Managing water scarcity in European and Chinese cropping systems

Author: Ana

农场水平下生物燃料作物的采用及其对流域水分平衡的影响

Published: 16 4 月 2021
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Categories: 出版物

Sustainability 2020, 12(24), 10596;

https://doi.org/10.3390/su122410596 (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

Abstract

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.

与西班牙业务组交流经验

Published: 14 4 月 2021
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Categories: 成果传播

On April the 7th, SHui partners at IAS-CSIC participated in the MAPA conference on “Exchange of experiences between Operational Groups and Projects focus on soils. MAPA is Ministry of Agriculture, Fisheries and Food from Spain.

During the webinar, SHui offered collaboration opportunities with Operational Groups and showed its current experience with one of them.

2021年2月水项目委员会会议

Published: 30 3 月 2021
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Categories: 大事件与媒体

Since the pandemic started and due to the travel restrictions, the SHui consortium, Project Board (PB) Meetings are taking place telematically every 4 months. On the 23rd February 2021, a new one was organized by IAS-CSIC with a total of 30 people attending. The main objectives of this PB meeting were:

  1. to show project progress since the last one in October, and for WPs to delineate
  2. the activities to perform, AND
  3. results to deliver during 2021.

Each WP leader and their teams shared their advances during the previous months and updated plans for the immediate future. This means that during the upcoming months, communication dissemination activities will be strengthened to increase the reach and impact of future publications and APPs. Finally, the planning for the final Conference in China at the end of 2021 started. However, details will need to be defined during March/April 2021.

利用NDVI对农作物冠层覆盖进行建模研究

Published: 23 2 月 2021
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Computers and Electronics in Agriculture 2021,  182,  106038, https://doi.org/10.1016/j.compag.2021.106038

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

 

Abstract

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

利用基于数字调度植物水分亏缺指数的智能灌溉来优化作物产量和水分利用效率

Published: 5 2 月 2021
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Agricultural Water Management 2021, 248, 106774 https://doi.org/10.1016/j.agwat.2021.106774

 

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

Highlights

  • 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.

 

Abstract

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.

委内瑞拉两大主要种植区土壤性质与香蕉生产力的关系

Published: 14 12 月 2020
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Journal of Soil Science and Plant Nutrition volume 20, pages2512–2524(2020)
https://link.springer.com/article/10.1007/s42729-020-00317-8
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.

Abstract

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.

将Sentinel-2叶面积指数数据同化为基于物理的作物生长模型以估算产量

Published: 14 12 月 2020
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Published by BOKU:
Francesco Novelli1, Heide Spiegel2, Taru Sandén2 and Francesco Vuolo1
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

Abstract

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.

半干旱葡萄园的土壤管理:不同水分条件下有机覆盖和免耕的结合效应

Published: 28 11 月 2020
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European Journal of Agronomy, 123 (2021) 126198

https://doi.org/10.1016/j.eja.2020.126198

 

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

 

Abstract

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.