Hydrologic response of an alpine watershed: Application of a meteorological wireless sensor network to understand streamflow generation

A field measurement campaign was conducted from June to October 2009 in a 20 km2 catchment of the Swiss Alps with a wireless network of 12 weather stations and river discharge monitoring. The objective was to investigate the spatial variability of meteorological forcing and to assess its impact on streamflow generation. The analysis of the runoff dynamics highlighted the important contribution of snowmelt from spring to early summer. During the entire experimental period, the streamflow discharge was dominated by base flow contributions with temporal variations due to occasional rainfall-runoff events and a regular contribution from glacier melt. Given the importance of snow and ice melt runoff in this catchment, patterns of near-surface air temperatures were studied in detail. Statistical data analyses revealed that meteorological variables inside the watershed exhibit spatial variability. Air temperatures were influenced by topographic effects such as slope, aspect, and elevation. Rainfall was found to be spatially variable inside the catchment. The impact of this variability on streamflow generation was assessed using a lumped degree-day model. Despite the variability within the watershed, the streamflow discharge could be described using the lumped model. The novelty of this work mainly consists in quantifying spatial variability for a small watershed and showing to which extent this is important. When the focus is on aggregated outputs, such as streamflow discharge, average values of meteorological forcing can be adequately used. On the contrary, when the focus is on distributed fields such as evaporation or soil moisture, their estimate can benefit from distributed measurements

Modelling soil carbon and nitrogen cycles during land use change. A review

Forested soils are being increasingly transformed to agricultural fields in response to growing demands for food crop. This modification of the land use is known to result in deterioration of soil properties, in particular its fertility. To reduce the impact of the human activities and mitigate their effects on the soil, it is important to understand the factors responsible for the modification of soil properties. In this paper we reviewed the principal processes affecting soil quality during land use changes, focusing in particular on the effect of soil moisture dynamics on soil carbon (C) and nitrogen (N) cycles. Both physical and biological processes, including degradation of litter and humus, and soil moisture evolution at the diurnal and seasonal time scales were considered, highlighting the impact of hydroclimatic variability on nutrient turnover along with the consequences of land use changes from forest to agricultural soil and vice-versa. In order to identify to what extent different models are suitable for long-term predictions of soil turnover, and to understand whether some simulators are more suited to specific environmental conditions or ecosystems, we enumerated the principal features of the most popular existing models dealing with C and N turnover. Among these models, we considered in detail a mechanistic compartment-based model. To show the capabilities of the model and to demonstrate how it can be used as a predictive tool to forecast the effects of land use changes on C and N dynamics, four different scenarios were studied, intertwining two different climate conditions (with and without seasonality) with two contrasting soils having physical properties that are representative of forest and agricultural soils. The model incorporates synthetic time series of stochastic precipitation, and therefore soil moisture evolution through time. Our main findings in simulating these scenarios are that 1) forest soils have higher concentrations of C and N than agricultural soils as a result of higher litter decomposition; 2) high frequency changes in water saturations under seasonal climate scenarios are commensurate with C and N concentrations in agricultural soils; and 3) due to their different physical properties, forest soils attenuate the seasonal climate-induced frequency changes in water saturation, with accompanying changes in C and N concentrations. The model was shown to be capable of simulating the long term effects of modified physical properties of agricultural soils, being thus a promising tool to predict future consequences of practices affecting sustainable agriculture, such as tillage (leading to erosion), ploughing, harvesting, irrigation and fertilization, leading to C and N turnover changes and in consequence, in terms of agriculture production