Evaluation of the RZWQM-CERES-Maize hybrid model for maize production

Li, Ma; Hoogenboom, Gerrit; Ahuja, Lajpat R.; Ascough, J. C.; Saseendran, S. A.

doi:10.1016/j.agsy.2005.02.001

Cited by 125 publications

(77 citation statements)

References 20 publications

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“…Thus, further studies using state-of-the-art agricultural system models are required to investigate the effects of climate change and heightened CO 2 on drainage, N loss and crop yield. Given its capability to accurately predict responses of crops and agroecosystems to changes in climate and especially to elevated CO 2 (Ko et al 2012), the Root Zone Water Quality Model (RZWQM2; Ahuja et al 2000;Ma et al 2005Ma et al , 2006 should be reliable conducting such research. RZWQM2 is an agricultural system model which considers hydrology, plant nutrition and growth, pesticide transport and transformation and agricultural management practices.…”

Section: List Of Acronymsmentioning

confidence: 99%

Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field

Wang

Xue

et al. 2015

Climatic Change

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The effect of climate change on crop production and nitrate-nitrogen (NO3-N) pollution from subsurface drained fields is of a great concern. Using the calibrated and validated RZWQM2 (coupled with CERESMaize and CROPGRO in DSSAT), the potential effects of climate change and elevated atmospheric CO2 concentrations (CO2) on tile drainage volume, NO3-N losses, and crop production were assessed integrally for the first time for a corn-soybean rotation cropping system near Gilmore City, Iowa. RZWQM2 simulated results under 20-year observed historical weather data (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009) and ambient CO2 were compared to those under 20-year projected future meteorological data (2045)(2046)(2047)(2048)(2049)(2050)(2051)(2052)(2053)(2054)(2055)(2056)(2057)(2058)(2059)(2060)(2061)(2062)(2063)(2064) and elevated CO2, with all management practices unchanged. The results showed that, under the future climate, tile drainage, NO3-N loss and flow-weighted average NO3-N concentration (FWANC) increased by 4.2 cm year−1 (+14.5 %), 11.6 kg N ha−1 year−1 (+33.7 %) and 2.0 mg L−1 (+16.4 %), respectively. Yields increased by 875 kg ha−1 (+28.0 %) for soybean [Glycine max (L.) Merr.] but decreased by 1380 kg ha−1(−14.7 %) for corn (Zea mays L.). The yield of the C3 soybean increased mostly due to CO2enrichment but increased temperature had negligible effect. However, the yield of C4 corn decreased largely because of fewer days to physiological maturity due to increased temperature and limited benefit of elevated CO2 to corn yield under subhumid climate. Relative humidity, short wave radiation and wind speed had small or negligible impacts on FWANC or grain yields. With the predicted trend, this study suggests that to mitigate NO3-N pollution from subsurface drained corn-soybean field in Iowa is a more challenging task in the future without changing current management practices. This study also demonstrates the advantage of an agricultural system model in assessing climate change impacts on water quality and crop production. Further investigation on management practice adaptation is needed. RightsWorks produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted. Abstract The effect of climate change on crop production and nitrate-nitrogen (NO 3 -N) pollution from subsurface drained fields is of a great concern. Using the calibrated and validated RZWQM2 (coupled with CERES-Maize and CROPGRO in DSSAT), the potential effects of climate change and elevated atmospheric CO 2 concentrations (CO 2 ) on tile drainage volume, NO 3 -N losses, and crop production were assessed integrally for the first time for a corn-soybean rotation cropping system near Gilmore City, Iowa. RZWQM2 simulated results under 20-year observed historical weather data (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006...

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Section: List Of Acronymsmentioning

confidence: 99%

Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field

Wang

Xue

et al. 2015

Climatic Change

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“…As a water quality model, RZWQM has been used widely for addressing pesticide management issues Ahuja et al, 1996, Azevedo et al, 1997bMa et al, 2004;Malone et al, 2004a,b,c). Recently, the CROPGRO and CERES crop growth models of DSSAT v3.5 (Decision Support System for Agrotechnology Transfer) were linked to RZWQM, which provided additional options for simulating plant growth (Ma et al, 2005(Ma et al, , 2006.…”

Section: Introductionmentioning

confidence: 99%

RZWQM simulated effects of crop rotation, tillage, and controlled drainage on crop yield and nitrate-N loss in drain flow

Ma¹,

Malone²,

Heilman

et al. 2007

Geoderma

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Accurate simulation of agricultural management effects on N loss in tile drainage is vitally important for understanding hypoxia in the Gulf of Mexico. An experimental study was initiated in 1978 at Nashua, Iowa of the USA to study long-term effects of tillage, crop rotation, and N management practices on subsurface drainage flow and associated N losses. The Root Zone Water Quality Model (RZWQM) was applied to evaluate various management effects in several previous studies. In this study, the simulation results were further analyzed for management effects (tillage, crop rotation, and controlled drainage) on crop production and N loss in drain flow. RZWQM simulated the observed increase in N concentration in drain flow with increasing tillage intensity from NT (no-till) to RT (ridge till) to CP (chisel plow) and to MP (moldboard plow). It also adequately simulated tillage effects on yearly drain flow and yearly N loss in drain flow. However, the model failed to simulate lower corn and soybean yields under NT than under MP, CP, and RT. On the other hand, RZWQM adequately simulated lower yearly drain flow and lower flow-weighted N concentration in drain flow under CS (corn-soybean) and SC (soybean-corn) than under CC (continuous corn). The model adequately simulated higher corn yield under CS and SC than under CC. Applying the newly suggested N management practice for the Midwest of controlled drainage, the model simulated a 30% reduction in drain flow and a 29% decrease in N losses in drain flow under controlled drainage (CD) compared to free drainage (FD). With most of the simulations in reasonably close agreement with observations, we concluded that RZWQM is a promising tool for quantifying the relative effects of tillage, crop rotation, and controlled drainage on N loss in drainage flow. Further improvements on simulated management effects on crop yield and N mineralization are needed, however. RightsWorks produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted. AbstractAccurate simulation of agricultural management effects on N loss in tile drainage is vitally important for understanding hypoxia in the Gulf of Mexico. An experimental study was initiated in 1978 at Nashua, Iowa of the USA to study long-term effects of tillage, crop rotation, and N management practices on subsurface drainage flow and associated N losses. The Root Zone Water Quality Model (RZWQM) was applied to evaluate various management effects in several previous studies. In this study, the simulation results were further analyzed for management effects (tillage, crop rotation, and controlled drainage) on crop production and N loss in drain flow. RZWQM simulated the observed increase in N concentration in drain flow with increasing tillage intensity from NT (no-till) to RT (ridge till) to CP (chisel plow) and to MP (moldboard plow). It also adequately simulated tillage effects on yearly drain flow and yearly N loss in drain flow....

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“…In addition to a generic crop model that can be parameterized to simulate specific crops, the model contains the CSM (Cropping System Models) crop modules of DSSAT v4.6 for simulation of specific crops [25,[43][44][45] (http://arsagsoftware.ars.usda.gov/). Studies verifying the capabilities of RZWQM2 for explaining and managing dryland and irrigated cropping systems in the Great Plains have been reported (for example, [43,[46][47][48]). Most recently, Saseendran et al [33] successfully modeled the effects of planting dates on seed cotton production in the Mississippi Delta region (Figure 1).…”

Section: Rzwqm2 Modelmentioning

confidence: 99%

Vulnerabilities and Adapting Irrigated and Rainfed Cotton to Climate Change in the Lower Mississippi Delta Region

Anapalli

Fisher

Reddy

et al. 2016

Climate

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Abstract:Anthropogenic activities continue to emit potential greenhouse gases (GHG) into the atmosphere leading to a warmer climate over the earth. Predicting the impacts of climate change (CC) on food and fiber production systems in the future is essential for devising adaptations to sustain production and environmental quality. We used the CSM-CROPGRO-cotton v4.6 module within the RZWQM2 model for predicting the possible impacts of CC on cotton (Gossypium hirsutum) production systems in the lower Mississippi Delta (MS Delta) region of the USA. The CC scenarios were based on an ensemble of climate projections of multiple GCMs (Global Climate Models/General Circulation Models) for climate change under the CMIP5 (Climate Model Inter-comparison and Improvement Program 5) program, that were bias-corrected and spatially downscaled (BCSD) at Stoneville location in the MS Delta for the years 2050 and 2080. Four Representative Concentration Pathways (RCP) drove these CC projections: 2.6, 4.5, 6.0, and 8.5 (these numbers refer to radiative forcing levels in the atmosphere of 2.6, 4.5, 6.0, and 8.5 W·m −2 ), representing the increasing levels of the greenhouse gas (GHG) emission scenarios for the future, as used in the Intergovernmental Panel on Climate Change-Fifth Assessment Report (IPCC-AR5). The cotton model within RZWQM2, calibrated and validated for simulating cotton production at Stoneville, was used for simulating production under these CC scenarios. Under irrigated conditions, cotton yields increased significantly under the CC scenarios driven by the low to moderate emission levels of RCP 2.6, 4.5, and 6.0 in years 2050 and 2080, but under the highest emission scenario of RCP 8.5, the cotton yield increased in 2050 but declined significantly in year 2080. Under rainfed conditions, the yield declined in both 2050 and 2080 under all four RCP scenarios; however, the yield still increased when enough rainfall was received to meet the water requirements of the crop (in about 25% of the cases). As an adaptation measure, planting cotton six weeks earlier than the normal (historical average) planting date, in general, was found to boost irrigated cotton yields and compensate for the lost yields in all the CC scenarios. This early planting strategy only partially compensated for the rainfed cotton yield losses under all the CC scenarios, however, supplemental irrigations up to 10 cm compensated for all the yield losses.

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Evaluation of the RZWQM-CERES-Maize hybrid model for maize production

Cited by 125 publications

References 20 publications

Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field

Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field

RZWQM simulated effects of crop rotation, tillage, and controlled drainage on crop yield and nitrate-N loss in drain flow

Vulnerabilities and Adapting Irrigated and Rainfed Cotton to Climate Change in the Lower Mississippi Delta Region

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