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Now showing 1 - 8 of 8
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    Monitoring hillslope moisture dynamics with surface ERT for enhancing spatial significance of hydrometric point measurements
    (Munich : EGU, 2015) Hübner, R.; Heller, K.; Günther, T.; Kleber, A.
    Besides floodplains, hillslopes are basic units that mainly control water movement and flow pathways within catchments of subdued mountain ranges. The structure of their shallow subsurface affects water balance, e.g. infiltration, retention, and runoff. Nevertheless, there is still a gap in the knowledge of the hydrological dynamics on hillslopes, notably due to the lack of generalization and transferability. This study presents a robust multi-method framework of electrical resistivity tomography (ERT) in addition to hydrometric point measurements, transferring hydrometric data into higher spatial scales to obtain additional patterns of distribution and dynamics of soil moisture on a hillslope. A geoelectrical monitoring in a small catchment in the eastern Ore Mountains was carried out at weekly intervals from May to December 2008 to image seasonal moisture dynamics on the hillslope scale. To link water content and electrical resistivity, the parameters of Archie's law were determined using different core samples. To optimize inversion parameters and methods, the derived spatial and temporal water content distribution was compared to tensiometer data. The results from ERT measurements show a strong correlation with the hydrometric data. The response is congruent to the soil tension data. Water content calculated from the ERT profile shows similar variations as that of water content from soil moisture sensors. Consequently, soil moisture dynamics on the hillslope scale may be determined not only by expensive invasive punctual hydrometric measurements, but also by minimally invasive time-lapse ERT, provided that pedo-/petrophysical relationships are known. Since ERT integrates larger spatial scales, a combination with hydrometric point measurements improves the understanding of the ongoing hydrological processes and better suits identification of heterogeneities.
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    Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile
    (Göttingen : Copernicus GmbH, 2018) Liersch, S.; Tecklenburg, J.; Rust, H.; Dobler, A.; Fischer, M.; Kruschke, T.; Koch, H.; Hattermann, F.F.
    Climate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth system models and 10 regional climate models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970-1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasize magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics and the effect of bias correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.
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    Climate-driven interannual variability of water scarcity in food production potential: A global analysis
    (Göttingen : Copernicus GmbH, 2014) Kummu, M.; Gerten, D.; Heinke, J.; Konzmann, M.; Varis, O.
    Interannual climatic and hydrologic variability has been substantial during the past decades in many regions. While climate variability and its impacts on precipitation and soil moisture have been studied intensively, less is known on subsequent implications for global food production. In this paper we quantify effects of hydroclimatic variability on global "green" and "blue" water availability and demand in global agriculture, and thus complement former studies that have focused merely on long-term averages. Moreover, we assess some options to overcome chronic or sporadic water scarcity. The analysis is based on historical climate forcing data sets over the period 1977-2006, while demography, diet composition and land use are fixed to reference conditions (year 2000). In doing so, we isolate the effect of interannual hydroclimatic variability from other factors that drive food production. We analyse the potential of food production units (FPUs) to produce a reference diet for their inhabitants (3000 kcal cap-1 day -1, with 80% vegetal food and 20% animal products). We applied the LPJmL vegetation and hydrology model to calculate the variation in green-blue water availability and the water requirements to produce that very diet. An FPU was considered water scarce if its water availability was not sufficient to produce the diet (i.e. assuming food self-sufficiency to estimate dependency on trade from elsewhere). We found that 24% of the world's population lives in chronically water-scarce FPUs (i.e. water is scarce every year), while an additional 19% live under occasional water scarcity (water is scarce in some years). Among these 2.6 billion people altogether, 55% would have to rely on international trade to reach the reference diet, while for 24% domestic trade would be enough. For the remaining 21% of the population exposed to some degree of water scarcity, local food storage and/or intermittent trade would be enough to secure the reference diet over the occasional dry years.
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    Three-dimensional monitoring of soil water content in a maize field using Electrical Resistivity Tomography
    (Munich : EGU, 2013) Beff, L.; Günther, T.; Vandoorne, B.; Couvreur, V.; Javaux, M.
    A good understanding of the soil water content (SWC) distribution at the field scale is essential to improve the management of water, soil and crops. Recent studies proved that Electrical Resistivity Tomography (ERT) opens interesting perspectives in the determination of the SWC distribution in 3 dimensions (3-D). This study was conducted (i) to check and validate how ERT is able to monitor SWC distribution in a maize field during the late growing season; and (ii) to investigate how maize plants and rainfall affect the dynamics of SWC distribution. Time Domain Reflectometry (TDR) measurements were used to validate ERT-inverted SWC values. Evolution of water mass balance was also calculated to check whether ERT was capable of giving a reliable estimate of soil water stock evolution. It is observed that ERT was able to give the same average SWC as TDR (R2 = 0.98). In addition, ERT gives better estimates of the water stock than TDR thanks to its higher spatial resolution. The high resolution of ERT measurements also allows for the discrimination of SWC heterogeneities. The SWC distribution showed that alternation of maize rows and inter-rows was the main influencing factor of the SWC distribution. The drying patterns were linked to the root profiles, with drier zones under the maize rows. During short periods, with negligible rainfall, the SWC decrease took place mainly in the two upper soil horizons and in the inter-row area. In contrast, rainfall increased the SWC mostly under the maize rows and in the upper soil layer. Nevertheless, the total amount of rainfall during the growing season was not sufficient to modify the SWC patterns induced by the maize rows. During the experimental time, there was hardly any SWC redistribution from maize rows to inter-rows. Yet, lateral redistribution from inter-rows to maize rows induced by potential gradient generates SWC decrease in the inter-row area and in the deeper soil horizons.
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    Impacts of future deforestation and climate change on the hydrology of the Amazon Basin: A multi-model analysis with a new set of land-cover change scenarios
    (Göttingen : Copernicus GmbH, 2017) Guimberteau, M.; Ciais, P.; Pablo, Boisier, J.; Paula Dutra Aguiar, A.; Biemans, H.; De Deurwaerder, H.; Galbraith, D.; Kruijt, B.; Langerwisch, F.; Poveda, G.; Rammig, A.; Andres Rodriguez, D.; Tejada, G.; Thonicke, K.; Von, Randow, C.; Randow, R.; Zhang, K.; Verbeeck, H.
    Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO2 levels. On the one hand, elevated CO2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Bolivian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3ĝ€°C by 2100 which drives up the evaporative demand, whereby precipitation increases by 8.5 %, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14ĝ€%, respectively. However, in south-east Amazonia, precipitation decreases by 10ĝ€% at the end of the dry season and the three LSMs produce a 6ĝ€% decrease of ET, which is less than precipitation, so that runoff decreases by 22 %. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31ĝ€% in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34ĝ€% over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the south-east, however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27ĝ€% in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast, we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.
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    Time-lapse gravity and levelling surveys reveal mass loss and ongoing subsidence in the urban subrosion-prone area of Bad Frankenhausen, Germany
    (Göttingen : Copernicus Publ., 2019) Kobe, Martin; Gabriel, Gerald; Weise, Adelheid; Vogel, Detlef
    We present results of sophisticated, high-precision time-lapse gravity monitoring that was conducted over 4 years in Bad Frankenhausen (Germany). To our knowledge, this is the first successful attempt to monitor subrosion-induced mass changes in urban areas with repeated gravimetry. The method provides an approach to estimate the mass of dissolved rocks in the subsurface. Subrosion, i.e. leaching and transfer of soluble rocks, occurs worldwide. Mainly in urban areas, any resulting ground subsidence can cause severe damage, especially if catastrophic events, i.e. collapse sinkholes, occur. Monitoring strategies typically make use of established geodetic methods, such as levelling, and therefore focus on the associated deformation processes. In this study, we combine levelling and highly precise time-lapse gravity observations. Our investigation area is the urban area of Bad Frankenhausen in central Germany, which is prone to subrosion, as many subsidence and sinkhole features on the surface reveal. The city and the surrounding areas are underlain by soluble Permian deposits, which are continuously dissolved by meteoric water and groundwater in a strongly fractured environment. Between 2014 and 2018, a total of 17 high-precision time-lapse gravimetry and 18 levelling campaigns were carried out in quarterly intervals within a local monitoring network. This network covers historical sinkhole areas but also areas that are considered to be stable. Our results reveal ongoing subsidence of up to 30.4 mm a−1 locally, with distinct spatiotemporal variations. Furthermore, we observe a significant time-variable gravity decrease on the order of 8 µGal over 4 years at several measurement points. In the processing workflow, after the application of all required corrections and least squares adjustment to our gravity observations, a significant effect of varying soil water content on the adjusted gravity differences was figured out. Therefore, we place special focus on the correlation of these observations and the correction of the adjusted gravity differences for soil water variations using the Global Land Data Assimilation System (GLDAS) Noah model to separate these effects from subrosion-induced gravity changes. Our investigations demonstrate the feasibility of high-precision time-lapse gravity monitoring in urban areas for sinkhole investigations. Although the observed rates of gravity decrease of 1–2 µGal a−1 are small, we suggest that it is significantly associated with subterranean mass loss due to subrosion processes. We discuss limitations and implications of our approach, as well as give a first quantitative estimation of mass transfer at different depths and for different densities of dissolved rocks.
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    Evaluating Experimental Design of ERT for Soil Moisture Monitoring in Contour Hedgerow Intercropping Systems
    (Hoboken, NJ : Wiley, 2012) Garré, S.; Günther, T.; Diels, J.; Vanderborght, J.
    Contour hedgerow intercropping systems have been proposed as an alternative to traditional agricultural practice with a single crop, as they are effective in reducing run-off and soil erosion. However, competition for water and nutrients between crops and associated hedgerows may reduce the overall performance of these systems. To get a more detailed understanding of the competition for water, spatially resolved monitoring of soil water contents in the soil-plant-atmosphere system is necessary. Electrical resistivity tomography (ERT) is potentially a valuable technique to monitor changes in soil moisture in space and time. In this study, the performance of different ERT electrode arrays to detect the soil moisture dynamics in a mono- and an intercropping system was tested. Their performance was analyzed based on a synthetic study using geophysical measures, such as data recovery and resolution, and using spatial statistics of retrieved water content, such as an adjusted coefficient of variation and semivariances. The synthetic ERT measurements detected differences between the cropping systems and retrieved spatial structure of the soil moisture distribution, but the variance and semivariance were underestimated. Sharp water content contrasts between horizons or in the neighborhood of a root water uptake bulb were smoothened. The addition of electrodes deeper in the soil improved the performance, but sometimes only marginally. ERT is therefore a valuable tool for soil moisture monitoring in the field under different cropping systems if an electrode array is used which can resolve the patterns expected to be present in the medium. The use of spatial statistics allowed to not only identify the overall model recovery, but also to quantify the recovery of spatial structures.
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    Feasibility study on prepolarized surface nuclear magnetic resonance for soil moisture measurements
    (Hoboken, NJ : Wiley, 2021) Hiller, Thomas; Costabel, Stephan; Radić, Tino; Dlugosch, Raphael; Müller‐Petke, Mike
    In the past few years, small-scale (2 m) prepolarized surface nuclear magnetic resonance (SNMR) has gained increasing interest in the research community. As recent studies demonstrated, the application of a strong prepolarization field enhances the SNMR signal of coils with a footprint <1 m2 up to a level that even enables investigations in urban areas. In particular, it is expected that this noninvasive method provides the soil moisture distribution in the upper 2 m of the subsurface in the near future. However, until now all field experiments have been carried out on water reservoirs only, in an approach to test and implement this rather new technique into the field of SNMR applications. We present the first prepolarized SNMR measurement on a real soil and demonstrate the general feasibility of this technique to qualitatively and quantitatively detect soil moisture in the upper first 0.5 m. Our soil moisture measurements are validated by independent time domain reflectometry data. To complement the field experiments with numerical simulations, we adapted the underlying SNMR spin dynamics simulations and account for prepolarization switch-off effects in the forward modeling of the SNMR excitation.