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Using Water and Agrochemicals in the soil, crop and Vadose Environment (WAVE) model to interpret nitrogen balance and soil water reserve under different tillage managements

Treść / Zawartość
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Warianty tytułu
PL
Użycie modelu Water and Agrochemicals in the soil, crop and Vadose Environment (WAVE) do interpretacji bilansu azotu i glebowych zasobów wody w różnych warunkach uprawy
Języki publikacji
EN
Abstrakty
EN
Applying models to interpret soil, water and plant relationships under different conditions enable us to study different management scenarios and then to determine the optimum option. The aim of this study was using Water and Agrochemicals in the soil, crop and Vadose Environment (WAVE) model to predict water content, nitrogen balance and its components over a corn crop season under both conventional tillage (CT) and direct seeding into mulch (DSM). In this study a corn crop was cultivated at the Irstea experimental station in Montpellier, France under both CT and DSM. Model input data were weather data, nitrogen content in both the soil and mulch at the beginning of the season, the amounts and the dates of irrigation and nitrogen application. The results show an appropriate agreement between measured and model simulations (nRMSE < 10%). Using model outputs, nitrogen balance and its components were compared with measured data in both systems. The amount of N leaching in validation period were 10 and 8 kg·ha–1 in CT and DSM plots, respectively; therefore, these results showed better performance of DSM in comparison with CT. Simulated nitrogen leaching from CT and DSM can help us to assess groundwater pollution risk caused by these two systems.
PL
Zastosowanie modeli do interpretacji zależności, które zachodzą w różnych systemach uprawy między glebą, wodą i roślinami umożliwia zbadanie odmiennych scenariuszy gospodarowania, a następnie wybór optymalnej opcji. Celem badań było zastosowanie modelu WAVE (Water and Agrochemicals in the soil, crop and Vadose Environment) do prognozowania zawartości wody, bilansu azotu i jego form w sezonie wegetacyjnym w warunkach konwencjonalnej uprawy (CT) i siewu bezpośrednio w mulcz (DSM). Oba systemy zastosowano do uprawy zbóż w stacji doświadczalnej Irstea w Montpellier we Francji. Danymi wejściowymi do modelu były warunki pogodowe, zawartość azotu w glebie i w mulczu na początku sezonu wegetacyjnego, dawki i terminy nawodnień oraz nawożenie azotem. Wyniki potwierdzają zgodność pomiarów i symulacji modelowych (nRMSE < 10%). Porównano bilans azotu i jego składników uzyskane za pomocą modelu i na podstawie danych z bezpośrednich pomiarów w obu wariantach upraw. Ilość wymywanego azotu w okresie badań wynosiła 10 (system CT) i 8 kg·ha–1 (system DSM). Taki wynik dowodzi korzystniejszego oddziaływania systemu DSM w porównaniu z systemem CT. Symulacja wymywania azotu z upraw w systemie CT i DSM umożliwia ocenę ryzyka zanieczyszczenia azotem wód gruntowych w wyniku stosowania obu systemów uprawy.
Wydawca
Rocznik
Tom
Strony
33--39
Opis fizyczny
Bibliogr. 27 poz., rys., tab.
Twórcy
autor
  • University of Guilan, Faculty of Agricultural Sciences, Irrigation and Drainage Department, Rasht, Iran
autor
  • University of Guilan, Faculty of Agricultural Sciences, Irrigation and Drainage Department, Rasht, Iran
  • National Research Institute of Science and Technology for Environment and Agriculture, Irstea, Montpellier, France
Bibliografia
  • [1] ADEKALU K.O., FAPOHUNDA H.O. 2006. A numerical model to predict crop yield from soil – water deficit. Biosystems Engineering. Vol. 94(3) p. 359–372.
  • [2] ADDISCOTT T.M. 2000. Tillage, mineralization and leaching. Soil and Tillage Research. Vol. 53 (3–5) p. 163–165.
  • [3] BANNAYAN M., HOOGENBOOM G. 2009. Using pattern recognition for estimating cultivar coefficients of a crop simulation model. Field Crops Research. Vol. 111 p. 290–302.
  • [4] BONFANTE A., BASILE A., ACUTIS M., DE MASCELLIS R., MANNA P., PEREGO A., TERRIBILE F. 2010. Swap, cropsyst and macro comparison in two contrasting soils cropped with maize in northern Italy. Agricultural Water Management. Vol. 97 p. 1051–1062.
  • [5] BROWN G., PASINI A., BENITO N.P., AQUINO A.M., CORREIA E. 2001. Diversity and functional role of soil macrofauna communities in Brazilian no tillage agroecosytems. In: International symposium on managing biodiversity in agricultural ecosystems. Ed. R. Lal. 8–10 November 2001, Montreal, Canada. IISD p. 19.
  • [6] CONFALONIERI R., BELLOCCHI G., TARANTOLA S., ACUTIS M., DONATELLI M., GENOVESE G. 2010. Sensitivity analysis of the rice model warm in Europe: exploring the effects of different locations, climates and methods of analysis on model sensitivity to crop parameters. Environmental Modelling and Software. Vol. 25 p. 479–488.
  • [7] DUWING C., NORMAND B., VAUCLIN M., VACHAUD G., GREEN S., BECQUER T. 2003. Evaluation of the WAVE model for predicting nitrate leaching for two contrasted soil and climate conditions. Vadose Zone Journal. Vol. 2(1) p. 76–89.
  • [8] ERENSTEIN O. 2003. Smallholder conservation farming in the tropics and subtropics: a guide to the development and dissemination of mulching with crop residues and cover crops. Agriculture, Ecosystems and Environment. Vol. 100 p. 17–37.
  • [9] FERNANDEZ J.E., SLAWINSKI C., MORENO F., WALCZAK R.T., VANCLOOSTER M. 2002. Simulating the fate of water in a soil–crop system of a semi-arid Mediterranean area with the WAVE 2.1 and the EURO-ACCESS-II models. Agricultural Water Management. Vol. 56 p. 113–129.
  • [10] KHALEDIAN M.R. 2009. Evaluation de la technique du semis direct en culture irriguee en comparaison avec le systeme de culture conventionnel. Dissertation. University of Montpellier II pp. 138.
  • [11] KHALEDIAN M.R., MAILHOL J.C., RUELLE P., ROSIQUE P. 2009. Adapting pilote model for water and yield management under direct seeding system: the case of corn and durum wheat in a Mediterranean context. Agricultural Water Management. Vol. 96 p. 757–770.
  • [12] MAILHOL J.C., OLUFAYO A.A., RUELLE P. 1997. Sorghum and sunflower evapotranspiration and yield from simulated leaf area index. Agricultural Water Management. Vol. 35 p. 167–182.
  • [13] MARINOV D., QUERNER E., ROELSMA J. 2005. Simulation of water flow and nitrogen transport for a Bulgarian experimental plot using SWAP and ANIMO models. Journal of Contaminant Hydrology. Vol. 77 p. 145–164.
  • [14] MUNOZ-CARPENA R., RITTER A., BOSCH D.D., SCHAFFER B., POTTER T.L. 2008. Summer cover crop impacts on soil percolation and nitrogen leaching from a winter corn field. Agricultural Water Management. Vol. 95 p. 633–644.
  • [15] OTTER-NACKE S., GODWIN D.C., RITCHIE J.T. 1987. Testing and validating the ceres-wheat model in the diverse environments. Agristars publ. No. Ym-15-00407. Ntis, Springfield, va. pp. 147.
  • [16] OUEDRAOGO E., MANDO A., BRUSSAARD L. 2004. Soil macrofaunal-mediated organic resource disappearance in semi-arid West Africa. Applied Soil Ecology. Vol. 27 p. 259–267.
  • [17] PANDA R.K., BEHERA S.K., KASHYAP P.S. 2003. Effective management of irrigation water for wheat under stressed conditions. Agricultural Water Management. Vol. 63(1) p. 37–56.
  • [18] PAYET N., FINDELING A., CHOPART J-L., FEDER F., NICOLINI E., SAINT MACARY H., VAUCLIN M. 2009. Modelling the fate of nitrogen following pig slurry application on a tropical cropped acid soil on the island of reunion (France). Agriculture, Ecosystems and Environment. Vol. 134 p. 218–233.
  • [19] RITTER A., MUNOZ-CARPENA R., REGALADO C.M., VANCLOOSTER M., LAMBOT S. 2004. Analysis of alternative measurement strategies for the inverse optimization of the hydraulic properties of a volcanic soil. Journal of Hydrology. Vol. 295 p. 124–139.
  • [20] SCHROTH G., SALAZAR E., DA SILVA Jr. J.P. 2001. Soil nitrogen mineralization under tree crops and a legume cover crop in multi-strata agroforestry in central Amazonia: spatial and temporal patterns. Experimental Agriculture. Vol. 37 p. 253–267.
  • [21] SEXTON B.T., MONCRIEF J.F., ROSEN C.J., GUPTA S.C., CHENG H.H. 1996. Optimizing nitrogen and irrigation inputs for corn on nitrate leaching and yield on a Coarse-Textured soil. Journal of Environmental Quality. Vol. 25 p. 982–992.
  • [22] SIMUNEK J., SEJNA M., VAN GENUCHTEN M.Th. 1999. The hydrus-2d software package or simulating the onedimensional movement of water, heat and multiple solutes in variably-saturated media. Ver. 2.0. IGWMC-TPS 53. International Ground Water Modeling Center, Colorado School of Mines, Golden, Colorado pp. 251.
  • [23] SPITTERS C.J.T., VAN KEULEN H., VAN KRAAILINGEN D.W.G. 1988. A simple but universal crop growth simulation model, surcros87. In: Simulation and systems management in crop protection. Ed. R. Rabbinge, S.A. Ward, H.H. van Laar. Wageningen, The Netherlands. Pudoc. Simulation monographs. Vol. 32 p. 147–181.
  • [24] TIMMERMAN A., FEYEN J. 2003. The wave model and its application; simulation of the substances water and agrochemicals in the soil, crop and vadose environment. Revista Corpoica. Vol. 4(1) p. 36–41.
  • [25] VAN GENUCHTEN M.Th. 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society America Journal. Vol. 44 p. 892–898.
  • [26] VANCLOOSTER M., VIAENA J., CHRISTIAENS K. 1994. Wave a mathematical model for simulating water and agrochemicals in the soil and vadose environment. Reference and user’s manual, release 2.0.
  • [27]VEREECKEN H., VANCLOOSTER M., SWERTS M., DIELS J. 1991. Simulating water and nitrogen behaviour in soil cropped with winter wheat. Fertilizer Research. Vol. 27 p. 233–243.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-70ef4b31-d138-49f0-8076-ab459b51c62f
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