Managing water scarcity in European and Chinese cropping systems

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Simulating water lateral inflow and its contribution to spatial variations of rainfed wheat yields

Published: 1 July 2022
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In European Journal of Agronomy

Authors: Tomás R. Tenreiro, Jakub Jeřábek, José A.Gómez, David Zumr, Gonzalo Martínez, Margarita García-Vila, and ElíasFereres

Abstract

Spatial variations of crop yields are commonly observed in typical rainfed systems worldwide. It is accepted that such variations are likely to be associated, among other factors, with water spatial variations due to lateral water flows occurring in fields with undulating topography. However, some of the main processes governing water spatial distribution such as lateral flow are not entirely considered by the most commonly adopted crop simulation models. This brings uncertainty to the process of yield simulation at field-scale, especially under water-limited conditions. Although it is expected that lateral water movement determines spatial variations of crop yields, it is still unclear what is the net contribution of lateral water inflows (LIF) to spatial variations of rainfed yields in fields of undulating topography. In this sense, by combining field experimentation, simulation models (HYDRUS-1D and AquaCrop), and the use of artificial neural networks, we assessed the occurrence and magnitude of LIF, and their impact on wheat yields in Cordoba, Spain, over a 30-year period. Seasonal precipitation varied over 30 years from 212.8 to 759.5 mm, and cumulative LIF ranged from 30 to 125 mm. The ratio of seasonal cumulative LIF divided by seasonal precipitation varied from 10.7% to 38.9% over the 30 years. The net contribution of LIF to spatial variations of rainfed potential yields showed to be relevant but highly irregular among years. Despite the inter-annual variability, typical of Mediterranean conditions, the occurrence of LIF caused simulated wheat yields to vary + 16% from up to downslope areas of the field. The net yield responses to LIF, in downslope areas were on average 383 kg grain yield (GY) ha−1, and the LIF marginal water productivity reached 24.6 ( ± 13.2) kg GY ha−1 mm−1 in years of maximum responsiveness. Decision makers are encouraged to take water spatial variations into account when adjusting management to different potential yielding zones within the same field. However, this process is expected to benefit from further advances in in-season weather forecasting that should be coupled with a methodological approach such as the one presented here.

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The Effects of Agricultural Conservation Practices on the Small Water Cycle: From the Farm- to the Management-Scale

Published: 9 May 2022
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In Land

Authors: Nina Noreika, Tailin Li, Julie Winterova, Josef Krasa and Tomas Dostal

Abstract

Reinforcing the small water cycle is considered to be a holistic approach to both water resource and landscape management. In an agricultural landscape, this can be accomplished by incorporating agricultural conservation practices; their incorporation can reduce surface runoff, increase infiltration, and increase the water holding capacity of a soil. Some typical agricultural conservation practices include: conservation tillage, contour farming, residue incorporation, and reducing field sizes; these efforts aim to keep both water and soil in the landscape. The incorporation of such practices has been extensively studied over the last 40 years. The Soil and Water Assessment Tool (SWAT) was used to model two basins in the Czech Republic (one at the farm-scale and a second at the management-scale) to determine the effects of agriculture conservation practice adoption at each scale. We found that at the farm-scale, contour farming was the most effective practice at reinforcing the small water cycle, followed by residue incorporation. At the management-scale, we found that the widespread incorporation of agricultural conservation practices significantly reinforced the small water cycle, but the relative scale and spatial distribution of their incorporation were not reflected in the SWAT scenario analysis. Individual farmers should be incentivized to adopt agricultural conservation practices, as these practices can have great effects at the farm-scale. At the management-scale, the spatial distribution of agricultural conservation practice adoption was not significant in this study, implying that managers should incentivize any adoption of such practices and that the small water cycle would be reinforced regardless.

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Keeping Up with Phosphorus Dynamics: Overdue Conceptual Changes in Vegetative Filter Strip Research and Management

Published: 6 April 2022
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In Frontiers in Environmental Science

Authors: David Ramler, Marc Stutter, Gabriele Weigelhofer, John N. Quinton, Rebecca Hood-Nowotny and Peter Strauss

Abstract

Vegetative filter strips (VFS) are best management practices with the primary aim of protecting surface waters from eutrophication resulting from excess nutrient inputs from agricultural sources. However, we argue that there is a substantial time and knowledge lag from the science underpinning VFS to policy and implementation. Focussing on phosphorus (P), we strive to introduce a holistic view on VFS that accounts for the whole functional soil volume, temporal and seasonal effects, the geospatial context, the climatic and physico-chemical basic conditions, and the intricate bio-geochemical processes that govern nutrient retention, transformation, and transport. Specifically, we suggest a step-wise approach to custom VFS designs that links and matches the incoming P from event to multi-annual timescales from the short- and mid-term processes of P retention in the effective soil volume and to the longer-term P retention and offtake coupled to the soil-vegetation system. An a priori assessment of the P export potential should be followed by bespoke VFS designs, in line with local conditions and socio-economic and ecological constraints. To cope with increasingly nutrient saturated or functionally insufficient VFS installed over the last decades, concepts and management strategies need to encompass the transition in understanding of VFS as simple nutrient containers to multifunctional buffer zones that have a complex inner life. We need to address these associated emerging challenges and integrate their implications more thoroughly into VFS research, monitoring, policy, and implementation than ever before. Only then we may get VFS that are effective, sustainable, and persistent.

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Spatiotemporal normalized ratio methodology to evaluate the impact of field-scale variable rate application

Published: 14 March 2022
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In Precision Agriculture

Authors: L. Katz, A. Ben-Gal, M. I. Litaor, A. Naor, M. Peres, I. Bahat, Y. Netzer, A. Peeters, V. Alchanatis & Y. Cohen

Abstract

Wide assimilation of precision agriculture among farmers is currently dependent on the ability to demonstrate its efficiency at the field-scale. Yet, most experiments that compare variable-rate vs uniform application (VRA and UA) are performed in strips, concentrated in a small portion of the field with limited extrapolation to the field scale. A spatiotemporal normalized ratio (STNR) methodology is proposed to evaluate the impact of VRA compared with UA for on-farm trials at the field scale. It incorporates a base year in which the whole plot is managed with UA and consecutive years in which half of the plot is managed with UA and the other half is managed with VRA. Additionally, a novel normalized relative comparison index (NRCI) is presented where the ratios of VRA/UA sub-plots are compared between a base year and a consecutive year, for any measured parameter. The NRCI determines the impact of VRA on variability using statistical measures of dispersion (variability measures) and on performance with statistical measures of central tendency (performance measures). Variability measures with NRCI values lower or higher than 1 indicate VRA management decreased or increased variability. Performance measures with NRCI lower or higher than 1 indicate subplot impairment or improvement, respectively due to VRA management. The methodology was demonstrated on a commercial drip irrigated peach orchard and a wine grape vineyard. NRCI results showed that VRA drip irrigation reduced water status in-field variability but did not necessarily increase yield. The benefits and limitations of the proposed design are discussed.

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Expansion of olive orchards and their impact on the cultivation and landscape through a case study in the countryside of Cordoba (Spain)

Published: 7 March 2022
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In Land Use Policy

Authors: G.Guzmán, A.Boumahdi, J.A.Gómez

Abstract

The sustainability of farming systems has been enhanced by legislation on different scales, but at the same time these policies also promote more productive systems through farming intensification (e.g., use of irrigation or high tree densities). This is the case of olive orchard expansion on cereal cropland in recent decades. This study analyses the impact of this expansion on orchard characteristics and landscape elements in a case study in the ’campiña‘ of Cordoba in Southern Spain based on the evolution of their surface and typologies during the period from 2005 to 2018. Our results show that olive orchards doubled their surface after the 13-year period, from 7997.8 to 16,447.6 ha. On average the new orchards tended to have higher plant density and a more frequent use of irrigation in the study period. Despite this trend towards intensification, the current situation shows a majority of rainfed (76.4%) and medium tree densities, 120–200 trees/ha, (42.7%) of the area. Nevertheless, newly intensified orchards are arising in the region, resulting in a mosaic of orchards of different characteristics (slope, tree density, soil type) and agricultural managements (irrigation, ground cover vegetation).

In addition, this characterization was complemented with an inventory of the existing semi-natural elements associated with these orchards to identify the current state of the regional agricultural landscape. A total number of 507 isolated trees and different linear and polygonal landscape elements (343.9 km and 714.0 ha, respectively), mainly segmented, were inventoried. From these polygonal landscape elements, a significant fraction (e.g., slopes, gullies, water banks and non-productive strips/faces) remains unvegetated (57%). Therefore, these elements must be considered in multiscale agricultural policies as potential restoration areas to enhance ecosystem service provisioning.

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Rhizosphere microbiomes can regulate plant drought tolerance

Published: 3 March 2022
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In Pedosphere

Authors: Mehtab Muhammad ASLAM, Eyalira J. OKAL, Aisha Lawan IDRIS, Zhang QIAN, Weifeng XU, Joseph K. KARANJA, Shabir H. WANI, Wei YUAN

Abstract

Beneficial root-associated rhizospheric microbes play a key role in maintaining host plant growth and can potentially allow drought-resilient crop production. The complex interaction of root-associated microbes mainly depends on soil type, plant genotype, and soil moisture. However, drought is the most devastating environmental stress that strongly reduces soil biota and can restrict plant growth and yield. In this review, we discussed our mechanistic understanding of drought and microbial response traits. Additionally, we highlighted the role of beneficial microbes and plant-derived metabolites in alleviating drought stress and improving crop growth. We proposed that future research might focus on evaluating the dynamics of root-beneficial microbes under field drought conditions. The integrative use of ecology, microbial, and molecular approaches may serve as a promising strategy to produce more drought-resilient and sustainable crops.

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Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations

Published: 24 December 2021
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In “Geosci. Model Dev.“

Authors: Shannon de Roos, Gabriëlle J. M. De Lannoy, and Dirk Raes

Abstract

The current intensive use of agricultural land is affecting the land quality and contributes to climate change. Feeding the world’s growing population under changing climatic conditions demands a global transition to more sustainable agricultural systems. This requires efficient models and data to monitor land cultivation practices at the field to global scale.

This study outlines a spatially distributed version of the field-scale crop model AquaCrop version 6.1 to simulate agricultural biomass production and soil moisture variability over Europe at a relatively fine resolution of 30 arcsec (∼1 km). A highly efficient parallel processing system is implemented to run the model regionally with global meteorological input data from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), soil textural information from the Harmonized World Soil Database version 1.2 (HWSDv1.2), and generic crop information. The setup with a generic crop is chosen as a baseline for a future satellite-based data assimilation system. The relative temporal variability in daily crop biomass production is evaluated with the Copernicus Global Land Service dry matter productivity (CGLS-DMP) data. Surface soil moisture is compared against NASA Soil Moisture Active–Passive surface soil moisture (SMAP-SSM) retrievals, the Copernicus Global Land Service surface soil moisture (CGLS-SSM) product derived from Sentinel-1, and in situ data from the International Soil Moisture Network (ISMN). Over central Europe, the regional AquaCrop model is able to capture the temporal variability in both biomass production and soil moisture, with a spatial mean temporal correlation of 0.8 (CGLS-DMP), 0.74 (SMAP-SSM), and 0.52 (CGLS-SSM). The higher performance when evaluating with SMAP-SSM compared to Sentinel-1 CGLS-SSM is largely due to the lower quality of CGLS-SSM satellite retrievals under growing vegetation. The regional model further captures the short-term and inter-annual variability, with a mean anomaly correlation of 0.46 for daily biomass and mean anomaly correlations of 0.65 (SMAP-SSM) and 0.50 (CGLS-SSM) for soil moisture. It is shown that soil textural characteristics and irrigated areas influence the model performance. Overall, the regional AquaCrop model adequately simulates crop production and soil moisture and provides a suitable setup for subsequent satellite-based data assimilation.

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The Small Water Cycle in the Czech Landscape: How Has It Been Affected by Land Management Changes Over Time?

Published: 24 December 2021
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In “Sustainability“

Authors: by Nina Noreika, Julie Winterová, Tailin Li, Josef Krása and Tomáš Dostál.

Abstract

For the Czech Republic to recover from the effects of past mismanagement, it is necessary to determine how its landscape management can be improved holistically by reinforcing the small water cycle. We conducted a scenario analysis across four time periods using SWAT (Soil and Water Assessment Tool) to determine the effects of land use, land management, and crop rotation shifts since the 1800s in what is now the Czech Republic. The 1852 and 1954 land-use scenarios behaved the most similarly hydrologically across all four scenarios, likely due to minimal landscape transformation and the fact that these two scenarios occur prior to the widespread incorporation of subsurface tile drainages across the landscape. Additionally, the crop rotation of 1920–1938 reinforces the small water cycle the most, while that of 1950–1989 reinforces the small water cycle the least. Diversified crop rotations should be incentivized to farmers, and increasing the areas of forest, brush, and permanent grassland should be prioritized to further reinforce the small water cycle. It is necessary to foster relationships and open communication between watershed managers, landowners, and scientists to improve the small water cycle and to pave the way for successful future hydrological modeling in the Czech Republic.

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Global sensitivity analysis of crop yield and transpiration from the FAO-AquaCrop model for drylands environments

Published: 2 December 2021
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In “Field Crops Research”

Authors: YangLu, Tendai P.Chibarabada, Matthew F.McCabe, Gabriëlle J.M.De Lannoy, JustinSheffield

Abstract

The application of crop models towards improved local scale prediction and precision management requires the identification and description of the major factors influencing model performance. Such efforts are particularly important for dryland areas which face rapid population growth and increasing constraints on water supplies. In this study, a global sensitivity analysis on crop yield and transpiration was performed for 49 parameters in the FAO-AquaCrop model (version 6.0) across three dryland farming areas with different climatic conditions. The Morris screening method and the variance-based Extended Fourier Amplitude Sensitivity Test (EFAST) method were used to evaluate the parameter sensitivities of several staple crops (maize, soybean or winter wheat) under dry, normal and wet scenarios. Results suggest that parameter sensitivities vary with the target model output (e.g., yield, transpiration) and the wetness condition. By synthesizing parameter sensitivities under different scenarios, the key parameters affecting model performance under both high and low water stress were identified for the three crops. Overall, factors relevant to root development tended to have large impacts under high water stress, while those controlling maximum canopy cover and senescence were more influential under low water stress. Parameter sensitivities were also shown to be stage-dependent from a day-by-day analysis of canopy cover and biomass simulations. Subsequent comparison with AquaCrop version 5.0 suggests that AquaCrop version 6.0 is less sensitive to uncertainties in soil properties.

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Multi-Step Calibration Approach for SWAT Model Using Soil Moisture and Crop Yields in a Small Agricultural Catchment

Published: 2 December 2021
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In “Water”

Authors: Francis Kilundu Musyoka, Peter Strauss, Guangju Zhao, Raghavan Srinivasan and Andreas Klik

Abstract

The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approach, where all the parameters governing various hydrological processes are calibrated simultaneously. Results showed that the model was capable of successfully predicting surface runoff, groundwater flow, soil profile water content, total streamflow and sediment yields with Nash-Sutcliffe efficiency (NSE) of greater than 0.75. Crop yields were also well simulated with a percent bias (PBIAS) ranging from −17% to 14%. Surface runoff calibration had the highest impact on streamflow output, improving NSE from 0.39 to 0.77. The step-wise calibration approach performed better for streamflow prediction than the simultaneous calibration approach. The results of this study show that the step-wise calibration approach is more accurate, and provides a better representation of different hydrological components and processes than the simultaneous calibration approach.
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