Improving catchment discharge predictions by inferring flow route contributions from a nested-scale monitoring and model setup

Abstract

Abstract. Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for the estimation of flow route volumes and for predictions of catchment discharge. In order to relate field-site measurements to the catchmentscale an upscaling approach is introduced that assumes that scale differences in flow route fluxes originate from differences in the relationship between groundwater storage and the spatial structure of the groundwater table. This relationship is characterized by the Groundwater Depth Distribution (GDD) curve that relates spatial variation in groundwater depths to the average groundwater depth. The GDDcurve was measured for a single field site (0.009 km 2 ) and simple process descriptions were applied to relate groundwater levels to flow route discharges. This parsimonious model could accurately describe observed storage, tube drain discharge, overland flow and groundwater flow simultaneously with Nash-Sutcliff coefficients exceeding 0.8. A probabilistic Monte Carlo approach was applied to upscale field-site measurements to catchment scales by inferring scale-specific GDD-curves from the hydrographs of two nested catchments (0.4 and 6.5 km 2 ). The estimated contribution of tube drain effluent (a dominant source for nitrates) decreased with increasing scale from 76-79% at the field-site to 34-61% andCorrespondence to: Y. van der Velde (ype.vandervelde@wur.nl) 25-50% for both catchment scales. These results were validated by demonstrating that a model conditioned on nestedscale measurements improves simulations of nitrate loads and predictions of extreme discharges during validation periods compared to a model that was conditioned on catchment discharge only.

Chloride circulation in a lowland catchment and the formulation of transport by travel time distributions

“…Nutrients like nitrates, phosphates and chlorides are introduced into the soil in the form of manure and fertilizers during the fertilization period (March to October). Regional estimates of the inputs clearly show a decreasing trend in agricultural loads: chloride decreased from about 250 kg/ha in 1983 to less than 130 kg/ha in 2008 (À48%) [van der Velde et al, 2010a]. Chlorides stemming from atmospheric sources are expected to be around a few mg/l, providing a negligible contribution if compared to uncertainty in anthropogenic loads.…”

“…The crop fields are densely drained by ditches and almost 50% of the land is artificially drained via a tile drain network. Overland flow is mainly due to saturation excess, which is frequently observed in winter and it is estimated to contribute, depending on the period, between 25% and 40% of total catchment discharge [van der Velde et al, 2010c. The response of the catchment is quickened also by the high efficiency of the tile drainage network.…”

“…Due to its geological and hydrogeological characteristics it has been used as a research catchment since the 1960s [Wosten et al, 1985;van Ommen et al, 1989;van der Velde et al, 2009van der Velde et al, , 2010avan der Velde et al, , 2010bBrauer et al, 2011]. Data series regarding rainfall, discharge, solar radiation, temperature, chemical concentration, water levels, etc.…”

“…While early studies focused on data-driven, parametric identifications of stationary TTDs [Kirchner et al, 2001;Broxton et al, 2009;Tetzlaff et al, 2011], recent developments explicitly incorporated the time variability of climatic conditions [Hrachowitz et al, 2010;Brooks et al, 2010], topographic controls [McGuire et al, 2005] and the spatial heterogeneity of soil properties [Fiori and Russo, 2008;Russo and Fiori, 2009]. More recent developments [Botter et al, 2010Rinaldo et al, 2011;van der Velde et al, 2010avan der Velde et al, , 2012Harman et al, 2011;Hrachowitz et al, 2013] have focused on the role played by the intermittency of stochastic rainfall and soil moisture dynamics as sources of nonstationarity for TTDs. The last works helped to improve common practices used in travel time distribution analyses, with particular regard to conceptual and practical differences between the travel time distribution conditional on a given injection time and that conditional on a given sampling time at the outlet, jointly with the differences of both with the residence time distributions (RTDs) of water particles in storage within the catchment at any time.…”

“…Chlorides are an example of solutes which can be considered either geogenic or anthropogenic, because the mass input to the terrestrial part of the hydrologic cycle, whose proper quantification is sometimes problematic [Neal et al, 1988;Tetzlaff et al, 2007;Dunn and Bacon, 2008], originates either from atmospheric deposition and/or from the application of inorganic fertilizers. In extensively managed croplands, however, chloride loads associated to massive fertilizations typically cloud atmospheric deposition, leading to streamflow chloride concentrations exceeding O 10 1 À Á (mg/l) [van der Velde et al, 2010a;Rouxel et al, 2011;Molenat et al, 2013]. Depending on the biogeochemical properties of the catchment soils, high-chloride input rates may determine a transfer of acidity to surface waters [Farrell, 1995], with negative impacts on the ecosystem functions provided by river biomes [e.g., Ikuta and Kitamura, 1995].…”