Hydrological responses of a watershed to historical land use evolution and future land use scenarios under climate change conditions

Watershed runoff is closely related to land use but this influence is difficult to quantify. This study focused on the Chaudière River watershed (Québec, Canada) and had two objectives: (i) to quantify the influence of historical agricultural land use evolution on watershed runoff; and (ii) to assess the effect of future land use evolution scenarios under climate change conditions (CC). To achieve this, we used the integrated modeling system GIBSI. Past land use evolution was constructed using satellite images that were integrated into GIBSI. The general trend was an increase of agricultural land in the 80's, a slight decrease in the beginning of the 90's and a steady state over the last ten years. Simulations showed strong correlations between land use evolution and water discharge at the watershed outlet. For the prospective approach, we first assessed the effect of CC and then defined two opposite land use evolution scenarios for the horizon 2025 based on two different trends: agriculture intensification and sustainable development. Simulations led to a wide range of results depending on the climatologic models and gas emission scenarios considered, varying from a decrease to an increase of annual and monthly water discharge. In this context, the two land use scenarios induced opposite effects on water discharge and low flow sequences, especially during the growing season. However, due to the large uncertainty linked to CC simulations, it is difficult to conclude that one land use scenario provides a better adaptation to CC than another. Nevertheless, this study shows that land use is a key factor that has to be taken into account when predicting potential future hydrological responses of a watershed

Selecting a calculation method to estimate sediment and nutrient loads in streams: Application to the Beaurivage River

Abstract Estimation of sediment and nutrient loads is of crucial interest for a good assessment of water pollution. This paper proposes an overview of existing estimation methods and a framework to select the most suited one given available streamflow and concentration data. Correlations between contaminant concentration and streamflow should first be checked to generate missing concentration values by regression. However, correlations are not always strong, in which case the ratio estimator method is more appropriate. Given a 6-year data set (1989)(1990)(1991)(1992)(1993)(1994)(1995) from the Beaurivage River (Québec, Canada) with, at best, a weekly sampling, the ratio estimator method was selected to estimate annual and seasonal loads of sediments and nutrients (N and P). Results show relatively steady annual loads (on average 8.1 and 1.1 kg ha yr K1 for total dissolved N and total P, respectively) and a low erosion rate (0.23 t ha yr K1 ). The results also confirm that nutrient and sediment transport via runoff is essentially a springtime process in this region, and they indicate that dissolved P represents the bulk of the total P load, most likely due to artificial subsurface drainage systems in the watershed. These results are compared to the results obtained by using averaging methods and to several other sources of information from literature, confirming the order of magnitude but highlighting some remaining uncertainties. Finally, some research avenues are proposed to improve the proposed framework and to investigate other estimation methods adapted to data characteristics.

Flood quantiles scaling with upper soil hydraulic properties for different land uses at catchment scale

[EN] Changes in land use within a catchment are among the causes of non-stationarity in the flood regime, as they modify the upper soil physical structure and its runoff production capacity. This paper analyzes the relation between the variation of the upper soil hydraulic properties due to changes in land use and its effect on the magnitude of peak flows: (1) incorporating fractal scaling properties to relate the effect of the static storage capacity (the sum of capillary water storage capacity in the root zone, canopy interception and surface puddles) and the upper soil vertical saturated hydraulic conductivity on the flood regime; (2) describing the effect of the spatial organization of the upper soil hydraulic properties at catchment scale; (3) examining the scale properties in the parameters of the Generalized Extreme Value (GEV) probability distribution function, in relation to the upper soil hydraulic properties. This study considered the historical changes of land use in the Combeima River catchment in South America, between 1991 and 2007, using distributed hydrological modeling of daily discharges to describe the hydrological response. Through simulation of land cover scenarios, it was demonstrated that it is possible to quantify the magnitude of peak flows in scenarios of land cover changes through its Wide-Sense Simple Scaling with the upper soil hydraulic properties.This research was funded partially by the COLCIENCIAS 567 doctoral fellowship program, Universidad del Tolima project 1300213 and Universidad de Ibague (Colombia) project 12-262-COL00, and by Universitat Politecnica de Valencia (Spain) and by the Spanish Research Project ECO-TETIS (ref. CGL2011-28776-C02-01) and TETIS-MED (ref. CGL2014-58127-C3-3-R). Thanks to The Shuttle Radar Topography Mission NASA, IDEAM and IGAC in Colombia, for providing digital elevation model, streamflow, rainfall data, and soil study of the Tolima Region.Peña-Rojas, LE.; Barrios Peña, MI.; Francés, F. (2016). Flood quantiles scaling with upper soil hydraulic properties for different land uses at catchment scale. Journal of Hydrology. 541:1258-1272. https://doi.org/10.1016/j.jhydrol.2016.08.031S1258127254

Loadings of dissolved organic matter and nutrients from the Neva River into the Gulf of Finland - Biogeochemical composition and spatial distribution within the salinity gradient

We studied the loadings of dissolved organic matter (DOM) and nutrients from the Neva River into the Eastern Gulf of Finland, as well as their distribution within the salinity gradient. Concentrations of dissolved organic carbon (DOC) ranged from 390 to 840 mu M, and were related to absorption of colored DOM (CDOM) at 350 nm, a(CDOM)(350), ranging from 2.70 to 17.8 m(-1). With increasing salinity both DOC and a(CDOM) decreased, whereas the slope of a(CDOM) spectra, S-CDOM(300-700), ranging from 14.3 to 21.2 mu m(-1), increased with salinity. Deviations of these properties from conservative mixing models were occasionally observed within the salinity range of approximately 1-4, corresponding to the region between 27 and 29 degrees E. These patterns are suggested to mostly reflect seasonal changes in properties of river end-member and hydrodynamics of the estuary, rather than non-conservative processes. On the other hand, observed nonlinear relationships observed between a(CDOM)*(350) and S-CDOM(275-295) emphasized the importance of photochemistry among various transformation processes of DOM. Dissolved inorganic nitrogen was effectively transformed in the estuary into particulate organic nitrogen (PON) and dissolved organic nitrogen (DON), of which DON was mostly exported from the estuary, enhancing productivity in nitrogen limited parts of the Gulf of Finland. DON concentrations ranged from 12.4 to 23.5 mu M and its estuarine dynamics were clearly uncoupled from DOC. In contrast to DOC, estuarine DON dynamics suggest that its production exceeds losses in the estuary. Total nitrogen (TN) and phosphorus (TP) loadings from the Neva River and St. Petersburg were estimated as 73.5 Gg N yr(-1) and 4.2 Gg P yr(-1), respectively. Approximately 59% of TN and 53% of TP loads were in organic forms. DOC and DON loadings were estimated as 741.4 Gg C yr(-1) and 19.0 Gg N yr(-1), respectively. Our estimate for DOC loading was evaluated against a previously published carbon budget of the Baltic Sea. According to the updated model, the Baltic Sea could be identified as a weak source of carbon into the atmosphere. (C) 2016 The Authors. Published by Elsevier B.V.Peer reviewe

National scale evaluation of the InVEST nutrient retention model in the United Kingdom

A wide variety of tools aim to support decision making by modelling, mapping and quantifying ecosystem services. If decisions are to be properly informed, the accuracy and potential limitations of these tools must be well understood. However, dedicated studies evaluating ecosystem service models against empirical data are rare, especially over large areas. In this paper, we report on the national-scale assessment of a new ecosystem service model for nutrient delivery and retention, the InVEST Nutrient Delivery Ratio model. For 36 river catchments across the UK, we modelled total catchment export of phosphorus (P) and/or nitrogen (N) and compared model outputs to measurements derived from empirical water chemistry data. The model performed well in terms of relative magnitude of nutrient export among catchments (best Spearman’s rank correlation for N and P, respectively: 0.81 and 0.88). However, there was wide variation among catchments in the accuracy of the model, and absolute values of nutrient exports frequently showed high percentage differences between modelled and empirically-derived exports (best median absolute percentage difference for N and P, respectively: ± 64%, ± 44%). The model also showed a high degree of sensitivity to nutrient loads and hydrologic routing input parameters and these sensitivities varied among catchments. These results suggest that the InVEST model can provide valuable information on nutrient fluxes to decision makers, especially in terms of relative differences among catchments. However, caution is needed if using the absolute modelled values for decision-making. Our study also suggests particular attention should be paid to researching input nutrient loadings and retentions, and the selection of appropriate input data resolutions and threshold flow accumulation values. Our results also highlight how availability of empirical data can improve model calibration and performance assessment and reinforce the need to include such data in ecosystem service modelling studies