1,721,260 research outputs found
Repeating patterns in runoff time series: A basis for exploring hydrologic similarity of precipitation and catchment wetness conditions
Full text linkRunoff responses to precipitation at the catchment scale exhibit a high variability in space and time due to a complex interaction of numerous factors, e.g., topography, land use, soil properties, geology, and climatic conditions. To find similar patterns in the runoff response and examine the effects of these factors on runoff variability, previous studies have either compared and classified catchments in space or focused on grouping extreme events. Here, we analyzed runoff processes in three highly instrumented catchments in Germany and Austria individually and compared them to themselves in time. To this end, we used long-term time series of 10 to 13 years and classified runoff events as similar by performing a cluster analysis based on calculated goodness-of-fit criteria between each possible pair of runoff events. For each cluster, we examined the degree to which precipitation and catchment wetness conditions were similar to themselves at the respective times when similar runoff events occurred by calculating Spearman rank correlation coefficients (ρ) as well as their descriptive statistics. The similarities assessed varied among the three catchments, with the two catchments in western Germany with maritime climates showing a stronger correlation for soil moisture conditions (ρ = 0.76 and ρ = 0.74) for classified similar runoff events rather than precipitation (ρ = 0.26 and ρ = 0.36). The Austrian catchment with a predominantly continental climate showed an overall higher correlation for precipitation (ρ = 0.57) and a lower one for soil moisture (ρ = 0.53) for similar runoff events compared to the other two catchments. The proposed method assesses similarity of precipitation and wetness conditions under similar runoff responses, and gives an indication of possible influencing factors controlling runoff generation in the three catchments in relation to their respective wetness and precipitation patterns. The similarities investigated help identify similar catchment functioning and can be used, for instance, to develop enhanced catchment similarity indices
Monitoring hydrological processes for land and water resources management in a Mediterranean ecosystem: The Alento River Catchment Observatory.
No full textIn recent years, the critical zone (CZ) of catchments across the Mediterranean region has been influenced by rapid changes in both climate seasonality and land use/land cover. Rural ecosystems in southern Europe are experiencing prolonged droughts, seriously compromising water resources availability and crop yields whilst increasing the risk of wildfire occurrence. Rainy seasons are likely to be characterized by intense storms that trigger floods resulting in increasing damage severity. The negative effects of anthropogenic disturbance on hydrological ecosystem services can be tempered by demand-side adaptation options and appropriate investments to ensure water supply under drought conditions. To shed light on some of the scientific challenges related to these issues, a Critical Zone Observatory (CZO) has being established in the Alento River catchment. Although sampling campaigns and monitoring investigations have been carried out in this area for more than twenty-five years, a more systematic research program was recently started to take comprehensive measurements in representative sub-catchments of the study area. These sites are instrumented with advanced ground-based sensor network platforms that provide hydro-meteorological variables and fluxes in the groundwater-soil-vegetation-atmosphere system. Hydrological models of different complexity exploit the gathered dense information to assess the impact of land use and climate changes on key functions and services of the CZO in the Alento River catchment
Statistical Exploration of SENTINEL-1 Data, Terrain Parameters, and in-situ Data for Estimating the Near-Surface Soil Moisture in a Mediterranean Agroecosystem
Full text linkReliable near-surface soil moisture (θ) information is crucial for supporting risk assessment of future water usage, particularly considering the vulnerability of agroforestry systems of Mediterranean environments to climate change. We propose a simple empirical model by integrating dual-polarimetric Sentinel-1 (S1) Synthetic Aperture Radar (SAR) C-band single-look complex data and topographic information together with in-situ measurements of θ into a random forest (RF) regression approach (10-fold cross-validation). Firstly, we compare two RF models' estimation performances using either 43 SAR parameters (θNovSAR) or the combination of 43 SAR and 10 terrain parameters (θNovSAR+Terrain). Secondly, we analyze the essential parameters in estimating and mapping θ for S1 overpasses twice a day (at 5 a.m. and 5 p.m.) in a high spatiotemporal (17 × 17 m; 6 days) resolution. The developed site-specific calibration-dependent model was tested for a short period in November 2018 in a field-scale agroforestry environment belonging to the “Alento” hydrological observatory in southern Italy. Our results show that the combined SAR + terrain model slightly outperforms the SAR-based model (θNovSAR+Terrain with 0.025 and 0.020 m3 m−3, and 89% compared to θNovSAR with 0.028 and 0.022 m3 m−3, and 86% in terms of RMSE, MAE, and R2). The higher explanatory power for θNovSAR+Terrain is assessed with time-variant SAR phase information-dependent elements of the C2 covariance and Kennaugh matrix (i.e., K1, K6, and K1S) and with local (e.g., altitude above channel network) and compound topographic attributes (e.g., wetness index). Our proposed methodological approach constitutes a simple empirical model aiming at estimating θ for rapid surveys with high accuracy. It emphasizes potentials for further improvement (e.g., higher spatiotemporal coverage of ground-truthing) by identifying differences of SAR measurements between S1 overpasses in the morning and afternoon
Integrating invasive and non-invasive monitoring sensors to detect field-scale soil hydrological behavior.
No full textIn recent decades, while great emphasis has been given to the monitoring of point-scale soil moisture patterns and field-scale integrated soil moisture, the measurement of matric potential has attracted little attention. Information on the soil matric potential is available in point-scale measurements but is still missing at field-scale. This state variable is necessary to understand hydrological fluxes and to determine the soil water retention function (WRF) for field-scale applications. In this study, we combine data from cosmic-ray neutron probes (CRNP, non-invasive proximal soil moisture sensors) and SoilNet wireless sensor networks (invasive ground-based soil moisture and matric potential sensors) installed in two sub-catchments with contrasting land-use (agroforestry vs. near-natural forest) to derive a field-scale WRF. We investigate the hypothesis that both sensor types provide effective measurements that are representative for the entire sub-catchment, as well as the drawbacks of integrating the different measurement scales of the sensor types (i.e., spatial-mean of distributed point-scale data vs. an integrated field-scale measurement). We found discrepancies in the data of the two sensor types related to the effects of the time-varying vertical measurement footprint of the CRNP, which induces a scale mismatch between CRNP-based soil moisture (referring mostly to near-surface depths) and the spatially averaged soil matric potential data measured at soil depths of 0.15 and 0.30 m. To remove the offsets, we opted to use the soil moisture index (SMI) based on the estimation of field capacity and wilting point, retrieved from the knowledge of the field-scale WRF. We found that the bimodality of SMI calculated with SoilNet-based soil moisture induced by Mediterranean rainfall seasonal behavior is not well-captured by CRNP-based soil moisture, except in a particularly dry year like 2017. The contrasts in SMI values between the two test sites were associated with differences in the spatial variability of soil moisture patterns explained by soil texture or terrain characteristics. We argue that field-scale WRFs are useful for the analysis of hydrological processes at the sub-catchment (field) scale and the application of distributed models
Improving stationary and mobile cosmic ray neutron soil moisture measurements Assessment of the cosmic ray neutron uncertainty and the potential of the thermal neutron signal
Full text linkSoil moisture has a major influence on the partitioning between infiltration and runoff, and thus affects groundwater recharge, floodings, and the susceptibility of hillslopes to landslides. In addition, soil moisture can influence weather and climate, and the availability of water for plant growth directly affects agricultural productivity and food supply. Soil moisture varies in time and space and on multiple scales, which leads to nonlinear environmental interactions and scaling problems. Thus, timely information on multiple scales is required to accurately characterize soil moisture dependent processes
Using real-time observations and land surface modelling for improved irrigation and water resources management in Mediterranean climate
Full text linkIrrigated agriculture is essential to sustain crop production and livelihoods of the rural population in semi-arid and arid regions such as the Mediterranean. Meanwhile, unsustainable irrigation practices, population growth, and climate change are increasing agricultural water demand while exacerbating water scarcity. Effective measures to reduce agricultural water consumption while sustaining a high level of crop production and securing environmental sustainability are therefore urgently needed.
This thesis aims at increasing the availability of environmental data and advancing the representation of agricultural systems in land surface models to improve local and regional scale irrigation and water resources management in the Mediterranean.
In the first part, the use of a low-cost weather station to deliver reliable and timely data for environmental monitoring, research, and modelling is assessed. Performance and data quality of multiple stations are examined in terms of inter-sensor variability and in comparison to a high-performance weather station.
The second part of this thesis focusses on improving the representation of typical Mediterranean crops in the Community Land Model version 5. A new sub-model to model deciduous fruit orchards is developed encompassing crop phenological stages, biomass growth and partitioning into different plant organs as well as typical management practices. The development is then tested using extensive field measurements from an apple orchard.
Finally, the new sub-model is used to assess irrigation and water management in a small Greek catchment dominated by irrigated apple orchards. First, simulated crop growth and soil moisture dynamics are examined in relation to irrigation and compared to observations from two monitored apple orchards. Thereby, further model improvements are made to represent the local irrigation practices. Subsequently, the model is applied at regional scale to determine irrigation requirements and examine the impact of different irrigation deficit scenarios on yield and crop water use efficiency as well as to assess the water saving potential in the catchment
Integrating ground-based and remote sensing-based monitoring of near-surface soil moisture in a Mediterranean environment.
No full textSpatially explicit near-surface soil moisture (θ) patterns at high temporal resolution play a very important role in environmental modelling for improving risk assessment and for quantifying the effects of climatic seasonality and land use/land cover change on ecosystem services and functions in Mediterranean catchments. Remote sensing data from the European Copernicus mission are highly acknowledged to serve as fast, reliable, and available suppliers for the derivation of area-wide, high grid-resolution information (20 m 20 m) on near-surface soil moisture patterns acquired at a regular temporal resolution (satellite overpass is every six days). To reliably map θ from remote sensing radar (i.e., Sentinel-1) satellite products, robust calibration with gridded ground-data is needed and use of either sporadically measured or continuously monitored θ is of crucial importance for validation procedures. This study integrates remote- and ground-based monitoring of local- to field-scale θ in the Alento hydrological observatory situated in southern Italy. This Critical Zone Observatory was recently established in the Mediterranean Region and equipped with a multi-sensor network infrastructure. The final aim of this study is to develop site-specific calibration functions to relate spectral measurements to gridded topographic features to estimate near-surface soil moisture patterns. Estimation performance will be evaluated by comparing remote sensing-based (Sentinel-1) with ground-based soil moisture measured during satellite overpass. The soil moisture transfer relations will eventually support high temporal catchment-based hydrological modeling of groundwater and surface water fluxes under consideration of the climatic variability and in feedback with the vegetation
Water and Sustainable Development
No full textLife on earth is not possible without water. Only 3 % of the total water available is freshwater. More than two thirds of it is locked up as ice in the polar regions or as glaciers and snow. The remaining third is made up of groundwater, surface waters (lakes, rivers) and water in the atmosphere. Freshwater, also called the raw material of the 21st century, is part of a global cycle, since it emerges from the earth, flows through streams and rivers into the sea and returns as precipitation to the earth again. Humans intervene in this cycle. Roughly two thirds of the available ground and surface water is globally withdrawn from the natural cycle for irrigation projects in agriculture. In many regions, a sufficient future water supply of the population is not ensured due to the overuse of freshwater resources. Above all the developing countries and emerging nations are affected. For example, the Aral Sea, which used to be the world's fourth largest freshwater lake, has meanwhile lost three quarters of its volume due to the irrigation of cotton plantations. According to the UNESCO's "World Water Development Report", at least two billion people in 48 countries will suffer from water scarcity by the middle of this century. Water pollution represents a further problem, which not only affects the developing countries, but also the industrialised countries. According to UN estimates, 95 % of all waste water worldwide is passed untreated into ground and surface waters, so that about half of the 500 largest rivers on earth are heavily polluted. Dramatic consequences for the health of the population in these regions have to be expected. The resource-conserving use of water resources is one of the important tasks of the future. In the sense of sustainable development, the focus must not only be on covering short-term demand, but time lags of hydrogeological processes must also be taken into account which only lead to serious impacts on human society in the course of decades. In view of the importance of freshwater and the problems of overusing it, a sustainable management of water as a natural resource must therefore be ensured. Therefore, the water demand of present generations should be covered without jeopardising the water supply for future generations. This basic principle of operationalising the sustainability principle is embodied in the European Union's Water Framework Directive in force since 2001. Its overriding aim is to ensure the good status of water resources in terms of quantity and quality in the EU member states across national borders. [...
Temperature-Corrected Calibration of GS3 and TEROS-12 Soil Water Content Sensors
No full textThe continuous monitoring of soil water content is commonly carried out using low-frequency capacitance sensors that require a site-specific calibration to relate sensor readings to apparent dielectric bulk permittivity (Kb) and soil water content (θ). In fine-textured soils, the conversion of Kb to θ is still challenging due to temperature effects on the bound water fraction associated with clay mineral surfaces, which is disregarded in factory calibrations. Here, a multi-point calibration approach accounts for temperature effects on two soils with medium to high clay content. A calibration strategy was developed using repacked soil samples in which the Kb-θ relationship was determined for temperature (T) steps from 10 to 40 °C. This approach was tested using the GS3 and TEROS-12 sensors (METER Group, Inc. Pullman, WA, USA; formerly Decagon Devices). Kb is influenced by T in both soils with contrasting T-Kb relationships. The measured data were fitted using a linear function θ = aKb + b with temperature-dependent coefficients a and b. The slope, a(T), and intercept, b(T), of the loam soil were different from the ones of the clay soil. The consideration of a temperature correction resulted in low RMSE values, ranging from 0.007 to 0.033 cm3 cm−3, which were lower than the RMSE values obtained from factory calibration (0.046 to 0.11 cm3 cm−3). However, each experiment was replicated only twice using two different sensors. Sensor-to-sensor variability effects were thus ignored in this study and will be systematically investigated in a future study. Finally, the applicability of the proposed calibration method was tested at two experimental sites. The spatial-average θ from a network of GS3 sensors based on the new calibration fairly agreed with the independent area-wide θ from the Cosmic Ray Neutron Sensor (CRNS). This study provided a temperature-corrected calibration to increase the accuracy of commercial sensors, especially under dry conditions, at two experimental sites
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