Sensitivity analysis of a catchment-scale nitrogen model

There are now considerable expectations that semi-distributed models are useful tools for supporting catchment water quality management. However, insufficient attention has been given to evaluating the uncertainties inherent to this type of model, especially those associated with the spatial disaggregation of the catchment. The Integrated Nitrogen in Catchments model (INCA) is subjected to an extensive regionalised sensitivity analysis in application to the River Kennet, part of the groundwater-dominated upper Thames catchment, UK The main results are: (1) model output was generally insensitive to land-phase parameters, very sensitive to groundwater parameters, including initial conditions, and significantly sensitive to in-river parameters; (2) INCA was able to produce good fits simultaneously to the available flow, nitrate and ammonium in-river data sets; (3) representing parameters as heterogeneous over the catchment (206 calibrated parameters) rather than homogeneous (24 calibrated parameters) produced a significant improvement in fit to nitrate but no significant improvement to flow and caused a deterioration in ammonium performance; (4) the analysis indicated that calibrating the flow-related parameters first, then calibrating the remaining parameters (as opposed to calibrating all parameters together) was not a sensible strategy in this case; (5) even the parameters to which the model output was most sensitive suffered from high uncertainty due to spatial inconsistencies in the estimated optimum values, parameter equifinality and the sampling error associated with the calibration method; (6) soil and groundwater nutrient and flow data are needed to reduce. uncertainty in initial conditions, residence times and nitrogen transformation parameters, and long-term historic data are needed so that key responses to changes in land-use management can be assimilated. The results indicate the general, difficulty of reconciling the questions which catchment nutrient models are expected to answer with typically limited data sets and limited knowledge about suitable model structures. The results demonstrate the importance of analysing semi-distributed model uncertainties prior to model application, and illustrate the value and limitations of using Monte Carlo-based methods for doing so. (c) 2005 Elsevier B.V. All rights reserved.

Effect of mycorrhizae and pH change at the root-soil interface on phosphorus uptake by Sorghum using a rhizocylinder technique

Sorghum (Sorghum bicolor) was grown for 40 days in. rhizocylinder (a growth container which permitted access to rh zosphere and nonrhizosphere soil), in two soils of low P status. Soils were fertilized with different rates of ammonium and nitrate and supplemented with 40 mg phosphorus (P) kg(-1) and inoculated with either Glomus mosseae (Nicol. and Gerd.) or nonmycorrhizal root inoculum.. N-serve (2 mg kg(-1)) was added to prevent nitrification. At harvest, soil from around the roots was collected at distances of 0-5, 5-10, and 10-20 mm from the root core which was 35 mm diameter. Sorghum plants, with and without mycorrhiza, grew larger with NH4+ than with NO3- application. After measuring soil pH, 4 3 suspensions of the same sample were titrated against 0.01 M HCl or 0.01 M NaOH until soil pH reached the nonplanted pH level. The acid or base requirement for each sample was calculated as mmol H+ or OFF kg(-1) soil. The magnitude of liberated acid or base depended on the form and rate of nitrogen and soil type. When the plant root was either uninfected or infected with mycorrhiza., soil pH changes extended up to 5 mm from the root core surface. In both soils, ammonium as an N source resulted in lower soil pH than nitrate. Mycorrhizal (VAM) inoculation did not enhance this difference. In mycorrhizal inoculated soil, P depletion extended tip to 20 mm from the root surface. In non-VAM inoculated soil P depletion extended up to 10 mm from the root surface and remained unchanged at greater distances. In the mycorrhizal inoculated soils, the contribution of the 0-5 mm soil zone to P uptake was greater than the core soil, which reflects the hyphal contribution to P supply. Nitrogen (N) applications that caused acidification increased P uptake because of increased demand; there is no direct evidence that the increased uptake was due to acidity increasing the solubility of P although this may have been a minor effect.

An application of the GLUE methodology for estimating the parameters of the INCA-N model

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist. (c) 2006 Elsevier B.V. All rights reserved.

Integrated Nitrogen CAtchment model (INCA) applied to a tropical catchment in the Atlantic Forest, Sao Paulo, Brazil

Stream-water flows and in-stream nitrate and ammonium concentrations in a small (36.7 ha) Atlantic Forest catchment were simulated using the Integrated Nitrogen in CAtchments (INCA) model version 1.9.4. The catchment, at Cunha, is in the Serra do Mar State Park, SE Brazil and is nearly pristine because the nearest major conurbations, Sao Paulo and Rio, are some 450 km distant. However, intensive farming may increase nitrogen (N) deposition and there are growing pressures for urbanisation. The mean-monthly discharges and NO3-N concentration dynamics were simulated adequately for the calibration and validation periods with (simulated) loss rates of 6.55 kg.ha(-1) yr(-1) for NO3-N and 3.85 kg.ha(-1) yr(-1) for NH4-N. To investigate the effects of elevated levels of N deposition in the future, various scenarios for atmospheric deposition were simulated; the highest value corresponded to that in a highly polluted area of Atlantic Forest in Sao Paulo City. It was found that doubling the atmospheric deposition generated a 25% increase in the N leaching rate, while at levels approaching the highly polluted Sao Paulo deposition rate, five times higher than the current rate, leaching increased by 240%, which would create highly eutrophic conditions, detrimental to downstream water quality. The results indicate that the INCA model can be useful for estimating N concentration and fluxes for different atmospheric deposition rates and hydrological conditions.