a significant reduction of soil erosion risk, as indicated by the relatively low values for the cover and management factor (C) of RUSLE, also calculated and presented in this study, but also the possibility of focusing further efforts on farmers with less experience. Our results indicate the persistence of a minor, but relevant, percentage of farmers using bare soil management (37%) and no mulching (20%), with a moderate concern on the impact of soil erosion on soil degradation and provision of ecosystem services. This suggests the need to concentrate efforts also on this cluster of farmers to enhance the success of what seems to be a remarkable expansion of the use of soil conservation measures in recent decades in Southern Spain, but also in similar areas in the Mediterranean basin.

First published: 09 January 2021

Funding information České Vysoké Učení Technické v Praze, Grant/Award Number: SGS20/156/OHK1/3T/11; European Commission, Grant/Award Number: 773903


We introduce the freely available web‐based Water in an Agricultural Landscape—NUčice Database (WALNUD) dataset that includes both hydrological and meteorological records at the Nučice experimental catchment (0.53 km2), which is representative of an intensively farmed landscape in the Czech Republic. The Nučice experimental catchment was established in 2011 for the observation of rainfall–runoff processes, soil erosion processes, and water balance of a cultivated landscape. The average altitude is 401 m a.s.l., the mean land slope is 3.9%, and the climate is humid continental (mean annual temperature 7.9°C, annual precipitation 630 mm). The catchment is drained by an artificially straightened stream and consists of three fields covering over 95% of the area which are managed by two different farmers. The typical crops are winter wheat, rapeseed, and alfalfa. The installed equipment includes a standard meteorological station, several rain gauges distributed across the basin, and a flume with an H‐type facing that is used to monitor stream discharge, water turbidity, and basic water quality indicators. Additionally, the groundwater level and soil water content at various depths near the stream are recorded. Recently, large‐scale soil moisture monitoring efforts have been introduced with the installation of two cosmic‐ray neutron sensors for soil moisture monitoring. The datasets consist of observed variables (e.g. measured precipitation, air temperature, stream discharge, and soil moisture) and are available online for public use. The cross‐seasonal, open access datasets at this small‐scale agricultural catchment will benefit not only hydrologists but also local farmers.

Sustainability 2020, 12(24), 10596; (registering DOI)


Published by CVUT:

Nina Noreika 1, Tailin Li 1,David Zumr 1,Josef Krasa 1,Tomas Dostal 1 and Raghavan Srinivasan 2

1 Faculty of Civil Engineering, Czech Technical University in Prague, 16000 Prague, Czech Republic
2 Department of Ecosystem Science and Management, Texas A&M University, College Station, TX 77843, USA

Received: 30 November 2020 / Revised: 14 December 2020 / Accepted: 16 December 2020 / Published: 18 December 2020


In the face of future climate change, Europe has encouraged the adoption of biofuel crops by its farmers. Such land-use changes can have significant impacts on the water balance and hydrological behavior of a system. While the heavy pesticide use associated with biofuel crops has been extensively studied, the water balance impacts of these crops have been far less studied. We conducted scenario analyses using the Soil and Water Assessment Tool (SWAT) to determine the effects of farm-scale biofuel crop adoption (rapeseed) on a basin’s water balance. We found that rapeseed adoption does not support the goal of developing a sustainable agricultural landscape in the Czech Republic. The adoption of rapeseed also had disproportionate effects on a basin’s water balance depending on its location in the basin. Additionally, discharge (especially surface runoff ratios), evapotranspiration, and available soil water content display significant shifts in the rapeseed adoption scenarios.
Journal of Soil Science and Plant Nutrition volume 20pages25122524(2020)
Published by CSIC:

Barlin Orlando Olivares, Miguel Araya-Alman, Cesar Acevedo-Opazo, Juan Carlos Rey, Paulo Canete-Salinas, Franca Gianni Kurina, Monica Balzarini, Deyanira Lobo, Juan A. Navas-Cortes, Blanca B. Landa and Jose Alfonso Gomez.


To identify the main edaphic variables most correlated to banana productivity in Venezuela and explore the development of an empirical correlation model to predict this productivity based on soil characteristics. Six agricultural fields located in two of the main banana production areas of Venezuela were selected. The experimental sites were in large farms (≥ 50 ha) with four productivity levels in “Gran Nain” bananas, with an area of 4 ha for each of four productive levels: High – High, High – Low, Low – High, and Low – Low. Sixty sampling points were used to characterize the soils under study. Additionally, a Productivity Index (PI) based on three different biometric data on plant productivity was proposed. Through hierarchical statistical analysis, the first 16 soil variables that best explained the PI were selected. Thus, five multiple linear regression models were estimated, using the stepwise regression method. Subsequently, a performance analysis was used to compare the prediction quality range and the error associated with the number of soil variables selected for the proposed models. The selected model included the following soil variables: Mg, penetration resistance, total microbial respiration, bulk density, and omnivorous free-living nematodes. These variables explain the PI with an R2 of 0.55, the mean absolute error (MAE) of 0.8, and the root of the mean squared error (RMSE) of 1.0. The five selected variables are proposed to characterize the soil Productivity Index in banana and could be used in a site-specific soil management program for the banana areas of Venezuela.

Agronomy 20199(5), 255
Published by BOKU:
1Institute of Surveying, Remote Sensing & Land Information (IVFL), University of Natural Resources and Life Sciences, Vienna (BOKU), Peter Jordan Str. 82, 1190 Vienna, Austria
2Department for Soil Health and Plant Nutrition, Austrian Agency for Health and Food Safety (AGES), Spargelfeldstrasse 191, 1220 Vienna, Austria
Remote sensing data, crop growth models, and optimization routines constitute a toolset that can be used together to map crop yield over large areas when access to field data is limited. In this study, Leaf Area Index (LAI) data from the Copernicus Sentinel-2 satellite were combined with the Environmental Policy Integrated Climate (EPIC) model to estimate crop yield using a re-calibration data assimilation approach. The experiment was implemented for a winter wheat crop during two growing seasons (2016 and 2017) under four different fertilization management strategies. A number of field measurements were conducted spanning from LAI to biomass and crop yields. LAI showed a good correlation between the Sentinel-2 estimates and the ground measurements using non-destructive method. A correlating fit between satellite LAI curves and EPIC modelled LAI curves was also observed. The assimilation of LAI in EPIC provided an improvement in yield estimation in both years even though in 2017 strong underestimations were observed. The diverging results obtained in the two years indicated that the assimilation framework has to be tested under different environmental conditions before being applied on a larger scale with limited field data.

European Journal of Agronomy, 123 (2021) 126198


Published by CEBAS-CSIC:

Ignacio Buesaab José M. Mirás-Avalosbc José M. De Paza Fernando Viscontia Felipe Sanzab Antonio Yevesab Diego Guerraab Diego S. Intriglioloab

aInstituto Valenciano de Investigaciones Agrarias (IVIA). Centro Desarrollo Agricultura Sostenible (CEDAS), Unidad asociada al CSIC “Riego en la agricultura mediterránea”, Apartado Ofcial, 46113 Moncada, Valencia, Spain

bDept. Riego. Centro de Edafología y Biología Aplicada del Segura (CEBAS-CSIC), Campus Universitario de Espinardo, PO Box 164, 30100 Murcia, Spain

cUnidad de Suelos y Riegos (asociada a EEAD-CSIC). Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), 50059, Montañana, Zaragoza, Spain



Optimizing water use in vineyards is crucial for ensuring the sustainability of viticulture in semi-arid regions, and this may be achieved by minimizing direct water evaporation from the soil through the use of mulching. In this context, the current study aimed at assessing the combined effects of the vine-row application of an organic mulch (vine prunings) and no-tillage under two water regimes on soil properties, plant water and nutritional status, yield and must composition of grapevine (Vitis vinifera L.) cv. Bobal grown under semi-arid conditions. For this purpose, a field experiment in a split-plot design was carried out for three years (2016–2018) in a mature Bobal vineyard located in Eastern Spain. Two soil management strategies (tillage and organic mulching with no-tillage) were assessed under two water regimes (rainfed and deficit drip irrigation) with four replications per combination. Vine responses were determined by measuring midday stem water potential, leaf nutrient concentrations, pruning weight, yield components and grape composition. Soil properties were assessed at the end of the experiment. Mulching and no-tillage positively affected vine water status under both water regimes, resulting in reductions in grape phenolic composition. Interactive effects of both water regime and soil management on water use efficiency were found. Regardless of soil management practice, irrigation increased yield and pruning weight when compared to rainfed conditions. Soil management had slight effects on vine nutritional status. At the end of the experiment, soil compaction increased and infiltration decreased as a consequence of mulching and no-tillage. Organic mulch and no-tillage improved vine water status, however, considering the final soil surface compaction and low water infiltration rate, longer-term studies are necessary to assess the sustainability of combining both practices.

Partner Publication (CVUT):

Thomas Weninger 1 , Edith Kamptner 1, Tomas Dostal 2 , Adelheid Spiegel 3 , and Peter Strauss 1
Institute for Land and Water Management, Federal Agency of Water Management, Pollnbergstraße 1, 3252 Petzenkirchen, Austria

Faculty of Civil Engineering, Department of Landscape Water Conservation, Czech Technical University Prague, Thákurova 7,
16629 Prague 6, Czech Republic

Institute for Soil Health and Plant Nutrition, Austrian Agency for Health and Food Safety, Spargelfeldstraße 191, 1220 Vienna, Austria
Received October 1, 2020; accepted November 13, 2020
Int. Agrophys., 2020, 34, 463-471

A b s t r a c t.

Reliable estimations of soil physical quality provide valuable information for the evaluation and advancement
of agricultural soil management strategies. In the agriculturally highly productive Pannonian basin in Eastern Austria, little emphasis has been placed on the determination of soil physical quality and corresponding soil degradation risks. Nevertheless, ongoing climate change, especially prolonged drought periods and higher rainfall intensity, will raise the need for appropriate soil management strategies. Soil physical quality was therefore assessed in nine soil profiles in a long-term tillage experiment which has been in operation since 1988 in Eastern Austria. Soil
samples from depths of between 2 and 37 cm and under three different tillage systems (conventional, reduced and minimal tillage) were analysed for various indicators of soil physical quality. The resulting classifications of soil physical quality in the different profiles were compared qualitatively and quantitatively together with an estimation concerning the representativeness of the soil physical quality indicators used. The outcomes showed severe soil
compaction under all tillage treatments and slight improvements in soil physical quality marginally above the working depth for the different treatments. Additionally, conversion to conservation tillage led to less pronounced improvements in soil physical quality under Pannonian conditions than have been reported in more humid climates.
K e y w o r d s: tillage intensity, soil compaction, soil water balance, soil management

Environmental Modelling and Software 131 (2020) 104770


Published by CEBAS-CSIC:

J.M. Ramírez-Cuesta a,*, R.G. Allen b, D.S. Intrigliolo a, A. Kilic c, C.W. Robison b, R. Trezza b, C. Santos d, I.J. Lorite d

a Dpto. Riego, Centro de Edafología y Biología Aplicada del Segura (CEBAS-CSIC), P.O. Box 164, 30100, Murcia, Spain

b University of Idaho, Kimberly Research Center, Kimberly, ID, 83341, USA

c University of Nebraska-Lincoln, Lincoln, NE, 68583-0973, USA

d IFAPA, Centro “Alameda del Obispo”, Alameda del Obispo s/n, Post office box: 3092, 14080, Cordoba, Spain



A novel ArcGIS toolbox that applies the Mapping Evapotranspiration with Internalized Calibration model was developed and tested in a semi-arid environment. The tool, named METRIC-GIS, facilitates the pre-processing operations and the automatic identification of potential calibration and pixels review. The energy balance components obtained from METRIC-GIS were contrasted with those from the original METRIC version (R2 = 1; RMSE = 0 W m−2 or mm day−1 for ETc) Additionally, an irrigated scheme located at southern Spain was considered for assessing Kc variability in the maize fields with METRIC-GIS. The identified spatial variability was mainly due to differences in irrigation regimes, crop management practices, and planting and harvesting dates. This information is critical for developing irrigation advisory strategies that contribute to the area sustainability. The developed tool facilitates data input introduction and reduces computational time by up to 50%, providing a more user-friendly alternative to other existing platforms that use METRIC.

Agricultural Water Management 230 (2020) 105979

Published by CAU and ARO:

Jianchu Shi a, Xun Wu b, Xiaoyu Wang a, Mo Zhang a, Le Han a, Wenjing Zhang a, Wen Liu a, Qiang Zuo a,*, Xiaoguang Wu c, Hongfei Zhang c, Alon Ben-Gal d
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 College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
c Land Management Center of Inner Mongolia Autonomous Region, Hohhot 010020, China
d Soil, Water and Environmental Sciences, Agricultural Research Organization, Gilat Research Center, Mobile Post Negev 85280, Israel


Plant water deficit index (PWDI) represents the extent of water stress by relating soil moisture to the ability of a plant to take up water including consideration of the relative distribution of soil water to roots. However, for a smart irrigation decision support system, we are challenged in determining reliable thresholds of PWDI to initiate irrigation events to achieve predetermined yield and/or water use efficiency (WUE) targets. Taking drip irrigated maize and sprinkler irrigated alfalfa as examples, field experiments were conducted to investigate the
choice and effects of PWDI thresholds. The results indicated that, with increasing PWDI thresholds, irrigation times and quantity of water, as well as crop transpiration, growth, and yield, were all significantly limited while WUE was enhanced except under extremely stressed conditions. To disconnect the unpredictable effects of other factors, yield and WUE were normalized to their corresponding potential values. Within the experimentally determined range of PWDI, relative yield and WUE were described with linear functions for maize, and linear
and quadratic functions for alfalfa, allowing identification of the most efficient threshold value according to the objective parameter of choice. The method described can be adopted in smart irrigation decision support systems with consideration of spatial variability and after further verification and improvement under more complicated situations with various crop types and varieties, environmental conditions, cultivation modes, and wider or dynamic PWDI thresholds allowing regulated deficit irrigation.