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Hydrology
Volume 11
Issue 12
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Hydrology, Volume 11, Issue 12 (December 2024) – 6 articles

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27 pages, 3446 KiB  
Article
A Novel Time-Varying P-III Distribution Curve Fitting Model to Estimate Design Floods in Three Gorges Reservoir Operation Period
by Yuzuo Xie, Shenglian Guo, Sirui Zhong, Xiaoya Wang, Jing Tian and Zhiming Liang
Hydrology 2024, 11(12), 203; https://doi.org/10.3390/hydrology11120203 - 26 Nov 2024
Viewed by 36
Abstract
Design floods are traditionally estimated based on the at-site annual maximum flood series, including historical information of hydraulic structures. Nevertheless, the construction and operation of upstream reservoirs undermine the assumption of stationarity in the downstream flood data series. This paper investigates non-stationary design [...] Read more.
Design floods are traditionally estimated based on the at-site annual maximum flood series, including historical information of hydraulic structures. Nevertheless, the construction and operation of upstream reservoirs undermine the assumption of stationarity in the downstream flood data series. This paper investigates non-stationary design flood estimation considering historical information from the Three Gorges Reservoir (TGR) in the Yangtze River. Based on the property that the distribution function of a continuous random variable increases monotonically, we proposed a novel time-varying P-III distribution coupled with the curve fitting method (referred to as the Tv-P3/CF model) to estimate design floods in the TGR operation period, and we comparatively studied the reservoir indices and parameter estimation methods. The results indicate that: (1) The modified reservoir index used as a covariate can effectively capture the non-stationary characteristics of the flood series; (2) The Tv-P3/CF model emphasizes the fitness of historical information, yielding superior results compared to time-varying P-III distribution estimated by the maximum likelihood method; (3) Compared to the original design values, the 1000-year design peak discharge Qm and 3-day and 7-day flood volumes in the TGR operation period are reduced by approximately 20%, while the 15-day and 30-day flood volumes are reduced by about 16%; (4) The flood-limited water level of the TGR can be raised from 145 m to 154 m, which can annually generate 0.32 billion kW h more hydropower (or increase by 6.8%) during flood season without increasing flood prevention risks. Full article
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16 pages, 6905 KiB  
Article
Analyzing Hydrodynamic Changes in Dubai Creek, UAE: A Pre- and Post-Extension Study
by Khaled Elkersh, Serter Atabay, Tarig Ali, Abdullah G. Yilmaz, Maruf Md. Mortula and Geórgenes H. Cavalcante
Hydrology 2024, 11(12), 202; https://doi.org/10.3390/hydrology11120202 - 25 Nov 2024
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Abstract
This paper presents a comparative study that examines the effects of the Dubai Creek extension on its hydrodynamics and water flushing dynamics. Dubai Creek (Khor Dubai) is a 24 km long artificial seawater stream located in the emirate of Dubai. The creek has [...] Read more.
This paper presents a comparative study that examines the effects of the Dubai Creek extension on its hydrodynamics and water flushing dynamics. Dubai Creek (Khor Dubai) is a 24 km long artificial seawater stream located in the emirate of Dubai. The creek has experienced the impact of the rapid urbanization of Dubai and a major 13 km extension project, which connected the creek to the Arabian Gulf from the other side. In this paper, two-dimensional hydrodynamic and flushing models were created using Delft3D Flexible Mesh (2021.03) to investigate the water circulation and water quality of the creek before and after the extension. The hydrodynamic models were calibrated and validated to accurately simulate water levels and currents with correlation values close to 1 and very small RMSE and bias. Flushing models were created to simulate water renewal along the creek. The results of the flushing models showed a significant improvement in the flushing characteristics of pollutants in terms of the residence times of the extended creek (Existing Creek) model compared to the old one (Old Creek). This improvement emphasized the positive impact of the creek extension project on the local aquatic ecosystem and its overall water quality. Full article
(This article belongs to the Special Issue Hydrodynamics and Water Quality of Rivers and Lakes)
17 pages, 11607 KiB  
Article
Groundwater Response to Snowmelt Infiltration in Seasonal Frozen Soil Areas: Site Monitoring and Numerical Simulation
by Yongjun Fang, Xinqiang Du, Xueyan Ye and Enbo Wang
Hydrology 2024, 11(12), 201; https://doi.org/10.3390/hydrology11120201 - 25 Nov 2024
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Abstract
Spring snowmelt has a significant impact on the hydrological cycle in seasonally frozen soil areas. However, scholars hold differing, and even opposing, views on the role of snowmelt during the thawing period in groundwater recharge. To explore the potential recharge effects of spring [...] Read more.
Spring snowmelt has a significant impact on the hydrological cycle in seasonally frozen soil areas. However, scholars hold differing, and even opposing, views on the role of snowmelt during the thawing period in groundwater recharge. To explore the potential recharge effects of spring snowmelt on groundwater in seasonal frozen soil areas, this study investigated the vadose zone dynamics controlled by soil freeze–thaw processes and snowmelt infiltration in the Northeast of China for 194 days from 31 October 2020 to 12 May 2021. Responses of groundwater level and soil moisture to snowmelt infiltration show that most snowmelt was infiltrated under the site despite the ground being frozen. During the unstable thawing period, surface snow had already melted, and preferential flow in frozen soil enabled the recharge groundwater by snowmelt (rainfall), resulting in a significant rise in groundwater levels within a short time. The calculated and simulated snowmelt (rainfall) infiltration coefficient revealed that during the spring snowmelt period, the recharge capacity of snowmelt or rainfall to groundwater at the site is 3.2 times during the stable thawing period and 4.5 times during the non-freezing period. Full article
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26 pages, 7774 KiB  
Article
Hydrological Sustainability of Dam-Based Water Resources in a Mediterranean Basin Undergoing Climate Change
by Nicola Montaldo, Serena Sirigu, Riccardo Zucca, Adriano Ruiu and Roberto Corona
Hydrology 2024, 11(12), 200; https://doi.org/10.3390/hydrology11120200 - 25 Nov 2024
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Abstract
The Flumendosa dams are a key part of the water resources system of the island of Sardinia. The analysis of a long-term (1922–2022) hydrological database showed that the Flumendosa basin has been affected by climate change since the middle of the last century, [...] Read more.
The Flumendosa dams are a key part of the water resources system of the island of Sardinia. The analysis of a long-term (1922–2022) hydrological database showed that the Flumendosa basin has been affected by climate change since the middle of the last century, associated with a decrease in winter precipitation and annual runoff (Mann–Kendall τ = −0.271), reduced by half in the last century, and an increase in the mean annual air temperature (Mann–Kendall τ = +0.373). We used a spatially distributed ecohydrological model and a water resources management model (WARGI) to define the economic efficiency and the optimal water allocation in the water system configurations throughout the evaluation of multiple planning and management rules for future climate scenarios. Using future climate scenarios, testing land cover strategies (i.e., forestation/deforestation), and optimizing the use of water resources, we predicted drier future scenarios (up to the end of the century) with an alarming decrease in water resources for agricultural activities, which could halt the economic development of Sardinia. In the future hydrological conditions (2024–2100), irrigation demands will not be totally satisfied, with up to 74% of future years being in deficit for irrigation, with a mean deficit of up to 52% for irrigation. Full article
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18 pages, 3346 KiB  
Review
The Catastrophic Water Loss of Ancient Lake Prespa: A Chronicle of a Death Foretold
by Dejan Trajkovski and Nadezda Apostolova
Hydrology 2024, 11(12), 199; https://doi.org/10.3390/hydrology11120199 - 25 Nov 2024
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Abstract
The Prespa–Ohrid lake system in the southwest Balkan region is the oldest permanent lake system in Europe and a global hotspot of biodiversity and endemism. Its smaller component, Lake Macro Prespa (or simply called Prespa), shared by North Macedonia, Albania and Greece has [...] Read more.
The Prespa–Ohrid lake system in the southwest Balkan region is the oldest permanent lake system in Europe and a global hotspot of biodiversity and endemism. Its smaller component, Lake Macro Prespa (or simply called Prespa), shared by North Macedonia, Albania and Greece has suffered a dramatic water-level fall (nearly 10 m since the 1950s). It was greater in the periods 1987–1993 and 1998–2004 and has further accelerated in the last 5 years. Analysis of satellite images (remote sensing) revealed that over the period 1984–2020 Prespa Lake lost 18.87 km2 of its surface (6.9% of its size, dropping from 273.38 km2 to 254.51 km2), with a decline in the volume of water estimated as about 54%, even reaching 56.8% in 2022. The environmental status of the lake has also been compromised and the process of its eutrophication is enhanced. The aim of this study is to summarize the current understanding of the diminishing trend in the water level and the factors that have contributed to it. The lake is highly sensitive to external impacts, including climate change, mainly restricted precipitation and increased water abstraction for irrigation. Importantly, nearly half of its outflow is through karst aquifers that feed Ohrid Lake. Of note, the hydrology and especially hydrogeology of the catchment has not been studied in sufficient detail and accurate data for the present state are missing, largely due to a lack of coordinated investigations by the three neighboring countries. However, recent estimation of the water balance of Prespa Lake, elaborated with the consideration of only the natural sources of inflow (precipitation and river runoff) and outflow (evaporation and loss of water through the karst channels) suggested a negative balance of 53 × 106 m3 annually. Our study also offers an estimated projection for the water level in the future in different climate scenarios based on linear regression models that predict its complete loss before the end of the present century. Full article
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26 pages, 7091 KiB  
Article
Advancing Coastal Flood Risk Prediction Utilizing a GeoAI Approach by Considering Mangroves as an Eco-DRR Strategy
by Tri Atmaja, Martiwi Diah Setiawati, Kiyo Kurisu and Kensuke Fukushi
Hydrology 2024, 11(12), 198; https://doi.org/10.3390/hydrology11120198 - 23 Nov 2024
Viewed by 305
Abstract
Traditional coastal flood risk prediction often overlooks critical geographic features, underscoring the need for accurate risk prediction in coastal cities to ensure resilience. This study enhances the prediction of coastal flood occurrence by utilizing the Geospatial Artificial Intelligence (GeoAI) approach. This approach employed [...] Read more.
Traditional coastal flood risk prediction often overlooks critical geographic features, underscoring the need for accurate risk prediction in coastal cities to ensure resilience. This study enhances the prediction of coastal flood occurrence by utilizing the Geospatial Artificial Intelligence (GeoAI) approach. This approach employed models—random forest (RF), k-nearest neighbor (kNN), and artificial neural networks (ANN)—and compared them to the IPCC risk framework. This study used El Salvador as a demonstration case. The models incorporated seven input variables: extreme sea level, coastline proximity, elevation, slope, mangrove distance, population, and settlement type. With a recall score of 0.67 and precision of 0.86, the RF model outperformed the other models and the IPCC approach, which could avoid imbalanced datasets and standard scaler issues. The RF model improved the reliability of flood risk assessments by reducing false negatives. Based on the RF model output, scenario analysis predicted a significant increase in flood occurrences by 2100, mainly under RCP8.5 with SSP5. The study also highlights that the continuous mangrove along the coastline will reduce coastal flood occurrences. The GeoAI approach results suggest its potential for coastal flood risk management, emphasizing the need to integrate natural defenses, such as mangroves, for coastal resilience. Full article
(This article belongs to the Special Issue Impacts of Climate Change and Human Activities on Wetland Hydrology)
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