Evaluation of modified DRAINMOD in predicting groundwater table fluctuations and yield of canola in paddy fields under snowy conditions (case study: Rasht Iran)

Hassanpour, Bahareh; Parsinejad, Masoud; Dalivand, F Salahshour; Kossari, H.

doi:10.1002/ird.614

Cited by 8 publications

(11 citation statements)

References 15 publications

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“…(2009) and Hassanpour et al . (2011). In the calibration system, the averages of daily simulated and measured NO 3 − ‐N concentrations were, respectively, 9.1 and 14.1 mg l −1 during three canola‐growing seasons.…”

Section: Resultsmentioning

confidence: 99%

Assessing water and nitrate‐N losses from subsurface‐drained paddy lands by DRAINMOD‐N II

Hashemi

Darzi‐Naftchali

2020

Irrigation and Drainage

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In this study, the effects of various drainage systems on water and nitrate-N losses were investigated using DRAINMOD-N II. Required field data were obtained during three growing seasons of canola in a subsurface drainage pilot in Mazandaran Province, northern Iran. The calibrated model was used to assess the effects of different drain depths (D = 0.10-0.90 m with 0.10 m intervals) and spacing (L = 10-90 m with 10 m intervals) on seasonal drainage water and NO 3 −-N concentration in drainage effluents. DRAINMOD-N II performance was assessed using different criteria including absolute deviation (AD), root mean square error (RMSE) and determination coefficient (R 2). The simulated and observed drainage discharges (0.97 vs 0.96 mm day −1) and NO 3-N concentrations (9.1 vs 14.1 mg l −1) were in good agreement in the calibration process. The model performance was also acceptable in the validation process (AD = 0.59-0.79 mm day −1 ; RMSE = 1.01-1.28 mm day −1 ; R 2 = 0.59-0.79 for drainage discharge and AD = 8.3-16.3 mg l −1 ; RMSE = 12.4-27.6 mg l −1 ; R 2 = 0.4 for NO 3-N). Based on the scenario analyses, the D0.40L50 drainage system was the best one, resulting in fewer environmental effects from the nitrate-N and water loss viewpoints.

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Section: Resultsmentioning

confidence: 99%

Assessing water and nitrate‐N losses from subsurface‐drained paddy lands by DRAINMOD‐N II

Hashemi

Darzi‐Naftchali

2020

Irrigation and Drainage

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“…The current study has also revealed that relatively few studies report validation of waterlogging models; of those that did, DRAINMOD (Evans et al, 1991; Hardjoamidjojo & Skaggs, 1982; Hassanpour et al, 2011), APSIM‐Oryza, and GLAM‐WOFOST (Li et al, 2016) were adequate (RMSE between simulated and observed yield was 382 and 453 kg ha −1 , respectively); APSIM‐Soybean and APSIM‐Oryza fit the data well.…”

Section: Synthesis: Pathways Used To Model Waterloggingmentioning

confidence: 60%

“…The model described only 63% of the variation in observed corn yields for the 12‐year period. Hassanpour et al (2011) also reported an overestimation of simulated canola yield in evaluating the performance of surface drainage and canola crop growth in DRAINMOD. The discrepancy between predicted and measured yields in this case may be attributed to the empirical factors in Equation 3.…”

Section: Modeling Crop Waterloggingmentioning

confidence: 98%

“…DRAINMOD Waterlogging stress is computed using a drainage index (SDI, aeration stress) and a crop specific sensitivity factor (SDI). , , Hassanpour et al (2011), Hiler et al (1974), and Skaggs et al (2012) CROPRWaterlogged dry matter growth is calculated by an aeration factor w AE and the maximum efficiency of the aeration factor (A AE , kg ha…”

Section: Swagman Destinymentioning

confidence: 99%

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The State of the Art in Modeling Waterlogging Impacts on Plants: What Do We Know and What Do We Need to Know

et al. 2020

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Models are key tools in our quest to better understand the impacts of soil waterlogging on plant growth and crop production. Here, we reviewed the state of the art of modeling approaches and compared the conceptual design of these models with recent experimental findings. We show that many models adopt an aeration stress (AS) principle where surplus water reduces air-filled porosity, with implications for root growth. However, subsequent effects of AS within each model vary considerably. In some cases, AS inhibits biomass accumulation (e.g. AquaCrop), altering processes prior to biomass accumulation such as light interception (e.g. APSIM), or photosynthesis and carbohydrate accumulation (e.g. SWAGMAN Destiny). While many models account for stage-dependent waterlogging effects, few models account for experimentally observed delays in phenology caused by waterlogging. A model intercomparison specifically designed for long-term waterlogged conditions (APSIM-Oryza) with models developed for dryland conditions with transient waterlogging would advance our understanding of the current fitness for purpose of exsiting frameworks for simulating transient waterlogging in dryland cropping systems. Of the point-based dynamic models examined here, APSIM-Soybean and APSIM-Oryza simulations most closely matched with the observed data, while GLAM-WOFOST achieved the highest performance of the spatial-regional models examined. We conclude that future models should incorporate waterlogging effects on genetic tolerance parameters such as (1) phenology of stress onset, (2) aerenchyma, (3) root hydraulic conductance, (4) nutrient-use efficiency, and (5) plant ion (e.g. Fe/Mn) tolerance. Incorporating these traits/effects into models, together with a more systematic model intercomparison using consistent initialization data, will significantly improve our understanding of the relative importance of such factors in a systems context, including feedbacks between biological factors, emergent properties, and sensitive variables responsible for yield losses under waterlogging.

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“…This further facilitates to take proper decisions in case of complicated situations when collection of field information were both costly and laborious. The results of the DRAINMOD model performance in South Africa (Malota and Senzanje, 2015 and Sema Kale, 2011), Egypt (Neveen et al, 2013), Israel (Sanai and Jain, 2006), Iowa (Singh et al, 2006), Iran (Hassanpour et al, 2011, Samipour et al, 2010and Ebrahimian et al, 2010 and Iraq (Hamdi et al, 2006), confirmed that DRAINMOD can reliably imitate SSDS for various soils and weather situations. Further, it is also found from reviews that the DRAINMOD model is widely used model for design of SSDS under shallow water table conditions as reported by Prasher et al (1996) Malota and Senzanje (2015) reported the prediction of WTDs and drain discharges successfully through DRAINMOD in irrigated conditions.…”

Section: Introductionmentioning

confidence: 80%

Calibration of DRAINMOD for prediction of water table depths and drain discharges under waterlogged Vertisols of Maharashtra, India

Rathod¹,

Dahiwalkar

Gorantiwar

et al. 2019

JANS

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An estimation of optimal design parameters of subsurface drainage system through monitoring of water table depths and drain discharges are expensive in terms of time and money. The simulation modeling is an effective tool for estimation of drainage design parameters at less cost and short time. In view to this, calibration of DRAINMOD model for prediction of water table depths and drain discharges were conducted by installing subsurface drainage system with 40 m drain spacing and 1.0 m drain depth at Agricultural Research Station, Kasbe Digraj, Dist. Sangli (Maharashtra) during 2012-13 to 2013-14. The field data on water table depth and drain discharge were used for calibration of DRAINMOD model. The input data files on climatic, soil, crop and drainage design system parameters were attached to DRAINMOD model and calibrated successfully. It is found that both observed and simulated water table depths and drain discharges showed a fluctuating trend and predicted both water table depths and drain discharges closely with the observed values during frequent rainy days and following the rainy days. The DRAINMOD model reliably predicted water table depths with a goodness of fit (R2 = 0.97), MAE (12.23 cm), RMSE (15.49 cm) and CRM (0.05); drain discharges with R2 of 0.93, MAE of 0.095 mm day-1, RMSE of 0.1876 mm day-1and CRM of 0.04. Thus, the calibrated DRAINMOD model can be used to simulate the water table depths and drain discharges in semi-arid climatic conditions of Maharashtra and in turn to estimate and evaluate drain spacing and depth.

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Evaluation of modified DRAINMOD in predicting groundwater table fluctuations and yield of canola in paddy fields under snowy conditions (case study: Rasht Iran)

Cited by 8 publications

References 15 publications

Assessing water and nitrate‐N losses from subsurface‐drained paddy lands by DRAINMOD‐N II

Assessing water and nitrate‐N losses from subsurface‐drained paddy lands by DRAINMOD‐N II

The State of the Art in Modeling Waterlogging Impacts on Plants: What Do We Know and What Do We Need to Know

Calibration of DRAINMOD for prediction of water table depths and drain discharges under waterlogged Vertisols of Maharashtra, India

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