Root Zone Water Quality Model (RZWQM2): Model Use, Calibration, and Validation

Ma, Liwang; Ahuja, Lajpat R.; Nolan, Bernard T.; Malone, Robert W.; Trout, Thomas J.; Qi, Zhiming

doi:10.13031/2013.42252

Cited by 149 publications

(69 citation statements)

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“…It has gained wide popularity in developing and evaluating management practices (Ma et al, 2012a). The DSSAT crop models were incorporated into RZWQM2 to better simulate crop growth and development (Jones et al, 2003;Ma et al, 2006aMa et al, , 2006b).…”

Section: Rzwqm2 Descriptionmentioning

confidence: 99%

Optimizing Irrigation Rates for Cotton Production in an Extremely Arid Area Using RZWQM2-Simulated Water Stress

Che¹,

Qi²,

Gu³

et al. 2017

Transactions of the ASABE

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Section: Rzwqm2 Descriptionmentioning

confidence: 99%

Optimizing Irrigation Rates for Cotton Production in an Extremely Arid Area Using RZWQM2-Simulated Water Stress

Che¹,

Qi²,

Gu³

et al. 2017

Transactions of the ASABE

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“…MACRO (Jarvis and Larsbo et al, 2012); SWAT ; SHAW (Flerchinger et al, 2012); EPIC/APEX (Wang et al, 2012); ADAPT ; RZWQM (Ma et al, 2012); MIKE SHE (Jaber and Shukla, 2012). 3.…”

Section: Key Recommendationsmentioning

confidence: 99%

Hydrologic and Water Quality Models: Key Calibration and Validation Topics

Moriasi¹,

Zeckoski²,

Arnold³

et al. 2015

Trans. ASABE

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ABSTRACT. As a continuation of efforts to provide a common background and platform for development of calibration and validation (C/V) guidelines for hydrologic and water quality (H/WQ) modeling, ASABE members worked to determine critical topics related to model C/V, perform a synthesis of a previously published special collection of articles and other relevant literature, and provide topic-specific recommendations based on the synthesis as well as personal modeling expertise. This article introduces a special collection of nine research articles covering key topics related to calibration and validation of H/WQ models. The topics include: terminology, hydrologic processes and model representationydrologic and water quality (H/WQ) models consist of interrelated assemblages of mathematical equations that represent complex physical, chemical, and biological processes governing the hydrology and fate and transport of sediments, nutrients, pesticides, and bacteria. H/WQ models are widely used to evaluate the impacts of changes in land use, land management, climate, and conservation practices on soil and water resources. Reliable models provide valuable information for making sound management, policy, and regulatory decisions. Comprehensive calibration and validation (C/V) of models is essential to obtain the "right outcomes" for the "right reasons" (Holling, 1978;Kirchner, 2006). Important components of proper C/V include selecting an appropriate model, setting up the model properly, establishing valid C/V strategies (Refsgaard and Henriksen, 2004), and capturing available datasets to represent the appropriate spatial and temporal scales (Kirchner, 2006).H/WQ models are valuable because they represent processes operating at various spatial and temporal scales simultaneously in a complex and interrelated manner. For example, the hydrology component of the Root Zone Water Quality Model (RZWQM; Ahuja et al., 2000) consists of interrelated hydrologic processes such as precipitation (including rainfall, snow, or irrigation), evaporation and transpiration (ET), surface runoff, infiltration, percolation, lateral flow, streamflow, and groundwater. However, no matter how detailed a model, it remains a simplification of the natural system in which some processes are characterized by rates and thresholds whose values are unknown. Be- cause many model parameters are typically available for calibration, the mere fitting of modeling results to observed data may result in good statistics of model performance but poor correspondence to the actual processes that the model is intended to represent. In such a case, a good fit is obtained for the wrong reasons. Application of such results can lead to incorrect conclusions with negative consequences (Dressel, 2010). The use of proper C/V practices can help prevent this circumstance while also allowing for a common foundation for interpretation of results and their comparison with other modeling studies (Refsgaard and Henriksen, 2004;Douglas-Mankin et al., 2010;Tuppad et al., 2011).Resear...

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“…Excellent reviews of sugarbeet models were provided by Vandendriessche and Ittersum (1995) and Baey et al (2014). However, all these models, except SIMBEET (Lee, 1983), simulate only plant growth and yield of sugarbeet and do not simulate agricultural management effects on soil and water quality (see also Ma et al, 2012). One approach is to incorporate a sugarbeet growth model into the Root Zone Water Quality Model (RZWQM) to study the plant-soil-water interactions in sugarbeet fields.…”

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confidence: 99%

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confidence: 99%

“…It has been widely used for simulating agricultural management effects on crop production and soil health and water quality (Jaynes and Miller, 1999;Ahuja et al, 2000;Saseendran et al, 2007;Malone et al, 2010;Ma et al, 2012). RZWQM2 is a significant upgrade from the earlier version of RZWQM (Ma et al, 2012). It incorporates surface energy balance from the SHAW (Simultaneous Heat and Water) model (Flerchinger et al, 2012) and the crop-specific growth modules from DSSAT (Decision Support System for Agrotechnology Transfer) (Jones et al, 2003).…”

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confidence: 99%

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