The cumulative impacts of small reservoirs on hydrology: A review.

The number of small reservoirs has increased due to their reduced cost, the availability of many favourable locations, and their easy access due to proximity. The cumulative impacts of such small reservoirs are not easy to estimate, even when solely considering hydrology, which is partially due to the difficulty in collecting data on the functioning of such reservoirs. However, there is evidence indicating that the cumulative impacts of such reservoirs are significant. The aim of this article is to present a review of the studies that address the cumulative impacts of small reservoirs on hydrology, focusing on the methodology and on the way in which these impacts are assessed. Most of the studies addressing the hydrological cumulative impacts focused on the annual stream discharge, with decreases ranging from 0.2% to 36% with a mean value of 13.4% ± 8% over approximately 30 references. However, it is shown that similar densities of small reservoirs can lead to different impacts on stream discharge in different regions. This result is probably due to the hydro-climatic conditions and makes defining simple indicators to provide a first guess of the cumulative impacts difficult. The impacts also vary in time, with a more intense reduction in the river discharge during the dry years than during the wet years. This finding is certainly an important point to take into consideration in the context of climate change. Two methods are mostly used to estimate cumulative impacts: i) exclusively data-based methods and ii) models. The assumptions, interests and shortcomings of these methods are presented. Scientific tracks are proposed to address the four main shortcomings, namely the estimation of the associated uncertainties, the lack of knowledge on reservoir characteristics and water abstraction and the accuracy of the impact indicators.

Pesticide fate modeling in soils with the crop model STICS: Feasibility for assessment of agricultural practices.

Numerous pesticide fate models are available, but few of them are able to take into account specific agricultural practices, such as catch crop, mixing crops or tillage in their predictions. In order to better integrate crop management and crop growth in the simulation of diffuse agricultural pollutions, and to manage both pesticide and nitrogen pollution, a pesticide fate module was implemented in the crop model STICS. The objectives of the study were: (i) to implement a pesticide fate module in the crop model STICS; (ii) to evaluate the model performance using experimental data from three sites with different pedoclimatic contexts, one in The Netherlands and two in northern France; (iii) to compare the simulations with several pesticide fate models; and (iv) to test the impact of specific agricultural practices on the transfer of the dissolved fraction of pesticides. The evaluations were carried out with three herbicides: bentazone, isoproturon, and atrazine. The strategy applied in this study relies on a noncalibration approach and sensitivity test to assess the operating limits of the model. To this end, the evaluation was performed with default values found in the literature and completed by sensitivity tests. The extended version of the STICS named STICS-Pest, shows similar results with other pesticide fate models widely used in the literature. Moreover, STICS-Pest was able to estimate realistic crop growth and catch crop dynamic, which thus illustrate agricultural practices leading to a reduction of nitrate and a change in pesticide leaching. The dynamic plot-scale model, STICS-Pest is able to simulate nitrogen and pesticide fluxes, when the hydrologic context is in the validity range of the reservoir (or capacity) model. According to these initial results, the model may be a relevant tool for studying the effect of long-term agricultural practices on pesticide residue dynamics in soil and the associated diffuse pollution transfer.

Modelling the fate of nonylphenolic compounds in the Seine River--part 2: assessing the impact of global change on daily concentrations.

This study aims at modelling the daily concentrations of nonylphenolic compounds such as 4-nonylphenol (4-NP), nonylphenol monoethoxylate (NP1EO) and nonylphenoxy acetic acid (NP1EC) within the Seine River downstream of Paris City for over a year, firstly in the present state (year 2010) and for years 2050 and 2100 in order to assess the consequences of global change on the fate of nonylphenolic compounds in the Seine river. Concentrations were first simulated for the year 2010 and compared to monthly measured values downstream of Paris. To achieve this goal, the hydrodynamic and biogeochemical model, ProSe, was updated to simulate the fate of 4-NP, NP1EO and NP1EC. The Seine upstream and Oise River (tributaries of the Seine River) concentrations are estimated according to concentrations-flow relationships. For Seine Aval wastewater treatment plant (SA-WWTP), the concentrations are considered constant and the median values of 11 campaigns are used. The biodegradation kinetics of 4-NP, NP1EO and NP1EC in the Seine River were deduced from the results of the companion paper. The Nash-Sutcliffe coefficient indicates a good efficiency to simulate the concentrations of 4-NP, NP1EC and NP1EO over an entire year. Eight scenarios were built to forecast the impacts of global warming (flow decrease), population growth (SA-WWTP flow increase) and optimisation of wastewater treatment (improvement of the quality of effluents) on annual concentrations of 4-NP, NP1EO and NP1EC at Meulan by 2050 and 2100. As a result, global warming and population growth may increase the concentrations of 4-NP, NP1EC and NP1EO, especially during low-flow conditions, while the optimisation of wastewater treatment is an efficient solution to balance the global change by reducing WWTP outflows.