Parameterization and Evaluation of Predictions of DSSAT/CANEGRO for Brazilian Sugarcane

The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.

Parametrização e avaliação do modelo DSSAT/Canegro para variedades brasileiras de cana-de-açúcar

O objetivo deste trabalho foi parametrizar e avaliar o modelo DSSAT/Canegro para cinco variedades brasileiras de cana-de-açúcar. A parametrização foi realizada a partir do uso de dados biométricos e de crescimento das variedades CTC 4, CTC 7, CTC 20, RB 86-7515 e RB 83-5486, obtidos em cinco localidades brasileiras. Foi realizada análise de sensibilidade local para os principais parâmetros. A parametrização do modelo foi feita por meio da técnica de estimativa da incerteza de probabilidade generalizada ("generalized likelihood uncertainty estimation", Glue). Para a avaliação das predições, foram utilizados, como indicadores estatísticos, o coeficiente de determinação (R²), o índice D de Willmott e a raiz quadrada do erro-médio (RMSE). As variedades CTC apresentaram índice D entre 0,870 e 0,944, para índice de área foliar, altura de colmo, perfilhamento e teor de sacarose. A variedade RB 83-5486 apresentou resultados similares para teor de sacarose e massa de matéria fresca do colmo, enquanto a variedade RB 86-7515 apresentou valores entre 0,665 e 0,873, para as variáveis avaliadas.

Simulação da produtividade de cana-de-açúcar nas regiões nordeste e sudeste do Brasil, utilizando o modelo DSSAT

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Simulação da produtividade de cana-de-açúcar (Saccharum officinarum L.) na região nordeste do Brasil, utilizando o modelo DSSAT

The objective of this study was to simulate the potential stem and sugar yield of sugar cane (Saccharum officinarum L.) in the Northeastern Brazil (Petrolina-PE and Teresina-PI) and analyze 4 varieties in different planting seasons in two environments: irrigated and rainfed cultivars. The model of simulation was DSSAT/CANEGRO (Decision Support System for Agrotechnology Transfer) and the four sugar cane varieties were as follows: RB86 7515, CTC 4, CTC 7 and CTC 20 (all in 1.5 year cycle). Analysis of variance was performed on the results and means were compared using the Tukey test with probability level at 5%. March is the recommended month for planting in Teresina, PI. In Petrolina, PE, rainfed planting is not advisable because of the extended water deficit all year long. In an irrigated environment, no difference was found concerning stem yield as a function of planting season, for all varieties in the study regions. The stem and sugar yields were always higher in irrigated environment as compared with those in rainfed environment in all municipalities and study varieties. The simulation model provided good estimate of stem and sugar yields as compared with experimental data in Teresina, PI.

Parametrização e avaliação do modelo DSSAT/Canegro para variedades brasileiras de cana-de-açúcar

O objetivo deste trabalho foi parametrizar e avaliar o modelo DSSAT/Canegro para cinco variedades brasileiras de cana-de-açúcar. A parametrização foi realizada a partir do uso de dados biométricos e de crescimento das variedades CTC 4, CTC 7, CTC 20, RB 86-7515 e RB 83-5486, obtidos em cinco localidades brasileiras. Foi realizada análise de sensibilidade local para os principais parâmetros. A parametrização do modelo foi feita por meio da técnica de estimativa da incerteza de probabilidade generalizada ("generalized likelihood uncertainty estimation", Glue). Para a avaliação das predições, foram utilizados, como indicadores estatísticos, o coeficiente de determinação (R2), o índice D de Willmott e a raiz quadrada do erro-médio (RMSE). As variedades CTC apresentaram índice D entre 0,870 e 0,944, para índice de área foliar, altura de colmo, perfilhamento e teor de sacarose. A variedade RB 83-5486 apresentou resultados similares para teor de sacarose e massa de matéria fresca do colmo, enquanto a variedade RB 86-7515 apresentou valores entre 0,665 e 0,873, para as variáveis avaliadas.

CSM-IXIM: A New Maize Simulation Model for DSSAT Version 4.5

Th e CERES-Maize model is the most widely used maize (Zea mays L.) model and is a recognized reference for comparing new developments in maize growth, development, and yield simulation. Th e objective of this study was to present and evaluate CSMIXIM, a new maize simulation model for DSSAT version 4.5. Code from CSM-CERES-Maize, the modular version of the model, was modifi ed to include a number of model improvements. Model enhancements included the simulation of leaf area, C assimilation and partitioning, ear growth, kernel number, grain yield, and plant N acquisition and distribution. Th e addition of two genetic coeffi cients to simulate per-leaf foliar surface produced 32% smaller root mean square error (RMSE) values estimating leaf area index than did CSM-CERES. Grain yield and total shoot biomass were correctly simulated by both models. Carbon partitioning, however, showed diff erences. Th e CSM-IXIM model simulated leaf mass more accurately, reducing the CSM-CERES error by 44%, but overestimated stem mass, especially aft er stress, resulting in similar average RMSE values as CSM-CERES. Excessive N uptake aft er fertilization events as simulated by CSM-CERES was also corrected, reducing the error by 16%. Th e accuracy of N distribution to stems was improved by 68%. Th ese improvements in CSM-IXIM provided a stable basis for more precise simulation of maize canopy growth and yield and a framework for continuing future model developments

Initializing the DSSAT-Century model: inverse calibration of carbon pools from apparent soil N mineralization

The CENTURY soil organic matter model was adapted for the DSSAT (Decision Support System for Agrotechnology Transfer), modular format in order to better simulate the dynamics of soil organic nutrient processes (Gijsman et al., 2002). The CENTURY model divides the soil organic carbon (SOC) into three hypothetical pools: microbial or active material (SOC1), intermediate (SOC2) and the largely inert and stable material (SOC3) (Jones et al., 2003). At the beginning of the simulation, CENTURY model needs a value of SOC3 per soil layer which can be estimated by the model (based on soil texture and management history) or given as an input. Then, the model assigns about 5% and 95% of the remaining SOC to SOC1 and SOC2, respectively. The model performance when simulating SOC and nitrogen (N) dynamics strongly depends on the initialization process. The common methods (e.g. Basso et al., 2011) to initialize SOC pools deal mostly with carbon (C) mineralization processes and less with N. Dynamics of SOM, SOC, and soil organic N are linked in the CENTURY-DSSAT model through the C/N ratio of decomposing material that determines either mineralization or immobilization of N (Gijsman et al., 2002). The aim of this study was to evaluate an alternative method to initialize the SOC pools in the DSSAT-CENTURY model from apparent soil N mineralization (Napmin) field measurements by using automatic inverse calibration (simulated annealing). The results were compared with the ones obtained by the iterative initialization procedure developed by Basso et al., 2011.

Simulações no CROPGRO/DSSAT do carbono no solo cultivado com soja sob plantio direto e preparo convencional, em clima subtropical do sul do Brasil.

Objetivou-se avaliar o potencial do modelo CROPGRO, inserido no DSSAT v.4,0 (Decision Support System for Agrotechnology Transfer) para simular o carbono no solo, no sistema plantio direto. Os dados foram coletados na Estação Experimental da Universidade Federal do Rio Grande do Sul (EEA/UFRGS), em Eldorado do Sul, durante o ano agrícola 2003/04, num delineamento em faixas, em Argissolo Vermelho distrófico típico. A semeadura da soja (cv. Fepagro RS10 - ciclo longo) ocorreu em 20/11/03 para uma população inicial em torno de 300 mil plantas ha-1. Foram utilizados dois sistemas de manejo do solo: preparo convencional (PC) e sistema plantio direto (PD) irrigados (I) e não irrigados (NI). Foram inseridos no DSSAT dados edáficos, meteorológicos diários e da cultura. Adotou-se o método Ceres, no CROPGROSoja para simular o teor de carbono (C) no solo. As simulações mostraram que há maior estoque de C em plantio direto irrigado em relação ao preparo convencional, demonstrando sensibilidade do CROPGRO-Soja ao manejo do solo. Os mais elevados resíduos de C em solo sob plantio direto evidenciam mitigações de emissões desse gás para a atmosfera em cultivos na região estudada.

The impact of El Nino Southern Oscillation phases on off-season maize yield for a subtropical region of Brazil

In recent years, maize has become one of the main alternative crops for the autumn winter growing season in the central-western and southeastern regions of Brazil. However, water deficits, sub-optimal temperatures and low solar radiation levels are common problems that are experienced during this growing season by local farmers. One methodology to assess the impact of variable weather conditions on crop production is the use of crop simulation models. The goal of this study was to evaluate the effect of climate variability on maize yield for a subtropical region of Brazil. Specific objectives for this study were (1) to analyse the effect of El Nino Southern Oscillation (ENSO) on precipitation and air temperature for four locations in the state of Sao Paulo and (2) to analyse the impact of ENSO on maize grown off-season for the same four locations using a crop simulation model. For each site, historical weather data were categorised as belonging to one of three phases of ENSO: El Nino (warm sea surface temperature anomalies in the Pacific), La Nina (cool sea surface temperature anomalies) or neutral, based on an index derived from observed sea surface temperature anomalies. During El Nino, there is a tendency for an increase in the rainfall amount during May for the four selected locations, and also during April, mainly in three of the locations, resulting in an increase in simulated maize yield planted between February 15 and March 15. In general, there was a decrease in the simulated yield for maize grown off-season during neutral years. This study showed how a crop model can be used to assess the impact of climate variability on the yield of maize grown off-season in a subtropical region of Brazil. The outcomes of this study can be very useful for both policy makers and local farmers for agricultural planning and decision making. Copyright (C) 2009 Royal Meteorological Society

Simulation of growth and development of irrigated cowpea in Piauí State by CROPGRO model

The objective of this work was to adapt the CROPGRO model, which is part of the DSSAT system, for simulating the cowpea (Vigna unguiculata) growth and development under soil and climate conditions of the Baixo Parnaíba region, Piauí State, Brazil. In the CROPGRO, only input parameters that define crop species, cultivars, and ecotype were changed in order to characterize the cowpea crop. Soil and climate files were created for the considered site. Field experiments without water deficit were used to calibrate the model. In these experiments, dry matter (DM), leaf area index (LAI), yield components and grain yield of cowpea (cv. BR 14 Mulato) were evaluated. The results showed good fit for DM and LAI estimates. The medium values of R² and medium absolute error (MAE) were, respectively, 0.95 and 264.9 kg ha-1 for DM, and 0.97 and 0.22 for LAI. The difference between observed and simulated values of plant phenology varied from 0 to 3 days. The model also presented good performance for yield components simulation, excluding 100-grain weight, for which the error ranged from 20.9% to 34.3%. Considering the medium values of crop yield in two years, the model presented an error from 5.6%.

Simulação do risco de deficit hídrico em regiões de expansão do cultivo de cana-de-açúcar no Brasil

O objetivo deste trabalho foi determinar o risco de deficit hídrico para a cultura da cana-de-açúcar em diferentes regiões brasileiras, com foco nas áreas de expansão. Para tanto, utilizou-se o modelo CSM-Canegro, para simular a produtividade da cana-planta de 12 meses, em 30 localidades. A partir dos valores estimados de produtividades potencial e atingível (produtividade sem irrigação), definiram-se as classes de risco de deficit hídrico de acordo com os níveis de eficiência climática, dada pela razão entre essas produtividades. O modelo simulou o efeito dos diferentes tipos de solo e datas de plantio sobre a produtividade, o que possibilitou caracterizar o risco de deficit hídrico associado à cultura. A região de maior risco é Petrolina, PE, enquanto as regiões de menor risco são as similares a Recife, PE, e Araguaína, TO.

Évaluation de la vulnérabilité des fermes productrices de maïs-grain du Québec aux variabilités et changements climatiques : les cas de Montérégie-Ouest et du Lac-Saint-Jean-Est

Réalisées aux échelles internationales et nationales, les études de vulnérabilité aux changements et à la variabilité climatiques sont peu pertinentes dans un processus de prise de décisions à des échelles géographiques plus petites qui représentent les lieux d’implantation des stratégies de réponses envisagées. Les études de vulnérabilité aux changements et à la variabilité climatiques à des échelles géographiques relativement petites dans le secteur agricole sont généralement rares, voire inexistantes au Canada, notamment au Québec. Dans le souci de combler ce vide et de favoriser un processus décisionnel plus éclairé à l’échelle de la ferme, cette étude cherchait principalement à dresser un portrait de l’évolution de la vulnérabilité des fermes productrices de maïs-grain des régions de Montérégie-Ouest et du Lac-St-Jean-Est aux changements et à la variabilité climatiques dans un contexte de multiples sources de pression. Une méthodologie générale constituée d'une évaluation de la vulnérabilité globale à partir d’une combinaison de profils de vulnérabilité aux conditions climatiques et socio-économiques a été adoptée. Pour la période de référence (1985-2005), les profils de vulnérabilité ont été dressés à l’aide d’analyses des coefficients de variation des séries temporelles de rendements et de superficies en maïs-grain. Au moyen de méthodes ethnographiques associées à une technique d’analyse multicritère, le Processus d’analyse hiérarchique (PAH), des scénarios d’indicateurs de capacité adaptative du secteur agricole susmentionné ont été développés pour la période de référence. Ceux-ci ont ensuite servi de point de départ dans l’élaboration des indicateurs de capacité de réponses des producteurs agricoles pour la période future 2010-2039. Pour celle-ci, les deux profils de vulnérabilité sont issus d’une simplification du cadre théorique de « Intergovernmental Panel on Climate Change » (IPCC) relatif aux principales composantes du concept de vulnérabilité. Pour la dimension « sensibilité » du secteur des fermes productrices de maïs-grain des deux régions agricoles aux conditions climatiques, une série de données de rendements a été simulée pour la période future. Ces simulations ont été réalisées à l’aide d’un couplage de cinq scénarios climatiques et du modèle de culture CERES-Maize de « Decision Support System for Agrotechnology Transfer » (DSSAT), version 4.0.2.0. En ce qui concerne l’évaluation de la « capacité adaptative » au cours de la période future, la construction des scénarios d’indicateurs de cette composante a été effectuée selon l’influence potentielle des grandes orientations économiques et environnementales considérées dans l’élaboration des lignes directrices des deux familles d’émissions de gaz à effet de serre (GES) A2 et A1B. L’application de la démarche méthodologique préalablement mentionnée a conduit aux principaux résultats suivants. Au cours de la période de référence, la région agricole du Lac-St-Jean-Est semblait être plus vulnérable aux conditions climatiques que celle de Montérégie-Ouest. En effet, le coefficient de variation des rendements du maïs-grain pour la région du Lac-St-Jean-Est était évalué à 0,35; tandis que celui pour la région de Montérégie-Ouest n’était que de 0,23. Toutefois, par rapport aux conditions socio-économiques, la région de Montérégie-Ouest affichait une vulnérabilité plus élevée que celle du Lac-St-Jean-Est. Les valeurs des coefficients de variation pour les superficies en maïs-grain au cours de la période de référence pour la Montérégie-Ouest et le Lac-St-Jean-Est étaient de 0,66 et 0,48, respectivement. Au cours de la période future 2010-2039, la région du Lac-St-Jean-Est serait, dans l’ensemble, toujours plus vulnérable aux conditions climatiques que celle de Montérégie-Ouest. Les valeurs moyennes des coefficients de variation pour les rendements agricoles anticipés fluctuent entre 0,21 et 0,25 pour la région de Montérégie-Ouest et entre 0,31 et 0,50 pour la région du Lac-St-Jean-Est. Néanmoins, en matière de vulnérabilité future aux conditions socio-économiques, la position relative des deux régions serait fonction du scénario de capacité adaptative considéré. Avec les orientations économiques et environnementales considérées dans l’élaboration des lignes directrices de la famille d’émission de GES A2, les indicateurs de capacité adaptative du secteur à l’étude seraient respectivement de 0,13 et 0,08 pour la Montérégie-Ouest et le Lac-St-Jean-Est. D’autre part, en considérant les lignes directrices de la famille d’émission de GES A1B, la région agricole du Lac-St-Jean-Est aurait une capacité adaptative légèrement supérieure (0,07) à celle de la Montérégie-Ouest (0,06). De façon générale, au cours de la période future, la région du Lac-St-Jean-Est devrait posséder une vulnérabilité globale plus élevée que la région de Montérégie-Ouest. Cette situation s’expliquerait principalement par une plus grande vulnérabilité de la région du Lac-St-Jean-Est aux conditions climatiques. Les résultats de cette étude doivent être appréciés dans le contexte des postulats considérés, de la méthodologie suivie et des spécificités des deux régions agricoles examinées. Essentiellement, avec l’adoption d’une démarche méthodologique simple, cette étude a révélé les caractéristiques « dynamique et relative » du concept de vulnérabilité, l’importance de l’échelle géographique et de la prise en compte d’autres sources de pression et surtout de la considération d’une approche contraire à celle du « agriculteur réfractaire aux changements » dans les travaux d’évaluation de ce concept dans le secteur agricole. Finalement, elle a aussi présenté plusieurs pistes de recherche susceptibles de contribuer à une meilleure évaluation de la vulnérabilité des agriculteurs aux changements climatiques dans un contexte de multiples sources de pression.

Simulating improved combinations tillage-rotation under dryland conditions.

The adequate combination of reduced tillage and crop rotation could increase the viability of dry land agriculture in Mediterrenean zones. Crop simulation models can support to examine various tillage-rotation combinations and explore management scenarios. The decision support system for agrotechnology transfer (DSSAT) (Hoogenboom et al., 2010) provides a suite of crop models suitable for this task. The objective of this work was to simulate the effects of two tillage systems, conventional tillage (ConvT) and no tillage (NoT), and three crop rotations, continuous cereal (CC), fallow-cereal (FallowC) and legume-cereal (LegumeC), under dry conditions, on the cereal yield, soil organic carbon (SOC) and nitrogen (SON) in a 15-year experiment, comparing these simulations with field observations.

Improving the management of water and nitrogen resources in cropping systems by using simulation models

Los modelos de simulación de cultivos permiten analizar varias combinaciones de laboreo-rotación y explorar escenarios de manejo. El modelo DSSAT fue evaluado bajo condiciones de secano en un experimento de campo de 16 años en la semiárida España central. Se evaluó el efecto del sistema de laboreo y las rotaciones basadas en cereales de invierno, en el rendimiento del cultivo y la calidad del suelo. Los modelos CERES y CROPGRO se utilizaron para simular el crecimiento y rendimiento del cultivo, mientras que el modelo DSSAT CENTURY se utilizó en las simulaciones de SOC y SN. Tanto las observaciones de campo como las simulaciones con CERES-Barley, mostraron que el rendimiento en grano de la cebada era mas bajo para el cereal continuo (BB) que para las rotaciones de veza (VB) y barbecho (FB) en ambos sistemas de laboreo. El modelo predijo más nitrógeno disponible en el laboreo convencional (CT) que en el no laboreo (NT) conduciendo a un mayor rendimiento en el CT. El SOC y el SN en la capa superficial del suelo, fueron mayores en NT que en CT, y disminuyeron con la profundidad en los valores tanto observados como simulados. Las mejores combinaciones para las condiciones de secano estudiadas fueron CT-VB y CT-FB, pero CT presentó menor contenido en SN y SOC que NT. El efecto beneficioso del NT en SOC y SN bajo condiciones Mediterráneas semiáridas puede ser identificado por observaciones de campo y por simulaciones de modelos de cultivos. La simulación del balance de agua en sistemas de cultivo es una herramienta útil para estudiar como el agua puede ser utilizado eficientemente. La comparación del balance de agua de DSSAT , con una simple aproximación “tipping bucket”, con el modelo WAVE más mecanicista, el cual integra la ecuación de Richard , es un potente método para valorar el funcionamiento del modelo. Los parámetros de suelo fueron calibrados usando el método de optimización global Simulated Annealing (SA). Un lisímetro continuo de pesada en suelo desnudo suministró los valores observados de drenaje y evapotranspiración (ET) mientras que el contenido de agua en el suelo (SW) fue suministrado por sensores de capacitancia. Ambos modelos funcionaron bien después de la optimización de los parámetros de suelo con SA, simulando el balance de agua en el suelo para el período de calibración. Para el período de validación, los modelos optimizados predijeron bien el contenido de agua en el suelo y la evaporación del suelo a lo largo del tiempo. Sin embargo, el drenaje fue predicho mejor con WAVE que con DSSAT, el cual presentó mayores errores en los valores acumulados. Esto podría ser debido a la naturaleza mecanicista de WAVE frente a la naturaleza más funcional de DSSAT. Los buenos resultados de WAVE indican que, después de la calibración, este puede ser utilizado como "benchmark" para otros modelos para periodos en los que no haya medidas de campo del drenaje. El funcionamiento de DSSAT-CENTURY en la simulación de SOC y N depende fuertemente del proceso de inicialización. Se propuso como método alternativo (Met.2) la inicialización de las fracciones de SOC a partir de medidas de mineralización aparente del suelo (Napmin). El Met.2 se comparó con el método de inicialización de Basso et al. (2011) (Met.1), aplicando ambos métodos a un experimento de campo de 4 años en un área en regadío de España central. Nmin y Napmin fueron sobreestimados con el Met.1, ya que la fracción estable obtenida (SOC3) en las capas superficiales del suelo fue más baja que con Met.2. El N lixiviado simulado fue similar en los dos métodos, con buenos resultados en los tratamientos de barbecho y cebada. El Met.1 subestimó el SOC en la capa superficial del suelo cuando se comparó con una serie observada de 12 años. El crecimiento y rendimiento del cultivo fueron adecuadamente simulados con ambos métodos, pero el N en la parte aérea de la planta y en el grano fueron sobreestimados con el Met.1. Los resultados variaron significativamente con las fracciones iniciales de SOC, resaltando la importancia del método de inicialización. El Met.2 ofrece una alternativa para la inicialización del modelo CENTURY, mejorando la simulación de procesos de N en el suelo. La continua emergencia de nuevas variedades de híbridos modernos de maíz limita la aplicación de modelos de simulación de cultivos, ya que estos nuevos híbridos necesitan ser calibrados en el campo para ser adecuados para su uso en los modelos. El desarrollo de relaciones basadas en la duración del ciclo, simplificaría los requerimientos de calibración facilitando la rápida incorporación de nuevos cultivares en DSSAT. Seis híbridos de maiz (FAO 300 hasta FAO 700) fueron cultivados en un experimento de campo de dos años en un área semiárida de regadío en España central. Los coeficientes genéticos fueron obtenidos secuencialmente, comenzando con los parámetros de desarrollo fenológico (P1, P2, P5 and PHINT), seguido de los parámetros de crecimiento del cultivo (G2 and G3). Se continuó el procedimiento hasta que la salida de las simulaciones estuvo en concordancia con las observaciones fenológicas de campo. Después de la calibración, los parámetros simulados se ajustaron bien a los parámetros observados, con bajos RMSE en todos los casos. Los P1 y P5 calibrados, incrementaron con la duración del ciclo. P1 fue una función lineal del tiempo térmico (TT) desde emergencia hasta floración y P5 estuvo linealmente relacionada con el TT desde floración a madurez. No hubo diferencias significativas en PHINT entre híbridos de FAO-500 a 700 , ya que tuvieron un número de hojas similar. Como los coeficientes fenológicos estuvieron directamente relacionados con la duración del ciclo, sería posible desarrollar rangos y correlaciones que permitan estimar dichos coeficientes a partir de la clasificación del ciclo. ABSTRACT Crop simulation models allow analyzing various tillage-rotation combinations and exploring management scenarios. DSSAT model was tested under rainfed conditions in a 16-year field experiment in semiarid central Spain. The effect of tillage system and winter cereal-based rotations on the crop yield and soil quality was evaluated. The CERES and CROPGRO models were used to simulate crop growth and yield, while the DSSAT CENTURY was used in the SOC and SN simulations. Both field observations and CERES-Barley simulations, showed that barley grain yield was lower for continuous cereal (BB) than for vetch (VB) and fallow (FB) rotations for both tillage systems. The model predicted higher nitrogen availability in the conventional tillage (CT) than in the no tillage (NT) leading to a higher yield in the CT. The SOC and SN in the top layer, were higher in NT than in CT, and decreased with depth in both simulated and observed values. The best combinations for the dry land conditions studied were CT-VB and CT-FB, but CT presented lower SN and SOC content than NT. The beneficial effect of NT on SOC and SN under semiarid Mediterranean conditions can be identified by field observations and by crop model simulations. The simulation of the water balance in cropping systems is a useful tool to study how water can be used efficiently. The comparison of DSSAT soil water balance, with a simpler “tipping bucket” approach, with the more mechanistic WAVE model, which integrates Richard’s equation, is a powerful method to assess model performance. The soil parameters were calibrated by using the Simulated Annealing (SA) global optimizing method. A continuous weighing lysimeter in a bare fallow provided the observed values of drainage and evapotranspiration (ET) while soil water content (SW) was supplied by capacitance sensors. Both models performed well after optimizing soil parameters with SA, simulating the soil water balance components for the calibrated period. For the validation period, the optimized models predicted well soil water content and soil evaporation over time. However, drainage was predicted better by WAVE than by DSSAT, which presented larger errors in the cumulative values. That could be due to the mechanistic nature of WAVE against the more functional nature of DSSAT. The good results from WAVE indicate that, after calibration, it could be used as benchmark for other models for periods when no drainage field measurements are available. The performance of DSSAT-CENTURY when simulating SOC and N strongly depends on the initialization process. Initialization of the SOC pools from apparent soil N mineralization (Napmin) measurements was proposed as alternative method (Met.2). Method 2 was compared to the Basso et al. (2011) initialization method (Met.1), by applying both methods to a 4-year field experiment in a irrigated area of central Spain. Nmin and Napmin were overestimated by Met.1, since the obtained stable pool (SOC3) in the upper layers was lower than from Met.2. Simulated N leaching was similar for both methods, with good results in fallow and barley treatments. Method 1 underestimated topsoil SOC when compared with a 12-year observed serial. Crop growth and yield were properly simulated by both methods, but N in shoots and grain were overestimated by Met.1. Results varied significantly with the initial SOC pools, highlighting the importance of the initialization procedure. Method 2 offers an alternative to initialize the CENTURY model, enhancing the simulation of soil N processes. The continuous emergence of new varieties of modern maize hybrids limits the application of crop simulation models, since these new hybrids should be calibrated in the field to be suitable for model use. The development of relationships based on the cycle duration, would simplify the calibration requirements facilitating the rapid incorporation of new cultivars into DSSAT. Six maize hybrids (FAO 300 through FAO 700) were grown in a 2-year field experiment in a semiarid irrigated area of central Spain. Genetic coefficients were obtained sequentially, starting with the phenological development parameters (P1, P2, P5 and PHINT), followed by the crop growth parameters (G2 and G3). The procedure was continued until the simulated outputs were in good agreement with the field phenological observations. After calibration, simulated parameters matched observed parameters well, with low RMSE in most cases. The calibrated P1 and P5 increased with the duration of the cycle. P1 was a linear function of the thermal time (TT) from emergence to silking and P5 was linearly related with the TT from silking to maturity . There were no significant differences in PHINT between hybrids from FAO-500 to 700 , as they had similar leaf number. Since phenological coefficients were directly related with the cycle duration, it would be possible to develop ranges and correlations which allow to estimate such coefficients from the cycle classification.