Ude Shankar

Estimating the sources and transport of nutrients in the Waikato River Basin, New Zealand

North Island of New Zealand. This first application of SPARROW outside of the United States included watersheds representative of a wide range of natural and cultural conditions and water-resources data that were well suited for calibrating and validating the models. We applied the spatially distributed model to a drainage network of nearly 5000 stream reaches and 75 lakes and reservoirs to empirically estimate the rates of nutrient delivery (and their levels of uncertainty) from point and diffuse sources to streams, lakes, and watershed outlets. The resulting models displayed relatively small errors; predictions of stream yield (kg ha � 1 yr � 1 ) were typically within 30% or less of the observed values at the monitoring sites. There was strong evidence of the accuracy of the model estimates of nutrient sources and the natural rates of nutrient attenuation in surface waters. Estimated loss rates for streams, lakes, and reservoirs agreed closely with experimental measurements and empirical models from New Zealand, North America, and Europe as well as with previous U.S. SPARROW models. The results indicate that the SPARROW modeling technique provides a reliable method for relating experimental data and observations from small catchments to the transport of nutrients in the surface waters of large river basins. INDEX TERMS: 1871 Hydrology: Surface water quality; 1803 Hydrology: Anthropogenic effects; 1806 Hydrology: Chemistry of fresh water; 1857 Hydrology: Reservoirs (surface);

The application of a GIS-based decision support system to predict nitrate leaching to groundwater in southern Germany

Abstract A decision support system has been developed in New Zealand which links national databases with a physically-based, basin-scale surface water quality model within a geographical information system (GIS) interface. In this study, the system is applied to a drainage basin in southern Germany, part of which is underlain by an aquifer which provides water for potable supply. The contamination of the groundwater resource by nitrate is of much concern in this area, and to aid in the prediction of groundwater contamination, the system is modified so that it can predict the concentrations of nitrate leached to groundwater. Model predictions over a six year period are compared with measured flow and concentration data from the river and concentration data from numerous boreholes. Model output in terms of nitrate leaching is displayed as a map over the extent of the aquifer so that areas particularly susceptible to nitrate leaching can be identified.

Creating rectangular bathymetry grids for environmental numerical modelling of gravel-bed rivers

Abstract The accuracy of bathymetry grids used in the numerical modelling of gravel-bed rivers has been identified as a potential limiting factor to the accuracy of the model output. This paper addresses the creation of two-dimensional rectangular grids from irregular data for gravel-bed rivers. A procedure based on the kriging algorithm is presented. The major features of the procedure are the detrending of the data, the addition of extra knowledge from sources such as photographs and site visits, as well as the use of the model semi-variogram. The calculated grid residual variance is significantly lower when the procedure is followed than when the kriging method is applied in a “black-box” fashion.

Can bottom-up procedures improve the performance of stream classifications?

Top-down methods for defining stream classifications are based on a conceptual model or expert-defined rules, whereas bottom-up methods use biological training data and statistical modelling. We compared the performance of six classification methods for explaining the taxonomic composition of invertebrate and fish assemblages recorded at 327 and 511 sites, respectively, distributed throughout France. Classification 1 and 2 were top-down classifications; The European Water Framework System A (WFDa,) and the French Hydro-ecoregions (HER 2). Four bottom-up classification procedures of increasing complexity were defined based on 11 variables that included watershed characteristics describing climate, topography, and geology, and site characteristics including elevation, bed slope and temperature. Classification 3 was defined using matrix correlation (MC) to select a combination of variable categories that produced the best discrimination of the observed taxonomic composition. Classification 4 and 5 were defined by clustering the sites based on their taxonomic data and then using linear discriminant analysis (LDA) and Random forests (RF) to discriminate the clusters based on the environmental variables. Classification 6 was defined using generalized dissimilarity modelling (GDM). Our hypothesis was that the bottom-up classifications would perform better because they flexibly accommodate complex relationships between compositional and environmental variation. We tested the classifications using the classification strength statistic (CS). The RF-based classification fitted the taxonomic patterns better than GDM or LDA and these latter classifications generally fitted better than the MC, WFDa or HER classifications. Cross validation analysis showed that differences in predictive CS (i.e. the CS statistics produced from sites not used in defining the classifications) were often significant. However, these differences were generally small. Gains in predictive performance of classifications appear to be small relative to the increase in complexity in the manner in which environmental variables are combined to define classes.

ON CHANNEL NETWORK FRACTAL PROPERTIES : A CASE OF STUDY OF THE HUTT RIVER BASIN, NEW ZEALAND

The paper considers river networks as three-dimensional self-affine fractal objects. The Hutt River basin (New Zealand∥ was selected for detailed analysis on the basis of a digital elevation model (DEM). To characterize network properties quantitatively we used three scaling exponents in the relationships l ∝ ℒυl, wℒυw, and h ∝ ℒυh where l, w, h are some characteristic longitudinal, transversal, and vertical scales of a channel network; ℒ is the total length of channel network in three-dimensional space; and υl, υw, and υh are the self-affine scaling exponents. We determined υl, υw, and υh using Lp ∝ Aβ, ℒp ∝ Aϵ, and S ∝ A−θ, where Lp is the length of the projection of the longest river channel on the horizontal plane, ℒp is the total length of channel network projection on the horizontal plane, A is the catchment area, and S is the local slope. An approximate relationship υh ≈ υl − θ(υl + υw) is derived which connects the main scaling exponents. For two New Zealand rivers, we found υl=0.60 and υw=0.40. On the basis of simple considerations, we estimated a range of possible values of υh from 0.1 to 0.5 with 0.2 for the case study. The slope-area-elevation relation introduced by Willgoose [1994] was applied to interpret data concerning υh. The influence of threshold area (TA) values on the scaling properties of channel networks is shown to be small, and double scaling relationships are suggested for connecting the physical scaling of channel networks with scaling caused by threshold effect.

A national-scale GIS-based system for modelling impacts of land use on water quality

Management of freshwater quality requires modelling tools for rapid evaluation of land use and management scenarios. This paper presents the CLUES (Catchment Land Use and Environmental Sustainability) model to address this need. CLUES provides steady state, spatially distributed, integrated catchment models tightly coupled to GIS software to predict mean annual loads of total nitrogen, total phosphorus, sediments and E.coli, and concentration of nutrients throughout New Zealand (268,000km2) with a subcatchment resolution of 0.5km2. CLUES also estimates potential nutrient concentrations for estuaries and provides key farm socio-economic indicators. The model includes a user interface for study area selection, scenario creation, data geo-visualisation, and export of results. It is pre-populated with spatial data and parameter values for New Zealand. Evaluation of the model and a summary of applications demonstrate the tractability and utility of national-scale rapid scenario assessment tools within a GIS framework. Display Omitted Stream water quality prediction at mean annual time-scale throughout New Zealand at kilometre-scale resolution.Rapid scenario generation and evaluation of land use change and management measures (mitigation factors, intensification).Includes links to an estuary nutrient component and simple socio-economic indicators.Has a growing number of applications for catchment, regional and national scenario assessment.

Using Simple Dilution Models to Predict New Zealand Estuarine Water Quality

A tool based on simple dilution models is developed to predict potential nutrient concentrations and flushing times for New Zealand estuaries. Potential nutrient concentrations are the concentrations that would occur in the absence of nutrient uptake or losses through biogeochemical processes, and so represent the pressure on a system due to nutrient loading. The dilution modelling approach gives a single time- and space-averaged concentration as a function of flow and nutrient input, with the capability to include seasonal nutrient and flow differences. This tool is intended to be used to identify estuaries likely to be highly sensitive to current nutrient loads based on their physical attributes, or to quickly compare the effects of different land-use scenarios on estuaries. The dilution modelling approach is applied both to a case study of a single New Zealand estuary, and used in a New Zealand-wide assessment of 415 estuaries. For the NZ-wide assessment, annual nutrient loads to each estuary were obtained from a GIS-based land-use model. Comparison with measured data shows that the predicted potential nitrate concentrations are significantly correlated with, but higher than, measured nitrate values from water quality sampling time series. This is consistent with expectations given that the measured concentrations include the effects of nitrogen uptake and loss. The estuary dilution modelling approach is currently incorporated into the GIS-land use model, and is also available as a web-app for assessing eutrophication susceptibility of New Zealand estuaries.

Some Current Issues In Using Diffuse Large Datasets For Environmental Modelling In New Zealand

Issues arising from the application of the SPARROW regional regression modelling technique to fluxes on nutrients in New Zealand streams are discussed. These include model scale dependency, as reflected in changing the DEM scale, and the lack of compatibility and transportability of the associated software. Nevertheless, this spatial referencing technique is demonstrating considerable advantages, because it manies the considerable spatially-referenced datasets with measurements routinely made in waterbodies. This facilitates the explanation of the relative importance of contaminant sources and may even be useful as a predictive tool (e.g., in showing the consequences of changing the land-use).