Sampling design for compliance monitoring of surface water quality: A case study in a Polder area

International agreements such as the EU Water Framework Directive (WFD) ask for efficient sampling methods for monitoring natural resources. In this paper a general methodology for designing efficient, statistically sound monitoring schemes is described. An important decision is the choice between a design-based and a model-based method, implying the choice between probability (random) sampling and purposive sampling. For mapping purposes, model-based methods are more appropriate, whereas to obtain valid results for the universe as a whole, such as in testing water quality standards against legal standards, we generally prefer a design-based method. Four basic sampling patterns in space-time universe are described: static, synchronous, static-synchronous, and rotational. A case study is carried out for monitoring the quality of surface water at two farms in western Netherlands, wherein a synchronous sampling design is applied, with stratified simple random sampling in both space and time. To reduce laboratory costs the aliquots taken at the locations of a given sampling round are bulked to form a composite. To test the spatiotemporal mean N-total concentration during the summer half-year against the MAR standard with a power of 80% at a concentration 15% below the MAR standard and with a confidence of 95%, six to nine sampling rounds are needed with 50 to 75 locations per sampling round. For P-total the required number of sampling rounds differs strongly between the two farms, but is for both farms much larger than for N-total

A disposition of interpolation techniques

A large collection of interpolation techniques is available for application in environmental research. To help environmental scientists in choosing an appropriate technique a disposition is made, based on 1) applicability in space, time and space-time, 2) quantification of accuracy of interpolated values, 3) incorporation of ancillary information, and 4) incorporation of process knowledge. The described methods include inverse distance weighting, nearest neighbour methods, geostatistical interpolation methods, Kalman filter methods, Bayesian Maximum Entropy methods, etc. The applicability of methods in aggregation (upscaling) and disaggregation (downscaling) is discussed. Software for interpolation is described. The application of interpolation techniques is illustrated in two case studies: temporal interpolation of indicators for ecological water quality, and spatio-temporal interpolation and aggregation of pesticide concentrations in Dutch surface waters. A valuable next step will be to construct a decision tree or decision support system, that guides the environmental scientist to easy-to-use software implementations that are appropriate to solve their interpolation problem. Validation studies are needed to assess the quality of interpolated values, and the quality of information on uncertainty provided by the interpolation method

Estimating space-time mean concentrations of nutrients in surface waters of variable depth

A monitoring scheme has been designed to test whether the space-time mean concentration total Nitrogen (N-total) in the surface water in the Northern Frisian Woodlands (NFW, The Netherlands) complies with standards of the European Water Framework directive. Since in statistical testing for compliance monitoring valid estimators for the mean and its variance are important, a design-based method is preferred above a model-based method. In the NFW-area the surface water depth varies in both space and time and can periodically equal zero, due to variation in precipitation and evapotranspiration. To account for this, space-time mean concentrations are estimated by the ratio of the estimated total mass of nutrient and the estimated total volume of water. The method is applied in the period from 1 April to 30 September 2008 to four hydrologically different subareas. Besides, the aim was to use the information on the spatial and temporal variance of N-total concentrations to optimize the numbers of sampling rounds and sampling locations per sampling round in future monitoring campaigns, given budgetary constraints. A bootstrap procedure was applied to account for uncertainty about the temporal and spatial variances in estimating the optimal number of sampling rounds and sampling locations. For two subareas the accuracy of the estimated space-time means can be improved by sampling more frequently at less locations (compared to the design applied in 2008), whereas for one subarea sampling less frequently at more locations increases the precision. For one subarea the sample data were rather inconclusive about the optimal sample sizes

The relationship between time series models for water table depth and physical information

The relationship between parameters of autoregressive moving average exogenous variable (ARMAX) models and physical information that can be derived from databases such as digital topographical maps, digital elevation maps and soil profile descriptionswas investigated at 51 sites with open sandy soils in the Pleistocene part of the Netherlands, The ARMAX parameters appeared to be weakly related with physical information. Water-table depth predicted with ARMAX models which were guessed using physical information have large systematic errors but relatively small random errors. It is concluded that the relationships between time series model paremters and physical information can be improved with respect to the modelling as well as the quality of the data used

Aggregation of ecological indicators for mapping aquatic nature quality : overview of existing methods and case studies

Indicators for aquatic nature quality are calculated using ecological monitoring data from individual sampling stations. For reporting purposes, these results need to be aggregated and scaled up to higher levels (catchment area, country). This report provides an overview of different existing spatial aggregation methods for this purpose, including an evaluation of their suitability for aquatic ecological indicators. So-called „model-based„ methods, consisting of some sort of „kriging¿ step followed by calculation of the arithmetic mean, appeared to be the most appropriate. Application of these methods to multimetric indicators of aquatic macroinvertebrates in two Dutch subcatchment areas confirmed their suitability. However, the methods that were used were based on aggregation (using kriging) over Euclidian (straight), distances. It is recommended to conduct further research on the suitability of interpolation through stream networks, i.e., through the waterways themselves

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Water regimes in the Brazilian Cerrados are sensitive to climatological disturbances and human intervention. The risk that critical water-table levels are exceeded over long periods of time can be estimated by applying stochastic methods in modeling the dynamic relationship between water levels and driving forces such as precipitation and evapotranspiration. In this study, a transfer function-noise model, the so called PIRFICT-model, is applied to estimate the dynamic relationship between water-table depth and precipitation surplus/deficit in a watershed with a groundwater monitoring scheme in the Brazilian Cerrados. Critical limits were defined for a period in the Cerrados agricultural calendar, the end of the rainy season, when extremely shallow levels

Towards a Soil Information System with quantified accuracy : a prototype for mapping continuous soil properties

This report describes the potential and functionality of software for spatial analysis, prediction and stochastic simulation of continuous soil properties using data from the Dutch Soil Information System (BIS). A geostatistical framework and R codes were developed. The geostatistical model of a soil property has a deterministic component representing the mean value within a soil category, and a stochastic component of standardized residuals. The standardized residuals are interpolated or simulated based on the simple kriging system. The software was tested in four case studies: exchangeable soil pH, clay content, organic matter content and Mean Spring Water table depth (MSW). It is concluded that the geostatistical framework and R codes developed in this study enable to predict values of continuous soil properties spatially, and to quantify the inaccuracy of these predictions. The inaccuracy of a spatial prediction at a certain location is quantified by the kriging variance, which can be interpreted as an indication of the uncertainty about the true value

Een blik op monitoring van de natuurlijke leefomgeving

Er wordt veel gemeten en waargenomen in de natuurlijke leefomgeving. Deze studie toont aan dat er veel kan worden verbeterd aan de bestaande monitoringpraktijk, wil de verkregen informatie worden benut in het beleid. Data worden nu namelijk volgens steekproefopzetten verzameld die verwerking tot de vereiste informatie in de weg staan. Monitoringnetwerken zijn niet flexibel genoeg om informatie te leveren voor nieuwe vragen uit de beleidspraktijk. Een algemene tekortkoming is dat statistische kennis onvoldoende wordt benut bij het ontwerpen van monitoringplannen. Deze studie is een pleidooi voor een geïntegreerde opzet van monitoringplannen met als principe: ‘begin aan het eind, en redeneer dan terug’

Environmental monitoring in heterogeneous soil-landscapes; A Dutch case study

The spatial heterogeneity of agricultural soil-landscapes is mostly not taken into account in environmental policies. Most environmental goals have been defined at national level or farm level but not at the landscape level. The potential for setting up a regional environmental monitoring network that supports self governance was explored. The research was performed in the Northern Friesian Woodland