Evaluation of the impact of various agricultural practices on nitrate leaching under the root zone of potato and sugar beet using the STICS soil–crop model

Jégo, Guillaume; Martinez, Miren; Antigüedad, Iñaki; Launay, Marie; Sánchez‐Pérez, José‐Miguel; Justes, Éric

doi:10.1016/j.scitotenv.2008.01.021

Cited by 65 publications

(33 citation statements)

References 33 publications

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“…However, nitrogen leaching is influenced by other factors such as temporal distribution and intensity of rain events, irrigation and nitrogen management or fertilizer type, which are not evaluated by the regression model [45]. However, the values computed using the regression model are in close agreement with results reported by other authors for different irrigated crops in Spain [46][47][48], with a nitrogen-leaching rate between 8% and 30% of the total nitrogen application for maize, 10%-15% for sugar beet and 35%-59% for potatoes. CWUModel has simulated a nitrogen-leaching rate of 12%-31%, 11%-17% and 30%-50% respectively.…”

Section: Limitation Of the Grey Water Footprint Analysissupporting

confidence: 84%

The Water Footprint of Agriculture in Duero River Basin

2015

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Abstract:The aim of this paper is to evaluate the green, blue and grey water footprint (WF) of crops in the Duero river basin. For this purpose CWUModel was developed. CWUModel is able to estimate the green and blue water consumed by crops and the water needed to assimilate the nitrogen leaching resulting from fertilizer application. The total WF of crops in the Spanish Duero river basin was simulated as 9473 Mm 3 /year (59% green, 20% blue and 21% grey). Cultivation of crops in rain-fed lands is responsible for 5548 Mm 3 /year of the WF (86% green and 14% grey), whereas the irrigated WF accounts for 3924 Mm 3 /year (20% green, 47% blue and 33% grey). Barley is the crop with the highest WF, with almost 37% of the total WF for the crops simulated for the basin, followed by wheat (17%). Although maize makes up 16% of the total WF of the basin, the blue and grey components comprise the 36% of the total blue and grey WF in the basin. The relevance of green water goes beyond the rain-fed production, to the extent that in long-cycle irrigated cereals it accounts for over 40% of the total water consumed. Nonetheless, blue water is a key component in agriculture, both for production and economically. The sustainability assessment shows that the current blue water consumption of crops causes a significant or severe water stress level in 2-5 months of the year. The anticipated expansion of irrigation in the coming years could hamper water management, despite the Duero being a relatively humid basin.

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Section: Limitation Of the Grey Water Footprint Analysissupporting

confidence: 84%

The Water Footprint of Agriculture in Duero River Basin

2015

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“…Although nitrate leaching in regions appears to be an inevitable process, an improvement in management practices leading to higher N fertilizer use efficiency is thought to reduce the potential for groundwater nitrate contamination. The environmental impact of agricultural pollutants depends on many different factors, such as fertilizer type, fixation, crop type, hydro-meteorological conditions (climatology and hydrogeology), crop management practices and soil characteristics [13]. Several authors have demonstrated the effect of different types of land cover on the hydrology of watersheds [14], a factor that is also directly linked to the nutrient transport within a watershed, particularly within the root zone.…”

Section: Nhmentioning

confidence: 99%

“…For the multiple environmental processes involved in the dynamics of N, such as atmosphere deposition and pesticide and fertilizer use, mathematical modeling is extremely valuable because it can help quantify the pollution, determine balances at the watershed scale and guide decisions to improve management [13] [15]. Thus, a model-based study is required to obtain information on the environmental effects considering anthropogenic data.…”

Section: Nhmentioning

confidence: 99%

SWAT Modeling of Nitrogen Dynamics Considering Atmospheric Deposition and Nitrogen Fixation in a Watershed Scale

Jung¹,

Kim²

2017

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The Soil and Water Assessment Tool (SWAT) nitrogen (N) water quality model considers the artificial inputs associated with human activities, including point and nonpoint source pollution loads. Although SWAT has the ability to simulate atmospheric N deposition and fixation, they were not considered in the modeling research. N deposition from the air is an important and considerable pathway for the input of N species into watersheds and water bodies, causing soil and water body acidification and the leaching of N into surface and groundwater, resulting in eutrophication and degraded water quality. The goal of this study is to assess the effects of atmospheric and agricultural N loads on stream water quality at the watershed scale. ) of total N was 0.69 considering atmospheric deposition, whereas it was 0.33 when removing the deposition effect. The results of this study demonstrate the potential for using the N dynamics between the atmosphere and land for SWAT assessments of nonpoint source pollution and for modeling stream water quality.

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“…STICS was developed by the French National Institute for Agronomic Research (INRA), comprising a large multidisciplinary community of researchers, from microclimate and soils to crop sciences (Brisson, 2004). This is a generic crop model that can be applied to a wide variety of crops, such as wheat (Brisson et al, 2002;Rodriguez et al, 2004), maize (Bruckler et al, 2000;Brisson et al, 2002;Debaeke, 2004), sugarcane (Valade et al, 2014) and banana (Brisson et al, 1998) and for many other purposes such as irrigation strategies (Katerji et al, 2010), carbon balances (de Noblet-Ducoudre et al, 2004), soil drainage (Tournebize et al, 2004) and nitrate contamination (Ledoux et al, 2007;Jego et al, 2008) and climate change impact assessment (Courault and Ruget, 2001;Juin et al, 2004;Gonzalez-Camacho et al, 2008). de Cortazar-Atauri (2006) adapted this model for grapevines assessing the necessary parameterizations.…”

Section: Dynamic Crop Modelsmentioning

confidence: 99%

Application of crop modelling to portuguese viticulture: implementation and added-values for strategic planning

Costa

Fraga

Malheiro

et al. 2015

Ciência Téc. Vitiv.

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SUMMARYGrapevine (Vitis vinifera L.) is a very important crop in Portugal, where the viticultural sector plays a central role in the national economy. The present study provides a review of most relevant research on grapevine modelling, giving particular emphasis to its past and future applicability to Portuguese conditions. A brief overview of the national sector, as well as of the prevailing physical and biological environments and viticultural practices is provided. Further, the terroir concept is discussed in view of the main controlling factors of grapevine development. Several crop models, either statistical or dynamic, that have reliably simulated grapevine/vineyard parameters, such as phenology, yield and quality, are referred. Statistical models are based on statistically significant relationships between a number of predictors and a given grapevine parameter. Dynamic crop models simulate plant growth and development and holistically integrate crop phenotype, soil profiles, weather and climate data and management practices in their simulations. Dynamic crop models are then becoming important decision support systems in viticulture. Additionally, they allow testing the effects of soils, management decisions and weather on crops. However, only a few dynamic models can properly simulate grapevine performance. Several studies also apply crop models under future conditions to assess the detrimental climate change impacts on grapevines. These crop models can be either applied to real-time monitoring and short-range predictions or to develop long-term climate change projections for the Portuguese viticulture. These studies will represent important added-values for the competitiveness and future sustainability of the winemaking sector in Portugal. RESUMOA videira (Vitis vinifera L.) é uma cultura de grande relevo em Portugal, onde o sector vitivinícola desempenha um papel central na economia nacional. O presente estudo fornece uma revisão de pesquisas mais relevantes sobre a modelação da videira, dando especial ênfase à sua aplicabilidade às condições específicas portuguesas. É dada uma visão sucinta do sector nacional, bem como das condições físicas, biológicas e práticas vitivinícolas predominantes. O conceito de terroir é discutido tendo em conta os principais fatores condicionantes do desenvolvimento da videira. São referidos vários modelos de culturas, estatísticos e dinâmicos, que têm simulado com sucesso as características da videira/vinha, fenologia, produtividade e qualidade. Os modelos estatísticos são baseados em relações estatisticamente significativas entre um número de preditores e uma determinada característica da videira. Os modelos dinâmicos simulam o crescimento e desenvolvimento da planta de forma holística, integrando nas suas simulações o fenótipo da cultura, perfis de solo, dados meteorológicos e práticas culturais. Por este motivo, os modelos dinâmicos estão a tornar-se importantes sistemas de apoio à decisão em viticultura. Além disso, permitem prever os efeitos do solo, das práticas cul...

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Evaluation of the impact of various agricultural practices on nitrate leaching under the root zone of potato and sugar beet using the STICS soil–crop model

Cited by 65 publications

References 33 publications

The Water Footprint of Agriculture in Duero River Basin

The Water Footprint of Agriculture in Duero River Basin

SWAT Modeling of Nitrogen Dynamics Considering Atmospheric Deposition and Nitrogen Fixation in a Watershed Scale

Application of crop modelling to portuguese viticulture: implementation and added-values for strategic planning

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