Climate change can considerably control the catchment-scale root zone storage capacity (S_umax) which is a critical factor affecting the moisture exchange between land and atmosphere, hydrological response, and biogeochemical processes in terrestrial hydrological systems. However, direct quantification of the changes of S_umax over long time periods at the catchment-scalehas so far been rare. This is mostly a result that it is difficult to quantify the effect of climate change on parameters of terrestrial hydrological models, which in turn contributes to considerable uncertainties in predictions of the hydrological response under changing climatic conditions. As a consequence, it remains unclear how climate change affects S_umax (e.g., precipitation regime, canopy water demand) and how changes in S_umax may affect partitioning of water fluxes and as a consequence, as well as catchment-scale physical transport of water quality, described by transit and resident time distributions.

The objectives of this study in the upper Neckar river basin in Germany are therefore to provide an analysis of why changes in S_umax can be observed as a result of changing climatic conditions over the past 7 decades and how this further affects hydrological and transport dynamics. More specifically, we test the hypotheses that (1) the changes in water fluxes and storage dynamics over that a 70-year period can be attributed to adaptations of the root zone storage capacity resulting from the changing climate (e.g., precipitation frequency or wetness condition), which affects (2) the shape of travel time distributions and young water fractions, in particular for evaporation fluxes, which are most affected by the climate-induced change S_umax over different periods.The analysis is carried out based on long-term hydrological (1953-2022) and radioactive isotope data (1961-2018), using a distributed hydrological model coupled with StorAge Selection (SAS) functions, which is simultaneously modelling streamflow and tracer dynamics and provides estimates of transit time distributions of different water fluxes and of resident time distributions in different storage components.

How to cite: Wang, S., Hrachowitz, M., and Schoups, G.: How does ecosystem adaptation to a changing climate affect catchment Transit Times Distributions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1548, https://doi.org/10.5194/egusphere-egu23-1548, 2023.

The active portion of river networks varies in time thanks to event-based and seasonal expansion-retraction cycles that mimic the unstradiness of the underlying climatic conditions. These rivers, usually referred to as temporary streams, constitute a major fraction of the global river network. Temporary streams provide a unique contribution to riverine ecosystems, as they host unique habitats that promote biodiversity. Nonetheless, the impacts of network dynamics on ecological processes and ecosystem services are not fully understood. In this contribution, we present a stochastic framework for the coupled simulation of active stream dynamics and the related occupancy of a metapopulation. The framework combines a stochastic model for the generation of synthetic streamflow time series with the hierarchical structuring of river network dynamics, to enable the simulation of the full spatio-temporal dynamics of the active portion of the stream network under a wide range of climatic settings. The hierarchical nature of stream dynamics - which postulates that during wetting nodes are  activated sequentially from the most to the least persistent, and deactivated in reverse order during drying - represents a key feature of the approach, as it enables a clear separation between the spatial and temporal dimensions of the problem. The framework is complemented with a stochastic dynamic metapopulation model that simulates the occupancy of a metapopulation on the simulated stream. Our results show that stream intermittency negatively impacts the average occupancy and the probability of extinction of the focus metapopulation. Likewise, the spatial correlation of flow persistency along the network bears a sizable impact on the mean network connectivity and occupancy. This effect is particularly important in drier climates, where most of the network undergoes sporadic and flashy activations, and species dispersal is regularly inhibited by river fragmentation. This approach offers a robust but parsimonious mathematical framework for the synthetic simulation of stream network dynamics under a broad range of climatic and morphological conditions, providing useful insights on stream expansion and retraction in its ecological significance.

How to cite: Bertassello, L. E., Durighetto, N., and Botter, G.: A stochastic eco-hydrological model reveals the impact of active stream dynamics and connectivity on metapopulation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7733, https://doi.org/10.5194/egusphere-egu23-7733, 2023.

How to cite: Wang, S., Miele, F., Benettin, P., Bernier-Latmani, R., and Rinaldo, A.: Spatially explicit linkages between redox potential cycles and soil moisture fluctuations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6409, https://doi.org/10.5194/egusphere-egu23-6409, 2023.

The extent of water from river and floodplain (groundwater, rainfall, and snowmelt) in an inundation is related to ecological processes such as vegetation development. A prominent example of this phenomenon is the Biebrza floodplain, which is a 220km² natural, temperate zone, fen wetland, with extensive river flooding. The lateral vegetation zonation in this area was related to the flooding frequency and water depth; however, more recent research showed that the extent of the river water zone within the inundation is a better predictor of the vegetation pattern. Despite its significance, the long-term sensitivity of vegetation zonation with respect to changing extent of water zones and climate was not investigated. In this study, we used the Hydraulic Mixing-Cell (HMC) method to simulate the extent of water from rainfall, snowmelt, groundwater discharge, and river flooding. The HMC is implemented in the HydroGeoSphere model, which was set up for the entire 7000 km² Biebrza catchment. The model was forced using the Twentieth Century Reanalysis data for the period 1881-2015 and using an ensemble of ten EURO-CORDEX simulations for RCP 2.6, 4.5, and 8.5 for the 2006-2099 period. The model output was used to establish vegetation models using three vegetation maps from 1960, 1980, and 2000 and the random forests algorithm. The results show that the vegetation pattern in Biebrza wetlands was predicted with higher accuracy with the water sources zonation predictors from the HMC, whereas the vegetation models using surface water depth and duration or soil moisture, groundwater discharge, and groundwater levels predictors had lower accuracy. Finally, the vegetation was predicted for the entire two centuries period to show that the vegetation change in Biebrza wetlands may occur due to change in water sources’ zonation, which is driven by climate.

How to cite: Berezowski, T. and Wassen, M.: Vegetation pattern in a natural wetland floodplain is predicted better using river-floodplain inundation extents than standard hydrological variables, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13159, https://doi.org/10.5194/egusphere-egu23-13159, 2023.

The EU Water Framework Directive WFD (60/2000) asks the achievement of a good ecological status of water bodies and requires the definition of ecological flows in Water Management Plans. Ecological flow definition goes beyond the minimum low-flow discharge and is defined as a hydrologic regime suitable for the aquatic ecosystem and preservation of biodiversity. Ecological status is monitored by environmental agencies and is based on the worst among the selected biological indicators (e.g., macroinvertebrate-based indices, nutrients and dissolved oxygen, macrophytes indices etc.). This work examines the hydrologic regimes of water bodies based on (i) monitored ecological status, (ii) water quality/quantity stressors and (iii) water balance computed with a distributed hydrologic model validated against recorded river discharge data. As water stressors climate, morphological alterations, land use, and water management indicators are accounted for in each river catchment. Machine learning classifiers are compared in their capability of predicting a good ecological status based on stressors.  The hydrologic model is used to determine flow duration curves and to extract seasonal patterns and characteristic discharges of river which currently satisfy the WFD requirements. The method is applied to the rivers of the Tuscany region (central Italy), which is part of the Hydrographic District of the Northern Appennines. The results show a significant role of climate and land use parameters in determining a less than good ecological status with a consequent need of dilution of pollutants and higher specific discharges. The different hydrologic regimes in different ecological status conditions highlight the capability of advanced eco-hydrologic modelling to overcome the limitations of the commonly adopted purely hydrologic approaches at district scale.

How to cite: Arrighi, C., De Simone, M., and Castelli, F.: Shaping eco-hydrologic flow regimes at regional scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6560, https://doi.org/10.5194/egusphere-egu23-6560, 2023.

Wetlands are increasingly considered as nature based solution as they provide valuable services and functions to the society and environment, such as water quality improvement and biodiversity support. However, while land use and climate change have been affecting the functions and service of these ecosystems, it has become important to study the large-scale behaviour of wetlands in the landscape. Consequently, previous studies have suggested studying wetlands within wetlandscapes, defined as catchments containing networks of several wetlands, in order to understand large-scale functions of wetlands and their response to land-use and climate changes. This emphasizes the ecohydrological interactions of wetlands rather than having focus of individual wetlands. As the concept of wetlandscape is new, we have been working on systematically quantifying its governing properties in two different studies.

In the first study, we systematically quantified ecohydrological properties of individual wetlands (e.g. wetland area, wetland catchment area and wetland type) in multiple wetlandscapes that may impact biodiversity and modulate nutrient flows as well as characteristics of the whole wetlandscape in terms of their large-scale processes and functions. Results from this work showed that large wetlandscapes generally contained features to support different ecosystem services compare to smaller wetlandscapes. More specifically, results indicated that small wetlandscapes have a poor ability to route water through their wetlands which was in contrast to large wetlandscapes. This implies that large wetlandscapes have a higher potential for large-scale retention of nutrients and contaminants.

The second study consisted of investigating spatial and temporal wetland storage dynamics for multiple wetlands in the landscape in order to address considerable knowledge gaps regarding hydrological functions of wetlands and wetlandscapes. More specifically, we use high-resolution monitoring of wetland water levels to assess storage patterns and inundation conditions. A key finding of this work is that the position of wetlands is important for storage dynamics and flood buffering. Notably we find that wetlands located in headwater regions showed larger water level variability during the growing season (spring, summer and autumn) and hence were more active in temporal water storage than wetlands located downstream in the wetlandscape. This variability in water level for headwater wetlands was also associated with complex and patchy inundation conditions, while downstream wetlands essentially showed dry-state conditions during the entire summer.

Results from both studies show that ecohydrological properties of wetlandscapes can have implications for ecosystem service delivery (e.g., biodiversity support and water quality) at regional level as well as for using wetlands as nature-based solution. Present results also support the importance of wetlandscape studies and the priority of a wetlandscape focus in future management programs to various regional environmental challenges.

How to cite: Åhlén, I., Hambäck, P., Thorslund, J., Frampton, A., Destouni, G., and Jarsjö, J.: Wetlandscape hydrology and ecosystem services, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3831, https://doi.org/10.5194/egusphere-egu23-3831, 2023.

Ecosystem Water Use Efficiency (WUE_e) is an ecohydrological indicator that shows the strength of coupling between the carbon cycle and water cycle, and it is calculated as the net carbon gain (estimated as Net Primary Productivity, NPP) per unit of water consumed by ecosystems (estimated as Evapotranspiration, ET). The carbon and water cycles, as well as the WUE_e is influenced by groundwater (GW) as it is one of the sources for supplying moisture to the terrestrial ecosystem. Various factors like meteorological factors (precipitation, temperature, aridity), vegetation types, irrigation, etc. affect the interaction between GW and WUE_e. Thus, the influence of GW on the dynamics of WUE_e varies spatially and temporally. In this study, remote sensing-based datasets of NPP, ET and Potential ET (PET) along with precipitation data from India Meteorological Department (IMD) and the mean annual water table depth (WTD) values taken from the equilibrium WTD model of Eurasia were utilized to analyze the response of WUE_e to GW fluctuations at yearly temporal scale across India. The concept of climatic elasticity of NPP (ε_NPP), ET (ε_ET) and WUE_e (ε_WUE), which is calculated as the ratio of normalised WUE_e (or NPP and ET) to Aridity Index (AI) was used to quantify the effect of climate change on the terrestrial ecosystem’s productivity. Our results showed that in general, WUE_e fluxes, i.e., NPP and ET, were higher in the regions having lower WTD, such as Western Ghats and north-eastern areas. Further, we examined the responses of vegetations to climatic changes at different WTD, and the effect of irrigation on WUE_e and its fluxes were studied. In general, the interactions between WTD and WUE_e (and its fluxes) were stronger in the irrigated croplands. Shrublands in arid regions of India (i.e., north-western states of India) were found to be more sensitive to aridity as compared to the wet and humid regions dominated by forests and croplands type of land cover. This study gives an insight into the interaction between the ecological performance of terrestrial ecosystem and groundwater, which will support reasonable land use and groundwater management over the entire country of India.

How to cite: Singh, A., Bejagam, V., and Sharma, A.: Examining the role of groundwater in the spatio-temporal variation of Ecosystem Water Use Efficiency in India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1618, https://doi.org/10.5194/egusphere-egu23-1618, 2023.

Vegetation is an important part of terrestrial ecosystem, and the vegetation growth condition is closely related to hydro-meteorological elements. Accurate simulation of ecohydrological elements is an important guarantee to maintain the security of ecosystem. Building physical models based on mechanistic processes such as the Soil and Water Assessment Tool (SWAT) is a solid way to understand the ecohydrological processes, but the simulation of vegetation growth is not accurate enough to interpret the entire complexity of ecohydrological processes. Data-driven machine learning models can efficiently and accurately identify the relationship between vegetation and hydrometeorological elements. Coupling distributed hydrological models and machine learning models is beneficial to improve the ecohydrological simulation accuracy, and to provide support for maintaining ecosystem security.

A watershed ecohydrological simulation framework was constructed by coupling SWAT and six machine learning methods in the headwater basin of the Yangtze River, called Jinsha River basin, China. Firstly, we established a SWAT model to get the temporal and spatial patter of hydro-meteorological factors including soil moisture, runoff, evapotranspiration, temperature and precipitation in the watershed by using meteorological factors from the gauging stations. Then Pearson correlation coefficients was utilized to identify factors that are more relevant to vegetation growth based on the lagged response of vegetation changes to hydro-meteorological factors. We also applied machine learning models to construct the regression relationship between climatical factors and two indicators reflecting vegetation growth, which are normalized difference vegetation Index (NDVI) and solar-induced chlorophyll fluorescence (SIF), achieving the prediction of vegetation growth status. Based on this framework, the ecohydrological elements data series from 1965-2014 were completed in the monitoring data sparse area to conduct a long time series and sequential analysis. Finally, trend analysis and partial correlation analysis were used to explore the variation characteristics of ecohydrological elements and their relationships with climate factors.

The results show that (1) the SWAT model can simulate the runoff process well of the whole Jinsha River basin (R²>0.84, NS >0.68), and the machine learning model can well estimate the SIF of the whole Jinsha River basin (NS>0.98, MSE<0.0003) and NDVI (NS=0.98, MSE=0.0005) in the upstream. (2) The vegetation type in the middle and downstream of the Jinsha River is mainly woodland, and the NDVI index has oversaturation phenomenon, so machine learnings can produce large biases, while the SIF data do not have such phenomenon, which is a better indicator to characterize the vegetation growth. (3) The trends and drivers of ecohydrological elements have obvious regional, and seasonal differences, and in general, temperature is the main driver of vegetation and precipitation is the main driver of runoff. This research built a new method to simulate ecohydrological processes in a spatio-temporal continuum, providing a strong support for ecohydrological evolution analysis.

How to cite: Zhao, Q., Zhang, X., and Li, C.: Attribution of Eco-hydrological changes based on coupled SWAT-ML method, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4727, https://doi.org/10.5194/egusphere-egu23-4727, 2023.

Soil bioturbation activity affects soil texture, bulk density, soil water content and redistribution of nutrients. All of these factors influence surface and subsurface sediment and hydrological processes, and thus are expected to shape the surface on large temporal scales. Previous studies have shown that the impact of bioturbation on these processes is not homogenous.

However, the factors, which determine if bioturbation will positively or negatively affect the named processes, remain unknown. For this reason, the inclusion of bioturbation into erosion and landscape models have up until now been limited. The few models which include it in their algorithms assume a linear positive relationship between bioturbation rates, and erosion, soil mixing and vegetation cover.

In our study, we tested the possibilities and limitations of including bioturbation into soil erosion modelling. We modelled the impact of bioturbation on sediment redistribution, surface runoff, subsurface runoff and infiltration capacity within several climate zones and identified environmental parameters determining the positive or negative impact of bioturbation on surface processes.

Our study area was located along Chilean climate gradient. We measured the needed soil properties and location of burrows created by bioturbating animals in the field. Then we applied machine learning algorithms and used satellite data as predictors to upscale the soil properties and burrow distribution into the catchment. At each of the predicted burrow locations we adjusted the topography, soil properties and vegetation cover accordingly. We implemented the predicted parameters into a semi-empirical model and ran the model for a time period of 3 years under two conditions: With and without integrated bioturbation. We validated the model using sediment fences located at the base of each catchment.

Model with integrated bioturbation activity had an R² of 0.71 while a model without bioturbation activity had an R² = 0.45. Bioturbation increased sediment redistribution in all but humid climate zone. The surface runoff increased in semi-arid zone while the infiltration capacity and subsurface runoff increased in the mediterranean and humid climate zone. Bioturbation increased sediment erosion at high and middle values of elevation, at high values of inclination and connectivity, and at low values of profile curvature. Bioturbation increased sediment accumulation at high values of surface roughness and topographic wetness index and at low values of vegetation cover.

How to cite: Grigusova, P., Larsen, A., Brandl, R., Kraus, D., Farwig, N., and Bendix, J.: Influence of bioturbation on sediment redistribution along climate gradient in Chile estimated by combining semi-empirical modelling, remote sensing and machine learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13201, https://doi.org/10.5194/egusphere-egu23-13201, 2023.

Recent consecutive drought years have led to multiple negative impacts on water-related ecosystem services in many parts of the world; these include reduced crop yields, increased tree mortality, persistent soil moisture deficits, lower groundwater levels and stream flow becoming more intermittent. Continuing negative rainfall anomalies, coupled with climate change projections of increased drought severity and frequency, drive an urgent need to increase resilience and integration in land and water management strategies. However, complex interactions between land cover change, hydrological  partitioning and water availability are difficult to quantify, especially at different temporal and spatial scales. Process-based ecohydrological modeling, particularly when calibrated with multiple data streams, is a powerful tool for estimating water partitioning and assessing the impact of alternative land management strategies on catchment water resources. We employed the spatially-distributed and tracer-aided ecohydrological model, EcH₂O-iso, to quantify the effects of current and potential future land use scenarios on ecohydrological water flux partitioning and water ages in a 66 km² drought-sensitive catchment in the North European Plain, Germany. The model was calibrated using hydrometric, ecohydrological and isotopic data at daily time steps for a period of 13 years (Jan 2007 –  Dec 2019). In conjunction with local stakeholders, we developed plausible, alternative land-use scenarios (including forest diversification and agroforestry schemes) based on the existing four primary land-use types (i.e., broad-leaved forests, conifer forests, arable agriculture and pasture) to evaluate spatial and temporal changes to water flux partitioning and water ages. This sought to identify the most drought-resilient land management plan especially in the context of  increased drought frequency and severity. The results showed that replacing conifer forests with uneven-aged mixed forests with younger broad-leaved trees had the most positive impacts in terms of reducing total evapotranspiration and increasing groundwater recharge in the catchment. The mixed-forest management alternatives also significantly reduced groundwater ages and subsurface water turnover times. This indicates that under this management soil moisture and groundwater stores will recover more quickly from drought than under existing land management. This study demonstrates an ecohydrological modelling approach that provides importance science-based evidence for policy makers allowing quantitative assessment of the impact of different land-use types on water partitioning and water availability. Other current work is coupling the tracer-aided ecohydrological model with a nitrate model for future assessment of biogeochemical processes.

Keywords: ecohydrological modeling; drought-sensitive area; water partitioning; water age

How to cite: Luo, S., Tetzlaff, D., Smith, A., and Soulsby, C.: Using tracer-aided ecohydrological models to assess the impact of alternative land use strategies on optimizing water availability in drought-sensitive catchments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-108, https://doi.org/10.5194/egusphere-egu23-108, 2023.

Water availability controls vegetation activity and the carbon balance of terrestrial ecosystems across a large portion of the global land surface. Although the influence of terrestrial water storage (TWS) on the land carbon balance is evident in globally aggregated measures, it remains unknown whether the large annual amplitudes in TWS are causally linked to water availability in the rooting zone of vegetation, or whether they reflect a correlation of plant water stress with water stored in other landscape elements that may not directly be connected to vegetation functioning (lakes, rivers, groundwater). Global models of the land surface typically ignore hillslope-scale variations in plant water availability, and water stores that are located beyond the soil, and beyond prescribed plant rooting depths. This simplification is partly owed to a lack of empirical information.

Here, we approach this gap from two angles: from the site scale using eddy covariance observations, and from the global scale using earth observations. Water mass balance constraints derived from thermal infrared-based evapotranspiration (ET) estimates and precipitation reanalysis data indicate plant-available water stores that exceed the storage capacity of 2 m deep soils across 37% of the Earth’s vegetated surface. Large spatial variations of the rooting zone water storage capacity across topographic and hydro-climatic gradients are tightly linked to the sensitivity of vegetation activity (measured by sun-induced fluorescence and by the evaporative fraction) to water deficits. Similar patterns between ET and cumulative water deficits emerge from site-level flux measurements. We found large variations of the vegetation sensitivity to dry conditions across sites and at several sites a muted response of ET to dry conditions in spite of large (>300 mm) seasonal water deficits at some sites.

Taken together, results we show here hint at a critical role of plant access to deep water stores and the need to extend the focus beyond moisture in the top 1-2 m of soil for understanding and simulating land-atmosphere exchange. Our results add to the emerging evidence that water stored in the weathered bedrock and plant access to groundwater may have a more important role in regulating land-atmosphere exchange and the carbon cycle than previously appreciated.

How to cite: Stocker, B., Tumber-Dávila, S. J., Konings, A. G., Anderson, M. C., Hain, C., Giardina, F., and Jackson, R. B.: Towards a better understanding of deep belowground water stores and their influence on land-atmosphere exchange and drought impacts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9503, https://doi.org/10.5194/egusphere-egu23-9503, 2023.

Abstract:

The connectivity of environmental compartments through chemical and biological exchanges is often difficult to study. However, understanding the functioning of fluxes is essential in the context of climate change and the assessment of anthropogenic impacts. These exchanges can be realized through water cycle fluxes establishing interactions between the atmosphere, surface water and land.

To examine the interactions between the atmosphere, surface water and land via water fluxes, we conducted a large scale field study at the watershed level, involving multiple disciplines from chemistry to meteorology and microbiology. The chemical and biological contents of water from the atmosphere (cloud and rain), to mid-mountain hydrological continuum (streams, wetlands and lake) and soil (agricultural plots) were assessed in the natural and agricultural area from Puy De Dôme (Central France) along an altitudinal gradient from puy de Dôme Mountain summit (1465 m asl) to the plain (~ 600 m asl). We set up experimental procedures for sampling, handling and analysing each environmental matrix, and the environmental context was characterized through meteorological and hydrological measurements and models. The biological and chemical variables included: isotopes of water (¹H/²H and ¹⁶O/¹⁸O; laser spectroscopy), major ions (Na⁺, NH4⁺, K⁺, Mg²⁺, Ca²⁺, Cl^-, NO₃^-, SO₄^-, IC), amino acids (LC-MS), bacterial diversity (16S metabarcoding and high-throughput sequencing) and microbial enzymatic activity associated with the nitrogen, carbon and phosphorus cycles (fluorimetric activity assays for whole Beta-Glucosidase, Leucine Aminopeptidase and Phosphatase activities).

The multi-compartment analysis revealed significant differences between the compartments by the chemical variables, highlighting the compartment specificity. We estimated a chemical flux of major ions and amino acids from the atmosphere to the surface (soil and surface water). Bacterial diversity analysis showed a core community in these compartments, confirming their connectivity. Thereafter, we tried to explain bacterial diversity by the chemical variables from the studied compartments. Our analysis on microbial enzymatic activity showed an enzymatic activity associated with the nitrogen, carbon and phosphorus cycles in clouds and rain.

Here, our study contributes to the understanding of atmosphere-surface interaction through field observations and atmospheric models and we attempted to better understand environmental fluxes. Our field study emphasized the importance of considering the interaction of environmental compartments in future investigations for future and gobal assessments of anthropogenic impacts, such as agrosystem effects to natural ecosystems.

Key words:

Field observations, Environmental interaction, Chemical flux, Microbial diversity, Atmosphere, Surface water, Soil.

How to cite: Labed-Veydert, T., Joly, M., Judon, C., Leremboure, M., Voyard, G., Forano, C., Bianco, A., Baray, J.-L., Artigas, J., Mallet, C., Latour, D., Roussel, E., Jame, P., Bonjour, E., Jabot, F., Pottier, J., and Amato, P.: Chemical and biological signatures of water and fluxes from clouds to rivers at the watershed level in a natural context., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6760, https://doi.org/10.5194/egusphere-egu23-6760, 2023.

Forest fires affects extensive areas each year around the world. An important percentage of those areas represent forested watersheds which provide water supply for different communities, from the microbial till the industrial scale. Forest fires can have an effect in erosion, runoff rates, loss of vegetation cover, rainfall interception, water repellence, among others, which affect the water quality in the streams. The change in the dynamic of a burned watershed produce variation in the DOC concentration, among other water quality parameters, which has a direct impact in the drinking water treatment. This meta-analysis explores post-fire effects in DOC concentrations, during the years after the fire. More than 50 watersheds were identified in the collection of the information. Changes in concentrations were documented primarily within the first 5 years after the fire. The studies were published between 2001 and 2020. We found that percentage of area burned, and fire severity have stronger effect on DOC concentrations. The study documents strong heterogeneity in responses to post-fire effects and DOC concentrations.

How to cite: Polack Huaman, J.: Post-fire effects on DOC concentrations in streams: A meta-analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11275, https://doi.org/10.5194/egusphere-egu23-11275, 2023.

Terrestrial carbon and water cycles are intricately related across spatial (leaf to global) and temporal (instantaneous to multi-annual) scales through multitude of coupled biogeochemical processes that govern the land water and carbon states and fluxes and their feedback to climate. Yet, there are clear discrepancies in modeling key carbon-water processes that lead to large uncertainties in model simulations that often divert away the observations. In fact, the terrestrial biogeochemical models used to represent vegetation-water-carbon interactions vary in complexity and parameterization that are often underconstrained. The current era of rapid growth of satellite Earth Observation, observational networks, and well as observation-based estimate, therefore, provides unprecedented opportunities to improve the models. Unfortunately, most terrestrial biogeochemical models often contain too rigid model structures, and are too demanding to carry out model-data-fusion experiments that leverage the strengths of observational data constraints.

In this study, we present a newly developed terrestrial/ecosystem model-data-integration (MDI) framework, the SINDBAD, that allows for seamless integration of diverse observational data to constrain terrestrial models of varying complexity. The SINDBAD provides a modular framework to create different combinations of terrestrial processes to realize a terrestrial model structure, which can be driven by observed data of climate and/or land characteristic and optimized against provided observation constraints using different cost metrics and parameter optimization methods. To demonstrate the capabilities, we present three MDI experiments of SINDBAD: setup E1 - a global scale model focused on vegetation's role on water cycle; setup E2 - a regional scale model with physiological coupling of water and carbon cycle focused on role of interannual variability of vegetation fraction; and setup E3 - an ecosystem scale model with a prognostic carbon cycle that is used to evaluate the values of using data for ecosystem carbon states.

In the simplest E1 setup, where vegetation only has structural influence on the water cycle, we find that the spatial information of vegetation using satellite-based vegetation index as model input shows clear improvement in the simulation of monthly runoff, as well as interannual variability of terrestrial water storage in arid regions. In setup E2, use of vegetation fraction data from geostationary satellite to drive a physiologically coupled model of water-carbon relations shows a clear improvement in the simulations of interannual variability of gross primary productivity only when the data includes the year-to-year variability of vegetation fraction. In fact, we find that the using mean seasonal cycle of vegetation fraction is able to reproduce the monthly variation but not the interannual variability. Lastly, in setup E3, which includes fully coupled water-carbon model with prognostic evolution of carbon pools with dynamic allocation scheme (with competition for light and water) reveals that the remote sensing observation of carbon states provides better constraints for the carbon cycle compared to the experiment where only eddy covariance measurements are used. The results also indicate that even coarser remote sensing data have a potential to complement ecosystem scale measurements of water and carbon fluxes to improve the prediction of carbon-water coupling at the ecosystem scale.

How to cite: Koirala, S., Jung, M., Trautmann, T., Reichstein, M., and Carvalhais, N.: SINDBAD: A modular framework for model data integration of carbon-water processes across scales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11339, https://doi.org/10.5194/egusphere-egu23-11339, 2023.

Climate change is altering the spatiotemporal pattern of precipitation toward more extreme conditions. However, it’s still unclear how a more variable hydroclimate influences soil biogeochemical cycling and resultant soil carbon emission. One key challenge is our limited understanding of how hydroclimate coupling with other environmental drivers regulates the composition and functions of soil microbial communities. Moreover, how this environmental feedback of soil microbial communities mediates soil biogeochemical processes. To overcome this challenge, we integrated published metagenomics datasets across the US to identify eight general soil enzyme functional classes (EFCs) involved in soil carbon (C), nitrogen (N), and Phosphorus (P) cycles. We then integrated this omics-informed microbial functional information with the corresponding hydroclimate and other environmental data to train and test a machine learning (ML) pipeline for predicting the spatial distribution of EFC composition across the US domain and its variability with changing hydroclimate. This ML-predicted microbial functional feedback to changing hydroclimate was finally coupled with the Community Land Model (CLM5.0) to assess its impact on microbially-mediated soil carbon emission. Our study showed that soil enzyme functional composition is sensitive to changing hydroclimate. Microbial communities decrease the investment in EFCs involved in SOM decomposition under drying conditions. Incorporating this microbial feedback to hydroclimate into the CLM5.0 captured soil carbon dynamics in the water-limited region. Output from this study, including the gridded EFC composition dataset and coupled model framework, can be applied to mitigate the uncertainty in projecting soil carbon-climate feedback under changing hydroclimate.

How to cite: Song, Y. and Fan, C.: Integrating omics, machine learning, and process-based land surface model to predict hydroclimate feedbacks of microbial functions and its implication for soil carbon emission, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12020, https://doi.org/10.5194/egusphere-egu23-12020, 2023.

This study assesses future extreme hydrological conditions in East Asia based on four Global Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 6 with biogeochemistry (CMIP6-BGC), which provides layers of vegetation and soil to estimate carbon and nitrogen cycle. We estimate the frequency and severity of extreme dry and wet conditions based on runoff using the threshold level method under Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) 585 scenarios. The differences in extremes between “standard”, which does not consider the detailed biogeochemical processes, and the “BGC” simulations are estimated to quantify the impacts of biogeochemical processes on the hydrological extremes. This study shows that the “standard” case is predicted to be more severe and pronged in intensity and duration of extremes in the future than that of the “BGC” case. For example, the duration of extreme dry and wet conditions in the “BGC” case shows less duration, about 21% and 12%, respectively, in the future than in the “standard” case in three GCMs ensemble. We demonstrate that the effects of the biogeochemical process should be considered to project future extremes because these extremes could be overestimated in “standard” simulations.

Acknowledgements

This work was supported by the Basic Science Research Program (2020R1A2C2007670) and the Framework of International Cooperation Program (2021K2A9A2A06038429) through the National Research Foundation of Korea (NRF).

How to cite: Lee, J. and Kim, Y.: Impacts of biogeochemical processes on hydrological extremes under future SSP585 scenario over East Asia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10583, https://doi.org/10.5194/egusphere-egu23-10583, 2023.

Quantifying the transfer of organic carbon (OC) from the terrestrial to the riverine ecosystems is of crucial importance to fully appreciate the carbon cycle at the catchment, regional and global scales. Dissolved Organic Carbon (DOC) represents one of the main forms in which terrestrial OC is leached to inland waters and the oceans. Its concentration in streams, rivers and lakes is critical for aquatic metabolism but also for the transport of metals and pollutants. In the past years, several studies in different experimental catchments observed increasing trends in DOC concentration in rivers, possibly linked to changes in land use and hydrologic regime.  Moreover, these studies unveiled how hydrologic variability imposes a strong control on DOC transport with streamflow producing events disproportionately contributing to the overall DOC export.  In this study, we explore the interaction between water and carbon cycles in the critical zone of an alpine catchment in order to quantify the flux of DOC exported from the soil to the stream via superficial or subsuperficial runoff. We couple the Water Age  theory to unravel the time water spends within hillslopes with the Reactivity Continuum model to quantify the degradation of DOC along the transport. The model is applied to the Oberer Seebach basin (Austria) for which extensive time series of streamflow DOC concentration and hydrological variables are available at high-frequency resolution (sub-daily measurements). For a subset of the DOC samples, the excitation emission matrices and the absorbance spectra are also available and allow deriving information on the quality and reactivity of DOC. We reproduce DOC concentration estimating the travel time distribution of water and assuming it dictates the time available for the continuous degradation of the DOC mixture. Results show that the model is able to well reproduce DOC streamflow concentration, capturing its complex relation with streamflow discharge over the three years of observations. In addition, the framework allows the estimation of the reactivity distribution of the exported DOC. To validate these results, we compare the estimated average reactivity with multiple fluorescence and absorbance indexes calculated from data, revealing significant correlations.

How to cite: Grandi, G., Bertuzzo, E., Catalán, N., Bernal, S., Fasching, C., and Battin, T. J.: Using travel time distributions and reactivity continuum to model terrestrial dissolved organic carbon export and reactivity in an Alpine catchment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15210, https://doi.org/10.5194/egusphere-egu23-15210, 2023.

The understanding of soil hydrological processes in agroforestry systems has increased in recent years. However, key aspects determining the successful functionality of agroecosystems (e.g. plant-water availability, nutrient supply) are influenced by many factors and are therefore challenging to generalize. Such information is critical for management and planning strategies. If dominant processes such as evapotranspiration and the related controls on the soil water stock can be represented adequately in hydrological models at the plot scale, they can provide useful insights for practitioners.

Here, we tested whether the physically-based CATFLOW model is capable of reproducing soil moisture dynamics in a South African agroforestry system consisting of windbreaks and irrigated blackberry plants. We initialised the model with matric potential measurements and calibrated it to soil moisture dynamics at two locations with differing vegetation within the test site. After successful calibration, several numerical experiments were performed to shed light on the presence and absence of windbreaks and of different irrigation strategies on the seasonal dynamics of plant available soil water at the test site. The model and observations were also compared in the frequency domain by using empirical mode decomposition as an additional model verification.

The measured soil moisture time series are dominated by a gradual drying of the soil throughout the summer, which is less pronounced in the deeper soil ranges, while several rain events interrupted this general pattern. The model captured the drying as well as the amplitudes of the rain peaks well. However, there was an offset between measured and modelled absolute values due to the initiation based on matric potential. The simulated water balance revealed distinct differences between the windbreak and berry rows due to differences in rain interception, and evapotranspiration or irrigation patterns. Similarities in the frequency spectrum of observed and modelled values were apparent. On the other hand, the modelled time series showed more distinct spectra and less noise. Currently, more detailed analyses are being carried out to extract information from the frequency spectra.

How to cite: Hoffmeister, S. and Zehe, E.: Modelling soil moisture dynamics of an irrigated agroforestry windbreak system in South Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3847, https://doi.org/10.5194/egusphere-egu23-3847, 2023.

Viticulture is an essential sector in agriculture as wine production plays a vital role in the socio-economic life of Europe. Grapevines are a valuable, long-lived species able to grow in hot and dry regions. We currently do not know whether grapevines entirely rely on deep soil water or they make substantial use of shallow water from summer precipitation events. Without knowing this, we poorly understand what fraction of summer precipitation inputs actually contributes to grapevine transpiration. This has implications for how we quantify grapevine-relevant precipitation budgets and for predicting the impacts of climate change on grape and wine production.

We investigated grapevine water use in a vineyard in the Chianti region, central Italy. During the growing season 2021, we monitored precipitation, temperature, and soil moisture at 30 and 60 cm depth. We collected over 250 samples for stable isotope analysis (hydrogen and oxygen) from rainfall, soil and plants. Since traditional plant water sampling is problematic for grapevines, we collected samples from shoots, leaves and from condensed leaf transpiration after sealed plastic bags were wrapped around some top branches. We use these alternative plant samples to reconstruct the isotopic signal in the xylem water and infer the plants’ seasonal water origin throughout the growing season.

Preliminary results show a progressive shift in the isotopic composition of sampled water. Precipitation samples fell on the Local Meteoric Water Line (LMWL) while soil samples deviated from it because of the effects of soil evaporation. The analysis of the seasonal origin of water revealed that soil water, and consequently xylem water, was mostly recharged during winter rainfall, consistently with the precipitation seasonal regime typically of the Mediterranean climate. The reconstructed xylem samples were generally less variable than soil water, indicating stable water sources, although in some occasion they were more spatially heterogeneous.  These results contribute to a better understanding of water interactions and uptake dynamics in important socio-economic agroecosystems such as vineyards.

How to cite: Benettin, P., Manca di Villahermosa, F., Dani, A., Verdone, M., Andreotti, C., Tagliavini, M., and Penna, D.: Ecohydrological dynamics and temporal water origin in European Mediterranean vineyards: a case study in Tuscany, Central Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16318, https://doi.org/10.5194/egusphere-egu23-16318, 2023.

Soil-plant-water monitoring allows stakeholders to obtain rapid information on plant stress caused by water or nutrient deficiencies. The main objective of the study was to investigate soil-plant-water interactions based on field measurements of plant reflectance and soil water content (SWC) under different land use types and inter-row managed vineyards. Four main study sites were investigated during the vegetation period: forest, grassland, cropland (sunflower), and vineyard. Three different soil management applications were studied in the vineyard: tilled (T), cover crops (CC), and grass (NT) inter-rows. SWCs were also measured within the row and between rows of vines to get a more complete picture of the hydrology of the sites. At each study site, we had several measurement points along a slope section, where each slope is prone to erosion. For continuous hydrological monitoring soil water and temperature sensors were placed 15 and 40cm below the ground at the top and bottom of the slopes. Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) sensors were used to measure leaf reflectance. All sites included a set of hemispherical sensor sets. Topsoil SWC, leaf NDVI and chlorophyll concentrations, and Leaf Area Index (LAI) were measured every two weeks using hand-held instruments.

Among the four land use types, the lowest SWC and soil temperature of the upper 20cm was observed in the forest, and the highest in the cropland. The in-row average topsoil SWCs and temperatures were lower in all study sites compared to the values measured in between rows. The lowest chlorophyll and NDVI values were observed in grassland, which also showed the highest drought stress. The grassed inter-row grapevines had significantly lower leaf chlorophyll contents than the other inter-row managed sites (p<0.001). The highest leaf chlorophyll contents were observed in the forest samples (17.14CCI) and the tilled vineyard (16.89CCI). Based on slope positions, the most distinguishable difference was observed for the CC vineyard plants, 17.6% higher values were observed at the top of the slope compared to the leaves at the bottom of the slope (p<0.01). The leaf NDVI values were not influenced by slope positions for the vineyard, cropland, or forest. However, significantly higher chlorophyll and NDVI values were noted for the grassland lower points than the upper. The most distinguishable differences between lower and upper slope positions’ SWC values were observed for the tilled vineyard slope, 59.4% and 35.0% higher overall SWC were measured for the in-row and between-row, respectively. Overall LAI values were the highest for the forest and the lowest for the grassland, where slope position did not affect plant leaf areas significantly. The steadily decreasing annual precipitation amount (from 740mm to 422mm between 2016 and 2022) makes the area more vulnerable to climate change and highlights the need for future work on the applications of water retention measures.

How to cite: Horel, Á., Bakacsi, Z., Zagyva, I., and Zsigmond, T.: Hydrological and plant growth changes in a small agricultural catchment: effects of inter-row soil management and land use types, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5540, https://doi.org/10.5194/egusphere-egu23-5540, 2023.

The Cambodian part of the Mekong Delta, is characterized by specific irrigation infrastructures, namely Prek channels. These trapezoidal earthen channels traditionally connect the Mekong’s mainstream to low-lying floodplains by breaching the elevated river banks. They act as vectors for both flooding and drainage during the annual Monsoon inundations. Furthermore, they fulfil a diverse set of ecosystem services for local communities, from providing dry season irrigation water to channelling nutrient-laden sediments to increase the fertility of agricultural plots. Given the recent shifts in the hydrological regime of the Mekong River - mainly due to climate change, hydropower construction, and land use changes - the role of Preks  in the sustainable management of the  floodplain agroecosystems becomes a crucial issue. For this reason, various initiatives by local stakeholders as well as national ministries and international development agencies have aimed to rehabilitate Prek channels in recent years and restore functionalities that have become impeded due to erosion and sediment clogging. However, there are different ways in which to rehabilitate Preks, and numerous potential project sites to choose from. 

The aim of this study is to build a method to assess the impact of different Prek rehabilitation scenarios on the local agroecosystem, under different hydrological framework conditions. In order to do so, an eco-hydrological model has been constructed in Python. It depicts a case study area of 43 km², comprising 10 Preks, located approximately 70 km South of the Cambodian capital Phnom Penh. The model is based on the results of remote sensing analyses combining Sentinel-1 and -2 images to determine land use and land cover (LULC) evolution, as well as the spatial and temporal distribution of seasonal  inundations. It also takes into account the results of field surveys and interviews with local stakeholders to make explicit the link between the hydrological processes catalysed by Preks and the ecosystem services from which local communities benefit, especially the provision of irrigation water during the dry season. 

Subsequently, this model was used to compare different rehabilitation scenarios - different canal excavation depths (called shallow and deep calibration), and the rehabilitation of different numbers of Preks in the case study area. In addition, the simulations were carried out for three different hydrological scenarios, based on past observations - one in which the annual Monsoon flood peak is lower than average, one in which it corresponds to the long-term mean, and one in which it is higher than average. This helps account for the likely long-term impact of delta- and basin-wide developments like LULC change, climate change, and hydropower construction, on local hydrological conditions such as the timing and duration of inundations. Initial results indicate that Prek rehabilitation, especially using deep calibration, has a significant impact on agricultural production through irrigation water provision. For instance, simulations show that, even in below-average hydrological years, blanket deep calibration of Preks in the study area could increase agricultural production by 33% in comparison to the reference year.  

How to cite: Orieschnig, C., Belaud, G., Venot, J.-P., and Massuel, S.: Agro-ecological impact assessment of irrigation canal rehabilitation scenarios under different hydrological conditions in the upper Mekong Delta, Cambodia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12853, https://doi.org/10.5194/egusphere-egu23-12853, 2023.

In the coming decades, the Mediterranean region is expected to be one of the areas most affected by climate change as models project a reduction in precipitation. It remains a question if some of the Mediterranean forests will be able to adapt and survive. Pinus brutia (pine) and Cupressus sempervirens (cypress) are two important forestry species in the Mediterranean region. Although they are both coniferous, they can have different strategies to cope with water stress. The objective of this study is to estimate water balance components of pine and cypress trees with observational tree sapflow and soil moisture data. The study site is located in Athalassa Forest Park, in Cyprus. The site has a surface area of 10 ha with an average slope of 4%. Average annual rainfall is 315 mm with a mean daily minimum temperature of 5° C during January and a mean daily maximum temperature of 37° C during August. The site was converted in 2011 from rainfed agriculture to a mixed forest by planting seedlings of different tree and shrub species. Hourly observations of sapflow (cm³) and volumetric soil moisture (%) from two pine and two cypress trees and surrounding soil were used for this study. Soil moisture sensors were installed under the tree canopy (0.4 to 0.9 m from the tree trunk), at the edge of the canopy (1.3 to 2.2 m from the tree trunk) and in the open area (midpoint between neighboring tree trunks, 2.6 to 3.5 m from the tree trunk). The sensors were installed at two opposite sides of each tree trunk, in the direction of the neighboring trees. Sensor depths were 10 cm, 30 cm and 50 cm, reaching a total of 60 sensors. Daily water balance calculations were made for the period 06/11/2020 to 29/06/2022 (20 months), in which total rainfall was 581 mm. The extent of the tree root zone area was estimated for different sets of assumptions. For a root zone depth of 60 cm and a root zone area radius of 2.2 m, transpiration amounted to 33.2% of the precipitation for one of the two cypress trees and 40.9% for the other tree, with losses (interception, soil evaporation and drainage) of 60.3% and 53.6% and soil moisture changes of 6.5% and 5.5%, respectively. The pine tree observations indicated a smaller root zone area. For a root zone depth of 60 cm and a radius of 1.7 m, the transpiration of the two pine trees amounted to 30.4% and 48.0% of the precipitation, losses were 60.6% and 50.7% and soil moisture changes were 9.0% and 1.3%. The effect of the different assumptions on the water balance components will be presented.

This research has received financial support from the PRIMA (2018 Call) SWATCH Project and the Water JPI (Joint Call 2018) FLUXMED Project, both funded by the Republic of Cyprus through the Cyprus Research and Innovation Foundation. The PRIMA programme is supported by Horizon 2020, the European Union's Framework Program for Research and Innovation.

How to cite: Djuma, H., Bruggeman, A., Eliades, M., Sofokleous, I., Zoumides, C., and Siakou, M.: Estimating water balance components of Pinus brutia and Cupressus sempervirens trees with observational tree sapflow and soil moisture data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12016, https://doi.org/10.5194/egusphere-egu23-12016, 2023.

Maintenance of waterways is often a challenging task with conflicting interests between different parties. They are subject to economical stresses through the industry and transportation sector on the one hand, on the other the European Water Framework Directive dictates to ensure (or lead them back to) a chemically and ecologically “good status” (which benefits the balance between regulating, supporting, providing and cultural ecosystem services).

To have a good decision base for ecological measures, local-scale high resolution temporal and spatial data is needed to make sound decisions for a sustainable river management, which extends to assess and monitor the succession of restoration areas and to document change.

The objective of the project RiverCloud is the development of a data acquisition platform which enables synchronous data collection with unmanned aerial vehicles (UAV) and unmanned surface vehicles (USV). On the base of this platform different sensors can be used for a holistic data base in semiterrestrial areas of streams: e.g. acoustic doppler current profilers, multi-parameter sensors, multibeam-echosounders and a 360° camera for the USV; Sensors on the UAV consist of a bathymetric range finder and an industrial grade camera for structure from motion application to derive high-resolution point clouds and orthomosaics.

Building upon this data base, a further objective is the detection of vegetation structures such as a canopy height, single trees and the balancing of aboveground biomass, as a regulating ecosystem service for carbon sequestration, from high-resolution point clouds by using open source software. The results from remote sensing data are tested against comparative data collected in the field. Workflow, results and benefits for river management will be presented. All data was collected in September 2022 along the river Rhine near Karlsruhe, Germany.

How to cite: Eberhardt, B., Heuner, M., Gattung, T., Hoffmann, M., Hansen, I., Lüthi, B., Teege, J., Neumann, E., Becker, R., and Blankenbach, J.: Synchronous detection of vegetation structures in semi-terrestrial areas of the Rhine via unmanned surface vehicles and unmanned aerial vehicles and its benefits for river management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1170, https://doi.org/10.5194/egusphere-egu23-1170, 2023.

The Noah-MP land surface model is a multi-parameterization model that simulates the components of the energy and water balances at the land surface and the interaction of these components with the atmosphere. Modifying and parameterizing the model equations with the use of field observations can improve model applications for the local area but also for areas with similar environmental conditions. Our objective is to improve the simulation of ET (evaporation, transpiration, interception) in Noah-MP, using soil moisture, sapflow and throughfall observations from a monitoring site in a pine forest near the 78-km² Peristerona watershed in Cyprus. The model simulations and evaluation period cover the years 2014 - 2018. The Jarvis stomatal conductance model in Noah-MP was modified to account for nocturnal transpiration.  The use of the Jarvis model with the nocturnal transpiration resulted in a substantial increase in transpiration. The modified Noah-MP simulated ET to amount to 79% of the total precipitation, close to the observed fraction of 76%, compared to a fraction of 45% obtained with the baseline set-up of Noah-MP with the Ball-Berry stomatal conductance model. The improved Noah-MP can be combined with the WRF-Hydro model and other hydrological models to simulate the entire terrestrial hydrological cycle.

This research has received financial support from the PRIMA (2018 Call) SWATCH Project, funded by the Republic of Cyprus through the Cyprus Research and Innovation Foundation. The PRIMA programme is supported by Horizon 2020, the European Union's Framework Program for Research and Innovation.

How to cite: Sofokleous, I., Eliades, M., Djuma, H., Siakou, M., and Bruggeman, A.: Observations and modelling of water balance components with the Noah-MP land surface model in a Mediterranean pine forest, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13529, https://doi.org/10.5194/egusphere-egu23-13529, 2023.

Macroinvertebrates are essential components of the aquatic ecosystem, and their assemblages are influenced by a variety of abiotic and biotic factors. The effects of water quality parameters on macroinvertebrate assemblages were studied in regulated and unregulated reaches of the Goulburn River, Australia. Analysis of similarities (ANOSIM) revealed significant differences in macroinvertebrate community compositions between river reaches and revealed that regulation plays a vital role in the composition of macroinvertebrates. SIMPER analysis was conducted to determine the contribution of each species to the average similarity between unregulated reach R1 and regulated reach R2, which is influenced by hydropeaking. The results show that Psephenidae, Eustheniidae, and Synthemistidae play a significant role in the observed differences between the two reaches. Redundancy analysis (RDA) and threshold indicator taxa analysis (TITAN) identified the water quality parameters and their associated indicator species, and the appropriate response threshold was determined. The results show that dissolved oxygen is the most important water quality parameter influencing macroinvertebrate community assemblage in unregulated reaches, whereas total suspended solids and ammonia nitrogen influenced community structure in regulated reaches. This research provides insight into the relative effects of water quality parameters on macroinvertebrate assemblages and their resilience to anthropogenic disturbance.

How to cite: Banad, S., Wei, Y., Dhanya, C. T., and Johnstone, R.: Investigating the effects of river regulation and water quality on macroinvertebrate communities in the Goulburn basin during the millennium drought, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9147, https://doi.org/10.5194/egusphere-egu23-9147, 2023.

Climate change and anthropogenic activities cause multiple changes in groundwater systems. Particularly, these processes lead to an increase in groundwater temperature under densely populated urban areas. While physico-chemical effects have been widely studied, the consequences for groundwater ecosystems are scarcely understood. However, a thorough understanding of how this sensitive ecosystem responds to various stressors, such as temperature, in urban environments is critical for a sustainable resource management.

Thus, the aim of this study is to provide an assessment of the groundwater fauna in and around the city of Karlsruhe, Germany. We examine the ecological status of an urban aquifer by analysing fauna and physico-chemical parameters in 39 groundwater monitoring wells between 2011 and 2022. For classification, we apply the groundwater ecosystem status index (GESI), in which a threshold of more than 70% of crustaceans and less than 20% of oligochaetes serves as an indication for very good and good ecological conditions. Our study reveals that only 35% of the wells in the residential, commercial and industrial areas, and 50% of wells in a natural forest area fulfil these criteria and can be classified as natural and unstressed groundwater habitats in 2011-2014. In 2022, however, all wells in the forest area show a very good or good ecological status, irrespective of changes in diversity and number of individuals. Repeated measurements in 2022 also show significant changes in groundwater fauna with only slight changes in the physico-chemical parameters over time. A significantly decreasing number of individuals per well together with a decreasing biodiversity both in the forest and urban areas is observed.

Overall, no clear spatial patterns in the ecological status are found with respect to land use and other anthropogenic impacts, such as groundwater temperatures. Nevertheless, we observe noticeable differences in the spatial distribution of groundwater species in combination with abiotic groundwater characteristics, such as groundwater temperature and geological settings. Monitoring wells in forest areas are characterized by lower groundwater temperatures, lower nitrate concentrations, and higher dissolved oxygen concentrations, indicating a link between abiotic groundwater characteristics and land use. In addition, these monitoring wells contain larger numbers of amphipods, which are considered as indicators of healthy ecosystems.

The results of our study reveal heterogeneous and time-varying conditions in urban and natural groundwater as a habitat, which do not allow a clear assessment of the ecological status with existing assessment approaches. In the future, additional indicators, such as groundwater temperature, local geology, presence of indicator species, delineation of site-specific characteristics and natural reference conditions, should be therefore also considered in ecological groundwater assessments.

How to cite: Koch, F., Menberg, K., Schweikert, S., Hengel, J., Spengler, C., Hahn, H. J., and Blum, P.: Urban groundwater fauna - natural or anthropogenically influenced?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5773, https://doi.org/10.5194/egusphere-egu23-5773, 2023.

The Palo Verde National Park Ramsar wetland (NW Costa Rica) has witnessed a shift in vegetation from diverse vegetation and large open water areas to a near monotypic stand of cattail (Typha domingensis) with limited open water. This resulted in a sharp reduction in the bird population and biodiversity overall.

Climate and anthropogenic-driven changes in the hydrologic regime of the wetland are thought to be among the drivers of this shift.  Yet, the understanding of the drivers and processes controlling the hydroperiod of the wetland remains limited.

In this study, we aimed to characterize the hydrological dynamics of the Palo Verde wetland based on a combination of in situ monitoring stations of the groundwater and surface water levels and remote sensing satellite data. We hypothesized that the shrinking and swelling cycles of the wetland’s clay soils play a major role in controlling wetland flooding through non-stationary infiltration effects. This phenomenon might modify the flooding pattern by the tidal river bordering the wetland. First, we analyzed the trend of the hydrological time series and several hydrological indicators to interrogate and characterize the shift in the hydroperiod. Then, based on a conceptual mass balance, we estimated water infiltration at a weekly resolution, taking into account the river input by overbank flooding during high tide events. We observed that the shrinking-swelling clay soil of the wetland generated contrasted infiltration patterns at the shift between the wet and dry seasons.

This work showcases how the combination of remote sensing and ground data can help in understanding eco-hydrological dynamics and shifts in complex systems such as Palo Verde.

How to cite: Alonso, A., Hall, D., Muñoz-Carpena, R., and Mathieu, J.: Shrinking and swelling soil cycles control a tropical wetland flooding through non-stationary infiltration effects, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16130, https://doi.org/10.5194/egusphere-egu23-16130, 2023.