Identifying and assessing uncertainty in hydrological pathways: a novel approach to end member mixing in a Scottish agricultural catchment

Abstract. Subsurface lateral flow from agricultural hillslopes is often overlooked compared with overland flow and tile drain flow, partly due to the difficulties in monitoring and quantifying. The objectives of this study were to examine how subsurface lateral flow generated through soil pedons from cropped hillslopes and to quantify its contribution to nitrate loading in the streams through an agricultural catchment in the subtropical region of China. Profiles of soil water potential along hillslopes and stream hydro-chemographs in a trenched stream below a cropped hillslope and at the catchment outlet were simultaneously recorded during two rainstorm events. The dynamics of soil water potential showed positive matrix soil water potential over impermeable soil layer at 0.6 to 1.50 m depths during and after the storms, indicating soil water saturation and drainage processes along the hillslopes irrespective of land uses. The hydro-chemographs in the streams, one trenched below a cropped hillslope and one at the catchment outlet, showed that the concentrations of particulate nitrogen and phosphorus corresponded well to stream flow during the storm, while the nitrate concentration increased on the recession limbs of the hydrographs after the end of the storm. All the synchronous data revealed that nitrate was delivered from the cropped hillslope through subsurface lateral flow to the streams during and after the end of the rainstorms. A chemical mixing model based onCorrespondence to: B. Zhang (bzhang@caas.ac.cn) electricity conductivity (EC) and H + concentration was successfully established, particularly for the trenched stream. The results showed that the subsurface lateral flow accounted for 29 % to 45 % of total stream flow in the trenched stream, responsible for 86 % of total NO − 3 -N loss (or 26 % of total N loss), and for 5.7 % to 7.3 % of total stream flow at the catchment outlet, responsible for about 69 % of total NO − 3 -N loss (or 28 % of total N loss). The results suggest that subsurface lateral flow through hydraulically stratified soil pedons have to be paid more attention for controlling non-point source surface water pollution from intensive agricultural catchment particularly in the subtropical areas with great soil infiltration.

“…Mohanty et al, 1998;van der Velde et al, 2010), dissolved phosphorous (e.g. Stamm et al, 1998;Sinaj et al, 2002) and pesticides (e.g. Zehe and Flühler, 2001) in many agricultural fields.…”

Section: Introductionmentioning

confidence: 99%

Subsurface lateral flow from hillslope and its contribution to nitrate loading in streams through an agricultural catchment during subtropical rainstorm events

Zhang

Tang

Gao

et al. 2011

“…As almost all model parameters are related to measurable parameters, a sensitivity analysis also provides important information for future field data acquisition to reduce measurement uncertainty and improve the model's reliability. Generally, two kind of sensitivity analysis can be distinguished: a global sensitivity and a local sensitivity analysis (Tiemeijer et al, 2007;Spear and Hornberger, 1980). With local techniques parameter interdependencies are ignored and were found to be unreliable for non-linear relationships between parameters and outputs which are typical for hydrological outputs (Tiemeyer et al, 2007;Muleta and Nicklow, 2005).…”

Section: Parameter Sensitivity and Uncertainty Analysismentioning

confidence: 99%

“…EMMA assumes that solute concentrations in a stream result from the mixing of two or more flow routes with a known concentration ("endmembers") and it is often used for hydrograph separation into contributions of individual flow routes (e.g. Tiemeyer et al, 2008;Soulsby et al, 2003;van der Velde et al, 2010). Given the uncertainty of fluxes and concentration of the different sources only a combination of EMMA with an uncertainty and sensitivity assessment will yield meaningful estimations of individual flow routes.…”

Section: Introductionmentioning

confidence: 99%

Quantifying water and salt fluxes in a lowland polder catchment dominated by boil seepage: a probabilistic end-member mixing approach

Louw

Velde

Zee

2011

Abstract. Upward saline groundwater seepage is leading to surface water salinization of deep lying polders in the Netherlands. Identifying measures to reduce the salt content requires a thorough understanding and quantification of the dominant sources of water and salt on a daily basis. However, as in most balance studies, there are large uncertainties in the contribution from groundwater seepage. Taking these into account, we applied a probabilistic (GLUE) endmember mixing approach to simulate two years of daily to weekly observations of discharge, salt loads and salt concentration of water pumped out of an artificially drained polder catchment area. We were then able to assess the contribution from the different sources to the water and salt balance of the polder and uncertainties in their quantification. Our modelling approach demonstrates the need to distinguish preferential from diffuse seepage. Preferential seepage via boils contributes, on average, 66 % to the total salt load and only about 15 % to the total water flux into the polder and therefore forms the main salinization pathway. With the model we were able to calculate the effect of future changes on surface water salinity and to assess the uncertainty in our predictions. Furthermore, we analyzed the parameter sensitivity and uncertainty to determine for which parameter the quality of field measurements should be improved to reduce model input and output uncertainty. High frequency measurements of polder water discharge and weighted concentration at the outlet of the catchment area appear to be essential for obtaining reliable simulations of water and salt fluxes and for allotting these to the different sources.

“…EMMA has not generally been considered appropriate for N modelling, because it assumes constant solute concentrations that characterise the different sources of water within a catchment. However, some success has been achieved in using nitrate as an end-member over short time periods, for flow separation of storm events (Petry et al, 2002;Soulsby et al, 2003), by identifying differences in nitrate concentration between waters sourced from overland flow, subsurface flow from agricultural field drains and groundwater.…”

Section: Introductionmentioning

confidence: 99%

“…One of the commonly observed characteristics of streamwater N signals is a dilution effect at the peak of the hydrograph (Cooper and Roberts, 1996;Soulsby et al, 2003). This can be explained by the occurrence of overland flow where water is transported very rapidly to a surface stream.…”

Section: Introductionmentioning

confidence: 99%

Nitrogen Risk Assessment Model for Scotland: II. Hydrological transport and model testing

Dunn¹,

Lilly²,

DeGroote³

et al. 2004

The amount and concentration of N in catchment runoff is strongly controlled by a number of hydrological influences, such as leaching rates and the rate of transport of N from the land to surface water bodies. This paper describes how the principal hydrological controls at a catchment scale have been represented within the Nitrogen Risk Assessment Model for Scotland (NIRAMS); it demonstrates their influence through application of the model to eight Scottish catchments, contrasting in terms of their land use, climate and topography. Calculation of N leaching rates, described in the preceding paper (Dunn et al., 2004), is based on soil water content determined by application of a weekly water balance model. This model uses national scale datasets and has been developed and applied to the whole of Scotland using five years of historical meteorological data. A catchment scale transport model, constructed from a 50m digital elevation model, routes flows of N through the sub-surface and groundwater to the stream system. The results of the simulations carried out for eight different catchments demonstrate that the NIRAMS model is capable of predicting time-series of weekly stream flows and N concentrations, to an acceptable degree of accuracy. The model provides an appropriate framework for risk assessment applications requiring predictions in ungauged catchments and at a national scale. Analysis of the model behaviour shows that streamwater N concentrations are controlled both by the rate of supply of N from leaching as well as the rate of transport of N from the land to the water.