Root Zone Water Quality Model Research Articles

Improving soil water storage with no‐till cover cropping in the Mississippi River Alluvial Basin

AbstractExcessive tillage reduces soil water storage and increases surface runoff. Cover crops can modify the effect of tillage on soil water dynamics, but limited information is available for the Mississippi River Alluvial Basin. This study was conducted to determine whether soil–water dynamics could be manipulated through conservation production systems affecting surface residue management. Effects of tillage (conventional tillage [CT] vs. no‐tillage [NT]) and cover cropping (no cover crop and Austrian pea [Pisum sativum L.] cover crop [CC]) on soil water balance during the CC season in sorghum (Sorghum bicolor L.) and cotton (Gossypium hirsutum L.) crops were modeled using the root zone water quality model for a site near Stoneville, MS, on “Commerce” silty‐loam soil. Capacitance sensors measured soil volumetric water content to 120 cm during CC growth in 2019 and 2020. Field calibration of sensors reduced root mean square error from 0.05 to 0.03 m3 m−3. Pooled across years, NT increased volumetric water content in the 0–40 and 40–120 soil layers by 8.5% and 6.8%, respectively, compared to CT. Regardless of the CC treatment and cropping system, NT reduced surface runoff by 24.5% over its conventional counterpart, while soil water storage increased from 2.35 to 5.23 cm within the 1.2‐m profile, resulting in a 17% increase in consumptive use of water (evapotranspiration). CC treatments did not impact soil water storage and consumptive water use. The results demonstrate that NT systems can affect water dynamics by increasing infiltration and soil water storage in the humid subtropical region of the United States.

Simulating synergistic effects of climate change and conservation practices on greenhouse gas emissions and crop growth in long-term maize cropping systems

Understanding the impacts of future climate change and long-term agronomic practices on environmental quality and agricultural productivity is critical to the development of sustainable agronomic management approaches. Given these requirements, the present study’s objective was to evaluate the potential impacts of climate change and long-term conservation practices on greenhouse gas (GHG) emissions and crop growth. To project potential future (2065–2084) climatic conditions for a field under a long-term maize cropping system situated in Nebraska (USA), 12 different combinations of regional climate models × global climate models (RCMs-GCMs) were generated under representative concentration pathway 8.5 (RCP8.5) and a heightened atmospheric carbon dioxide concentration ([CO2]atm = 714.1 ppm). Then, employing a well-calibrated instance of the Root Zone Water Quality Model (RZWQM2), the effects of four long-term conservation practices were simulated under the 12 RCMs-GCMs. Compared to other climatic factors (e.g., shortwave radiation, wind run, and relative humidity), temperature, precipitation, and [CO2]atm played more important roles for future carbon dioxide (CO2) and nitrous oxide (N2O) emissions, global warming potential (GWP), soil organic carbon (SOC), crop yield, and total crop biomass. The sum of their relative contributions to GHG emissions and crop growth exceeded 83.9 % across all treatments. Under future climatic conditions, CO2 and N2O emissions increased significantly — 19.4 % ± 5.8 % and 26.6 % ± 8.9 %, respectively — compared to those under historical baseline conditions. Likewise, the GWP increased by 19.8 ± 5.8 %. Although rising [CO2]atm afforded limited benefits in terms of crop photosynthesis rates, rising future temperatures shortened crop growth cycles, resulting in a net decrease of 9.1 % ± 1.9 % in maize yield and 4.2 % ± 1.6 % in total biomass. SOC saw a net increase of 4.8 % ± 0.4 % under the future (vs. baseline) climate. Compared to residue removal with no-till treatment, annual CO2 and N2O emissions in the long-term maize cropping system were predicted to increase by 26.8 % and 27.9 % between 2065 and 2084 under residue retention with tillage treatment, respectively. Whereas crop yield and biomass were not significantly affected by residue or tillage management practices. The simulation method provided valuable evidence for management decisions to assess the synergistic effects of climate change and long-term agronomic practices on the environment and agricultural productivity. Further investigation is needed on the effects of other climate RCPs and agronomic management for sustainable agricultural production.

Predicting the effect of weir management on the discharge of a controlled drainage system in a changing climate

Subsurface drainage in humid areas prevents field waterlogging but also transports nutrients to freshwater systems. Controlled drainage (CD) reduces drainage discharge and nutrient transport from fields. Some regions are expected to experience increased precipitation in the future, requiring CD to be evaluated under a changing climate. The objective of this study was to compare the performance of CD under two weir managements for a future period (2030–2059) and historical period (1992-2021) in southeast Michigan, USA. Climate projections were obtained for the shared socioeconomic pathway 245 emission scenario. Aggressive management involved maintaining the weir height at 40 cm during the growing season and 15 cm during the non-growing season, with a longer period of managed flow compared to common management, which maintained the weir height at 50 cm during the growing season and 30 cm during the non-growing season. It was predicted that the 30-year average annual precipitation would not change significantly in the future. The 30-year average mean monthly temperature would increase by 3.0°C in the future compared to the historical period. We performed simulations using the calibrated Root Zone Water Quality Model 2 (RZWQM2). The average drainage discharge in the future indicated a 20% increase in the 30-year average drainage discharge for a field with free drainage. The CD with common and aggressive managements reduced drainage discharge by 59% and 67% for the historical period, whereas the performance of CD was even better for the future period (63% and 72%, respectively). The improved future performance of CD can be attributed to a shift in precipitation patterns, with reduced precipitation during the growing season and increased precipitation during the non-growing season. As a result, the more aggressive weir management during this period created additional opportunities for reducing drainage discharge. In conclusion, aggressive management resulted in a slightly better flow-reducing performance than common management while indicating that both methods would effectively reduce drainage discharge in the likely future scenario.

Impact of irrigation management on crop water footprint reduction using RZWQM2 in Baghdad, Iraq

Water scarcity becomes a serious global challenge in several world regions and particularly in the Middle East. Appropriate irrigation practice is critical for improving crop yield and alleviating crop water footprint (WF). To alleviate water scarcity, the possibility of reducing wheat and barley water footprint has been examined through alternative surface irrigation practices. The WF was compared under farmers’ irrigation practice and experimental irrigation practice to discover the impact of irrigation practices on the reduction of WF in the west of Baghdad. Weather data and crop management information were collected from 2016 to 2020 for the farmer’s fields in the study area as well as for the experimental field. The Root Zone Water Quality Model (RZWQM2) was used for estimating wheat and barley evapotranspiration. The study results showed that the crop WF was well estimated using the RZWQM2 due to the model capability and accuracy for estimating the impact of field management on crop evapotranspiration and crop water use. Experimental irrigation practice could improve crop yield, water use efficiency, and water profitability by up to 28%, 35%, and 35%, respectively; while the WF was reduced by 35%, compared to the farmers’ irrigation practice. The WF of the wheat crop was lower than the barley WF due to the low barley production.

Exploring the effects of subsoiling tillage under various irrigation regimes on the evapotranspiration and crop water productivity of winter wheat using RZWQM2

Food security is an important pre-requisite for human well-being; however, water shortages and poor quality of arable land threaten food security in the North China Plain (NCP). Subsoiling and proper irrigation can improve soil structure and increase crop yield. This study investigated the effects of two tillage methods (rotary tillage at 15 cm depth, R15; subsoiling at 35 cm depth, S35) combined with three irrigation treatments (no irrigation during the winter wheat growing season, I0; 60 mm irrigation at the jointing stage, I1; 60 mm irrigation at both the jointing and heading stages, I2) on soil moisture dynamics, evapotranspiration, and winter wheat yield. The Root Zone Water Quality Model (RZWQM2) was adopted after calibration and validation base on a field experiment. The results showed that the normalized root mean square errors (calibration and test) between the actual and simulated values of soil water storage (SWS), evapotranspiration (ET), and yield were 7.45–10.87%, 3.80–7.21%, and 5.38–14.15%, respectively. Subsoiling improved winter wheat soil moisture conditions, yield, and crop water productivity (CWP), and irrigation during the winter wheat growing seasons increased crop yield (I2 > I1 > I0) and CWP (I1 > I2 > I0). The best yield treatment during the 2020–2022 winter wheat growing seasons was S35-I2. However, the CWP of S35-I1 was 2.67% higher than that of S35-I2. Tillage methods change the ET structure of winter wheat fields. Compared to rotary tillage, subsoiling reduced actual ET by 16.11% and increased actual transpiration by 10.44%. The results of this study indicate that subsoiling at a depth of 35 cm and 60 mm irrigation at the jointing stage could improve the CWP of winter wheat in the NCP.

Simulating fate and transport of non-steroidal anti-inflammatory drugs using Root Zone Water Quality Model 2.

The fate and transport of non-steroidal anti-inflammatory drugs (NSAIDs) in soil are determined by various processes, and the complexity of the system lends itself to the use of computer simulation models to help understand it. This study demonstrated the first attempt to use empirical data from lab incubation and field studies to parameterize and test a process-based agricultural systems model, Root Zone Water Quality Model 2 (RZWQM2), to simulate the fate and transport of naproxen (NPX), ibuprofen (IBF), and ketoprofen (KTF) in field-based lysimeters amended with alkaline-treated biosolids (ATBs). The model calibrated for the soil-water balance module and contaminant transport module was used to predict water seepage through the soil profile in 2017 and 2018 within a 15% error of the field measured data, with model performance statistics such as Nash-Sutcliffe model efficiency (NSE) and R2 all greater than 0.70. The overall predicted percent recovery of initial spiked NSAIDs in both soil and water samples, after further calibration of the contaminant transport module, was within the same order of magnitude as the measured data. The model underestimated the percent recovery of initial spiked NSAIDs at the 30- to 55-cm soil depth for all treatments on day 3. The calibrated soil subsurface aerobic half-lives of NPX and IBF were found to be considerably lower than their laboratory-measured half-lives obtained from the incubation study. The overall performance of RZWQM2 in simulating the soil hydrology and behavior of NSAIDs in soil profiles receiving various rates of ATB amendments was satisfactory.

A modularized parallel distributed High–Performance computing framework for simulating seasonal frost dynamics in Canadian croplands

The winter/spring season in cold climate regions has been recognized as a critical period for cropland nutrient loss and greenhouse gas emissions and has been predicted to be vulnerable to climate change. Agricultural system models serve as essential tools in anticipating potential outcomes. The RZ-SHAW model, combining the Simultaneous Heat and Water Model (SHAW) with the Root Zone Water Quality Model 2 (RZWQM2), comprehensively describes snow and soil freezing dynamics. Showing promising results in simulating winter frost dynamics it, however, remains computationally intensive. High-performance computing has been recognized as a promising approach to reducing simulation runtimes. A modularized parallel distributed high-performance computing (HPC) framework (RS-DPCF) with both multi-threading (MT) and multi-processing (MP) capability was developed for RZ–SHAW calibration and simulation. Two case studies demonstrated that the developed RS-DPCF program could significantly reduce RZ–SHAW calibration time, allow improved computation resource scalability, and perform field-scale simulations of overwintering conditions for multiple croplands across Canada. For the RZ–SHAW model, MT provided a parallel-computing efficiency superior to that of MP.

Optimization of Nitrogen Fertilizer Management in the Yellow River Irrigation Area Based on the Root Zone Water Quality Model

Strategic management of nitrogen fertilizers can not only mitigate agricultural nitrogen pollution but also significantly enhance crop yield and nitrogen use efficiency. This study was designed to determine the optimal nitrogen fertilizer management strategy for the Yellow River irrigation area. Leveraging two years of field data related to soil water nitrogen and summer maize growth indices, parameters for the Root Zone Water Quality Model 2 (RZWQM2) were calibrated and validated. Subsequently, various scenarios were generated to simulate the impacts of different nitrogen application rates and basal chasing ratios on summer maize yield, nitrogen agronomic efficiency, nitrogen physiological efficiency, and nitrogen apparent recovery rate. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was employed for a comprehensive evaluation. RZWQM2 can effectively simulate the dynamic changes in soil moisture and nitrogen in the Yellow River irrigation area, and the results indicated that the mean relative error (MRE) between the simulated and observed values varied from 5.77% to 14.09%, and 4.36% to 33.01%, while the root mean square error (RMSE) ranged from 0.016 to 0.037 cm3/cm3, and 0.111 to 1.995 mg/kg. The normalized root mean square error (NRMSE) varied between 6.20% to 14.42% and 5.24% to 17.84%, respectively. The results validate the model’s effectiveness in simulating summer maize yields and nitrogen metrics under varying nitrogen fertilizer management practices. A nitrogen application rate of 180–200 kg/hm2 (expressed in terms of pure nitrogen) in the Yellow River irrigation area could adequately meet the requirements for summer maize production. The recommended nitrogen fertilizer management strategy in the Yellow River irrigation area involves applying 200 kg/hm2 of nitrogen in a 1:2:1 ratio during the sowing, trumpeting, and anthesis stages.

Harvested winter rye energy cover crop: multiple benefits for North Central US

Cover crops (CCs) can reduce nitrogen (N) loss to subsurface drainage and can be reimagined as bioenergy crops for renewable natural gas production and carbon (C) benefits (fossil fuel substitution and C storage). Little information is available on the large-scale adoption of winter rye for these purposes. To investigate the impacts in the North Central US, we used the Root Zone Water Quality Model to simulate corn-soybean rotations with and without winter rye across 40 sites. The simulations were interpolated across a five-state area (IA, IL, IN, MN, and OH) with counties in the Mississippi River basin, which consists of ∼8 million ha with potential for rye CCs on artificially drained corn-soybean fields (more than 63 million ha total). Harvesting fertilized rye CCs before soybean planting in this area can reduce N loads to the Gulf of Mexico by 27% relative to no CCs, and provide 18 million Mg yr−1 of biomass-equivalent to 0.21 EJ yr−1 of biogas energy content or 3.5 times the 2022 US cellulosic biofuel production. Capturing the CO2 in biogas from digesting rye in the region and sequestering it in underground geologic reservoirs could mitigate 7.5 million Mg CO2 yr−1. Nine clusters of counties (hotspots) were identified as an example of implementing rye as an energy CC on an industrial scale where 400 Gg yr−1 of rye could be sourced within a 121 km radius. Hotspots consisted of roughly 20% of the region’s area and could provide ∼50% of both the N loss reduction and rye biomass. These results suggest that large-scale energy CC adoption would substantially contribute to the goals of reducing N loads to the Gulf of Mexico, increasing bioenergy production, and providing C benefits.

Measured and simulated effects of residue removal and amelioration practices in no-till irrigated corn (Zea mays L.)

Reducing nitrous oxide (N2O) emissions to the atmosphere is expected to provide substantial climate mitigation benefits. Herein, we measured soil N2O emission and crop yield responses in a nine-year, no-till continuous corn system under contrasting management practices including irrigation (full; deficit), corn stover retention (100 % retention; maximum mechanical removal), and cover crop use (winter cereal rye, Secale cereale L.; no cover crop). Field-measured data were used to construct a structural equation model (SEMobs) to explore the causal effects of management on soil N2O emissions. We also used the Root Zone Water Quality Model 2 (RZWQM2) to simulate management effects on soil N2O emission. Structural equation modeling was used for the field-measured data (SEMobs) and the RZWQM2 simulated data (SEMsim) to quantify management relationships with soil and determine whether relationships observed in field data were captured by RZWQM2 simulations. Our experimental field results showed that stover removal decreased annual N2O emissions compared to stover retention, only for deficit irrigated soil (2.83 ± 1.31 vs. 4.49 ± 3.65 kg N ha−1 y−1) and that deficit irrigation decreased annual N2O emissions compared to full irrigation, only for soil with cover crops (3.31 ± 3.19 vs. 4.11 ± 3.80 kg N ha−1 y−1). The SEMobs and SEMsim results showed similar direction and magnitude of relationships between daily soil N2O emissions and various management and environmental drivers. Our study improved the mechanistic understanding for the effects of agricultural management on soil N2O emissions and can help reduce N2O emissions from agricultural systems.

Climate Change Effects on Irrigated Corn Growth in the Lower Mississippi Delta

Abstract In this study, the possible climate change impacts on irrigated corn production in the lower Mississippi delta (LMD) region were analyzed. The observed daily maximum and minimum air temperature, wind speed, relative humidity (RH), and precipitation from 1960 to 2018 were used in the analysis. The length of the growing season, evapotranspiration (ET), and crop yield estimates from the precalibrated Root Zone Water Quality Model (RZWQM) were also used. Trend analyses were performed on growing-season averages for temperature, RH, and wind speed; growing-season totals for precipitation and ET; daily values of minimum and maximum temperature; and averages of RH and wind speed at critical corn growth stages. The last day of spring freezing (LDSF) and days with an average daily air temperature Ta of more than 35°C during corn silking were also included in the analysis. The trend analysis was performed using the modified Mann–Kendall test, Pettitt test, and Sen’s slope at a significance level of p ≤ 0.05. The results from our study pointed out increases in minimum Ta, increases in the number of days with Ta exceeding 35°C during the corn silking stage, increases in RH and decreases in ET, advancement of the LDSF by 2 weeks, and 8% reductions in corn yield that could be attributed to changes in climate. If the observed trends in climate (climate variability and change) and yield reductions continue in the region, it could be challenging to grow the corn crop in the LMD profitably. Significance Statement In recent years, growing corn and soybeans instead of cotton has been gaining popularity in the lower Mississippi delta (LMD) region. Our study is aimed to understand how climate change in the recent past (1960–2018) has affected irrigated corn production in LMD. This will help us to better understand the expected consequences of the future climate. We used observations of daily weather data from 1960 to 2018 and corn yield, water balance, and crop yield results from a computer model designed to simulate corn production. Tools were used to analyze trends and patterns in the data and results. Our analysis pointed out significant changes in weather, water balance, and yield decline for irrigated corn in the LMD.

Water Budget of Urban Turf Field and Optimal Irrigation Schedule Simulation in an Ecotone between Semi-Humid and Semi-Arid Regions, Northern China

Water security in the ecotone between semi-humid and semi-arid regions (EHA) is very vulnerable and sensitive to climate change and human interferences. Urban turf irrigation is a primary consumer of urban water resources in the EHA, which places huge pressures on water security by substantial irrigated water use due to the expansion of urban turf planting. Based on a 2-year (2020–2021) turf experiment in Zhangjiakou City, a typical water-deficit city in the EHA of northern China, the water budget for turf was measured and analyzed. Furthermore, the Root Zone Water Quality Model (RZWQM2) was employed to evaluate the optimal irrigation scheme for turf. The results showed that the average volumetric water content in the 0–40 cm soil layer was maintained above 23% in 2020–2021. The evapotranspiration in growth period of turf accounted for more than 70% of the annual evapotranspiration, and the deep seepage in turf soil accounted for 49.67% and 60.28% of the total precipitation and irrigation in 2020 and 2021, respectively, during the vigorous growth period of the turf from May to September. The calibrated RZWQM2 showed a robust ability to simulate the water changes in turf. The d-values (consistency index) between the simulated and observed volumetric water contents and evapotranspiration were both greater than 0.90. In the aspects of irrigation scenarios, the T60%-12 scenario (TA-B, where A is 100%, 80%, 60% or 40% of the total irrigation amount and B is the number of irrigation events corresponding to A) was determined as the best irrigation schedule in our study area because of lower evapotranspiration, seepage and higher turf soil water storage under this irrigation scenario, also resulting from the comparison of different irrigation scenarios using the entropy-weight-TOPSIS method. In such an optimal scenario, T60%-12 irrigation treatment reduced the irrigated water requirement of turf by 40% (142.06 mm) and the seepage amount by 28.07% (39.05 mm), and had the lowest negative impacts on the turf growth.

Calibration and Validation of RZWQM2-P Model to Simulate Phosphorus Loss in a Clay Loam Soil in Michigan

Highlights RZWQM2-P was tested and validated for clay loam soil using daily discharge and load data. The model performed satisfactorily in predicting hydrology and TP load, but DRP prediction was unsatisfactory. Inability of the model to simulate P loss in subsurface drainage discharge after fertilization event was one of the reasons for the unsatisfactory model performance. Abstract. Phosphorus (P) loss and transport through subsurface drainage systems is a primary focus for addressing harmful algal blooms in freshwater systems. The recent development of the phosphorus (P) routine of the Root Zone Water Quality Model (RZWQM2-P) has the potential to enhance our understanding of the fate and transport of P from subsurface-drained fields to surface water. However, there is a need to test the model under different fertilization, soil, climate, and cropping conditions. The objective of this study was to test the model's performance with daily drainage discharge, dissolved reactive phosphorus (DRP), and total phosphorus (TP) load collected from a subsurface-drained field with clay loam soil. We calibrated RZWQM2-P using two years of measured data. Subsequently, we validated RZWQM2-P using a year and nine months of measured data. We used the Nash-Sutcliffe model efficiency (NSE) and percentage bias (PBIAS) statistics for the RZWQM2-P model evaluation. The results showed that the model performance was “good” (daily NSE = 0.66 and PBIAS = -7.16) in predicting hydrology for the calibration period. For the validation period, the hydrology prediction of the model was “very good” (daily NSE = 0.76), but it had a “satisfactory” underestimation bias (PBIAS = 23.57). The model’s performance was “unsatisfactory” in simulating DRP for both calibration (daily NSE = 0.31 and PBIAS = -61.50) and validation (daily NSE = 0.32 and PBIAS = 43.68) periods. The P model showed “satisfactory” performance in predicting TP load for both calibration (daily NSE = 0.46 and PBIAS = -32.41) and validation (daily NSE = 0.39 and PBIAS = 42.90) periods, although both periods showed “unsatisfactory” percent bias. The underperformance may have been due to the model’s inability to partition fertilizer P into different P pools under high water tables or ponding conditions when using daily data. In conclusion, the RZWQM2-P model performed well for drainage discharge with daily data, but further investigation is needed to improve the P component of the model. Keywords: Field-scale modeling, Nutrient load, Phosphorus modeling, Subsurface drainage, Tile drainage, Water Quality.

Climate Change in a Semi-Arid Environment: Effects on Crop Rotation with Dairy Manure Applications

Highlights Spring wheat yields increase with high temperatures and the minimal impact of increased CO2. At high temperatures and increased CO2, spring barley yields increase; yields decrease at only high temperatures. Potato and sugarbeet yields decrease with climate change. Climate change had little impact in soil nitrogen processes. Abstract. Agricultural crops grown in the irrigated semi-arid region of southern Idaho account for almost two-thirds of the median household income in the region. The impacts of climate change on cropping systems and the availability of water for irrigation would be a serious challenge for the state's economic dependence on agriculture. The objective of the study was to simulate the future impact of climate change on a crop rotation of spring wheat-potato-spring barley-sugarbeet grown in the semi-arid region of southern Idaho using conventional management practices and a high dairy manure application. The Root Zone Water Quality Model (RZWQM2) simulations used bias-corrected and spatially disaggregated projections from the World Climate Research Program’s coupled model inter-comparison project phase 5 to generate 40 GCM projections for the time from 2071-2099. The 28-yr scenarios were designed to simulate the impact of temperature and CO2 regimes on crop production, soil nitrogen mineralization, nitrogen seepage, deep seepage of water, and nitrous oxide emissions. Data from a field experiment in southern Idaho with conventional fertilizer practices and annual applications of 52 Mg ha-1 dairy manure with a crop rotation of spring wheat-potato-spring barley-sugarbeet were used in the RZWQM2 simulations. Results were compared to a baseline scenario of conventional management practices, historical weather data, and ambient CO2. Spring wheat yield increased by 22% and 16% for manure and fertilizer treatments, respectively, compared to the baseline scenario. Using the same comparison, potato tuber yield decreased by 65% and 60% in the manure and fertilizer treatments, respectively, for the highest temperature and CO2 increase scenarios. Spring barley produced a 33% higher yield with increased temperature and CO2. However, yield decreased when temperature increased, but CO2 remained unchanged. Sugarbeet yields decreased by 16% and 18% for manure and fertilizer treatments, respectively, compared to the baseline scenario. Nitrogen mineralization, N seepage from the profile, and nitrous oxide emissions were strongly influenced by the manure applications, and there was little simulated impact of climate change on these processes. These simulation results indicate that genetic enhancements or alternative management will be needed to maintain potato and sugar beet production levels in semi-arid areas, while spring barley and wheat yields may increase, assuming adequate irrigation water supplies are available. Keywords: Nitrogen Mineralization, Potato, RZWQM2, Spring Barley, Spring Wheat, Sugarbeet.

Advanced practice-aided tile drain configuration: A solution to achieving environmentally sustainable agricultural production

Alternatives to conventional crop production practices are needed to achieve environmental sustainability. Because tile-drained crop production systems in the Midwestern United States are one of the single largest contributors to environmental degradation, we explored alternative tile drain configurations by changing the tile spacing and depth of tile-drained fields in central Illinois and then by evaluating comprehensively the impacts of different tile drain configurations on crop productivity and environmental sustainability using the Root Zone Water Quality Model 2 (RZWQM2). An analytic hierarchy process (AHP), which is a multicriteria decision analysis (MCDA) tool, was used to evaluate the optimum tile spacing and depth scenario. The model simulations and AHP tested three management schemes designated as “agricultural productivity” (AP), “environmental sustainability” (ES), and “advance in technology” (AT). The schemes were designed based on three criteria: operational cost, crop profit, and environmental control. Analysis showed that deeper tiles and narrower tile spacing resulted in decreases in flow and nitrate loss from runoff, seepage (SP), and lateral flow (LF), and increases in tile flow, total nitrate loss, and crop yields. On the basis of MCDA, the AP management scheme resulted in higher CP and total nitrate loss, whereas opposite outcomes were generated by the ES management scheme. Under the AT management scheme, higher ranked scenarios resulted in higher CP and lower total amounts of nitrate entering streams. Our analysis indicates that the AT scheme can simultaneously enhance crop production and ES through advances in tile drainage water treatment.

Can one‐time calibration of measured soil hydraulic input parameters yield appropriate simulations of RZWQM2?

AbstractAgricultural system models can help quantify soil water dynamics, crop evapotranspiration, and crop growth with a high temporal resolution to enhance soil and crop management. Simplifying the process of model calibration and validation is an important aspect for crop model use. The objective of this study was to explore the capability of using the Root Zone Water Quality Model (RZWQM2) with soil hydraulic property input parameters (SHPIPs) identified once under a given crop for other crops without recalibrating. A field experiment with soybean [Glycine max (L.) Merr.], corn (Zea mays L.), wheat (Triticum aestivum L.), and fallow soil was conducted from 2015 to 2017. The soil hydraulic property parameter calibration process was evaluated. Four model scenarios of calibrating measured SHPIPs for soybean, corn, wheat, and fallow soil were created. The RZWQM2 simulation results showed high sensitivity to the model inputs of the SHPIPs. Model input parameters of bulk density, field capacity, permanent wilting point, and saturated hydraulic conductivity showed a large effect on model simulations. Model inputs of soil water content θ at field capacity and permanent wilting point showed high impact on water holding capacity and crop development, whereas the model input parameters of saturated hydraulic conductivity and bulk density yielded a high effect on soil water dynamics. All model scenarios presented satisfactory results with regard to soil water dynamics, evapotranspiration, crop growth, and mineral nitrogen, indicating that, for a particular field, RZWQM2 calibrated for one season performs well for other seasons without recalibration.

Long‐Term Simulation of Snow Cover and Its Potential Impacts on Seasonal Frost Dynamics in Croplands Across Southern Canada

AbstractIn northern climates, accurate simulation of thermal and hydrological budgets for farmlands overwinter is crucial for both an accurate prediction of spring flooding and the successful management of nutrient losses. As snow cover influences soil freezing dynamics, it has been hypothesized that reduced snow cover due to warmer winters might intensify soil freezing. The present study was designed to test this hypothesis. Drawing upon observed snow depth and soil temperature data collected from six research farms across Southern Canada over various time spans from 1989 to 2020, the root zone water quality model, integrated with the simultaneous heat and water model (RZ‐SHAW), was calibrated and validated. The potential influence of warmer winter on shifts in soil frost dynamics was evaluated by estimating soil freezing dynamics for each farmland site under various air temperature scenarios using the RZ‐SHAW model. Soil frozen depth in the eastern Canada sites increased with increasing air temperature in some years but decreased under the highest air temperature increases of 3.5°C. The monthly relationship between snow depth and soil frozen depth was determined through partial correlation analysis. Snow was most effective in alleviating soil freezing in the months of January and February, a period when snow cover depth was least affected by warming air temperatures. This study suggests that the hypothesis of increasing soil frozen depth under global warming‐induced snow cover reduction holds true in conditions where soil energy lost through reduced snow cover outweighed the soil energy gained through warmer air temperature.

RZWQM2 Simulated Drip Fertigation Management to Improve Water and Nitrogen Use Efficiency of Maize in a Solar Greenhouse

The drip fertigation technique is a modern, efficient irrigation method to alleviate water scarcity and fertilizer surpluses in crop production, while the precise quantification of water and fertilizer inputs is difficult for drip fertigation systems. A field experiment of maize (Zea mays L.) in a solar greenhouse was conducted to meet different combinations of four irrigation rates (I125, I100, I75 and I50) and three nitrogen (N) fertilizer rates (N125, N100 and N75) under surface drip fertigation (SDF) systems. The Root Zone Water Quality Model (RZWQM2) was used to assess the response of soil volumetric water content (VWC), leaf area index (LAI), plant height and maize yield to different SDF managements. The model was calibrated by the I100N100 scenario and validated by the remaining five scenarios (i.e., I125N100, I75N100, I50N100, I100N125 and I100N75). The predictions of VWC, LAI and plant height were satisfactory, with relative root mean square errors (RRMSE) < 9.8%, the percent errors (PBIAS) within ±6%, indexes of agreement (IoA) > 0.85 and determination of coefficients (R2) > 0.71, and the relative errors (RE) of simulated yields were in the range of 1.5–7.2%. The simulation results showed that both irrigation and fertilization had multiple effects on water and N stresses. The calibrated model was subsequently used to explore the optimal SDF scenarios for maximizing yield, water use efficiency (WUE) or nitrogen use efficiency (NUE). Among the SDF managements of 21 irrigation rates × 31 N fertilizer rates, the optimal SDF scenarios were I120N130 for max yield (10516 kg/ha), I50N70 for max WUE (47.3 kg/(ha·mm)) and I125N75 for max NUE (30.2 kg/kg), respectively. The results demonstrated that the RZWQM2 was a promising tool for evaluating the effects of SDF management and achieving optimal water and N inputs.

Development of RZ-SHAW for simulating plastic mulch effects on soil water, soil temperature, and surface energy balance in a maize field

A shortcoming of the RZ-SHAW model (A hybrid version of Root Zone Water Quality Model and The Simultaneous Heat and Water Model) is that it cannot simulate the plastic mulching technology which is widely used in arid areas. Our objectives in this study were to develop RZ-SHAW to include a new plastic module, and to evaluate the model’s performance over three years of maize (Zea mays L.) production in China. A new plastic module was added to compute changes in the shortwave and longwave radiation transfer, turbulent heat and vapor transfer from the surface, and the energy and water balances in the system associated with a plastic mulch layer. The modified RZ-SHAW model can adequately simulate soil water (0.017 cm3 cm−3 ≤ RMSE ≤ 0.030 cm3 cm−3) and capture the evaporation reduction and transpiration increase under plastic mulch. The model overestimated the increased soil temperatures under plastic mulch (2.3 ℃ over the 100-cm profile) compared to the measured data (1.4 ℃). Overall, the revised RZ-SHAW model adequately simulated soil water and heat exchange under plastic mulch conditions. The modified RZ-SHAW model can be used as an effective decision tool for management optimization in plastic mulched cropland.

Comparison of simulated nitrogen management strategies using DRAINMOD-DSSAT and RZWQM2

Agroecosystem models provide valuable insights into agricultural management decisions and can serve as a useful tool to quantify the effects of management practices under varying conditions where field experimentations are impractical. We evaluated a newly integrated comprehensive model, DRAINMOD-DSSAT, for hydrology, nitrogen (N) dynamics, and crop yield using eight years (1993–2000) of measured data from a no-tilled subsurface-drained, corn-soybean agricultural system near Danville, Illinois. The model satisfactorily predicted drainage flow and NO3-N losses with Nash-Sutcliffe efficiency (NSE), the ratio of the root mean squared error to the standard deviation (RSR), and percent bias (PBIAS) of 0.68 and 0.60, 0.56 and 0.63, and − 11.6% and − 2.2%, respectively, and crop yield with nRMSE, PBIAS and index of agreement (d) of 8.4%, − 0.6%, and 1, respectively. For the same experimental dataset, the performance comparison of DRAINMOD-DSSAT to Root Zone Water Quality Model (RZWQM2) demonstrated that the two models were most different in their simulation of N loss through seepage and denitrification. Further, we used DRAINMOD-DSSAT to simulate the effects of management practices (N application rates and timings) on NO3-N losses and crop yield and compared them with RZWQM2 simulated results. The results showed that both models provided the same conclusion on the effects of N management strategy on NO3-N losses and crop yield, but they differ in quantity. This study supports being cautious in using only one model to conclude the quantification of the effectiveness of particular agricultural management practices.