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Advances in Hydrology: Flow and Velocity Analysis in Rivers

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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (20 April 2024) | Viewed by 17011

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Special Issue Editors

Dr. Bojan Đurin

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Guest Editor

Department of Civil Engineering, University North, Jurja Križanića 31b, 42000 Varaždin, Croatia
Interests: water supply and drainage; hydrology; hydrotechnical facilities; hydropower plants; renewable energy; multicriteria methods; climate changes
Special Issues, Collections and Topics in MDPI journals

Dr. Fabio Di Nunno

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Guest Editor

Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio 43, 03043 Cassino, FR, Italy
Interests: two-phase air-water flows; optical measurement techniques for multiphase flows; machine learning for hydraulic engineering; wastewater management
Special Issues, Collections and Topics in MDPI journals

Dr. Suraj Kumar Singh

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Guest Editor

Centre for Sustainable Development, Suresh Gyan Vihar University, Jaipur 302017, India
Interests: water logging and flood hazards; geospatial applications in water resources; disaster management; hydro geomorphology; urban planning and wasteland mapping

Special Issue Information

Dear Colleagues,

An accurate and reliable analysis of river hydrological regimes is a key factor in proper water resource management in countering the risks associated with extreme events such as droughts and floods. This has become even more relevant in recent decades due to climate change and human activity, making this analysis complex and challenging.

This Special Issue intends to gather all actual and relevant papers about the mentioned problems and their solutions, including new insight into the analyzed topic through the original scientific papers, review papers, and real case study presentations. All relevant disciplines, including hydrology, GIS, machine learning procedures, and all other disciplines that could be overlapped with this Special Issue, are welcomed.

Moreover, all knowledge and experience about the technology of measuring river flow and velocity are also appropriate for consideration for the submission of the manuscripts related to the mentioned. Integrating geospatial technology, GIS, and geoinformatics has revolutionized our ability to analyze and model river flow and velocity, allowing us to understand better and manage our water resources. This Special Issue will feature original research articles, reviews, and case studies on applying geospatial technology in river flow and velocity analysis.

Overall, this Research Topic aims to cover recent advances in the following topics:

Development of innovative methods for river flow and velocity analysis;
Development of methodologies and strategies for the analysis of the extreme flow events;
Spatio-temporal analysis of river parameters aimed at investigating the complex relationships between the analyzed quantities and the geomorphological characteristics of the study areas;
Integration of geospatial technology, GIS, and geoinformatics in river flow and velocity analysis;
Applications of remote sensing in river flow and velocity analysis;
Development of river flow and velocity models using geospatial technology;
Assessment of river health using geospatial technology and river flow and velocity analysis;
Impacts of climate change on river flow and velocity;
Case studies in river flow and velocity analysis using geospatial technology;
Integration of citizen science in river flow and velocity analysis;
Challenges and opportunities in river flow and velocity analysis using geospatial technology.

Dr. Bojan Đurin
Dr. Fabio Di Nunno
Dr. Suraj Kumar Singh
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

river
hydrology
velocity
flow
GIS
geoinformatics
extremes
geospatial technology
artificial intelligence
remote sensing

Published Papers (12 papers)

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Research

20 pages, 3557 KiB

Open AccessArticle

Impact of Future Climate Scenarios and Bias Correction Methods on the Achibueno River Basin

by Héctor Moya, Ingrid Althoff, Juan L. Celis-Diez, Carlos Huenchuleo-Pedreros and Paolo Reggiani

Water 2024, 16(8), 1138; https://doi.org/10.3390/w16081138 - 17 Apr 2024

Viewed by 444

Abstract

Future climate scenarios based on regional climate models (RCMs) have been evaluated widely. However, the use of RCMs without bias correction may increase the uncertainty in the assessment of climate change impacts, especially in mountain areas. Five quantile mapping methods (QMMs) were evaluated as bias correction methods for precipitation and temperature in the historical period (1979–2005) of one local climate model and three RCMs at the Achibueno River Basin, southcentral Chile. Additionally, bias-corrected climate scenarios from 2025 to 2050 under two Representative Concentration Pathways (RCPs) were evaluated on the hydrological response of the catchment with the Soil and Water Assessment Tool (SWAT+). The parametric transformation function and robust empirical quantile were the most promising bias correction methods for precipitation and temperature, respectively. Climate scenarios suggest changes in the frequency and amount of precipitation with fluctuations in temperatures. Under RCP 2.6, partial increases in precipitation, water yield, and evapotranspiration are projected, while for RCP 8.5, strong peaks of precipitation and water yield in short periods of time, together with increases in evapotranspiration, are expected. Consequently, flooding events and increasing irrigation demand are changes likely to take place. Therefore, considering adaptation of current and future management practices for the protection of water resources in southcentral Chile is mandatory. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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22 pages, 2862 KiB

Open AccessArticle

Large-Scale Hydrological Models and Transboundary River Basins

by Charalampos Skoulikaris

Water 2024, 16(6), 878; https://doi.org/10.3390/w16060878 - 19 Mar 2024

Viewed by 724

Abstract

Large-scale hydrological modeling is an emerging approach in river hydrology, especially in regions with limited available data. This research focuses on evaluating the performance of two well-known large-scale hydrological models, namely E-HYPE and LISFLOOD, for the five transboundary rivers of Greece. For this purpose, discharge time series at the rivers’ outlets from both models are compared with observed datasets wherever possible. The comparison is conducted using well-established statistical measures, namely, coefficient of determination, Percent Bias, Nash–Sutcliffe Efficiency, Root-Mean-Square Error, and Kling–Gupta Efficiency. Subsequently, the hydrological models’ time series are bias corrected through scaling factor, linear regression, delta change, and quantile mapping methods, respectively. The outputs are then re-evaluated against observations using the same statistical measures. The results demonstrate that neither of the large-scale hydrological models consistently outperformed the other, as one model performed better in some of the basins while the other excelled in the remaining cases. The bias-correction process identifies linear regression and quantile mapping as the most suitable methods for the case study basins. Additionally, the research assesses the influence of upstream waters on the rivers’ water budget. The research highlights the significance of large-scale models in transboundary hydrology, presents a methodological approach for their applicability in any river basin on a global scale, and underscores the usefulness of the outputs in cooperative management of international waters. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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13 pages, 10806 KiB

Open AccessArticle

Effect of Skewness Orientation on Morphological Adjustments in Alluvial Meandering Streams

by Ryan Good, David Nguyen, Hossein Bonakdari, Andrew Binns and Bahram Gharabaghi

Water 2024, 16(6), 851; https://doi.org/10.3390/w16060851 - 15 Mar 2024

Viewed by 616

Abstract

Predicting morphological adjustments in alluvial meandering streams remains a challenging task due to the complex nature of the governing inter-related dynamic flow and sediment transport processes. This difficulty is increased in streams with irregular single-channel planform geometries, such as skewed meanders, where the meander apex is shifted in either the up-valley or down-valley direction relative to the meander centroid. Research in confined bank flume experiments has shown that the geometry difference affects flow characteristics and streambed development. The present study extends upon these findings by being the first to investigate the effects of skewness orientation in a wide-channel flume with a fully unconfined bed and banks. Three experiments were completed with an up-valley skewed, a down-valley skewed, and a non-skewed symmetrical channel, using well-sorted coarse sand and no sediment feed. The results had some variabilities in erosion and magnitude of morphological developments due to initial experimental conditions, but our analysis of the bedform positioning showed notable similarities and differences between the geometries. Bedforms typically formed upstream of the apex, with differences in their stream-wise direction extents. This research highlights how channel width-to-depth ratio and bank erodibility significantly impact river evolution, offering new insights into the dynamics of skewed meandering river channels. This study is a novel step towards a better understanding of skewed meandering rivers in unconfined alluvial channels and highlights opportunities for further research. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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25 pages, 10041 KiB

Open AccessArticle

Predicting the Flow Fields in Meandering Rivers with a Deep Super-Resolution Convolutional Neural Network

by Xiaohui Yan, Fu Du, Tianqi Zhang, Qian Cui, Zuhao Zhu and Ziming Song

Water 2024, 16(3), 425; https://doi.org/10.3390/w16030425 - 28 Jan 2024

Viewed by 932

Abstract

The hydrodynamic model, based on the strict conservation of momentum and continuity equations, can accurately simulate the distribution of a flow field. However, significant computing time and storage space requirements limit real-time prediction. Machine learning is well known for its fast computing speed and powerful learning ability, but its accuracy depends on an abundance of training data, hindering its wider use in locations without sufficient measurements. Application restrictions in data-deficient areas can be addressed through transfer learning, provided that two areas share common characteristics. In this study, a machine learning method based on a deep super-resolution convolutional neural network (DSRCNN) and transfer learning is proposed, validated, and applied to model two bend flows and one realistic test case. Firstly, the hydrodynamic model was established and validated against measured data. The validated model was considered to have the ability to generate real data and was used to generate a comprehensive data set for training and validating the machine learning model. Three different methods were compared and tested, with Realizable k-ε performing better than the others in predicting the outer bank flow distribution. DSRCNN was compared to a plain SRCNN (PSRCNN), as well as Bilinear, Nearest, and Bicubic methods, and the results showed that DSRCNN had the best performance. We compared Raw, RT, and TL methods, finding that the TL method performed the best overall. Therefore, the research results showed that the developed super-resolution convolutional neural network can provide more reliable predications and serve as an ideal tool for simulating flow field distribution in bends. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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14 pages, 6893 KiB

Open AccessArticle

Time-Lagged Response of Streamflow in the Lower Yellow River to the Water Regulation by Xiaolangdi Reservoir: Implication for Efficient Water Supply

by Juan Wang, Jinquan Xu and Dongxian Kong

Water 2024, 16(1), 78; https://doi.org/10.3390/w16010078 - 24 Dec 2023

Cited by 1 | Viewed by 844

Abstract

The Lower Yellow River (LYR) is a vital water resource for agriculture, industry, and domestic use in the surrounding areas. Understanding the delayed response of local streamflow response to remote reservoir operations is crucial for effective water management and flood control. In this work, we utilize historical hydrological data and statistical analysis techniques to investigate the time-lagged response of streamflow in the LYR to water regulation by the Xiaolangdi Reservoir. The results demonstrate that there is a time lag of 1.98 days, 2.86 days, and 3.93 days between the record of water regulation at Xiaolangdi Reservoir and the arrival time at Gaocun, Aishan, and Lijin stations, respectively. Time lag correction is proven to be crucial when establishing the relationship between the daily streamflows in the LYR and those at Xiaolangdi station. Further analysis reveals that the travel distance of streamflow is the dominant factor determining the lag time, with a time lag coefficient of 0.57 days per hundred kilometers. It is expected that the findings in this study could offer a fundamental basis for decision-makers in water resource management. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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21 pages, 4827 KiB

Open AccessArticle

Ecological Flow Analysis through an Ecohydraulic-Based Catchment Scale Approach

by Mahdi Sedighkia and Bithin Datta

Water 2024, 16(1), 59; https://doi.org/10.3390/w16010059 - 23 Dec 2023

Viewed by 709

Abstract

Ecological flow regime analysis through developing a novel ecohydraulic optimization method is the objective of this study in which three components are linked. Hydrological analysis is the first component in which average monthly flow is assessed in different hydrological conditions by applying a drought index in the selected control points or representative reaches in the river basin. Another component is the ecological model in which field ecological studies are used for selecting the target species, and habitat loss was modelled through the fuzzy method. The outputs of the hydrological analysis and hydraulic habitat simulation were then applied in the structure of the optimization model in which minimizing ecological impacts and water supply loss were defined as the purposes. Different evolutionary algorithms were used in the optimization process. A decision-making system was utilized to finalize ecological flow by selecting the privileged algorithm. According to the outputs, the proposed method can mitigate ecological impacts and water supply losses simultaneously. Either particle swarm optimization or differential evolution algorithm is the best approach for ecological flow in this research work. The outputs of optimization indicated that the reliability of the water supply in dry years is less than 32%, while it is more than 80% in wet years, which means that changing the hydrological condition will increase the portion of ecological flow regime significantly. In other words, the reliability of the water supply can be reduced by more than 50%. Hence, using other water resources such as groundwater is necessary in dry years in the study area. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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25 pages, 9660 KiB

Open AccessArticle

Comparative Assessment of Different Image Velocimetry Techniques for Measuring River Velocities Using Unmanned Aerial Vehicle Imagery

by Firnandino Wijaya, Wen-Cheng Liu, Suharyanto and Wei-Che Huang

Water 2023, 15(22), 3941; https://doi.org/10.3390/w15223941 - 12 Nov 2023

Viewed by 1191

Abstract

The accurate measurement of river velocity is essential due to its multifaceted significance. In response to this demand, remote measurement techniques have emerged, including large-scale particle image velocimetry (LSPIV), which can be implemented through cameras or unmanned aerial vehicles (UAVs). This study conducted water surface velocity measurements in the Xihu River, situated in Miaoli County, Taiwan. These measurements were subjected to analysis using five distinct algorithms (PIVlab, Fudaa-LSPIV, OpenPIV, KLT-IV, and STIV) and were compared with surface velocity radar (SVR) results. In the quest for identifying the optimal parameter configuration, it was found that an IA size of 32 pixels × 32 pixels, an image acquisition frequency of 12 frames per second (fps), and a pixel size of 20.5 mm/pixel consistently yielded the lowest values for mean error (ME) and root mean squared error (RMSE) in the performance of Fudaa-LSPIV. Among these algorithms, Fudaa-LSPIV consistently demonstrated the lowest mean error (ME) and root mean squared error (RMSE) values. Additionally, it exhibited the highest coefficient of determination (R² = 0.8053). Subsequent investigations employing Fudaa-LSPIV delved into the impact of various water surface velocity calculation parameters. These experiments revealed that alterations in the size of the interrogation area (IA), image acquisition frequency, and pixel size significantly influenced water surface velocity. This parameter set was subsequently employed in an experiment exploring the incorporation of artificial particles in image velocimetry analysis. The results indicated that the introduction of artificial particles had a discernible impact on the calculation of surface water velocity. Inclusion of these artificial particles enhanced the capability of Fudaa-LSPIV to detect patterns on the water surface. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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22 pages, 11528 KiB

Open AccessArticle

Flow Measurement Methods in Small Tributaries of the Teles Pires River, Southern of the Amazon Hydrological Region

by Daniela Roberta Borella, Rhavel Salviano Dias Paulista, Marco Aurélio Barbosa Alves, Charles Campoe Martim, Célio Jacinto da Silva, Frederico Terra de Almeida and Adilson Pacheco de Souza

Water 2023, 15(21), 3811; https://doi.org/10.3390/w15213811 - 31 Oct 2023

Viewed by 878

Abstract

The intensification of conflicts associated with the use of water in the transition region of the Cerrado and Amazon biomes caused by population and economic growth, combined with the interest in generating energy from hydroelectric plants, raise the need to quantify the surface water availability of rivers contributing with different drainage areas. The present study estimated and compared in loco measurements of liquid flow (Q_L) and the depth of rivers in the Teles Pires river basin by reference methods (MLN-7 hydrometric windlass and metal rod/winch) and by Acoustic Current Profiler by Doppler Effect (ADCP RiverRay), in this last method the uncertainty estimate of the total measurement time by ADCP was evaluated. Field measurements were carried out at monthly intervals between March 2020 and October 2021, seeking to represent the water seasonality and depth and Q_L variations in the cross-sections of the Caiabi 1 and 2, Celeste, Preto and Renato rivers. The evaluated rivers had a net flow between 3.48 and 60.78 m³ s⁻¹ by the windlass and between 2.66 and 54.30 m³ s⁻¹ by the ADCP, while the depths obtained were from 0.17 to 6.34 m by the rod/winch and from 0.65 to 6.20 m by the ADCP. The methods resulted in similar measurements of net flow and depth in each of the cross-sections, and the statistical performance of the linear regression model was satisfactory with a Willmott concordance index of 0.9977 and 0.9819 for estimates of Q_L and of the depth of the cross-sections, respectively. The ADCP accurately measured the net discharge and depth in shallow (up to 6.5 m) cross-sections of the Teles Pires River relative to the reference method. Determining the total measurement time and pairs of transects to obtain accurate Q_L by ADCP depends on the hydraulic characteristics of the watercourses. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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30 pages, 8930 KiB

Open AccessArticle

Assessment of Hydrological Response to Climatic Variables over the Hindu Kush Mountains, South Asia

by Muhammad Umer Masood, Saif Haider, Muhammad Rashid, Waqar Naseer, Chaitanya B. Pande, Bojan Đurin, Fahad Alshehri and Ismail Elkhrachy

Water 2023, 15(20), 3606; https://doi.org/10.3390/w15203606 - 15 Oct 2023

Cited by 1 | Viewed by 1389

Abstract

The impact of climate extremes, such as heat waves and extreme rainfall, can cause harvest failures, flooding, and droughts that ultimately threaten global food security, harming the region’s economy. Fluctuations in streamflow indicate the sensitivity of streamflow responding to extreme precipitation events and other climatic variables (temperature extremes) that play a significant role in its generation. Pakistan is also considered one of the climate change hotspot regions in the world. The devastating impacts have often occurred in recent decades due to an excess or shortage of streamflow, majorly generated from the Upper Indus Basin (UIB). To better understand climate extremes’ impact on streamflow, this study examined climate extremes and streamflow (Q) changes for three decades: 1990–1999, 2000–2009, and 2010–2019. Observed streamflow and meteorological data from nine sub-catchments across all climatic zones of the UIB were analyzed using RGui (R language coding program) and partial least squares regression (PLSR). Climatic variables were estimated, including precipitation extremes, temperature extremes, and potential evapotranspiration. The Mann–Kendal test was applied to the climatic indices, revealing that precipitation increased during the last 30 years, while maximum and minimum temperatures during the summer months decreased in the Karakoram region from 1990 to 2019. The spatiotemporal trend of consecutive dry days (CDD) indicated a more increasing tendency from 1990 to 2019, compared to the consecutive wet days (CWD), which showed a decreasing trend. PLSR was applied to assess the relation between climatic variables (extreme P, T indices, and evapotranspiration). It was found that the dominant climatic variables controlling annual streamflow include the r95p (very wet days) and R25mm (heavy precipitation days), maximum precipitation event amount, CWD, PRCPTOT (annual total precipitation), and RX5 (maximum five-day precipitation). The TXn (Min Tmax) and Tmax mean (average maximum temperature) dominate streamflow variables. Moreover, the impact of evapotranspiration (ET) on variations in streamflow is more pronounced in arid catchments. Precipitation is the predominant factor influencing streamflow generation in the UIB, followed by temperature. From streamflow quantification, it was found that climate-driven annual streamflow decreased during 1999–2019 in comparison to 1990–1999, with an increase in a few catchments like Kalam, which increased by about 3.94% from 2000 to 2010 and 10.30% from 2010 to 2019, and Shigar, which increased by 0.48% from 2000 to 2009 and 37.37% from 2010 to 2019 concerning 1990–1999. These variations were due to changes in these climatic parameters. The PLSR approach enables the identification of linkages between climatic variables and streamflow variability and the prediction of climate-driven floods. This study contributes to an enhanced identification and hydroclimatological trends and projections. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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26 pages, 11608 KiB

Open AccessArticle

Assessment of Ground Water Quality of Lucknow City under GIS Framework Using Water Quality Index (WQI)

by Nazmu Saqib, Praveen Kumar Rai, Shruti Kanga, Deepak Kumar, Bojan Đurin and Suraj Kumar Singh

Water 2023, 15(17), 3048; https://doi.org/10.3390/w15173048 - 25 Aug 2023

Cited by 1 | Viewed by 3909

Abstract

Continuous groundwater quality monitoring is crucial for ensuring safe drinking and irrigation by mitigating risks from geochemical contaminants through appropriate treatment methods. Therefore, the primary objective of this study was to assess the suitability of groundwater collected from Lucknow, India, for both drinking and irrigation. Forty samples were collected from different sites within the study area to evaluate groundwater quality. Various parameters such as pH, turbidity, total dissolved solids (TDS), chlorides (

{C l}^{-}

), total alkalinity, total hardness, sulphate (

{S O}_{4}^{2 -}

), nitrate (

{N O}_{3}^{-}

), fluorides (

F^{-}

), iron (Fe), arsenic (As), magnesium (

{M g}^{2 +}

), and calcium (

{C a}^{2 +}

) were analyzed. The weighted arithmetic water quality index (WAWQI), a vital rating system representing overall water quality, was employed to classify the water into different categories, such as very good, good, moderate, poor, and unfit for drinking. This classification is invaluable for public awareness and decision-making to make informed decisions regarding effective management, treatment, and sustainable societal development on a broader scale. A correlation matrix was generated and analyzed to observe correlations between the various parameters. Additionally, spatial distribution maps for the analyzed parameters and WQI were prepared using the inverse distance weighted (IDW) method. The study found that WQI values in the area ranged from 2.64 to 168.68, indicating good water quality in most places except for the Kukrail region, where the water quality is unfit for drinking purposes. The water quality map shows that 86% of the area falls under the very good category, 14.63% under good to moderate quality, and 0.37% is categorized as unfit for drinking. Consequently, the findings suggest that the groundwater in the studied area is safe and suitable for drinking and irrigation purposes. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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18 pages, 8978 KiB

Open AccessArticle

Real-Time Control Operation Method of Water Diversion Project Based on River Diversion Disturbance

by Pengyu Jin, Chao Wang, Jiahui Sun, Xiaohui Lei and Hao Wang

Water 2023, 15(15), 2793; https://doi.org/10.3390/w15152793 - 02 Aug 2023

Viewed by 831

Abstract

Changes in water diversion flow are the major disturbance sources in the daily operation of water diversion projects. Ensuring efficient and safe project operation while dealing with different degrees of water diversion disturbance is crucial for real-time control operation. Based on the historical water diversion projects in China and abroad, this study constructs the water diversion disturbance conditions, selects the typical disturbance lines, and constructs the control objectives for different water diversion disturbance lines. The discrete state space equation of the multi-channel pool integral time-delay model is introduced and used as the system prediction model. Concurrently, the simulation results of the river channel hydrodynamic model are used to correct the system state. The model predictive control algorithm is established according to the objective functions of different typical water distribution disturbance lines, and the control strategy of the control gate and pump station along the water diversion project is formulated to assist in the decision making of the project scheduling operation scheme. The proposed method can better cope with different degrees of river diversion disturbance, compensate for the loss of control performance caused by the low accuracy of the generalized model simulation, and improve water level control and sluice regulation. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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20 pages, 18038 KiB

Open AccessArticle

Decoding Chambal River Shoreline Transformations: A Comprehensive Analysis Using Remote Sensing, GIS, and DSAS

by Saurabh Singh, Gowhar Meraj, Pankaj Kumar, Suraj Kumar Singh, Shruti Kanga, Brian Alan Johnson, Deepak Kumar Prajapat, Jatan Debnath and Dhrubajyoti Sahariah

Water 2023, 15(9), 1793; https://doi.org/10.3390/w15091793 - 07 May 2023

Cited by 7 | Viewed by 3638

Abstract

Illegal sand mining has been identified as a significant cause of harm to riverbanks, as it leads to excessive removal of sand from rivers and negatively impacts river shorelines. This investigation aimed to identify instances of shoreline erosion and accretion at illegal sand mining sites along the Chambal River. These sites were selected based on a report submitted by the Director of the National Chambal Sanctuary (NCS) to the National Green Tribunal (NGT) of India. The digital shoreline analysis system (DSAS v5.1) was used during the elapsed period from 1990 to 2020. Three statistical parameters used in DSAS—the shoreline change envelope (SCE), endpoint rate (EPR), and net shoreline movement (NSM)—quantify the rates of shoreline changes in the form of erosion and accretion patterns. To carry out this study, Landsat imagery data (T.M., ETM+, and OLI) and Sentinel-2A/MSI from 1990 to 2020 were used to analyze river shoreline erosion and accretion. The normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) were used to detect riverbanks in satellite images. The investigation results indicated that erosion was observed at all illegal mining sites, with the highest erosion rate of 1.26 m/year at the Sewarpali site. On the other hand, the highest accretion was identified at the Chandilpura site, with a rate of 0.63 m/year. We observed significant changes in river shorelines at illegal mining and unmined sites. Erosion and accretion at unmined sites are recorded at −0.18 m/year and 0.19 m/year, respectively, which are minor compared to mining sites. This study’s findings on the effects of illegal sand mining on river shorelines will be helpful in the sustainable management and conservation of river ecosystems. These results can also help to develop and implement river sand mining policies that protect river ecosystems from the long-term effects of illegal sand mining. Full article

(This article belongs to the Special Issue Advances in Hydrology: Flow and Velocity Analysis in Rivers)

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