Proceedings of the USDA-ARS workshop "Real world" infiltration

Compiled and edited by L.R. Ahuja and Amy Garrison.Includes bibliographical references.Proceedings of the 1996 workshop held on July 22-25, 1996 in Pingree Park, Colorado

Workshop on computer applications in water management: proceedings of the 1995 workshop

Compiled and edited by L. Ahuja, J. Leppert, K. Rojas, E. Seely.Also published as: Great Plains Agricultural Council publication, no. 154.Includes bibliographical references.Presented at the Workshop on computer applications in water management: proceedings of the 1995 workshop held on May 23-25, 1995 at Colorado State University in Fort Collins, Colorado

Simulating Atrazine Transport Using Root Zone Water Quality Model for Iowa Soil Profiles

The pesticide component of the Root Zone Water Quality Model (RZWQM) was calibrated and evaluated for two tillage systems: no-till (NT) and moldboard plow (MB). The RZWQM is a process-based model that simulates the water and chemical transport processes in the soil-crop-atmosphere system. Observed data on atrazine concentrations in the soil profile, for model calibration and testing, were obtained from a field study in Iowa. Two statistical parameters, maximum error (ME) and coefficient of determination (CD), were used to evaluate the ability of the RZWQM to predict atrazine concentrations in the soil profile. The ME, CD, and other statistical tests indicated that there was a significant difference between predicted and observed atrazine concentrations. Comparison of simulated vs. observed atrazine concentrations with 1:1 line showed that atrazine concentrations were overpredicted, especially in the later part of the growing season. However, the model correctly predicted depth of atrazine penetration in the soil profile. Also, the range of predicted atrazine concentrations was within the same order of magnitude as observed concentrations. Although observed atrazine concentrations were usually higher in surface layers under MB than in NT treatment, the model did not show any consistent tillage effects on atrazine distribution in the soil profile. The results from this simulation study indicated that the following factors may be critical and should be considered when simulating pesticide transport in the subsurface environment: (i) macropore flow, (ii) variation in Koc and pesticide half-life with depth, and (iii) interception of pesticide by surface residue during application

RZWQM simulation of long-term crop production, water and nitrogen balances in Northeast Iowa

Agricultural system models are tools to represent and understand major processes and their interactions in agricultural systems. We used the Root Zone Water Quality Model (RZWQM) with 26 years of data from a study near Nashua, IA to evaluate year to year crop yield, water, and N balances. The model was calibrated using data from one 0.4 ha plot and evaluated by comparing simulated values with data from 29 of the 36 plots at the same research site (six were excluded). The dataset contains measured tile flow that varied considerably from plot to plot so we calibrated total tile flow amount by adjusting a lateral hydraulic gradient term for subsurface lateral flow below tiles for each plot. Keeping all other soil and plant parameters constant, RZWQM correctly simulated year to year variations in tile flow (r2 = 0.74) and N loading in tile flow (r2 = 0.71). Yearly crop yield variation was simulated with less satisfaction (r2 = 0.52 for corn and r2 = 0.37 for soybean) although the average yields were reasonably simulated. Root mean square errors (RMSE) for simulated soil water storage, water table, and annual tile flow were 3.0, 22.1, and 5.6 cm, respectively. These values were close to the average RMSE for the measured data between replicates (3.0, 22.4, and 5.7 cm, respectively). RMSE values for simulated annual N loading and residual soil N were 16.8 and 47.0 kg N ha−1, respectively, which were much higher than the average RMSE for measurements among replicates (7.8 and 38.8 kg N ha−1, respectively). The high RMSE for N simulation might be caused by high simulation errors in plant N uptake. Simulated corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yields had high RMSE (1386 and 674 kg ha−1) with coefficient of variations (CV) of 0.19 and 0.25, respectively. Further improvements were needed for better simulating plant N uptake and yield, but overall, results for annual tile flow and annual N loading in tile flow were acceptable

Simulating Atrazine Transport Using Root Zone Water Quality Model for Iowa Soil Profiles

The pesticide component of the Root Zone Water Quality Model (RZWQM) was calibrated and evaluated for two tillage systems: no-till (NT) and moldboard plow (MB). The RZWQM is a process-based model that simulates the water and chemical transport processes in the soil-crop-atmosphere system. Observed data on atrazine concentrations in the soil profile, for model calibration and testing, were obtained from a field study in Iowa. Two statistical parameters, maximum error (ME) and coefficient of determination (CD), were used to evaluate the ability of the RZWQM to predict atrazine concentrations in the soil profile. The ME, CD, and other statistical tests indicated that there was a significant difference between predicted and observed atrazine concentrations. Comparison of simulated vs. observed atrazine concentrations with 1:1 line showed that atrazine concentrations were overpredicted, especially in the later part of the growing season. However, the model correctly predicted depth of atrazine penetration in the soil profile. Also, the range of predicted atrazine concentrations was within the same order of magnitude as observed concentrations. Although observed atrazine concentrations were usually higher in surface layers under MB than in NT treatment, the model did not show any consistent tillage effects on atrazine distribution in the soil profile. The results from this simulation study indicated that the following factors may be critical and should be considered when simulating pesticide transport in the subsurface environment: (i) macropore flow, (ii) variation in Koc and pesticide half-life with depth, and (iii) interception of pesticide by surface residue during application.This article is from JEQ 26 (1997): 153–167, doi:10.2134/jeq1997.00472425002600010023x.</p

WRRCTR No.143 Water Conduction in Hawaii Oxic Soils

Oxic soils on Oahu were studied to develop and test simplified methods of determining the hydraulic conductivity of unsaturated soils, to test some simple infiltration models, and to assess the utility of soil survey mapped units in defining hydrologically similar soils. Field measurements of water infiltration and redistribution were accomplished on 21 sites located on the Lahaina, Molokai, and Wahiawa soil series. Water retention curves measured on undisturbed soil cores from the Ap1, Ap2, and B horizons of each site provided a means of determining the downward flux of water during redistribution from soil water suction measurements over time. These data allowed calculation of hydraulic conductivities (by a detailed Darcy analysis) of soil at various depths in the soil profile and for a range of water contents and suctions. The detailed analysis and field infiltration data provided a means of evaluating two new simplified methods of determining hydraulic conductivity functions of well-drained soils; the new methods are sufficiently accurate and economical to be used in watershed characterization. Also, field measured sorptivity and water redistribution data were used to successfully predict cumulative infiltration with the Talsma-Parlange and Green-Ampt equations, respectively. Statistical analysis of field and laboratory data suggested that soil maps of central Oahu would not be particularly useful in delineating soil areas of relative homogeneity with respect to hydrologic properties. These results further emphasize the need for simple methods to characterize hydrologic properties of importance.Bureau of Reclamation U.S. Department of the Interior Grant/Contract No. 14-34-0001-7026, -7116 (B-048-HI); 14-34-0001-7116, -8078 (B-054-HI

RZWQM simulation of long-term crop production, water and nitrogen balances in Northeast Iowa

Agricultural system models are tools to represent and understand major processes and their interactions in agricultural systems. We used the Root Zone Water Quality Model (RZWQM) with 26 years of data from a study near Nashua, IA to evaluate year to year crop yield, water, and N balances. The model was calibrated using data from one 0.4 ha plot and evaluated by comparing simulated values with data from 29 of the 36 plots at the same research site (six were excluded). The dataset contains measured tile flow that varied considerably from plot to plot so we calibrated total tile flow amount by adjusting a lateral hydraulic gradient term for subsurface lateral flow below tiles for each plot. Keeping all other soil and plant parameters constant, RZWQM correctly simulated year to year variations in tile flow (r2 = 0.74) and N loading in tile flow (r2 = 0.71). Yearly crop yield variation was simulated with less satisfaction (r2 = 0.52 for corn and r2 = 0.37 for soybean) although the average yields were reasonably simulated. Root mean square errors (RMSE) for simulated soil water storage, water table, and annual tile flow were 3.0, 22.1, and 5.6 cm, respectively. These values were close to the average RMSE for the measured data between replicates (3.0, 22.4, and 5.7 cm, respectively). RMSE values for simulated annual N loading and residual soil N were 16.8 and 47.0 kg N ha−1, respectively, which were much higher than the average RMSE for measurements among replicates (7.8 and 38.8 kg N ha−1, respectively). The high RMSE for N simulation might be caused by high simulation errors in plant N uptake. Simulated corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yields had high RMSE (1386 and 674 kg ha−1) with coefficient of variations (CV) of 0.19 and 0.25, respectively. Further improvements were needed for better simulating plant N uptake and yield, but overall, results for annual tile flow and annual N loading in tile flow were acceptable.This article is from Geoderma 140 (2007): 247–259, doi:10.1016/j.geoderma.2007.04.009.</p

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multi‐model assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N ha‐1) for five environments in SSA, including cool sub‐humid Ethiopia, cool semi‐arid Rwanda, hot sub‐humid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from two‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average rRMSE of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter‐comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low‐input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer