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  • 1
    Article
    Article
    Hydroclimatic variability and riparian wetland restoration control the hydrology and nutrient fluxes in a lowland agricultural catchment / (2021)
    Elsevier,
    Details
    UID:
    kobvindex_IGB000025166
    ISSN: 1879-2707
    In: Journal of Hydrology. - 603(2021)Part B, Art. 126904
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  • 2
    Online Resource
    Online Resource
    Tracer-aided modelling of hydrological and biogeochemical processes in a mixed land-use, lowland catchment / (2023)
    Berlin,
    Details
    UID:
    almahu_BV049569737
    Format: 1 Online-Ressource (xxiii, 288 Seiten) : , Illustrationen, Diagramme, Karten.
    Content: In einer Zeit, in der menschliche Aktivitäten mit geologischen Kräften konkurrieren und sich das Klima ständig verändert, ist das Verständnis hydrologischer Prozesse essenziell. Die Quantifizierung hydrologischer Prozesse ist jedoch aufgrund der räumlichen Heterogenität der Umweltfaktoren, die die zugrunde liegenden Prozesse beeinflussen, eine Herausforderung. Daher wurden in dieser Arbeit eine Reihe gemeinsamer, miteinander verbundener Ansätze oder Technologien entwickelt und in einem Einzugsgebiet mit gemischter Landnutzung, dem Demnitz Millcreek (DMC, 66 km2), getestet. Durch die Anwendung von Datenanalyse, Modelling, Machine-learning und Unmanned-vehicle technologies haben wir nicht nur die hydrologischen Prozesse in diesem repräsentativen Einzugsgebiet entschlüsselt, sondern auch - aus einer breiteren Perspektive - den optimalen Methode zur gemeinsamen Nutzung vorhandener Technologien ermittelt, um Unsicherheiten bei Modellierung dieser Prozesse auf der Ebene des Einzugsgebiets zu verringern.
    Content: Englische Version: Understanding hydrological processes is essential in an era when human activities rival geologic-scale forces and the climate consistently changes. However, hydrological quantifications are challenging due to the spatial heterogeneity in environmental drivers of the underlying processes. Therefore in this thesis, a series of common linked approaches or technologies were developed and tested in a mixed-landuse catchment, the Demnitzer Millcreek (DMC, 66 km2). By applying data analysis, distributed modelling, machine-learning, and unmanned-vehicle technologies, we not only unraveled the hydrological processes in this representative catchment, but also from a wider perspective - identified the optimal way to jointly use the existing technologies to reduce the uncertainty in monitoring and modelling these processes at the catchment-scale.
    Note: [Tag der Verteidigung]: 20.09.2023. - Der Text enthält eine Zusammenfassung in deutscher und englischer Sprache.. - Veröffentlichung der elektronischen Ressource auf dem edoc-Server der Humboldt-Universität zu Berlin: 2024 , Dissertation Humboldt-Universität zu Berlin 2023
    Additional Edition: Erscheint auch als Druck-Ausgabe Wu, Songjun Tracer-aided modelling of hydrological and biogeochemical processes in a mixed land-use, lowland catchment
    Language: English
    Subjects: Geography
    RVK:
    RG 60357
    RVK:
    RG 60363
    RVK:
    RB 10232
    Keywords: Fließgewässer ; Nährstoffeintrag ; Hydrologie ; Wassergüte ; Fernerkundung ; Modellierung ; Hochschulschrift
    DOI: 10.18452/27796
    URN: urn:nbn:de:kobv:11-110-18452/28928-8
    URL: Volltext  (kostenfrei)
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    HU Berlin
  • 3
    Book
    Book
    Tracer-aided modelling of hydrological and biogeochemical processes in a mixed land-use, lowland catchment / (2023)
    Berlin,
    Details
    UID:
    almahu_BV049575900
    Format: xxiii, 288 Seiten : , Illustrationen, Diagramme, Karten (farbig).
    Content: In einer Zeit, in der menschliche Aktivitäten mit geologischen Kräften konkurrieren und sich das Klima ständig verändert, ist das Verständnis hydrologischer Prozesse essenziell. Die Quantifizierung hydrologischer Prozesse ist jedoch aufgrund der räumlichen Heterogenität der Umweltfaktoren, die die zugrunde liegenden Prozesse beeinflussen, eine Herausforderung. Daher wurden in dieser Arbeit eine Reihe gemeinsamer, miteinander verbundener Ansätze oder Technologien entwickelt und in einem Einzugsgebiet mit gemischter Landnutzung, dem Demnitz Millcreek (DMC, 66 km2), getestet. Durch die Anwendung von Datenanalyse, Modelling, Machine-learning und Unmanned-vehicle technologies haben wir nicht nur die hydrologischen Prozesse in diesem repräsentativen Einzugsgebiet entschlüsselt, sondern auch - aus einer breiteren Perspektive - den optimalen Methode zur gemeinsamen Nutzung vorhandener Technologien ermittelt, um Unsicherheiten bei Modellierung dieser Prozesse auf der Ebene des Einzugsgebiets zu verringern.
    Content: Englische Version: Understanding hydrological processes is essential in an era when human activities rival geologic-scale forces and the climate consistently changes. However, hydrological quantifications are challenging due to the spatial heterogeneity in environmental drivers of the underlying processes. Therefore in this thesis, a series of common linked approaches or technologies were developed and tested in a mixed-landuse catchment, the Demnitzer Millcreek (DMC, 66 km2). By applying data analysis, distributed modelling, machine-learning, and unmanned-vehicle technologies, we not only unraveled the hydrological processes in this representative catchment, but also from a wider perspective - identified the optimal way to jointly use the existing technologies to reduce the uncertainty in monitoring and modelling these processes at the catchment-scale.
    Note: [Tag der Verteidigung]: 20.09.2023. - Der Text enthält eine Zusammenfassung in deutscher und englischer Sprache. , Dissertation Humboldt-Universität zu Berlin 2023
    Additional Edition: Erscheint auch als Online-Ausgabe Wu, Songjun Tracer-aided modelling of hydrological and biogeochemical processes in a mixed land-use, lowland catchment 10.18452/27796
    Additional Edition: urn:nbn:de:kobv:11-110-18452/28928-8
    Language: English
    Subjects: Geography
    RVK:
    RG 60357
    RVK:
    RG 60363
    RVK:
    RB 10232
    Keywords: Fließgewässer ; Nährstoffeintrag ; Hydrologie ; Wassergüte ; Fernerkundung ; Modellierung ; Hochschulschrift
    URL: Volltext  (kostenfrei)
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    Book
    Fulltext
    HU Berlin get availability status
  • 4
    Article
    Article
    Disentangling the influence of landscape characteristics, hydroclimatic variability and land management on surface water NO3-N dynamics : spatially distributed modeling over 30 yr in a lowland mixed land use catchment (2022)
    Wiley,
    Details
    UID:
    kobvindex_IGB000025312
    ISSN: 1944-7973
    In: Water Resources Research. - 58(2022)2, Art. e2021WR030566
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  • 5
    Online Resource
    Online Resource
    Integrating Tracers and Soft Data Into Multi‐Criteria Calibration: Implications From Distributed Modeling in a Riparian Wetland (2023)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_29229
    Format: 1 Online-Ressource (21 Seiten)
    ISSN: 0043-1397 , 1944-7973 , 0043-1397 , 1944-7973
    Content: Calibrating distributed hydrological models often leads to equifinality due to complex model structures, which can be further exacerbated in wetlands due to spatio‐temporal heterogeneity in ecohydrological processes. Here, step‐wise calibrations of the physically‐based distributed model EcH2O‐iso was conducted in a data‐rich wetland by minimizing a weighted average of the errors on discharge, stream isotopes, groundwater (GW) isotopes, and soil moisture. Results showed multi‐criteria calibration outperformed single‐criterion calibration as it strongly increased the overall performance, yet only marginally degraded performance of each calibration target. Isotopes were highlighted as appropriate auxiliary data as they effectively constrained the model with relatively small weights (0.1). However, those parameter sets that minimize the errors could still lead to physically implausible simulations of uncalibrated internal states or fluxes. This was further demonstrated by an approach developed to check internal fluxes based on soft data (transpiration and lateral flow), suggesting 54% of optimized models gave “right answers for the wrong reasons.” By excluding those models against soft data, such an approach further constrained equifinality, and unraveled potential inconsistencies between observations and calibration. Modeling represented the wetland as a slow‐draining system mainly fed by GW, but also influenced by near‐surface flow during winter or summer convectional events. Further, heterogeneity in hydrological functioning was partly attributed to distinct evapotranspiration patterns between contrasting vegetation communities. Therefore, this study not only provided insights into wetland functioning, but also revealed potential equifinality even with abundant data for calibration, and potential solutions based on the integration of isotopes and soft data.
    Content: Peer Reviewed
    In: [New York] : Wiley, 59,11, 0043-1397
    In: 1944-7973
    Language: English
    DOI: 10.18452/28610
    DOI: 10.1029/2023WR035509
    URN: urn:nbn:de:kobv:11-110-18452/29229-2
    URL: Volltext  (kostenfrei)
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    Online Resource
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    HU Berlin
  • 6
    Online Resource
    Online Resource
    Disentangling the Influence of Landscape Characteristics, Hydroclimatic Variability and Land Management on Surface Water NO3-N Dynamics: Spatially Distributed Modeling Over 30 yr in a Lowland Mixed Land Use Catchment (2022)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_29754
    Format: 1 Online-Ressource (20 Seiten)
    Content: Nitrate (NO3-N) mobilization is generally controlled by available sources, hydrological connectivity, and biogeochemical transformations along the dominant flow paths. However, their spatial heterogeneity and complex interactions often impede integrated understanding of NO3-N dynamics at the catchment scale. To fully integrate spatiotemporal information for NO3-N simulations, a grid-based model, mHM-Nitrate, was applied to a 68 km2 lowland, mixed land use catchment (Demnitzer Millcreek, DMC) near Berlin. The model successfully captured the spatiotemporal distribution of flow and NO3-N between 2001 and 2019, but was less successful in 1992–2000 due to land management changes. Re-optimization of relative parameters was subsequently conducted for this period to understand management effects. The simulated results revealed landscape characteristics and hydroclimatic variability as the main controlling factors on respective spatial and temporal patterns. The combined effects of vegetation cover and fertilizer inputs dictated the spatial distribution of water and NO3-N fluxes, while wetness condition determined the temporal NO3-N dynamics by regulating hydrological connectivity and NO3-N mobilization. Denitrification was also closely coupled with hydroclimatic conditions, which accounted for ∼20% of NO3-N inputs. In contrast, restoration of riparian wetlands had a modest impact on NO3-N export (∼10% reduction during 2001–2019), suggesting further interventions (e.g., reducing fertilizer application or increased wetland areas) are needed. Our modeling application demonstrated that mHM-Nitrate could provide robust spatially distributed simulations of hydrological and NO3-N fluxes over a long-term period and could successfully differentiate the key controlling factors. This underlines the model's value in contributing to an evidence base to guide future management practices under climate change.
    Content: Peer Reviewed
    In: [New York] : Wiley, 58,2
    Language: English
    DOI: 10.18452/29128
    DOI: 10.1029/2021WR030566
    URN: urn:nbn:de:kobv:11-110-18452/29754-7
    URL: Volltext  (kostenfrei)
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    HU Berlin
  • 7
    Online Resource
    Online Resource
    Improved understanding of vegetation dynamics and wetland ecohydrology via monthly UAV‐based classification (2023)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_28221
    Format: 1 Online-Ressource (9 Seiten)
    ISSN: 0885-6087 , 1099-1085 , 0885-6087 , 1099-1085
    Content: Vegetation classification is an essential prerequisite for understanding vegetation‐water relations at a range of spatial scales. However, in site‐specific applications, such classifications were mostly based on a single Unmanned Aerial Vehicle (UAV) flight, which can be challenging in grasslands and/or herbaceous‐dominated systems, as those communities are small in size and highly mixed. Here, we conducted monthly UAV flights for two years in a riparian wetland in Germany, with acquired imagery used for vegetation classification on a monthly basis under different strategies (with or without auxiliary information from other flights) to increase understanding in ecohydrology. The results show that multi‐flight‐based classification outperformed single‐flight‐based classification due to the higher classification accuracy. Moreover, improved sensitivity of temporal changes in community distribution highlights the benefits of multi‐flight‐based classification ‐ providing a more comprehensive picture of community evolution. From reference to the monthly community distribution, we argue that a combination of two or three flights in early‐ and late‐summer is enough to achieve comparable results to monthly flights, while mid‐summer would be a better timing in case only one flight is scheduled. With such detailed vegetation mapping, we further interpreted the complex spatio‐temporal heterogeneity in NDVI and explored the dominant areas and developmental progress of each community. Impacts from management (mowing events) were also evaluated based on the different responses between communities in two years. Finally, we explored how such vegetation mapping could help understand landscape ecohydrology, and found that the spatio‐temporal distribution of minimal soil moisture was related to NDVI peaks of local community, while grass distribution was explained by both topography and low moisture conditions. Such bi‐directional relationships proved that apart from contributing to an evidence base for wetland management, multi‐flight UAV vegetation mapping could also provide fundamental insights into the ecohydrology of wetlands.
    Content: Peer Reviewed
    In: New York, NY : Wiley, 37,9, 0885-6087
    In: 1099-1085
    Language: English
    DOI: 10.18452/27568
    DOI: 10.1002/hyp.14988
    URN: urn:nbn:de:kobv:11-110-18452/28221-3
    URL: Volltext  (kostenfrei)
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    HU Berlin
  • 8
    Online Resource
    Online Resource
    Using stable water isotopes to understand ecohydrological partitioning under contrasting land uses in a drought‐sensitive rural, lowland catchment (2022)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_27793
    Format: 1 Online-Ressource (20 Seiten)
    Content: Vegetation plays an essential role in water partitioning, as it strongly influences evapotranspiration, infiltration and water retention. To analyse the influence of vegetation on water partitioning under innovative land management strategies, we used stable water isotopes as natural tracers to monitor precipitation, soil water and groundwater fluxes over the growing season of 2021 (March–October). We selected eight plot sites with four contrasting land covers and soil types in the drought-sensitive Demnitzer Millcreek Catchment (DMC) in NE Germany. The land use types include forest, grassland, and arable with the latter being subdivided into conventional (e.g., crops) and innovative (e.g., agroforestry) sites. Two weather stations, a flux tower, and in situ soil moisture monitoring complemented our isotopic data with a hydroclimatic context. The year of 2021 had near-normal precipitation totals compared to the prolonged drought of 2018–20. Soil water storage was highest at the agricultural sites, while lowest at the forest, though this reflected both the influence of soil properties (as forests dominated sand soils while crops loam soils) and the greater evapotranspiration from forests. We also estimated soil water ages and found the greatest isotopic variability and fastest turnover of water in the upper soils of arable sites. The forest soil water had the most limited variability in isotopic composition and tended to be older, revealing lower levels of groundwater recharge. Conventional and innovative cropping sites were similar to each other, likely due to the early tree development stage in agroforestry schemes under the latter. Our investigation revealed the forest sites are potentially most vulnerable to limited water availability in the DMC and land use changes in agricultural land lacked major differences in ecohydrological fluxes over the study year. The study further underlines the need for long-term observations of recent adaptive land use changes and drought-sensitive vegetation to improve our understanding and evolve drought resilient land management strategies considering time lags in impacts and non-stationarity.
    Content: Peer Reviewed
    In: New York, NY : Wiley, 36,12
    Language: English
    DOI: 10.18452/27126
    DOI: 10.1002/hyp.14779
    URN: urn:nbn:de:kobv:11-110-18452/27793-1
    URL: Volltext  (kostenfrei)
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    HU Berlin
  • 9
    Online Resource
    Online Resource
    Identifying Dominant Processes in Time and Space: Time‐Varying Spatial Sensitivity Analysis for a Grid‐Based Nitrate Model (2022)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_26458
    Format: 1 Online-Ressource (23 Seiten)
    Content: Distributed models have been increasingly applied at finer spatiotemporal resolution. However, most diagnostic analyses aggregate performance measures in space or time, which might bias subsequent inferences. Accordingly, this study explores an approach for quantifying the parameter sensitivity in a spatiotemporally explicit way. We applied the Morris method to screen key parameters within four different sampling spaces in a grid‐based model (mHM‐Nitrate) for NO3‐N simulation in a mixed landuse catchment using a 1‐year moving window for each grid. The results showed that an overly wide range of aquatic denitrification rates could mask the sensitivity of the other parameters, leading to their spatial patterns only related to the proximity to outlet. With adjusted parameter space, spatial sensitivity patterns were determined by NO3‐N inputs and hydrological transport capacity, while temporal dynamics were regulated by annual wetness conditions. The relative proportion of parameter sensitivity further indicated the shifts in dominant hydrological/NO3‐N processes between wet and dry years. By identifying not only which parameter(s) is(are) influential, but where and when such influences occur, spatial sensitivity analysis can help evaluate current model parameterization. Given the marked sensitivity in agricultural areas, we suggest that the current NO3‐N parameterization scheme (land use‐dependent) could be further disentangled in these regions (e.g., into croplands with different rotation strategies) but aggregated in non‐agricultural areas; while hydrological parameterization could be resolved into a finer level (from spatially constant to land use‐dependent especially in nutrient‐rich regions). The spatiotemporal sensitivity pattern also highlights NO3‐N transport within soil layers as a focus for future model development.
    Content: Peer Reviewed
    In: [New York] : Wiley, 58,8
    Language: English
    DOI: 10.18452/25789
    DOI: 10.1029/2021WR031149
    URN: urn:nbn:de:kobv:11-110-18452/26458-1
    URL: Volltext  (kostenfrei)
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    HU Berlin
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