Description: Although the hydrological effects of land use change have been studied extensively, only few datasets are available to accurately describe, model, and predict detailed changes in spatiotemporal patterns of hydrological fluxes and states due to land use change. The Wustebach catchment within the TERENO (TERrestrial Environmental Observatories) network in Germany provides a unique monitoring setup to measure the major components of the water balance (evapotranspiration, discharge, precipitation) and the spatiotemporal distribution of soil moisture before and after a partial deforestation. Here, we present five years of measured hydrological data, including all major water budget components three years before and two years after a partial deforestation. A data-driven approach was used to understand changes and related feedback mechanisms in spatiotemporal hydrological response patterns. As expected from earlier studies, the partial deforestation caused a decrease in evapotranspiration and an increase in discharge. A closer look at the high resolution datasets revealed new insights in the intra-annual variability and relationship between the water balance components. The overall decrease in evapotranspiration caused a large increase in soil water storage in the deforested region, especially during the summer period, which in turn caused an increase in the frequency of high discharge in the same period. Although the evapotranspiration in the forested region was larger on average, the deforested region showed a higher evapotranspiration during part of the summer period. This could be related to wetter conditions in the deforested area, accompanied with the emergence of grass vegetation. At the same time, wetter soil moisture conditions in the deforested area increased the spatial variance of soil moisture in the summer and therewith altered the relationship between spatial mean and variance. Altogether, this study illustrates that detailed spatiotemporal monitoring can provide new insights into the hydrological effects of partial deforestation. (C) 2016 Elsevier B.V. All rights reserved.

Description: Soil moisture signatures provide a promising solution to overcome the difficulty of evaluating soil moisture dynamics in hydrologic models. Soil moisture signatures are metrics that quantify the dynamic aspects of soil moisture timeseries and enable process-based model evaluations. To date, soil moisture signatures have been tested only under limited land-use types. In this study, we explore soil moisture signatures' ability to discriminate different dynamics among contrasting land-uses. We applied a set of nine soil moisture signatures to datasets from six in-situ soil moisture networks worldwide. The dataset covered a range of land-use types, including forested and deforested areas, shallow groundwater areas, wetlands, urban areas, grazed areas, and cropland areas. Our set of signatures characterized soil moisture dynamics at three temporal scales: event, season, and a complete timeseries. Statistical assessment of extracted signatures showed that (1) event-based signatures can distinguish different dynamics for all the land-uses, (2) season-based signatures can distinguish different dynamics for some types of land-uses (deforested vs. forested, urban vs. greenspace, and cropped vs. grazed vs. grassland contrasts), (3) timeseries-based signatures can distinguish different dynamics for some types of land-uses (deforested vs. forested, urban vs. greenspace, shallow vs. deep groundwater, wetland vs. non-wetland, and cropped vs. grazed vs. grassland contrasts). Further, we compared signature-based process interpretations against literature knowledge; event-based and timeseries-based signatures generally matched well with previous process understandings from literature, but season-based signatures did not. This study will be a useful guideline for understanding how catchment-scale soil moisture dynamics in various land-uses can be described using a standardized set of hydrologically relevant metrics.

Description: Integrated observation platforms have been set up to investigate consequences of global change within a terrestrial network of observatories (TERENO) in Germany. The aim of TERENO is to foster the understanding of water, energy, and matter fluxes in terrestrial systems, as well as their biological and physical drivers. Part of the Lower Rhine Valley-Eifel observatory of TERENO is located within the Eifel National Park. Recently, the National Park forest management started to promote the natural regeneration of near-natural beech forest by removing a significant proportion of the spruce forest that was established for timber production after World War II. Within this context, the effects of such a disturbance on forest ecosystem functioning are currently investigated in a deforestation experiment in the Wustebach catchment, which is one of the key experimental research sites within the Lower Rhine Valley-Eifel observatory. Here, we present the integrated observation system of the Wustebach test site to exemplarily demonstrate the terrestrial observatory concept of TERENO that allows for a detailed monitoring of changes in hydrological and biogeochemical states and fluxes triggered by environmental disturbances. We present the observation platforms and the soil sampling campaign, as well as preliminary results including an analysis of data consistency. We specifically highlight the capability of integrated datasets to enable improved process understanding of the post-deforestation changes in ecosystem functioning.

Description: The effects of land use change on the occurrence and frequency of preferential flow (fast water flow through a small fraction of the pore space) and piston flow (slower water flow through a large fraction of the pore space) are still not fully understood. In this study, we used a five year high resolution soil moisture monitoring dataset in combination with a response time analysis to identify factors that control preferential and piston flow before and after partial deforestation in a small headwater catchment. The sensor response times at 5, 20 and 50 cm depths were classified into one of four classes: (1) non-sequential preferential flow, (2) velocity based preferential flow, (3) sequential (piston) flow, and (4) no response. The results of this analysis showed that partial deforestation increased sequential flow occurrence and decreased the occurrence of no flow in the deforested area. Similar precipitation conditions (total precipitation) after deforestation caused more sequential flow in the deforested area, which was attributed to higher antecedent moisture conditions and the lack of interception. At the same time, an increase in preferential flow occurrence was also observed for events with identical total precipitation. However, as the events in the treatment period (after deforestation) generally had lower total, maximum, and mean precipitation, this effect was not observed in the overall occurrence of preferential flow. The results of this analysis demonstrate that the combination of a sensor response time analysis and a soil moisture dataset that includes pre- and post-deforestation conditions can offer new insights in preferential and sequential flow conditions after land use change.

Description: The effects of land use change on the occurrence and frequency of preferential flow (fast water flow through a small fraction of the pore space) and piston flow (slower water flow through a large fraction of the pore space) are still not fully understood. In this study, we used a five year high resolution soil moisture monitoring dataset in combination with a response time analysis to identify factors that control preferential and piston flow before and after partial deforestation in a small headwater catchment. The sensor response times at 5, 20 and 50 cm depths were classified into one of four classes: (1) non-sequential preferential flow, (2) velocity based preferential flow, (3) sequential (piston) flow, and (4) no response. The results of this analysis showed that partial deforestation increased sequential flow occurrence and decreased the occurrence of no flow in the deforested area. Similar precipitation conditions (total precipitation) after deforestation caused more sequential flow in the deforested area, which was attributed to higher antecedent moisture conditions and the lack of interception. At the same time, an increase in preferential flow occurrence was also observed for events with identical total precipitation. However, as the events in the treatment period (after deforestation) generally had lower total, maximum, and mean precipitation, this effect was not observed in the overall occurrence of preferential flow. The results of this analysis demonstrate that the combination of a sensor response time analysis and a soil moisture dataset that includes pre- and post-deforestation conditions can offer new insights in preferential and sequential flow conditions after land use change.

Description: Hydroxylamine (NH2OH), a reactive intermediate of several microbial nitrogen turnover processes, is a potential precursor of nitrous oxide (N2O) formation in the soil. However, the contribution of soil NH2OH to soil N2O emission rates in natural ecosystems is unclear. Here, we determined the spatial variability of NH2OH content and potential N2O emission rates of organic (Oh) and mineral (Ah) soil layers of a Norway spruce forest, using a recently developed analytical method for the determination of soil NH2OH content, combined with a geostatistical Kriging approach. Potential soil N2O emission rates were determined by laboratory incubations under oxic conditions, followed by gas chromatographic analysis and complemented by ancillary measurements of soil characteristics. Stepwise multiple regressions demonstrated that the potential N2O emission rates, NH2OH and nitrate (NO3-) content were spatially highly correlated, with hotspots for all three parameters observed in the headwater of a small creek flowing through the sampling area. In contrast, soil ammonium (NH4+) was only weakly correlated with potential N2O emission rates, and was excluded from the multiple regression models. While soil NH2OH content explained the potential soil N2O emission rates best for both layers, also NO3- and Mn content turned out to be significant parameters explaining N2O formation in both soil layers. The Kriging approach was improved markedly by the addition of the co-variable information of soil NH2OH and NO3- content. The results indicate that determination of soil NH2OH content could provide crucial information for the prediction of the spatial variability of soil N2O emissions. (C) 2016 Elsevier Ltd. All rights reserved.

Description: Understanding natural controls on N and C biogeochemical cycles is important to estimate human impacts on these cycles. This study examined the spatiotemporal relationships between time series of weekly monitored stream and groundwater N and C (assessed by NO3- and dissolved organic C [DOC]) in the forested Wustebach catchment (Germany). In addition to traditional correlation analysis, we applied wavelet transform coherence (WTC) analysis to study variations in the correlation and lag time between the N and C time series for different time scales. Median transit times were used to connect hydrologic and water chemistry data. We defined three stream-water groups: (i) subsurface runoff dominated locations with strong seasonal fluctuations in concentrations, short transit times, and strong negative C/N correlations with short time lags, (ii) groundwater dominated locations, with weaker seasonal fluctuations, longer transit times, and weaker C/N correlations with lags of several months, and (iii) intermediate locations, with moderate seasonal fluctuations, moderate transit times, and strong C/N correlations with short time lags. Water transit times could be identified as key drivers for the C/N relationship and we conclude that C and N transport in stream water can be explained by mixing of groundwater and subsurface runoff. Complemented by transit times and the hydrochemical time series, WTC analysis allowed us to discriminate between different water sources (groundwater vs. subsurface runoff). In conclusion, we found that in time series studies of hydrochemical data, e.g., DOC and NO3-, WTC analysis can be a viable tool to identify spatiotemporally dependent relationships in catchments.

Description: Current understanding of the variability in soil properties and their relationship to processes and spatial patterns in forested landscapes is limited due to the scarcity of datasets providing such information. Here we present a spatially highly resolved dataset (http://teodoor.icg.kfa-juelich.de/ibg3searchportal2/dispatch?metadata.detail.view.id=e3886301-7252-4142-b1a4-333dfe7f1ca4) that provides detailed information on the three-dimensional variability of biogeochemical properties in the Wustebach catchment (western Germany), a long-term environmental observation site of the TERENO (Terrestrial Environmental Observatories) project. High-resolution soil sampling was conducted, and physical and biogeochemical soil parameters were recorded per horizon. The dataset is helpful in the analysis of the spatial heterogeneity in biogeochemical properties within soil horizons and with depth through the soil profile. In addition, it shows links between hydrological and biogeochemical properties and processes within the system. Overall, the dataset provides a high-resolution view into (re) cycling, leaching, and storage of nutrients on the catchment scale in a forested headwater catchment.

Description: The highly dynamic nature of preferential flow in time and space makes it challenging to identify and analyze its occurrence at the catchment scale. Novel analysis methods using soil moisture sensor response times offer an opportunity to investigate catchment-wide controls on preferential flow. The aim of this study was to identify factors that control preferential flow occurrence based on 3-year soil moisture monitoring using a wireless sensor network in the Wustebach catchment, Germany. At 101 locations, the sensor response times at three depths (5, 20, and 50 cm) were classified into one of four classes: (1) non-sequential preferential flow, (2) velocity-based preferential flow, (3) sequential flow, and (4) no response. A conceptual model, postulating that preferential flow in the Wustebach catchment is dominated by differences in soil type, landscape position, and rainfall input, was proposed for hypothesis testing. To test the conceptual model, the classification results were combined with spatial and event-based data to understand and identify controlling factors. Spatial parameters consisted of hydrological, topographical, and soil physical and chemical parameters. Temporal factors included precipitation characteristics and antecedent soil moisture conditions. The conceptual model as proposed could only be partly confirmed. Event-based occurrence of preferential flow was highly affected by precipitation amount, with a nearly catchment-wide preferential response during large storm events. During intermediate events, preferential flow was controlled by small-scale heterogeneity, instead of showing catchment-wide patterns. The effect of antecedent catchment wetness on the occurrence of preferential flow was generally less profound, although a clear negative relationship was found for precipitation events with more than 25 mm. It was found that spatial occurrence of preferential flow was however governed by small-scale soil and biological features and local processes, and showed no obvious relationship with any of the selected spatial parameters. Overall, the results demonstrate that sensor response time analysis can offer innovative insights into the spatial temporal interrelationship of preferential flow occurrence. (C) 2016 Elsevier B.V. All rights reserved.

Description: The natural measurements of uranium (U) are important for establishing natural baseline levels of U in soil. The relations between U and other elements are important to determine the extent of geological origin of soil U. The present study was aimed at providing a three-dimensional view of soil U distribution in a forested catchment (ca. 38.5 ha) in western Germany. The evaluated data, containing 155 sampled points, each with four major soil horizons (L/Of, Oh, A, and B), were collected from two existing datasets. The vertical U distribution, the lateral pattern of U in the catchment, and the occurrence of correlations between U and three groups of elements (nutrient elements, heavy metals, and rare earth elements) were examined. The results showed the median U concentration increased sevenfold from the top horizon L/Of (0.14 mg kg−1) to the B horizon (1.01 mg kg−1), suggesting a geogenic origin of soil U. Overall, soil U concentration was found to be negatively correlated with some plant macronutrients (C, N, K, S, Ca) but positively with others (P, Mg, Cu, Zn, Fe, Mn, Mo). The negative correlations between U and some macronutrients indicated a limited accumulation of plant-derived U in soil, possibly due to low phytoavailability of U. Positive correlations were also found between U concentration and heavy metals (Cr, Co, Ni, Ga, As, Cd, Hg, Pb) or rare earth elements, which further pointed to a geogenic origin of soil U in this forested catchment.