High Resolution Simulation of Nitrate and Ammonium From Point and Diffuse Sources in a Small Headwater Catchment DOI Creative Commons
Caroline Spill, Matthias Gaßmann

Hydrological Processes, Год журнала: 2025, Номер 39(2)

Опубликована: Фев. 1, 2025

ABSTRACT Catchment water quality models are common tools for assessing hydrochemical processes in catchments. They improve the process understanding and help to identify pollutant sources. However, spatial temporal resolution of many is too coarse represent occurring within minutes or hours, making them unsuitable use fast‐responding Examples such cases headwater catchments influenced by urban agglomerations. ZIN‐AgriTra a physically based model that allows simulations with fine (< 1 h) 100 m) resolution. As it also implementation point sources, suitable simulation mixed land use. In this study, we test first time ability nitrogen transport transformation source catchment. High series wastewater treatment plant (WWTP) effluent quantities were available as input model. For combined sewer overflow (CSO) discharges, only discharge times measured. knowledge was still valuable during calibration improved CSO contributions events. Our setup modelling strategy allowed us simulate nitrate ammonium export from catchment sufficiently. Overall, sources have significant impact sensitivity parameters influencing mixing ratio between stream discharge. found large on quantity, not considering would inevitably lead incorrect parameterisation parameters. Models should become more inclusive order be able catchments, especially places, where data availability limited.

Язык: Английский

River water quality shaped by land–river connectivity in a changing climate DOI
Li Li, Julia L. A. Knapp, Anna Lintern

и другие.

Nature Climate Change, Год журнала: 2024, Номер 14(3), С. 225 - 237

Опубликована: Март 1, 2024

Язык: Английский

Процитировано

73
Water quality improves with increased spatially surface hydrological connectivity in plain river network areas DOI
Su Yang,

Guishan Yang,

Bing Li

и другие.

Journal of Environmental Management, Год журнала: 2025, Номер 377, С. 124703 - 124703

Опубликована: Фев. 25, 2025

Язык: Английский

Процитировано

3
Analyzing urban form influence on pluvial flooding via numerical experiments using random slices of actual city data DOI
Chao Mei, H. Shi, Jiahong Liu

и другие.

Journal of Hydrology, Год журнала: 2024, Номер 633, С. 130916 - 130916

Опубликована: Фев. 21, 2024

Язык: Английский

Процитировано

11
Advancing Hydrology through Machine Learning: Insights, Challenges, and Future Directions Using the CAMELS, Caravan, GRDC, CHIRPS, PERSIANN, NLDAS, GLDAS, and GRACE Datasets DOI Open Access
F. M. Hasan,

Paul Medley,

Jason Drake

и другие.

Water, Год журнала: 2024, Номер 16(13), С. 1904 - 1904

Опубликована: Июль 3, 2024

Machine learning (ML) applications in hydrology are revolutionizing our understanding and prediction of hydrological processes, driven by advancements artificial intelligence the availability large, high-quality datasets. This review explores current state ML hydrology, emphasizing utilization extensive datasets such as CAMELS, Caravan, GRDC, CHIRPS, NLDAS, GLDAS, PERSIANN, GRACE. These provide critical data for modeling various parameters, including streamflow, precipitation, groundwater levels, flood frequency, particularly data-scarce regions. We discuss type methods used significant successes achieved through those models, highlighting their enhanced predictive accuracy integration diverse sources. The also addresses challenges inherent applications, heterogeneity, spatial temporal inconsistencies, issues regarding downscaling LSH, need incorporating human activities. In addition to discussing limitations, this article highlights benefits utilizing high-resolution compared traditional ones. Additionally, we examine emerging trends future directions, real-time quantification uncertainties improve model reliability. place a strong emphasis on citizen science IoT collection hydrology. By synthesizing latest research, paper aims guide efforts leveraging large techniques advance enhance water resource management practices.

Язык: Английский

Процитировано

11
Geospatial modelling of seasonal water and electricity consumption in Doha's residential buildings using multiscale geographically weighted regression (MGWR) and Bootstrap analysis DOI Creative Commons
Rana N. Jawarneh, Ammar Abulibdeh

Sustainable Cities and Society, Год журнала: 2024, Номер 113, С. 105654 - 105654

Опубликована: Июль 9, 2024

Ensuring sustainable water and electricity consumption in urban residential buildings is a growing challenge worldwide, particularly rapidly developing regions with harsh climates. This study examines the seasonal variation of Doha, Qatar, exploring interconnectedness land use/land cover (LULC) socio-demographic characteristics household consumption. For this purpose, we employed statistical analysis (i.e. Pearson correlation Bootstrap analysis) advanced geostatistical models, including Geographically Weighted Regression (GWR) Multiscale (MGWR), to analyze monitor spatial variations The methods involved assessing relationship between surface temperature (LST), water-electricity consumption, analyzing impact demographic variables. Key findings indicate significant spatiotemporal influenced by changes LULC such as size structure. highlight need for integrated planning energy policies that consider impacts enhance efficiency sustainability settings. Furthermore, results underscore importance addressing complex interplay development resource policy-making.

Язык: Английский

Процитировано

11
An enhanced framework for simulating urban pluvial flooding: Integrating nested watersheds and urban areas with spatial heterogeneity DOI

Chenlei Ye,

Weihong Liao, Zongxue Xu

и другие.

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 132875 - 132875

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

2
Influence of urban green space landscape pattern on river water quality in a highly urbanized river network of Hangzhou city DOI
Ziyu Liu, Lijuan Liu, Yan Li

и другие.

Journal of Hydrology, Год журнала: 2023, Номер 621, С. 129602 - 129602

Опубликована: Май 1, 2023

Язык: Английский

Процитировано

22
Concepts and evolution of urban hydrology DOI
Tim D. Fletcher, Matthew J. Burns, Kathryn Russell

и другие.

Nature Reviews Earth & Environment, Год журнала: 2024, Номер 5(11), С. 789 - 801

Опубликована: Окт. 24, 2024

Язык: Английский

Процитировано

8
A Holistic Catchment‐Scale Framework to Guide Flood and Drought Mitigation Towards Improved Biodiversity Conservation and Human Wellbeing DOI Creative Commons
Phillip J. Haubrock, Rachel Stubbington, Nicola Fohrer

и другие.

Wiley Interdisciplinary Reviews Water, Год журнала: 2025, Номер 12(1)

Опубликована: Янв. 1, 2025

ABSTRACT As climatic extremity intensifies, a fundamental rethink is needed to promote the sustainable use of freshwater resources. Both floods and droughts, including water scarcity, are exacerbating declines in river biodiversity ecosystem services, with consequences for both people nature. Although this global challenge, densely populated regions such as Europe, East Asia North‐America, well most affected by climate change, particularly vulnerable. To date mitigation measures have mainly focused on individual, local‐scale targets, often neglecting hydrological connectivity within catchments interactions among hydrology, biodiversity, change human wellbeing. A comprehensive approach improve infiltration, retention groundwater recharge, thereby mitigating impacts heavy rainfall droughts scarcity. We propose holistic catchment‐scale framework that combines conventional civil engineering methods, nature‐based solutions conservation actions. This integrates legislation, substantial funding governance structure transcends administrative discipline boundaries, enabling coordinated actions across multiple spatial temporal scales. It necessitates collaboration local regional stakeholders citizens, scientists practitioners. vision management resources could synergistic effects support mitigate functional ecosystems deliver benefits people.

Язык: Английский

Процитировано

1
Continuous Simulations for Predicting Green Roof Hydrologic Performance for Future Climate Scenarios DOI Creative Commons

Komal Jabeen,

Giovanna Grossi, Michele Turco

и другие.

Hydrology, Год журнала: 2025, Номер 12(2), С. 41 - 41

Опубликована: Фев. 19, 2025

Urban green spaces, including roofs (GRs), are vital infrastructure for climate resilience, retaining water in city landscapes and supporting ecohydrological processes. Quantifying the hydrologic performance of GRs urban environment future scenarios is original contribution this research developed within URCA! project. For purpose, a continuous modelling approach undertaken to evaluate hydrological expressed by means runoff volume peak flow reduction at event scale long data series (at least 20 years). To investigate prediction climates, simple methodological proposed, using monthly projection factors definition rainfall temperature time series, transferring system parametrization current model one. The proposed tested experimental GR sites Genoa Rende, located Northern Southern Italy, respectively. Referring both Rende sites, simulation results analysed demonstrate how varies with respect characteristics, total depth, maximum intensity ADWP scenarios.

Язык: Английский

Процитировано

1