Application of the SWAP model to simulate the field water cycle under deficit irrigation in Beijing, China

Ma, Ying; Feng, Shi-Ming; Huo, Zailin; Song, Xinshan

doi:10.1016/j.mcm.2010.11.034

Cited by 53 publications

(28 citation statements)

References 13 publications

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“…Eitzinger et al (2004) found that the SWAP model (version 2.0.7d) insignificantly underestimated the measured soil water content on plots with spring barley, whereas the RMSE values ranged from 1.7 to 3.5% depending on soil type. Ma et al (2011) reported that there were strong correlations (R 2 = 0.77-0.86) between the measured and predicted soil water content after the SWAP model and the average RMSE values of simulated soil water content varied from 2.7 to 4.3% at the depth of 0-20 cm. However, the results of Jiang et al (2011) showed that the SWAP model could overestimate the soil water content at the depth of 15 cm and predict it efficiently at the depths of 35, 65, and 95 cm.…”

Section: Resultsmentioning

confidence: 98%

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

Balashov¹,

Buchkina²,

Rizhiya³

et al. 2014

International Agrophysics

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A b s t r a c t. The objectives of the research were to: fulfil the preliminary assessment of the sensitivity of the soil, water, atmosphere, and plant and denitrification and decomposition models to variations of climate variables based on the existing soil database; validate the soil, water, atmosphere, and plant and denitrification and decomposition modelled outcomes against measured records for soil temperature and water content. The statistical analyses were conducted by the sensitivity analysis, Nash-Sutcliffe efficiency coefficients and root mean square error using measured and modelled variables during three growing seasons. Results of sensitivity analysis demonstrated that: soil temperatures predicted by the soil, water, atmosphere, and plant model showed a more reliable sensitivity to the variations of input air temperatures; soil water content predicted by the denitrification and decomposition model had a better reliability in the sensitivity to daily precipitation changes. The root mean square errors and Nash-Sutcliffe efficiency coefficients demonstrated that: the soil, water, atmosphere, and plant model had a better efficiency in predicting seasonal dynamics of soil temperatures than the denitrification and decomposition model; and among two studied models, the denitrification and decomposition model showed a better capability in predicting the seasonal dynamics of soil water content.K e y w o r d s: agroecosystem modelling, model validation, soil water content, soil temperature, Spodosols

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Section: Resultsmentioning

confidence: 98%

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

Balashov¹,

Buchkina²,

Rizhiya³

et al. 2014

International Agrophysics

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“…Table 2). The detailed measurements and results at the LC, TZ and YC sites were demonstrated by Zhang et al (2004), Ma et al (2011) andFang et al (2007), respectively. The SWAP model was setup at the three sites, which was described in detail in the following.…”

Section: Model Setup At the Three Representative Sitesmentioning

confidence: 84%

“…The vegetation parameters including the LAI and CH at different crop development stages, length of crop cycle, and maximum rooting depth were measured at each site Ma et al, 2011;Fang et al, 2007). The initial crop parameters including the extinction coefficient for diffuse and direct visible light, minimum canopy resistance, limiting pressure heads, and salinity were set to the values recommended by van Dam et al (1997).…”

Section: Model Setup At the Three Representative Sitesmentioning

confidence: 99%

“…It is a physically based agro-hydrological model with extensive features to account for soil heterogeneity and boundary conditions. The SWAP model has been tested and validated for a wide range of climate and agricultural systems in semi-arid areas (Sarwar et al, 2000;Droogers et al, 2001) including the NCP (Ma et al, 2011;Huo et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of optimal irrigation scheduling and groundwater recharge at representative sites in the North China Plain with SWAP model and field experiments

Feng

Song

2015

Computers and Electronics in Agriculture

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a b s t r a c tThe application of water saving irrigation is essential to alleviate the rapid depletion of groundwater resources in water crisis areas such as the North China Plain (NCP). The integrated effects of climate, soil and groundwater conditions on water balance and crop response need to be further studied. It is imperative to investigate spatial differences of irrigation scheduling and groundwater recharge within the NCP for regional water management. In this study, three representative sites including Luancheng (LC), Tongzhou (TZ) and Yucheng (YC) with different precipitation, soil and water table conditions were selected. The SWAP model was established at each site to compare optimal irrigation scheduling and groundwater recharge of the winter wheat-summer maize double cropping system under different hydrological years. Largest optimal irrigation amount and additional irrigation at the winter-dormancy stage of wheat were required for the TZ site in each hydrological year. The optimal irrigation scheduling was almost same at the three sites for summer maize, except that no irrigation was needed at filling stage in dry year at the YC site. The average annual groundwater recharge under optimal irrigation was in the order of YC (108.4 mm), TZ (63.8 mm) and LC (0.4 mm). Furthermore, the groundwater recharge occurred throughout the double cropping seasons in YC, but it occurred only in summer maize season at the LC and TZ sites. The net irrigation amount of the optimal irrigation scheduling was reduced by 51.2%, 24.9% and 77.2% compared to reference practice at the LC, TZ and YC sites, respectively. The amount of groundwater recharge depended on the local precipitation and irrigation, while water table depth and soil texture mainly influenced the delay time of groundwater recharge relative to the water input events.

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“…The Soil, Water, Atmosphere and Plant (SWAP) model has been intensively validated during the past 2 decades (van Dam et al, 1997;Gusev and Nasonova, 2003;Kroes et al, 2000;Gusev et al, 2011;Ma et al, 2011). Different versions of SWAP are validated against various observed hydrothermal characteristics.…”

Section: Introductionmentioning

confidence: 99%

A hybrid model to simulate the annual runoff of the Kaidu River in northwest China

Chen

Bai

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. Fluctuant and complicated hydrological processes can result in the uncertainty of runoff forecasting. Thus, it is necessary to apply the multi-method integrated modeling approaches to simulate runoff. Integrating the ensemble empirical mode decomposition (EEMD), the back-propagation artificial neural network (BPANN) and the nonlinear regression equation, we put forward a hybrid model to simulate the annual runoff (AR) of the Kaidu River in northwest China. We also validate the simulated effects by using the coefficient of determination (R 2 ) and the Akaike information criterion (AIC) based on the observed data from 1960 to 2012 at the Dashankou hydrological station. The average absolute and relative errors show the high simulation accuracy of the hybrid model. R 2 and AIC both illustrate that the hybrid model has a much better performance than the single BPANN. The hybrid model and integrated approach elicited by this study can be applied to simulate the annual runoff of similar rivers in northwest China.

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Application of the SWAP model to simulate the field water cycle under deficit irrigation in Beijing, China

Cited by 53 publications

References 13 publications

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

Evaluation of optimal irrigation scheduling and groundwater recharge at representative sites in the North China Plain with SWAP model and field experiments

A hybrid model to simulate the annual runoff of the Kaidu River in northwest China

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