Journal of Hydro-environment Research最新文献

Sedimentation in front of a dam is the main obstacle against reservoir sustainability. Due to the limited availability of suitable new dam sites, the ramifications of inefficient sediment management are associated with socio-economic concerns and environmental issues. Most of the existing sediment management techniques are unfavorable for arid and semi-arid regions due to their impacts on available water storage and power generation. Therefore, pressure flushing is an economical desilting method as it releases little water through the bottom outlet. However, one of the main disadvantages of pressurized flushing is limited sediment removal near the bottom outlet. In this paper, the impacts of a dendritic, bottomless, and extended (DBE) structure were investigated to develop the scour cone to a broader area. Several experiments were carried out with four different diameters (125, 160, 200, and 250 mm), four different lengths (30, 50, 80, and 110 cm), and three discharge rates (12.5, 15, and 18 L/s), to identify the dimensions of the extended structure with the most efficient operation. The results indicated that the DBE structure with a length dimensionless index of $L_{\mathrm{DBE}}/D_o=10,$ a diameter dimensionless index of $D_{\mathrm{DBE}}/D_o=1.14$, and an outflow discharge dimensionless index of ${\mathrm{Fr}}_o=1.82$, yielded a 36.55-fold increase in the sediment flushing cone dimensions and sediment removal efficiency compared to a reference test. Finally, a dimensionless equation is presented for calculating the sediment flushing cone dimensions, according to a statistical analysis of the results. Two diagrams are provided to illustrate the interrelationship between the distance limits of scour, length, and diameter of the structure and outlet discharges.

Monitoring the water level and volume changes of lakes and reservoirs is essential for deepening our understanding of the temporal and spatial dynamics of water resources in the Yellow River Basin, with a view to better utilizing and managing water resources. In recent years, there have been many studies on monitoring water level and volume changes in inland waters, but they were mainly focused on radar altimetry and the full waveform LiDAR ICESat, which was retired in 2010. Few studies based on the latest photon-counting LiDAR ICESat-2 have been reported. Compared with previous sensors, ICESat-2 has great advantages in footprint size, transmitting frequency, pulse number, etc, but its performance in monitoring water level and volume changes in inland waters has not been fully explored. Here we investigated the spatial distribution of water level and volume changes of 11 lakes and 8 reservoirs in the Yellow River Basin based on ICESat-2 and Google Earth Engine, and analyzed the factors affecting the measurement uncertainties. In-situ validation of lake level in Lake Qinghai indicates that the Root Mean Square Error (RMSE) of our result is only 7 cm after the reference coordinate system conversion. We found that the water level trend of the natural lake shows significant seasonal variations, while the water level trend of the reservoir shows a sharp rise and fall. In addition, precipitation plays a decisive role in the changes in natural lake levels and indirectly affects the artificial control of reservoirs’ water discharges. The uncertainty of water volume change monitoring is mainly affected by water level measurement uncertainty for lakes, while for reservoirs, that is affected by the combination of water level and area measurement uncertainties. The stability of lake level measurement increases with the increase in photon counts. The introduction of ICESat-2 ATL13 Significant Wave Height might lead larger standard deviation in water level measurement. According to the law of propagation of uncertainty, the uncertainty of the water volume change estimation by the combination of ICESat-2 and GEE is less than 9 %.

Floating treatment wetlands (FTWs) use plants’ roots for water quality improvement. The plants are supported by a buoyant structure deployed at the water surface. The roots form a porous zone beneath the structure and remove pollutants carried in suspension through filtering, absorption and uptake. This paper used CFD simulation to model FTWs arranged in series and spanning the channel width and to study the effects of root length and spacing between FTWs on flow distribution and mass removal. The root zone was modelled as a porous media, and removal was computed using first-order decay, for which a range of removal constants was tested. Longer roots increased the reactive volume of the root zone, which increased the fraction of pollutant inflow entering the FTWs. Increasing the distance between FTWs allowed greater mixing between water that went through and beneath the upstream FTW. This increased the concentration entering each FTW, which enhanced mass removal per FTW. However, a larger distance between FTWs reduced the number of FTWs in the channel, reducing the reactive volume. In the tradeoff between mixing and reactive volume, the reactive volume was more important, such that total removal in the channel increased with longer roots and more units of FTW (shorter gap distance). However, removing the gap entirely was detrimental, as FTWs in series removed more mass than a continuous FTW of same volume. This study points to two design recommendations for FTWs in series. First, if resources for building FTWs are not limiting, but the channel length is, it is preferable to prioritize higher reactive volume (shorter gap distance) to achieve maximum removal per channel length. Second, if resources for FTWs are limiting, but channel length is not, it is better to place the FTWs with a longer gap distance, preferably along enough to allow mixing over the full depth between FTWs, as this will achieve maximum removal per FTW.

The air flow induced by a water jet freely falling inside a vertical pipe with its top and bottom both open to the atmosphere was investigated experimentally and numerically. In the experiments, the radial air velocity distribution and the air pressure variation along the vertical pipe were measured. The air drag of the falling water jet was related to the jet surface disturbance and analyzed by introducing the equivalent friction factor. A predictive model was developed for the air flow inside a 3-m-high pipe based on the momentum equation and its results compared well with the experimental measurements. Numerical simulations were also conducted by approximating the free-falling water jet as a continuous moving solid with diameter and velocity varying in the direction of motion. The effects of pipe size on the air velocity profile and the induced air flow rate were examined. The simulation results showed that the streamwise air velocity profiles inside pipes of different sizes approached the same after a certain traveling distance. The maximum induced air flow rate was found at the pipe diameter of about 20 times of initial water jet diameter.

The analysis of the water distribution network is complicated and requires several assumptions to simplify its problem definition. Demand Driven Analysis (DDA) is typically used to analyse the network assuming that all network nodes can deliver the required demand regardless of the available pressure. In the case of analysing an existing network under deficit condition such as pipe breakage or extra demand required for firefighting, assumptions used to simulate the network with DDA is not valid. Node Head Flow Relationship (NHFR) should be considered through Pressure Driven Analysis (PDA) to analyse the network. Most PDA methods assume that the networks are airtight which means that if the pressure at any demand node is negative, delivered demand will be equal to zero and the flow is permitted in the connected pipes (Siphonic flow). This assumption is hydraulically incorrect since the air is allowed to get into the connected pipes and prevent their flow leading to node isolation. In this paper, a new Pressure Driven Analysis to Prevent Siphonic Flow (PDA-SF) approach is proposed to analyze the network under deficit conditions and consider isolating the nodes that show available head less than node elevation. The PDA-SF was tested and compared to previous methods in four case studies under steady state analysis or extended period simulation. The case studies cover also different network conditions whether node isolation is needed or not. The PDA-SF was able to solve different networks where other methods failed to achieve the required demand or service pressure. The new PDA-SF method shall enable peers and modelers to better simulate and analysis water distribution networks.

Downscaling techniques are required to describe the linkages between Global Climate Model outputs at coarse-grid resolutions to surface hydrologic variables at relevant finer scales for climate change impact and adaptation studies. In particular, several statistical methods have been proposed in many previous studies for downscaling of extreme temperature series for a single local site without taking into account the observed spatial dependence of these series between different locations. The present study proposes therefore an improved statistical approach to downscaling of daily maximum (Tmax) and minimum (Tmin) temperature series located at many different sites concurrently. This new multisite multivariate statistical downscaling (MMSD) method was based on a combination of the modeling of the linkages between local daily temperature extremes and global climate predictors by a multiple linear regression model; and the modeling of its stochastic components by the combined singular value decomposition and multivariate autoregressive (SVD-MAR) model to represent more effectively and more accurately the space-time variabilities of these extreme daily temperature series. Results of an illustrative application using daily extreme temperature data from a network of four weather stations in Bangladesh and two different NCEP/NCAR reanalysis datasets have indicated the effectiveness and accuracy of the proposed approach. In particular, this new approach was found to be able to reproduce accurately the basic statistical properties of the Tmax and Tmin at a single site as well as the spatial variability of temperature extremes between different locations. In addition, it has been demonstrated that the proposed method can produce better results than those given by the widely-used single-site downscaling SDSM procedure, especially in preserving the observed inter-site correlations.

In subtropical coastal waters, the explosive growth of phytoplankton under favorable conditions can lead to water discolouration and massive fish kills. Manual field sampling and laboratory analysis of chlorophyll-a concentration (Chl-a) as an indicator to algal biomass, is resources intensive and time consuming, delaying responses to disastrous harmful algal blooms. Cloudy weather often precludes the use of satellite images for water quality and algal bloom monitoring. This study aims at developing an estimator algorithm for quantitative mapping of surface Chl-a for coastal waters, based on surface reflectance measurement from an Unmanned Aerial Vehicle (UAV) with a five-band multispectral camera. The surface reflectance is obtained from calibrated multispectral images which are radiometric-corrected against incoming solar radiation. It is found that Chl-a has an inverse correlation with the Normalized Green-Red Difference Index (NGRDI). A regression estimator model for Chl-a from NGRDI is developed, showing excellent performance for fish farms in coastal waters with different characteristics. The technology is demonstrated for mapping the spatial and temporal variation of Chl-a during an algal bloom, offering a useful complement to traditional field monitoring for fisheries management and emergency response.

In this study, a series of laboratory tests were performed to investigate the effects of side ramp slope, crest length, and porous media properties on the flow regimes, water-surface profiles, discharge coefficients, and energy dissipation in embankment gabion weirs with upstream and downstream slopes. 24 physical models of solid and gabion weirs with three different upstream/downstream slopes (90°, 45° and 26.5°) were created. To investigate the complexity of flow over the porous-fluid interface and through the porous material, three-dimensional (3D) numerical simulations were developed. In numerical simulation, the standard k-ε turbulence model was utilized. A structured mesh domain was used to simulate the physical model. Water surface profiles above the porous weirs were used for comparison between the numerical simulations and measured data. These comparisons helped determine variables in the numerical simulations. Numerical simulation enables visualization of streamlines around and through the gabion weirs. In addition, mean stream wise velocity profiles above and within the porous structures were obtained. Numerical simulations showed that a reduction in the slope of the upstream face leads to an increased curvature of streamlines and the velocity distribution exhibits a non-uniform wavy shape due to the geometrical properties of the weirs. As the velocity profiles move downstream, the velocity distribution within the porous structures were more affected by the presence of the pores. The experimental results show that decreasing upstream slopes, from 90° to 26.5°, leads to decreased discharge coefficients. However, in all cases, gabion weirs lead to greater discharge coefficients than those of similar solid weirs. For milder side slopes, discharge ratios (flow passing through all faces of the gabion weirs over the inlet discharge) decreased nonlinearly. Moreover, with increasing the inlet discharge, relative energy dissipation was reduced up to 45% in gabion weirs.

River restoration aims to apply environmentally-friendly structures for bank protection in meandering rivers to restore their natural habitat. Enhanced Permeable Groin (EPG) is a novel river restoration technique that can improve the fish habitat environment in a river system by creating a series of eco-friendly scour pools. This study reports the results of two groups of 3D velocity measurements in a 180-degree channel bend in cases with and without an EPG for clear water conditions to characterize the mechanisms leading to the primary stages of the scouring phenomenon. The analysis revealed that the presence of an EPG amplified the velocity magnitude in the regions near the tip of the vane and increased its value in the middle of the channel 1.13 times the bend without the structure. In addition, the comparison showed that the EPG reduced the velocity magnitude in the recirculation zone by an average of 38%. Secondary currents including main and outer bank cells were observed in the case without the structure. The presence of the EPG in the flow field effectively increased the outer-bank cell strength by 11 times compared to that without the structure. The low-value contours of the bed shear stresses were observed in the zone downstream of the structure for a distance of 6 times the effective length of the structure. Based on the results of this study, the generation of a recirculation zone with low-velocity and shear stress values can provide suitable conditions for aquatic habitats, deep-bodied fish assemblages, aquatic vegetation, shrub roots, and tree roots along the outer bank.

The popular Natural Resources Conservation Service Curve Number (NRCS-CN) (earlier known as Soil Conservation Service Curve Number (SCS-CN) method of rainfall-runoff modeling has often faced the criticism of exhibiting quantum jumps in runoff computations because of the sudden jumps appearing in CN-values derived from NEH-4 tables for three antecedent moisture conditions (AMC), viz., AMC-I, AMC-II, and AMC-III valid for dry, normal, and wet conditions, respectively. The variability of antecedent soil moisture within an AMC category is responsible for the abrupt jump and other deficiencies in the CN method for runoff estimation. This paper suggests a novel procedure to account for the antecedent moisture (M), preventing quantum jumps and eliminating deficiencies in determination of CN and, in turn, estimation of direct runoff. Its validity was verified utilizing the observed rainfall (P)-runoff (Q) events from 36 US watersheds, four sub-catchments of the Godavari basin, and small agricultural plots at Roorkee, India. The performance of the proposed model (M5) for runoff prediction was compared with the existing NRCS-CN (M1), Mishra and Singh (2002) (M2), Singh et al. (2015) (M3), and Verma et al. (2021) (M4) model using various performance indices. Using the CNs derived from observed events, model M5 was seen to have performed better than M1-M4 in terms of Nash Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), and Percent Bias (PBIAS) for the data of US watersheds, and CN-P correlation improved as the coefficient of determination (R²) enhanced. Similarly, using the RS & GIS-based CNs on natural watersheds of the Godavari basin and considering AMC-I, the performance of M5 was again better than M1-M4 in terms of RMSE, Mean Bias Error (mBIAS), Mean Absolute Error (MAE), and Normalized-Nash Sutcliffe Efficiency (NNSE). Interestingly, there existed a significant (p < 0.05) relationship between the in-situ water content (w) measured for the experimental plots of Roorkee and the model input variable antecedent moisture (M), offering a physical touch to the conceptual model.