bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Simulations of 2D Hydraulic Jumps by a Parallel SPH Model
Authors: Lin Jinbo , Mao Hongfei , Ding Weiye , Jia Baozhu , Pan Xinxiang , Jin Sheng
Published: September 2021

Hydraulic jumps are a rapid transition from supercritical to subcritical flow and generally occur in rivers or spillways. Owing to the high energy dissipation rate, hydraulic jumps are widely applied as energy dissipators in hydraulic projects. To achieve efficient and accurate simulations of 2D hydraulic jumps in open channels, a parallel Weakly Compressible Smoothed Particle Hydrodynamics model (WCSPH) with Shepard Density filter was established in this study. The acceleration of the model was obtained by OpenMP to reduce execution time. To further reduce execution time, a suitable and efficient scheduling strategy was selected for the parallel numerical model by comparing parallel speed-ups under different scheduling strategies in OpenMP. Following this, two test cases of uniform flow in open channels and hydraulic jumps with different inflow conditions were investigated to validate the model. The comparison of the water depth and velocity fields between the numerical results and the analytical solution generally showed good agreement, although there was a minor discrepancy in conjugate water depths. The numerical results showed free surface undulation with decreasing amplitude, which is more consistent with physical reality, with a low inflow Froude number. Simultaneously, the Shepard filter was able to smooth the pressure fields of the hydraulic jumps with a high inflow Froude number. Moreover, the parallel speed-up was generally able to reach theoretical maximum acceleration by analyzing the performance of the model according to different particle numbers.
Assessment of Land Use/Land Cover Change and Morphometric Parameters in the Keta Lagoon Complex Ramsar Site, Ghana
Authors: Duku Eric , Mattah Precious Agbeko Dzorgbe , Angnuureng Donatus Bapentire
Published: September 2021

The rapid urbanization, industrialization, agricultural activities, and increasing trend of some natural hazards, such as climate change, particularly in coastal areas, necessitate the continual assessment of critical but fragile ecosystems like that of the Keta Lagoon Complex Ramsar Site (KLCRS). This productive ecosystem in Ghana faces serious threats from intensive exploitation, physical modification, changes in water regime, and water pollution. The current study employed geospatial and intensity analysis to assess the pattern of land use/land cover (LULC) change for almost the past three decades and morphometric parameters of the KLCRS landscape. Landsat Satellite images for 1991, 2007, and 2020 were acquired to uncover the pattern of LULC change, while morphometric changes were assessed using global Advance Space Thermal Emission and Radiometer (ASTER) digital elevation model (DEM) data and the spatial analyst tools in GIS software. The result established that the acceleration of land transformation was intensive between 2007 and 2020, which could be linked to population growth and increased socio-economic activities. There was a net gross gain of built-up that originated largely from the conversion of marsh, dense vegetation, and cultivated land. Prior to this period, cultivated land recorded net gain (125.51 km2) between 1991 and 2007, whereas dense vegetation and marshland showed a net loss of 151.37 km2 and 2.44 km2, respectively. The gain of cultivated land largely targeted marshland in both time intervals. The construction of saltpans contributed largely to the small increase in water extent. The morphometric analysis revealed the groundwater potential of the KLCRS. The low-lying nature of the landscape makes the area susceptible to coastal flooding. The trend of the observed changes could invariably affect the ecological integrity of the landscape, hence suggesting the need for immediate preparation and implementation of marine and coastal spatial plans by relevant stakeholders.
Evaluation of ERA5 Precipitation Accuracy Based on Various Time Scales over Iran during 2000–2018
Authors: Izadi Naser , Karakani Elaheh Ghasemi , Saadatabadi Abbas Ranjbar , Shamsipour Aliakbar , Fattahi Ebrahim , Habibi Maral
Published: September 2021

In regional studies, reanalysis datasets can extend precipitation time series with insufficient observations. In the present study, the ERA5 precipitation dataset was compared to observational datasets from meteorological stations in nine different precipitation zones of Iran (0.125° × 0.125° grid box) for the period 2000–2018, and measurement criteria and skill detection criteria were applied to analyze the datasets. The results of the daily analysis revealed that the correlation between ERA5 and observed precipitation were larger than 0.5 at 90% of stations. Also, The daily standard relative bias indicated that precipitation was overestimated in zone 6. As detection criteria, the frequency bias index (FBI) and proportion correct (PC) showed that the ERA5 data could capture daily precipitation events. Correlation confidence comparisons between the ERA5 and observational time series at daily, monthly, and seasonal scales revealed that the correlation confidence was higher at monthly and seasonal scales. The standard relative bias results at monthly and seasonal scales followed the daily relative bias results, and most of the ERA5 underestimations during the summer belonged to zone 1 in the coastal area of the Caspian Sea with convective precipitation. In addition, some complex mountainous regions were associated with overestimated precipitation, especially in northwest Iran (zone 6) in different time scales.
Assessment of Ensemble Models for Groundwater Potential Modeling and Prediction in a Karst Watershed
Authors: Farzin Mohsen , Avand Mohammadtaghi , Ahmadzadeh Hassan , Zelenakova Martina , Tiefenbacher John P.
Published: September 2021

Due to numerous droughts in recent years, the amount of surface water in arid and semi-arid regions has decreased significantly, so reliance on groundwater to meet local and regional demands has increased. The Kabgian watershed is a karst watershed in southwestern Iran that provides a significant proportion of drinking and agriculture water supplies in the area. This study identified areas with karst groundwater potential using a combination of machine learning and statistical models, including entropy-SVM-LN, entropy-SVM-SG, and entropy-SVM-RBF. To do this, 384 karst springs were identified and mapped. Sixteen factors that are related to karst potential were identified from a review of the literature, and these were compiled for the study area. The 384 locations were randomly separated into two categories for training (269 location) and validation (115 location) datasets to be used in the modeling process. The ROC curve was used to evaluate the modeling results. The models used, in general, were good at determining the location of karst groundwater potential. The evaluation showed that the E-SVM-RBF model had an area under the curve of 0.92, indicating that it was most accurate estimator of groundwater potential among the ensemble models. Evaluation of the relative importance of each of the 16 factors revealed that land use, a vector ruggedness measure, curvature, and topography roughness index were the most important explainers of the presence of karst groundwater in the study area. It was also found that the factors affecting the presence of karst springs are significantly different from non-karst springs.
Improvement of Downstream Flow by Modifying SWAT Reservoir Operation Considering Irrigation Water and Environmental Flow from Agricultural Reservoirs in South Korea
Authors: Kim Jinuk , Lee Jiwan , Park Jongyoon , Kim Sehoon , Kim Seongjoon
Published: September 2021

This study aims to develop a reservoir operation rule adding downstream environmental flow release (EFR) to the exclusive use of irrigation water supply (IWS) from agricultural reservoirs through canals to rice paddy areas. A reservoir operation option was added in the Soil and Water Assessment Tool (SWAT) to handle both EFR and IWS. For a 366.5 km2 watershed including three agricultural reservoirs and a rice paddy irrigation area of 4744.7 ha, the SWAT was calibrated and validated using 21 years (1998–2018) of daily reservoir water levels and downstream flow data at Gongdo (GD) station. For reservoir water level and streamflow, the average root means square error (RMSE) ranged from 19.70 mm to 19.54 mm, and the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) had no effect on the improved SWAT. By applying the new reservoir option, the EFR amount for a day was controlled by keeping the reservoir water level up in order to ensure that the IWS was definitely satisfied in any case. The downstream mean wet streamflow (Q95) decreased to 5.70 m3/sec from 5.71 m3/sec and the mean minimum flow (Q355) increased to 1.05 m3/sec from 0.94 m3/sec. Through the development of a SWAT reservoir operation module that satisfies multiple water supply needs such as IWR and EFR, it is possible to manage agricultural water in the irrigation period and control the environmental flow in non-irrigation periods. This study provides useful information to evaluate and understand the future impacts of various changes in climate and environmental flows at other sites.
Intra-Body Variations of Stable Isotope Ratios (δ13C, δ15N) and Influence of Storage Methods in Aquatic and Post-Aquatic Stages of the Common Toad, Bufo bufo
Authors: Reshetnikov Andrey N. , Korobushkin Daniil I.
Published: September 2021

Isotopic signatures of carbon and nitrogen are widely used for analysis of the structure of food webs in aquatic ecosystems. The study of animals raises a number of methodological questions, including choice of representative tissues and organs for sampling as well as storage of the studied organisms. Furthermore, the impacts of preservation methods can be tissue-specific, age-specific, and even taxon-specific; thus, studies of these impacts on particular taxa are necessary. We focused on the C and N isotope composition of the common toad (Bufo bufo), one of the most widespread European anuran amphibians. We hypothesized that its different tissues and organs may vary in isotopic composition, and ethanol and freezing may have different effects on isotopic values. Our results showed that both “tissue” and “storage method” factors significantly affected the δ13C values of tadpoles and postmetamorphic juveniles, whereas only the “tissue” factor had a significant effect on the δ15N values. The two stages, tadpoles and postmetamorphs, should be analyzed separately despite the brief postmetamorphic period of the juveniles. The skin, legs, muscles, and tail in tadpoles and legs, muscles and heart in juveniles can be used for δ13C and δ15N analysis regardless of the method of storage. The results will serve for the optimization of future study designs in isotopic ecology.
Effect of Periodic Winter Irrigation on Salt Distribution Characteristics and Cotton Yield in Drip Irrigation under Plastic Film in Xinjiang
Authors: Feng Jinping , Liu Hongguang , Wang Gang , Tian Rumeng , Cao Minghai , Bai Zhentao , He Tianming
Published: September 2021

Winter irrigation is an effective means of salt leaching, but the long-term effect on salinity is unclear. In 2008–2019, three different soil types of farmlands were selected as the study area by drip irrigation under film mulch combined with periodic winter irrigation in the non-growth period. The salinity of 0–150 cm as well as the survival rate and yield of cotton in the non-growth and growth periods were monitored, respectively. The mass fraction of soil salt decreased rapidly under winter irrigation, and then, the salt content in each observation layer increased with years of cultivation. After 10 years of application, the soil salt content basically stabilized at a low level. In 2008, the salinity of the 0–150 cm observation layer of loamy clay, loam, and sandy loam varied within 6–60, 10–65, and 4–22 g·kg−1; after four winter irrigations in 2019, corresponding values dropped below 5.74, 3, and 4.76 g·kg−1, respectively. The salinity returns rate of the different observation layers all exceeded 40%. The desalination rate of the different soils after four winter irrigations all exceeded 63.52%. Cotton survival rate and yield in different soils were directly proportional to each other. After the second winter irrigation, the survival rates on the different soils all exceeded 60%. The results of this study can provide technical support for the sustainable development of different types of soil, farmers’ income increase, and salinization land improvement.
Improving Efficiency of Hydrological Prediction Based on Meteorological Classification: A Case Study of GR4J Model
Authors: Wei Xiaojing , Guo Shenglian , Xiong Lihua
Published: September 2021

Distribution of hydrological parameters is varied under contrasting meteorological conditions. However, how to determine the most suitable parameters on a predefined meteorological condition is challenging. To address this issue, a hydrological prediction method based on meteorological classification is established, which is conducted by using the standardized runoff index (SRI) value to identify three categories, i.e., the dry, normal and wet years. Three different simulation schemes are then adopted for these categories. In each category, two years hydrological data with similar SRI values are divided into a set; then, one-year data are used as the calibration period while the other year is for testing. The Génie Rural à 4 paramètres Journalier (GR4J) rainfall-runoff model, with four parameters x1, x2, x3 and x4, was selected as an experimental model. The generalized likelihood uncertainty estimation (GLUE) method is used to avoid parameter equifinality. Three basins in Australia were used as case studies. As expected, the results show that the distribution of the four parameters of GR4J model is significantly different under varied meteorological conditions. The prediction efficiency in the testing period based on meteorological classification is greater than that of the traditional model under all meteorological conditions. It is indicated that the rainfall-runoff model should be calibrated with a similar SRI year rather than all years. This study provides a new method to improve efficiency of hydrological prediction for the basin.
Machine Learning Models Applied to Manage the Operation of a Simple SWRO Desalination Plant and Its Application in Marine Vessels
Authors: Marichal Plasencia Graciliano Nicolás , Camacho-Espino Jorge , Ávila Prats Deivis , Peñate Suárez Baltasar
Published: September 2021

In this work, two machine learning techniques, specifically decision trees (DTs) and support vector machines (SVMs), were applied to optimize the performance of a seawater reverse osmosis (SWRO) desalination plant with a capacity of 100 m3 per day. The input variables to the system were seawater pH, seawater conductivity, and three requirements: permeate flow rate, permeate conductivity, and total energy consumed by the desalination plant. These requirements were decided based on a cost function that prioritizes the water needs in a vessel and the maximum possible energy savings. The intelligent system modifies the actuators of the plant: feed flow rate control and high-pressure pump (HPP) operating pressure. This tool is proposed for the optimal use of desalination plants in marine vessels. Although both machine learning techniques output satisfactory results, it was concluded that the DTs technique (HPP pressure: root mean square error (RMSE) = 0.0104; feed flow rate: RMSE = 0.0196) is more accurate than SVMs (HPP pressure: RMSE = 0.0918; feed flow rate: RMSE = 0.0198) based on the metrics used. The final objective of the paper is to extrapolate the implementation of this smart system to other shipboard desalination plants and optimize their performance.
Spoiled for Choice during Cold Season? Habitat Use and Potential Impacts of the Invasive Silurus glanis L. in a Deep, Large, and Oligotrophic Lake (Lake Maggiore, North Italy)
Authors: De Santis Vanessa , Volta Pietro
Published: September 2021

The ecological features of invasive alien species are crucial for their effective management. However, they are often lacking in newly invaded ecosystems. This is the case of the European catfish Silurus glanis L. in Lake Maggiore, where the species is present since 1990, but no scientific information is available on its ecology. To start filling this knowledge gap, 236 catfish (67 cm to 150 cm of total length) were collected, measured, and dissected for stomach content analyses from three localities and in two habitats (littoral vs. pelagic) in late autumn/early winter. The NPUE and BPUE (individuals (N) and biomass (B, in grams) per unit effort (m2), respectively) of catfish were generally higher in littoral (NPUE > 0.01; BPUE > 96) than in pelagic habitats (NPUE < 0.009; BPUE < 114), but the catfish had, on average, larger sizes in pelagic habitats. Overall, 581 individual prey items were recorded, belonging to 12 taxa. Pelagic catfish specialized their diet exclusively on three prey fish (coregonids, shad, and roach), whilst the diet of littoral catfish was more variable and dominated by crayfish, perch, and roach. These results highlighted for the first time the interaction of larger catfish with the lake’s pelagic food web, and thus possible consequences are discussed, including the potential contrasting role S. glanis may have for the lake’s fishery.
Spatiotemporal Correlation Feature Spaces to Support Anomaly Detection in Water Distribution Networks
Authors: Gomes Susana C. , Vinga Susana , Henriques Rui
Published: September 2021

Monitoring disruptions to water distribution dynamics are essential to detect leakages, signal fraudlent and deviant consumptions, amongst other events of interest. State-of-the-art methods to detect anomalous behavior from flowarate and pressure signal show limited degrees of success as they generally neglect the simultaneously rich spatial and temporal content of signals produced by the multiple sensors placed at different locations of a water distribution network (WDN). This work shows that it is possible to (1) describe the dynamics of a WDN through spatiotemporal correlation analysis of pressure and volumetric flowrate sensors, and (2) analyze disruptions on the expected correlation to detect burst leakage dynamics and additional deviant phenomena. Results gathered from Portuguese WDNs reveal that the proposed shift from raw signal views into correlation-based views offers a simplistic and more robust means to handle the irregularity of consumption patterns and the heterogeneity of leakage profiles (both in terms of burst volume and location). We further show that the disruption caused by leakages can be detected shortly after the burst, highlighting the actionability of the proposed correlation-based principles for anomaly detection in heterogeneous and georeferenced time series. The computational approach is provided as an open-source tool available at GitHub.
Comparison of Seasonal Flow Rate Change Indices Downstream of Three Types of Dams in Southern Quebec (Canada)
Authors: Delisle Francis , Assani Ali Arkamose
Published: September 2021

The objective of this study is to use two hydrological indices (coefficients of variation and immoderation) to analyze the impacts of dam management methods on seasonal daily flow rate change downstream of three dams: Manouane (diversion-type management method), Ouareau (natural-type management method) and Matawin (inversion-type management method). The results show that this change is far greater downstream of the Matawin dam (characterized by an inversion-type management method) than downstream of the two other dams. Moreover, downstream of the Matawin dam, this daily flow rate change increases significantly over time, while decreasing downstream of the two other dams and in natural rivers. Lastly, this change is better correlated with climate downstream of the Ouareau dam than downstream of the two other dams. It is positively correlated with winter and spring temperatures as well as summer and fall rain. Contrary commonly accepted hypothesis, this study shows that the impacts of dams generally result in an increase of the seasonal flow rate change in Quebec.
A Spatial Structure Variable Approach to Characterize Storm Events for Coastal Flood Hazard Assessment
Authors: Favaretto Chiara , Martinelli Luca , Ruol Piero
Published: September 2021

Over the last decades, the evaluation of hazards and risks associated with coastal flooding has become increasingly more important in order to protect population and assets. The general purpose of this research was to assess reliable coastal flooding hazard maps due to overflow and wave overtopping. This paper addresses the problem of defining credible joint statistics of significant wave heights Hs and water levels ζ, focusing on the selection of the sample pair that characterizes each sea storm, to evaluate the occurrence probability of extreme events. The pair is selected maximizing a spatial structure variable, i.e., a linear combination of Hs and ζ, specific to each point of the area at risk. The structure variable is defined by the sensitivity of the flooding process to Hs and ζ, as found by analyzing a set of inundation maps produced through a Simplified Shallow-Water numerical model (SSW). The proposed methodology is applied to a coastal stretch in the Venetian littoral (Italy), by means of a 30 year-long time series recorded at the “Acqua Alta” oceanographic research tower, located in the Northern Adriatic Sea in front of the Venetian lagoon. The critical combination of Hs and ζ forming the structure variable is presented in a map, and it can be related to the topography and the presence of mitigation measures. The return period associated with the two recent large storms that occurred in this area in 2018 and 2019 is also investigated. The proposed procedure gives credible occurrence probabilities for these events, whereas other approaches would consider them extremely unlikely.
Application of Tea Polyphenols and Their Effects on Ultrafiltration Effluent Disinfection and Microbial Risk
Authors: Feng Cuimin , Wei Tong , Qing Shan , Han Fang , Tao Xingcheng
Published: September 2021

To reduce the risk of by-products from traditional disinfection technology and to ensure safe water quality, tea polyphenols (TP) were used as disinfectants after the ultrafiltration (UF) process. The disinfectant effect of TP was tested on the total number of bacteria and changes in bacterial community structure, and pathogen virulence factors were detected by Illumina’s high-throughput sequencing technology. The results showed that the recommended dosage of TP for water treatment after UF was 5 mg/L, which can effectively inhibit bacterial growth and maintain the disinfectant effect for up to 48 h later. In the disinfection process, the degradation of the tea polyphenols concentration was fitted to the equation of the second order reaction kinetics. The lower the initial concentration and the higher the reaction temperature, the faster the TP decay. The metagenomic analysis of the microorganisms indicated that disinfection with tea polyphenols reduced the diversity of microorganisms in the water and altered the structure of the bacterial community. The existence of tea polyphenols also significantly inhibited the growth of potential common Gram-negative pathogens, especially Mycobacterium. TP disinfectant can also reduce the diversity and abundance of pathogenic bacterial virulence factors and improve biological safety in drinking water.
Turbulent Flow through Random Vegetation on a Rough Bed
Authors: Coscarella Francesco , Penna Nadia , Ferrante Aldo Pedro , Gualtieri Paola , Gaudio Roberto
Published: September 2021

River vegetation radically modifies the flow field and turbulence characteristics. To analyze the vegetation effects on the flow, most scientific studies are based on laboratory tests or numerical simulations with vegetation stems on smooth beds. Nevertheless, in this manner, the effects of bed sediments are neglected. The aim of this paper is to experimentally investigate the effects of bed sediments in a vegetated channel and, in consideration of that, comparative experiments of velocity measures, performed with an Acoustic Doppler Velocimeter (ADV) profiler, were carried out in a laboratory flume with different uniform bed sediment sizes and the same pattern of randomly arranged emergent rigid vegetation. To better comprehend the time-averaged flow conditions, the time-averaged velocity was explored. Subsequently, the analysis was focused on the energetic characteristics of the flow field with the determination of the Turbulent Kinetic Energy (TKE) and its components, as well as of the energy spectra of the velocity components immediately downstream of a vegetation element. The results show that both the vegetation and bed roughness surface deeply affect the turbulence characteristics. Furthermore, it was revealed that the roughness influence becomes predominant as the grain size becomes larger.
Nature-Based Solutions for Agriculture in Circular Cities: Challenges, Gaps, and Opportunities
Authors: Canet-Martí Alba , Pineda-Martos Rocío , Junge Ranka , Bohn Katrin , Paço Teresa A. , Delgado Cecilia , Alenčikienė Gitana , Skar Siv Lene Gangenes , Baganz Gösta F. M.
Published: September 2021

Urban agriculture (UA) plays a key role in the circular metabolism of cities, as it can use water resources, nutrients, and other materials recovered from streams that currently leave the city as solid waste or as wastewater to produce new food and biomass. The ecosystem services of urban green spaces and infrastructures and the productivity of specific urban agricultural technologies have been discussed in literature. However, the understanding of input and output (I/O) streams of different nature-based solutions (NBS) is not yet sufficient to identify the challenges and opportunities they offer for strengthening circularity in UA. We propose a series of agriculture NBS, which, implemented in cities, would address circularity challenges in different urban spaces. To identify the challenges, gaps, and opportunities related to the enhancement of resources management of agriculture NBS, we evaluated NBS units, interventions, and supporting units, and analyzed I/O streams as links of urban circularity. A broader understanding of the food-related urban streams is important to recover resources and adapt the distribution system accordingly. As a result, we pinpointed the gaps that hinder the development of UA as a potential opportunity within the framework of the Circular City.
Integrated Water Quality Management Model for the Rural Transboundary River Basin—A Case Study of the Sutla/Sotla River
Authors: Ćosić-Flajsig Gorana , Karleuša Barbara , Glavan Matjaž
Published: September 2021

The intensive use of soil and water resources results in a disbalance between the environmental and economic objectives of the river basin. The water quality management model supports good water status, especially downstream of dams and reservoirs, as in the case of the Sutla/Sotla river basin. This research aims to develop a new, improved integrated water quality management model of rural transboundary basins to achieve environmental objectives and protection of the Natura 2000 sites. The model uses river basin pressure analysis to assess the effects of climate and hydrological extreme impacts, and a programme of basic and supplementary measures. The impact assessment of BASE MODEL, PAST, and FUTURE scenarios was modelled using the soil and water assessment tool (SWAT) based on land use, climate and hydrological data, climate change, presence or lack of a reservoir, and municipal wastewater and agriculture measures. Eight future climate change scenarios were obtained with optimistic (RCP4.5) and pessimistic (RCP8.5) forecasts for two periods (2020–2050 and 2070–2100), both with and without a reservoir. The model shows that the most significant impacts on the waterbody come from the nutrients and sediment hotspots, also shows the risk of not achieving good water status, and water eutrophication risk. The modelled average annual increase in sediment is from 4 to 25% and in total N from 1 to 8%, while the change in total P is from −5 to 6%. The conducted analysis provides a base for the selection of tailor-made measures from the catalogue of the supplementary measures that will be outlined in future research.
Identification of Groundwater Potential Recharge Zones in Flinders Ranges, South Australia Using Remote Sensing, GIS, and MIF Techniques
Authors: Ahmed Alaa , Alrajhi Abdullah , Alquwaizany Abdulaziz S.
Published: September 2021

In Australia, water resource management is a major environmental, biological, and socio-economic issue, and will be an essential component of future development. The Hawker Area of the central Flinders Ranges, South Australia suffers from a lack of reliable data to help with water resource management and decision making. The present study aimed to delineate and assess groundwater recharge potential (GWRP) zones using an integration between the remote sensing (RS), geographic information system (GIS), and multi-influencing factors (MIF) approaches in the Hawker Area of the Flinders Ranges, South Australia. Many thematic layers such as lithology, drainage density, slope, and lineament density were established in a GIS environment for the purpose of identifying groundwater recharge potential zones. A knowledge base ranking from 1 to 5 was assigned to each individual thematic layer and its categories, depending on each layer’s importance to groundwater recharge potential zones. All of the thematic layers were integrated to create a combined groundwater potential map of the study area using weighting analysis in ArcGIS software. The groundwater potential zones were categorized into three classes, good, moderate, and low. The resulting zones were verified using available water data and showed a relative consistency with the interpretations. The findings of this study indicated that the most effective groundwater potential recharge zones are located where the lineament density is high, the drainage density is low, and the slope is gentle. The least effective areas for groundwater recharge are underlain by shale and siltstone. The results indicated that there were interrelationships between the groundwater recharge potential factors and the general hydrology characteristics scores of the catchment. MIF analysis using GIS mapping techniques proved to be a very useful tool in the evaluation of hydrogeological systems and could enable decision makers to evaluate, better manage, and protect a hydrogeological system using a single platform.
Experimental Analysis on the Use of Counterflow Jets as a System for the Stabilization of the Spatial Hydraulic Jump
Authors: Sharoonizadeh Shokoofeh , Ahadiyan Javad , Scorzini Anna Rita , Di Bacco Mario , Sajjadi Mohsen , Moghadam Manoochehr Fathi
Published: September 2021

This study presents an investigation on the use of submerged counterflow jets as a means for stabilizing the spatial hydraulic jump occurring in abruptly expanding channels. The characteristics of the flow downstream from the stilling basin and the main parameters influencing the effectiveness of the device in improving flow uniformity and reducing scouring potential are examined in laboratory tests, under several geometric configurations and hydraulic boundary conditions. The position within the stilling basin and the jet density (i.e., the number of orifices issuing the counterflow jets) were found to be important parameters influencing the performance of the device. Overall, the results indicate that this dissipation system has promising capabilities in forcing the transition from supercritical to subcritical flow, by significantly shortening the protection length needed to limit the phenomena of instability associated with spatial hydraulic jumps.
Enhancing Water Supply Resilience in a Tropical Island via a Socio-Hydrological Approach: A Case Study in Con Dao Island, Vietnam
Authors: Nguyen Duc Cong Hiep , Nguyen Duc Canh , Luu Thi Tang , Le Tan Cuong , Kumar Pankaj , Dasgupta Rajarshi , Nguyen Hong Quan
Published: September 2021

Socio-hydrological approaches are gaining momentum due to the importance of understanding the dynamics and co-evolution of water and human systems. Various socio-hydrological approaches have been developed to improve the adaptive capacity of local people to deal with water-related issues. In this study, a social-hydrological approach was developed to enhance the water supply resilience in Con Dao Island, Vietnam. We used a water-balance model, involving the Water Evaluation and Planning (WEAP) tool, to conduct a scenario-based evaluation of water demands. In doing so, we assessed the impacts of socio-economic development, such as population growth and climate change, on increasing water demand. The modelling results showed that the existing reservoirs—the main sources to recharge the groundwater (accounting for 56.92% in 2018 and 65.59% in 2030)—play a critical role in enhancing water supply resilience in the island, particularly during the dry season. In addition, future water shortages can be solved by investment in water supply infrastructures in combination with the use of alternative water sources, such as rainwater and desalinated seawater. The findings further indicate that while the local actors have a high awareness of the role of natural resources, they seem to neglect climate change. To meet the future water demands, we argue that upgrading and constructing new reservoirs, mobilizing resources for freshwater alternatives and investing in water supply facilities are among the most suitable roadmaps for the island. In addition, strengthening adaptive capacity, raising awareness and building professional capacity for both local people and officials are strongly recommended. The research concludes with a roadmap that envisages the integration of social capacity to address the complex interaction and co-evolution of the human–water system to foster water-supply resilience in the study area.
Analysis of the Influencing Factors of Drought Events Based on GRACE Data under Different Climatic Conditions: A Case Study in Mainland China
Authors: Cui Lilu , Zhang Cheng , Yao Chaolong , Luo Zhicai , Wang Xiaolong , Li Qiong
Published: September 2021

The occurrence of droughts has become more frequent, and their intensity has increased in mainland China. With the aim of better understanding the influence of climate background on drought events in this region, we analyzed the role of the drought-related factors and extreme climate in the formation of droughts by investigating the relationship between the drought severity index (denoted as GRACE-DSI) based on the terrestrial water storage changes (TWSCs) derived from Gravity Recovery and Climate Experiment (GRACE) time-variable gravity fields and drought-related factors/extreme climate. The results show that GRACE-DSI was consistent with the self-calibrating Palmer Drought Severity Index in mainland China, especially for the subtropical monsoon climate, with a correlation of 0.72. Precipitation (PPT) and evapotranspiration (ET) are the main factors causing drought events. However, they play different roles under different climate settings. The regions under temperate monsoon climate and subtropical monsoon climate were more impacted by PPT, while ET played a leading role in the regions under temperate continental climate and plateau mountain climate. Moreover, El Niño–Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) events mainly caused abnormalities in PPT and ET by affecting the strength of monsoons (East Asian and Indian monsoon) and regional highs (Subtropical High, Siberian High, Central Asian High, etc.). As a result, the various affected regions were prone to droughts during ENSO or NAO events, which disturbed the normal operation of atmospheric circulation in different ways. The results of this study are valuable in the efforts to understand the formation mechanism of drought events in mainland China.
Threats to Cultural Heritage Caused by the Global Sea Level Rise as a Result of the Global Warming
Authors: Ciski Mateusz , Rząsa Krzysztof
Published: September 2021

Climate change resulting from global warming has an increasing impact on Earth. The resulting sea level rise is starting to be noticed in some regions today, and based on projections, could have severe consequences in the future. These consequences would primarily be felt by residents of coastal areas, but through the potential for irreparable damage to cultural heritage sites, could be significant for the general public. The primary aim of the research undertaken in this article was to assess the threat to cultural heritage objects on the case study area of Tri-City, Poland. A review of available elevation data sources for their potential use in analyses of sea level changes was required. The selection of the optimal data source for the cultural heritage threat analysis of historic sites was carried out. The analyses were conducted for three scenarios, using ArcGIS Pro 2.7 software. A series of maps were thus prepared to show the threats to specific historic sites for various global sea level rise scenarios. Even with the slightest rise in sea level, monuments could be permanently lost. The authors point out that a lack of action to stop climate change could result not only in economic but also cultural losses.
TIEOF: Algorithm for Recovery of Missing Multidimensional Satellite Data on Water Bodies Based on Higher-Order Tensor Decompositions
Authors: Kulikov Leonid , Inkova Natalia , Cherniuk Daria , Teslyuk Anton , Namsaraev Zorigto
Published: September 2021

Satellite research methods are frequently used in observations of water bodies. One of the most important problems in satellite observations is the presence of missing data due to internal malfunction of satellite sensors and poor atmospheric conditions. We proceeded on the assumption that the use of data recovery methods based on spatial relationships in data can increase the recovery accuracy. In this paper, we present a method for missing data reconstruction from remote sensors. We refer our method to as Tensor Interpolating Empirical Orthogonal Functions (TIEOF). The method relies on the two-dimensional nature of sensor images and organizes the data into three-dimensional tensors. We use high-order tensor decomposition to interpolate missing data on chlorophyll a concentration in lake Baikal (Russia, Siberia). Using MODIS and SeaWiFS satellite data of lake Baikal we show that the observed improvement of TIEOF was 69% on average compared to the current state-of-the-art DINEOF algorithm measured in various preprocessing data scenarios including thresholding and different interpolating schemes.
Predicting Intent to Conserve Freshwater Resources Using the Theory of Planned Behavior (TPB)
Authors: Gibson Kristin E. , Lamm Alexa J. , Woosnam Kyle Maurice , Croom D. B.
Published: September 2021

Freshwater resources are being rapidly depleted by unsustainable human activities in the United States (U.S.), causing concern for water security. If individuals were targeted with appropriate information, public engagement in water conservation may increase. Political affiliation and ideology may play a role in grouping individuals based on their engagement in water conservation, as environmental issues are politically contentious in the U.S. The purpose of the study was to determine if political affiliation, political ideology, and theory of planned behavior variables related to water conservation predicted intent to engage in water conservation. Data were collected from 1049 U.S. residents using non-probability opt-in sampling methods. Descriptive statistics and multiple linear regression models were used to analyze the data via the Statistical Package for the Social Sciences (SPSS) 26. The results from a multiple linear regression model revealed that political affiliation, political ideology, attitude, subjective norms, and perceived behavioral control predicted 27.5% of variance in respondents’ intent to engage in water conservation; however, the variance accounted for was mostly attributed to theory of planned behavior variables. The findings have implications for environmental communication, namely focusing on increasing subjective norms towards water conservation.
Development of a Numerical Multi-Layered Groundwater Model to Simulate Inter-Aquifer Water Exchange in Shelby County, Tennessee
Authors: Villalpando-Vizcaino Rodrigo , Waldron Brian , Larsen Daniel , Schoefernacker Scott
Published: September 2021

Inter-aquifer water exchange between the shallow and Memphis aquifers in Shelby County, Tennessee may pose a contamination threat due to the downward migration of younger, poor quality groundwater into deeper, more pristine aquifer. Discontinuities (breaches) in the upper Claiborne confining unit (UCCU) allow for leakage into the Memphis aquifer, a sand-dominated aquifer that provides about 95% of the groundwater used in the Memphis area. This study created a multi-layered 3D groundwater model for Shelby County using the United States Geological Survey’s MODFLOW-NWT program to evaluate water exchange for a simulation period from January 2005 to December 2016. Results indicate an overall leakage through the UCCU of 61 m3/min into the Memphis aquifer in Shelby County, accounting for 10% of its water budget inflow, with localized areas experiencing as much as 20% water exchange. As young water tends to stay in the upper part of the Memphis aquifer, water budget assessment for the upper 60 m of the Memphis aquifer revealed leakage representing 29% of the zone inflow, and as much as 53% in certain areas. More localized studies must be conducted to understand the location, characteristics, and orientation of the confining unit breaches, as well as the inter-aquifer water exchange.
Multiple-Depth Soil Moisture Estimates Using Artificial Neural Network and Long Short-Term Memory Models
Authors: Han Heechan , Choi Changhyun , Kim Jongsung , Morrison Ryan R. , Jung Jaewon , Kim Hung Soo
Published: September 2021

Accurate prediction of soil moisture is important yet challenging in various disciplines, such as agricultural systems, hydrology studies, and ecosystems studies. However, many data-driven models are being used to simulate and predict soil moisture at only a single depth. To predict soil moisture at various soil depths with depths of 100, 200, 500, and 1000 mm from the surface, based on the weather and soil characteristic data, this study designed two data-driven models: artificial neural networks and long short-term memory models. The developed models are applied to predict daily soil moisture up to 6 days ahead at four depths in the Eagle Lake Observatory in California, USA. The overall results showed that the long short-term memory model provides better predictive performance than the artificial neural network model for all depths. The root mean square error of the predicted soil moisture from both models is lower than 2.0, and the correlation coefficient is 0.80–0.97 for the artificial neural network model and 0.90–0.98 for the long short-term memory model. In addition, monthly based evaluation results showed that soil moisture predicted from the data-driven models is highly useful for analyzing the effects on the water cycle during the wet season as well as dry seasons. The prediction results can be used as basic data for numerous fields such as hydrological study, agricultural study, and environment, respectively.
Development of an Interdisciplinary Prediction System Combining Sediment Transport Simulation and Ensemble Method
Authors: Ho Hao-Che , Chiang Yen-Ming , Lin Che-Chi , Lee Hong-Yuan , Huang Cheng-Chia
Published: September 2021

The change in movable beds is related to the mechanisms of sediment transport and hydrodynamics. Numerical modelling with empirical equations and the simplified momentum equation is the common means to analyze the complicated sediment transport processing in river channels. The optimization of parameters is essential to obtain the proper results. Inadequate parameters would cause errors during the simulation process and accumulate the errors with long-time simulation. The optimized parameter combination for numerical modelling, however, is rarely discussed. This study adopted the ensemble method to simulate the change in the river channel, with a single model combined with multiple parameters. The optimized parameter combinations for a given river reach are investigated. Two river basins, located in Taiwan, were used as study cases, to simulate river morphology through the SRH-2D, which was developed by the U.S. Bureau of Reclamation. The input parameters related to the sediment transport module were randomly selected within a reasonable range. The parameter sets with proper results were selected as ensemble members. The concentration of sedimentation and bathymetry elevation was used to conduct the calibration. Both study cases show that 20 ensemble members were good enough to capture the results and save simulation time. However, when the ensemble members increased to 100, there was no significant improvement, but a longer simulation time. The result showed that the peak concentration and the occurrence of time could be predicted by the ensemble size of 20. Moreover, with consideration of the bed elevation as the target, the result showed that this method could quantitatively simulate the change in bed elevation. With both cases, this study showed that the ensemble method is a suitable approach for river morphology numerical modelling. The ensemble size of 20 can effectively obtain the result and reduce the uncertainty for sediment transport simulation.
Scientometric Analysis-Based Review for Drought Modelling, Indices, Types, and Forecasting Especially in Asia
Authors: Wu Dan , Li Yanan , Kong Hui , Meng Tingting , Sun Zenghui , Gao Han
Published: September 2021

An extended drought period with low precipitation can result in low water availability and issues for humans, animals, and plants. Drought forecasting is critical for water resource development and management as it helps to reduce negative consequences. In this study, scientometric analysis and manual comprehensive analysis on drought modelling and forecasting are used. A scientometric analysis is used to determine the current research trend using bibliometric data and to identify relevant publication field sources with the most publications, the most frequently used keywords, the most cited articles and authors, and the countries that have made the greatest contributions to the field of water resources. This paper also tries to provide an overview of water issues, such as drought classification, drought indices, historical droughts, and their impact on Asian countries such as China, Pakistan, India, and Iran. There have been many models established for this purpose and choosing the appropriate model for study is a long procedure for researchers. An appropriate, comprehensive, pedagogical study of model ideas and historical implementations would benefit researchers by helping them to avoid overlooking viable model options, thus reducing their time spent on the topic. As a result, the goal of this paper is to review drought-forecasting approaches and recommend the best models for the Asian region. The models are divided into four categories based on their mechanisms: Regression analysis, stochastic modelling, machine learning, and dynamic modelling. The basic concepts of each approach in terms of the model’s historical use, benefits, and limitations are explained. Finally, prospects for future drought research in Asia are discussed as well as potential modelling techniques.