Influence of different nitrate–N monitoring strategies on load estimation as a base for model calibration and evaluation

Model-based predictions of the impact of land management practices on nutrient loading require measured nutrient flux data for model calibration and evaluation. Consequently, uncertainties in the monitoring data resulting from sample collection and load estimation methods influence the calibration, and thus, the parameter settings that affect the modeling results. To investigate this influence, we compared three different time-based sampling strategies and four different load estimation methods for model calibration and compared the results. For our study, we used the river basin model Soil and Water Assessment Tool on the intensively managed loess-dominated Parthe watershed (315 km2) in Central Germany. The results show that nitrate–N load estimations differ considerably depending on sampling strategy, load estimation method, and period of interest. Within our study period, the annual nitrate–N load estimation values for the daily composite data set have the lowest ranges (between 9.8% and 15.7% maximum deviations related to the mean value of all applied methods). By contrast, annual estimation results for the submonthly and the monthly data set vary in greater ranges (between 24.9% and 67.7%). To show differences between the sampling strategies, we calculated the percentage deviation of mean load estimations of submonthly and monthly data sets as related to the mean estimation value of the composite data set. For nitrate–N, the maximum deviation is 64.5% for the submonthly data set in the year 2000. We used average monthly nitrate–N loads of the daily composite data set to calibrate the model to achieve satisfactory simulation results [Nash–Sutcliffe efficiency (NSE) 0.52]. Using the same parameter settings with submonthly and monthly data set, the NSE dropped to 0.42 and 0.31, respectively. Considering the different results from the monitoring strategy and the load estimation method, we recommend both the implementation of optimized monitoring programs and the use of multiple load estimation methods to improve water quality characterization and provide appropriate model calibration and evaluation data.

[1]  R. Ferguson.  Accuracy and precision of methods for estimating river loads , 1987 .

[2]  Brian E. Haggard,et al.  PRACTICAL GUIDANCE FOR DISCHARGE AND WATER QUALITY DATA COLLECTION ON SMALL WATERSHEDS , 2006 .

[3]  R. D. Harmel,et al.  CONSIDERATIONS IN SELECTING A WATER QUALITY SAMPLING STRATEGY , 2001 .

[4]  Graham A. Mills,et al.  Strategic monitoring for the European Water Framework Directive , 2006 .

[5]  M. H. Johnson,et al.  FLOW-PROPORTIONAL, TIME-COMPOSITED, AND GRAB SAMPLE ESTIMATION OF NITROGEN EXPORT FROM AN EASTERN COASTAL PLAIN WATERSHED , 2000 .

[6]  Soroosh Sorooshian,et al.  Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration , 1999 .

[7]  Dale M. Robertson,et al.  INFLUENCE OF DIFFERENT TEMPORAL SAMPLING STRATEGIES ON ESTIMATING TOTAL PHOSPHORUS AND SUSPENDED SEDIMENT CONCENTRATION AND TRANSPORT IN SMALL STREAMS 1 , 2003 .

[8]  F. H. Verhoff,et al.  River Nutrient and Chemical Transport Estimation , 1980 .

[9]  Martin Volk,et al.  Towards the implementation of the European Water Framework Directive?: Lessons learned from water quality simulations in an agricultural watershed , 2009 .

[10]  Dale M. Robertson,et al.  Influence of various water quality sampling strategies on load estimates for small streams , 1999 .

[11]  A. Tappin,et al.  European land-based pollutant loads to the North Sea: an analysis of the Paris Commission data and review of monitoring strategies , 1997 .

[12]  R. D. Harmel,et al.  UNCERTAINTY IN MEASURED SEDIMENT AND NUTRIENT FLUX IN RUNOFF FROM SMALL AGRICULTURAL WATERSHEDS , 2005 .

[13]  L. Gottschalk,et al.  Validation of a distributed hydrological model against spatial observations , 1999 .

[14]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[15]  Jeffrey G. Arnold,et al.  The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions , 2007 .

[16]  W. Bauwens,et al.  Application of Automated Measurement Stations for Continuous Water Quality Monitoring of the Dender River in Flanders, Belgium , 2005, Environmental monitoring and assessment.

[17]  J. Arnold,et al.  SWAT2000: current capabilities and research opportunities in applied watershed modelling , 2005 .

[18]  J. Arnold,et al.  Predicting Water, Sediment and NO3-N Loads under Scenarios of Land-use and Management Practices in a Flat Watershed , 2004 .

[19]  Pamela J. Edwards,et al.  Comparison of methods for calculating annual solute exports from six forested Appalachian watersheds , 1997 .

[20]  Santanu Kumar Behera,et al.  Evaluation of management alternatives for an agricultural watershed in a sub-humid subtropical region using a physical process based model , 2006 .

[21]  Desmond E. Walling,et al.  The reliability of suspended sediment load data , 1981 .

[22]  R. D. Harmel,et al.  AUTOMATED STORM WATER SAMPLING ON SMALL WATERSHEDS , 2003 .

[23]  Jeffrey G. Arnold,et al.  Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations , 2007 .

[24]  Jeffrey G. Arnold,et al.  Estimating hydrologic budgets for three Illinois watersheds , 1996 .

[25]  I. G. Littlewood,et al.  Hydrological regimes, sampling strategies, and assessment of errors in mass load estimates for United Kingdom rivers , 1995 .

[26]  Jeffrey G. Arnold,et al.  CUMULATIVE UNCERTAINTY IN MEASURED STREAMFLOW AND WATER QUALITY DATA FOR SMALL WATERSHEDS , 2006 .

[27]  Peter M. Allen,et al.  Automated Base Flow Separation and Recession Analysis Techniques , 1995 .

[28]  H. Allen Torbert,et al.  Minimum flow considerations for automated storm sampling on small watersheds , 2002 .

[29]  Branislav Vrana,et al.  A "toolbox" for biological and chemical monitoring requirements for the European Union's Water Framework Directive. , 2006, Talanta.

[30]  Raghavan Srinivasan,et al.  A GIS‐Coupled Hydrological Model System for the Watershed Assessment of Agricultural Nonpoint and Point Sources of Pollution , 2004, Trans. GIS.

[31]  Sudhindra N. Panda,et al.  Modelling of an Agricultural Watershed using Remote Sensing and a Geographic Information System , 2005 .

[32]  Mazdak Arabi,et al.  Modeling long-term water quality impact of structural BMPs , 2006 .

[33]  D. Walling,et al.  Load estimation methodologies for British rivers and their relevance to the LOIS RACS(R) programme , 1997 .

[34]  Jens Christian Refsgaard,et al.  The inadequacy of monitoring without modelling support. , 2007, Journal of environmental monitoring : JEM.

[35]  Michael J. Singer,et al.  Timing, frequency of sampling affect accuracy of water-quality monitoring , 1999 .

[36]  D. R. Smith,et al.  Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications , 2009, Environ. Model. Softw..

[37]  Forrest T. Izuno,et al.  TIME VERSUS FLOW COMPOSITE WATER SAMPLING FOR REGULATORY PURPOSES IN THE EVERGLADES AGRICULTURAL AREA , 1998 .

[38]  I. G. Littlewood,et al.  Annual freshwater river mass loads from Great Britain, 1975–1994: estimation algorithm, database and monitoring network issues , 2005 .