Disturbed forest affects the hydrological processes in a small mountain catchment

2020 ◽  
Author(s):  
Roman Juras ◽  
Yuliya Vystavna ◽  
Soňa Hnilicová
Keyword(s):  
Water Balance ◽  
Residence Time ◽  
Isotopic Analysis ◽  
Subsurface Water ◽  
Water Residence Time ◽  
Mountain Catchment ◽  
Undisturbed Forest ◽  
Disturbed Forest ◽  
Lake Catchment ◽  
Stable Isotopes Of Water

<p>Hydrological response covered by disturbed forest catchments are in a focus of hydrologist last decades, mainly because the connection with widespread droughts. In this study, we compare two mountain catchments in Šumava Mts. (Czech Republic), both with small glacial lakes. Plešné lake catchment is characterised by disturbed forest by a bark beetle calamity. Contrary, Čertovo lake catchment features with undisturbed forest. Both catchments have comparable geological, climate setting and origin forest types. Stable isotopes of water were used for determining the hydrological pathways and water residence time. The results show that the state of the forest significantly affects the water balance of the catchments, but the mean residence time seems to be independent on this. On the other hand, even small changes in water residence time are important for the solutes and nutrients transport in the catchments. The lakes are fed by surface and subsurface water originating from liquid precipitation in and mostly snow in winter. The isotopic analysis helps to understand how much the snow cover affects the water balance during the hydrological year in two catchments with different forest stands.</p>

Residence Time in Hyporheic Bioactive Layers Explains Nutrient Uptake in Streams

2021 ◽  
Author(s):  
Eugènia Martí ◽  
Angang Li ◽  
Susana Bernal ◽  
Brady Kohler ◽  
Steven A. Thomas ◽  
...  
Keyword(s):  
Nutrient Uptake ◽  
Water Column ◽  
Residence Time ◽  
Hyporheic Zone ◽  
Morphological Characteristics ◽  
Subsurface Water ◽  
Water Residence Time ◽  
Stream Channels ◽  
Nutrient Spiraling ◽  
Tracking Model

<p>Human activities negatively impact water quality by supplying excessive nutrients to streams. To investigate the capacity of streams to take up nutrients from the water column, we usually add nutrients to stream reaches, calculate the fraction of added nutrients that is taken up, and identify the environmental conditions controlling nutrient uptake. A common idea is that nutrient uptake increases with increasing water residence time because of increased contact time between solutes and organisms. Yet, water residence time only partially explains the temporal and spatial variability of nutrient uptake, and the reasons behind this variability are still not well understood. In this talk I’ll present a study which shows that good characterization of spatial heterogeneity of surface-subsurface flow paths and bioactive hot spots within streams is essential to understanding the mechanisms of in-stream nutrient uptake. The basis of this study arises from the use and interpretation of nutrient uptake results from the Tracer Additions for Spiraling Curve Characterization (TASCC) method. This model has been rapidly adopted to interpret in-stream nutrient spiraling metrics (e.g, nutrient uptake) over a range of concentrations from breakthrough curves (BTCs) obtained during pulse solute injection experiments. TASCC analyses often identify hysteresis in the relationship between spiraling metrics and concentration as nutrient concentration in BTCs rises and falls. The mechanisms behind these hysteresis patterns have yet to be determined. We hypothesized that difference in the time a solute is exposed to bioactive environments (i.e., biophysical opportunity) between the rising and falling limbs of BTCs causes hysteresis in TASCCs. We tested this hypothesis using nitrate empirical data from a solute addition combined with a process-based particle-tracking model representing travel times and transformations along each flow path in the water column and hyporheic zone, from which the bioactive zone comprised only a thin superficial layer. In-stream nitrate uptake was controlled by hyporheic exchange and the cumulative time nitrate spend in the bioactive layer. This bioactive residence time generally increased from the rising to the falling limb of the BTC, systematically generating hysteresis in the TASCC curves. Hysteresis decreased when nutrient uptake primarily occurred in the water column compared to the hyporheic zone, and with increasing the distance between the injection and sampling points. Hysteresis increased with the depth of the hyporheic bioactive layer. Our results indicate that the organisms responsible for nutrient uptake are confined within a thin layer in the stream sediments and that the bioactive residence time at the surface-subsurface water interface is important for nutrient uptake. I will end the talk illustrating how these findings can have important implications for in-stream nutrient uptake within the context of restoration practices addressed to modify the hydro-morphological characteristics of stream channels.</p>

scholarly journals The use of disturbed and undisturbed forest by masked titi monkeys Callicebus personatus melanochir is proportional to food availability

Oryx ◽  
2002 ◽  
Vol 36 (2) ◽  
pp. 133-139 ◽  
Author(s):  
Stefanie Heiduck
Keyword(s):  
Home Range ◽  
Atlantic Rainforest ◽  
Forest Types ◽  
Clear Cut ◽  
Titi Monkey ◽  
Eastern Brazil ◽  
Titi Monkeys ◽  
Undisturbed Forest ◽  
Disturbed Forest ◽  
One Year

The masked titi Callicebus personatus melanochir is a threatened primate, endemic to the Atlantic rainforest of eastern Brazil. The Atlantic rainforest has been reduced to only 5% of its former extent, and only 2% consists of undisturbed forest. The survival of the masked titi monkey is therefore dependent on its ability to utilise disturbed forest habitat. A group of four masked titi monkeys was observed for one year in a plot that contained both disturbed and undisturbed forest. The group used a home range of 22 ha, which comprised 58% undisturbed forest, 31% selectively logged forest and 11% forest that was regrowing after a clear-cut. The titi monkeys did not use the different forest types in proportion to the availability of each within their home range: undisturbed forest was used more than expected from its proportional availability, and disturbed forest was used less than expected. Use of forest types appeared to be determined by the availability of food resources. Undisturbed forest had the most food per unit area and regrowing forest had the least. This study shows that masked titi monkeys may be able to survive in disturbed forest habitats if these areas are of high enough quality to contain sufficient food and other resources.

scholarly journals Simulating Surface and Subsurface Water Balance Changes Due to Burn Severity

2018 ◽  
Vol 17 (1) ◽  
pp. 180099 ◽  
Author(s):  
Adam L. Atchley ◽  
Alicia M. Kinoshita ◽  
Sonya R. Lopez ◽  
Laura Trader ◽  
Richard Middleton
Keyword(s):  
Water Balance ◽  
Subsurface Water ◽  
Burn Severity

scholarly journals Water balance estimation in high Alpine terrain by combining distributed modeling and a neural network approach (Berchtesgaden Alps, Germany)

2012 ◽  
Vol 16 (7) ◽  
pp. 1969-1990 ◽  
Author(s):  
G. Kraller ◽  
M. Warscher ◽  
H. Kunstmann ◽  
S. Vogl ◽  
T. Marke ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Water Balance ◽  
Hydrological Model ◽  
Water Transfer ◽  
Subsurface Water ◽  
Network Approach ◽  
Neural Network Approach ◽  
Distributed Modeling ◽  
Artificial Neural

Abstract. The water balance in high Alpine regions is often characterized by significant variation of meteorological variables in space and time, a complex hydrogeological situation and steep gradients. The system is even more complex when the rock composition is dominated by soluble limestone, because unknown underground flow conditions and flow directions lead to unknown storage quantities. Reliable distributed modeling cannot be implemented by traditional approaches due to unknown storage processes at local and catchment scale. We present an artificial neural network extension of a distributed hydrological model (WaSiM-ETH) that allows to account for subsurface water transfer in a karstic environment. The extension was developed for the Alpine catchment of the river "Berchtesgadener Ache" (Berchtesgaden Alps, Germany), which is characterized by extreme topography and calcareous rocks. The model assumes porous conditions and does not account for karstic environments, resulting in systematic mismatch of modeled and measured runoff in discharge curves at the outlet points of neighboring high alpine subbasins. Various precipitation interpolation methods did not allow to explain systematic mismatches, and unknown subsurface hydrological processes were concluded as the underlying reason. We introduce a new method that allows to describe the unknown subsurface boundary fluxes, and account for them in the hydrological model. This is achieved by an artificial neural network approach (ANN), where four input variables are taken to calculate the unknown subsurface storage conditions. This was first developed for the high Alpine subbasin Königsseer Ache to improve the monthly water balance. We explicitly derive the algebraic transfer function of an artificial neural net to calculate the missing boundary fluxes. The result of the ANN is then implemented in the groundwater module of the hydrological model as boundary flux, and considered during the consecutive model process. We tested several ANN setups in different time increments to investigate ANN performance and to examine resulting runoff dynamics of the hydrological model. The ANN with 5-day time increment showed best results in reproducing the observed water storage data (r2 = 0.6). The influx of the 20-day ANN showed best results in the hydrological model correction. The boundary influx in the subbasin improved the hydrological model, as performance increased from NSE = 0.48 to NSE = 0.57 for subbasin Königsseetal, from NSE = 0.22 to NSE = 0.49 for subbasin Berchtesgadener Ache, and from NSE = 0.56 to NSE = 0.66 for the whole catchment within the test period. This combined approach allows distributed quantification of water balance components including subsurface water transfer.

scholarly journals Mapping and Assessing Commercial Fisheries Services in the Lithuanian Part of the Curonian Lagoon

Fishes ◽  
2022 ◽  
Vol 7 (1) ◽  
pp. 19
Author(s):  
Edgaras Ivanauskas ◽  
Andrius Skersonas ◽  
Vaidotas Andrašūnas ◽  
Soukaina Elyaagoubi ◽  
Artūras Razinkovas-Baziukas
Keyword(s):  
Spatial Distribution ◽  
Residence Time ◽  
Fish Species ◽  
Circulation Model ◽  
Curonian Lagoon ◽  
Water Residence Time ◽  
Total Catch ◽  
Catch Per Unit Effort ◽  
Commercial Fish ◽  
The Impact

The spatial distribution of biomass of main commercial fish species was mapped to estimate the supply of a provisioning fishery service in the Curonian lagoon. Catch per unit effort (CPUE) was used as a proxy to estimate the efficiency of commercial fishing and, subsequently, the potential biomass of fishes. The relationship between distinctive characteristics of the fishing areas and corresponding commercial catches and CPUE was analyzed using multivariate analysis. The total catch values and CPUE used in the analyses were derived from the official commercial fishery records. RDE analysis was used to assess the variation of both catch and CPUE of commercial fish species, while the percentages of bottom sediment type coverage, average depth, annual salinity, and water residence time in each of the fishing squares were used as explanatory variables. This distance e-based redundancy analysis allowed for the use of non-Euclidean dissimilarity indices. Fisheries data spatial distribution map indicated the lack of coherence between the spatial patterns of commercial catches and CPUE distribution in the northern part of the lagoon. Highest CPUE values were estimated in the central-eastern part of the lagoon as compared to the western part of the lagoon where CPUE values were substantially lower. Both total catch and CPUE appeared not to be related to the type of bottom habitats statistically while being spatially correlated in-between. However, the impact of salinity and water residence time calculated using the 3D hydraulic circulation model on the distribution of both CPUE and commercial catches was statistically significant.

scholarly journals Coexisting ecosystem states in a tropical coastal lagoon under progressive eutrophication in the northern Cuban keys

2018 ◽  
Vol 82 (3) ◽  
pp. 139 ◽  
Author(s):  
Roberto González-De Zayas ◽  
Martin Merino-Ibarra ◽  
Patricia M. Valdespino-Castillo ◽  
Yunier Olivera ◽  
Sergio F. Castillo-Sandoval
Keyword(s):  
Residence Time ◽  
Coastal Lagoon ◽  
Spatial And Temporal Variability ◽  
Positive Trend ◽  
Water Residence Time ◽  
Effective Management ◽  
Management Options ◽  
Trophic Index ◽  
Tropical Coastal Lagoon ◽  
Mollusc Assemblages

Through a nested suite of methods here we contrast the coexistence of different ecosystem states in a tropical coastal lagoon, the Laguna Larga, with increasing eutrophication stress between 2007 and 2009. Water temperature averaged 27.4°C in the lagoon and showed a slight positive trend during the study period. Salinity averaged 35.0±6.2, exhibiting high spatial and temporal variability, and also a slight positive trend in time. In contrast, dissolved oxygen showed a substantial decreasing trend (–0.83 ml L–1 y–1; –13.3% y–1) over the period, while nutrients increased dramatically, particularly total phosphorus (2.6 µM y–1), in both cases sustaining the progression of eutrophication in the lagoon during the three years we sampled. The Karydis nutrient load-based trophic index showed that the lagoon has a spatial pattern of increasing eutrophication from the sea and the outer sector (oligotrophic-mesotrophic) to the central (mesotrophic) and the inner sector (mesotrophic-eutrophic). Two ecosystem states were found within the lagoon. In the outer oligotrophic sector, the dominant primary producers were macroalgae, seagrasses and benthic diatoms, while mollusc assemblages were highly diverse. In the inner and central sectors (where trophic status increased toward the inner lagoon) a phytoplankton-dominated ecosystem was found where mollusc assemblages are less diverse. In spite of the progression of eutrophication in the lagoon, these two different ecosystems coexisted and remained unchanged during the study period. Apparently, the effect of water residence time, which increases dramatically toward the inner lagoon, dominated over that of nutrient loadings, which is relatively more homogeneously distributed along the lagoon. Therefore, we consider that actions that reduce the water residence time are likely the most effective management options for this and other similarly choked lagoons.

scholarly journals Water balance estimation in high Alpine terrain by combining distributed modeling and a neural network approach (Berchtesgaden Alps, Germany)

2012 ◽  
Vol 9 (1) ◽  
pp. 215-259
Author(s):  
G. Kraller ◽  
M. Warscher ◽  
H. Kunstmann ◽  
S. Vogl ◽  
T. Marke ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Water Balance ◽  
Water Transfer ◽  
Subsurface Water ◽  
Distributed Model ◽  
Network Approach ◽  
Neural Network Approach ◽  
Distributed Modeling ◽  
Artificial Neural

Abstract. The water balance in high Alpine regions is often characterized by significant variation of meteorological variables in space and time, a complex hydrogeological situation and steep gradients. The system is even more complex when the rock composition is dominated by soluble limestone, because unknown underground flow conditions and flow directions lead to unknown storage quantities. Reliable distributed modeling cannot be implemented by traditional approaches due to unknown storage processes at local and catchment scale. We present an artificial neural network extension of a distributed hydrological model (WaSiM-ETH) that allows to account for subsurface water transfer in a karstic environment. The extension was developed for the Alpine catchment of the river "Berchtesgadener Ache" (Berchtesgaden Alps, Germany), which is characterized by extreme topography and calcareous rocks. The model assumes porous conditions and does not account for karstic environments, resulting in systematic mismatch of modeled and measured runoff in discharge curves at the outlet points of neighboring high alpine sub-catchments. Various precipitation interpolation methods did not allow to explain systematic mismatches, and unknown subsurface hydrological processes were concluded as the underlying reason. We introduce a new method that allows to describe the unknown subsurface boundary fluxes, and account for them in the distributed model. This is achieved by an Artificial Neural Network approach (ANN), where three input variables are taken to calculate the unknown subsurface storage conditions. We explicitly derive the algebraic transfer function of an artificial neural net to calculate the missing boundary fluxes. The result of the ANN is then implemented in the groundwater module of the distributed model as boundary flux, and considered during the consecutive model process. The ANN was able to reproduce the observed water storage data sufficiently (r2 = 0.48). The boundary influx in the sub-catchment improved the distributed model, as performance increased from NSE = 0.34 to NSE = 0.57. This combined approach allows distributed quantification of water balance components including subsurface water transfer.

scholarly journals Principles of constructed wetlands designing

2019 ◽  
Vol 27 (4) ◽  
pp. 255-263
Author(s):  
Kseniia Y. Rybka ◽  
Nataliia M. Shchegolkova
Keyword(s):  
Constructed Wetlands ◽  
Residence Time ◽  
Aquatic Plants ◽  
Subsurface Water ◽  
Technological Parameters ◽  
Agricultural Wastewater ◽  
Universal Principles ◽  
The World ◽  
Individual Type

Constructed wetlands (CW) - shallow surfaces or subsurface water bodies, planted with higher aquatic plants and designed to treat wastewater - have been actively used in world practice for the last decades. There are no universal principles for designing such systems, so for each combination of landscape (in which a CW is located) and the quality of wastewater, an individual type of CW is selected. The article provides an overview of the principles adopted in the world for calculating the main technological parameters of CWs (choice of the type of CW, calculation of the area of CW, the residence time of the water in the system, the choice of filtering medium, etc.) developed on the basis of numerous functioning objects. The recommendations given in the article are applicable for small and mediumsized CWs intended for the treatment of domestic, storm and agricultural wastewater.

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