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Journal of Hydrology
Elsevier
Journal of Hydrology

Elsevier

0022-1694

Journal of Hydrology/Journal Journal of HydrologySCIISTPEIAHCI
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    Storm event analysis of four forested catchments on the Atlantic coastal plain using a modified SCS-CN rainfall-runoff model

    Callahan, T. J.Morrison, A.Vulava, V.Hitchcock, D. R....
    18页
    查看更多>>摘要：In this study, we calibrated and tested the Soil Conservation Service Curve Number (SCS-CN) based Modified Sahu-Mishra-Eldo (MSME) model for predicting storm event direct runoff (Q(tot)) and its soil saturation coefficient alpha as a threshold antecedent moisture condition for partitioning into overland surface and shallow subsurface runoff components. The model calibration was performed using 36 storm events from 2008 to 2015 on a 160-ha low-gradient forested watershed (WS80) on poorly drained soil. The model was further validated without cali-bration using data from 2011 to 2015 on two sites [115 ha (Conifer) and 210 ha (Eccles Church)] and from 2008 to 2011 on a third site, the 100-ha Upper Debidue Creek (UDC), all similar forested watersheds on the Atlantic Coastal Plain, USA. The calibrated MSME model was able to accurately predict the estimated Q(tot_pred) for the WS80 watershed, with calculated Nash-Sutcliffe efficiency coefficient (NSE), RMSE-standard deviation ratio (RSR), and percent bias (PBIAS) of 0.80, 0.44, and 16.7%, respectively. By applying the same calibrated alpha value of 0.639 from the WS80 to two other similar poorly drained watersheds, the MSME model satisfactorily predicted the estimated Q(tot_pred) for both the Eccles Church (NSE = 0.64; RSR = 0.57; PBIAS = 28.9%) and Conifer (NSE = 0.60; RSR = 0.58; PBIAS = 21.3%) watersheds, respectively. The MSME model, however, yielded un-satisfactory results (NSE =-0.13, RSR = 2.06, PBIAS = 616.3%) on the UDC watershed with coarse-textured soils, indicating the possible association of the alpha coefficient with soil subsurface texture. Based on the analysis of event rainfall and pre-event water table elevation, and linking them with the calibrated alpha coefficient that describes the proportion of saturated depth in a soil profile, it was found that rainfall was the main determining factor for overland runoff generation. These results demonstrate the MSME model's potential to predict direct runoff in poorly drained forested watersheds, which serve as a reference for urbanizing coastal landscapes in a changing climate.
      原文链接:
    • NSTL
    • Elsevier

    Influence of hydrogeological and operational parameters on well pumping capacity

    Shandilya, Raghwendra N.Bresciani, EtienneKang, Peter K.Lee, Seunghak...
    12页
    查看更多>>摘要：Numerous studies have analyzed how groundwater levels respond to pumping depending on aquifer and well characteristics. This study investigates how, conversely, the pumping capacity of a well depends on hydrogeological and operational conditions. The analysis is based on an analytical solution that considers wellbore storage and skin effects. The solution depends on aquifer transmissivity, aquifer storativity, well radius, well surface casing radius, skin layer transmissivity, pumping duration, and maximum allowable head change. We first conduct a sensitivity analysis of dimensionless pumping capacity to the three dimensionless parameters on which it depends. The results show strongly nonlinear relationships and an important effect of wellbore storage for small dimensionless pumping durations. Since the primary (dimensional) parameters are the ones that one ultimately needs to characterize or engineer in practice, we also conduct a sensitivity analysis of the primary system. The results show that, besides being trivially linearly related with the maximum allowable head change, pumping capacity (defined as a volume) is almost linearly related with aquifer transmissivity and pumping duration. Given the broad natural range of transmissivity values, transmissivity is the most critical parameter to determine for the estimation of pumping capacity. In contrast, pumping capacity is little sensitive to aquifer storativity and well radius, and so the precise determination of these parameters is less critical. Finally, we investigate the relationship between pumping capacity and specific capacity, the latter being a commonly used indicator of the productivity of wells. Our analysis confirms the previously acknowledged limitation of specific capacity for predicting pumping capacity when the duration of the specific capacity test is much smaller than the operational pumping duration. The theoretical insights gained from this study will assist groundwater scientists and engineers in their research, planning, and design activities.
      原文链接:
    • NSTL
    • Elsevier

    Entity aware sequence to sequence learning using LSTMs for estimation of groundwater contamination release history and transport parameters

    Anshuman, AatishEldho, T., I
    19页
    查看更多>>摘要：Groundwater contaminant sources identification and parameter estimation using the simulation-optimization (S/O) approach require numerous runs of the computationally expensive simulation model through the optimization algorithm. The computational cost can be effectively reduced by using a surrogate model which can accurately approximate the simulation model. With the advent of deep learning, Long Short-Term Memory (LSTM) networks, which are suitable to learn sequential data, are being increasingly applied to regression problems involving time dependencies. However, for the simultaneous contaminant source identification and parameter estimation problem, the surrogate model requires to establish a relationship between release histories at the source locations to concentration measurements at observation points subject to given values of aquifer parameters. In this study, a novel deep neural network framework Entity Aware Sequence to sequence learning using Long Short-Term Memory (EAS-LSTM) is proposed as a surrogate model which takes both sequential i.e., release histories at the source locations at different stress periods and static variables i.e., transport parameters as inputs to predict breakthrough curves (BTCs) at observation points. The proposed surrogate model is applied to a heterogeneous field scale aquifer with 4 zones. The Mean Squared Error (MSE) using EAS-LSTM is 0.0033 ppm(2) which is significantly better than that of Kriging and Support Vector Regression (SVR) which are 0.048 ppm(2) and 1.302 ppm(2) respectively. Comparison of EAS-LSTM model performance with Kriging and SVR based models demonstrates its higher accuracy. Further, the optimization algorithms for inverse modelling, the performances of Multiverse Optimizer (MVO), Grey wolf optimization (GWO) and Particle swarm optimization (PSO) are investigated. It is observed that the combination of EAS-LSTM and MVO provides better results in comparison to other surrogate simulation optimization (SSO) models.
      原文链接:
    • NSTL
    • Elsevier

    Exploring the links between variations in snow cover area and climatic variables in a Himalayan catchment using earth observations and CMIP6 climate change scenarios

    Dharpure, Jaydeo K. K.Chatterjee, DebrupaSahu, RakeshGagnon, Alexandre S. S....
    16页
    查看更多>>摘要：The spatial extent of the Snow Cover Area (SCA) of the Bhagirathi River Basin (BRB) has changed in recent decades, impacting the hydrology of the region. Previous studies examining variations in SCA in the region have yet been limited to the effects of terrain variables, namely elevation, slope and aspect, without considering the influence of climate variability. This study first investigates temporal changes in SCA and Terrestrial Water Storage (TWS) in the BRB during the period 2001-2019, which were calculated using satellite images from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Gravity Recovery and Climate Experiment (GRACE), respectively, and their linkages to variation in climatic variables, and then examines how future climate change could impact on the SCA of the basin and its implications for water resources.& nbsp;A trend analysis revealed an increase in the SCA during the study period, correlating with an increase in precipitation and TWS over the basin. Statistically significant positive correlation were detected between the post-monsoon (r = 0.49, p < 0.05) and winter (r = 0.54, p < 0.05) SCA and precipitation, while a negative correlation was identified between SCA and Tmax during the post-monsoon (r =-0.53, p < 0.05) and winter (r =-0.69, p < 0.05) seasons. Climate change scenarios, obtained from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and downscaled over the study region, project an increase in both maximum and minimum temperature, and precipitation for the pre-monsoon and winter seasons in the 2030 s under two Shared Socioeconomic Pathway (SSP) greenhouse gas (GHG) emission scenarios: SSP245 and SSP585. These scenarios, together with a Multiple-Linear Regression (MLR) model developed on the basis of the relationships identified between variations in SCA and climatic variables, indicate a reduction in the SCA at 4000 + m altitudes in all seasons under both scenarios, thereby resulting a decline in the Bhagirathi river flow in spite of a projected increase in precipitation. This study demonstrates the impact of projected changes in climate on the SCA of a Himalayan catchment, and the potential implications for regions where snowmelt is important to streamflow regimes.& nbsp;
      原文链接:
    • NSTL
    • Elsevier

    Intense denitrification and sewage effluent result in enriched N-15 in N2O from urban polluted rivers

    Li, XingYu, YongxiangFan, HaoxinTang, Changyuan...
    10页
    查看更多>>摘要：Urban polluted rivers are important sources of N2O because they receive heavy nitrogen loads containing N2O and its precursors. Understanding the N2O budget is vital to the formulation of N2O emissions reduction policies. The isotopic ratios of N2O from different sources can provide insights into global N2O budgets. Isotopic ratios of N2O from soil and marine has been well studied, yet few studies have explored dynamics of dissolved N2O and its isotopic ratios in urban polluted rivers. In this study, we quantified N2O concentrations, environmental variables and the production pathways of N2O, measured the nitrogen isotope ratios of nitrate and ammonia to revealed the nitrogen pollution sources, assessed the isotopic ratios of N2O emitted from a series of polluted rivers and compare them with those of soils, oceans, and freshwaters, and revealed the influence of N2O production pathways and nitrogen pollution sources on the delta N-15-N2O and N2O concentrations of urban polluted rivers in Shenzhen City, China. The concentrations of dissolved N2O ranged from 0.3 to 2482.9 nmol/L, with most values exceeding those equilibrium with the atmosphere, indicating that these rivers in urban subtropical areas are significant N2O sources to atmosphere. The isotopic ratios of dissolved N2O from polluted rivers varied widely, with delta N-15-N2O ranging from-11.9%o to 34.8%o, delta O-18-N2O from 37.9%o to 68.2%o, and SP from-10.5%o to 36.2%o. The delta N-15 of emitted N2O from water surface to atmosphere ranged from-11.9%o to +34.8%o, with a mean value of +9.2%o, which was higher than that from natural rivers, soil, and the troposphere. delta N-15(sp) and delta O-18 values of dissolved N2O were adopted to quantify the relative contributions of nitrification (f), denitrification (1f), and the magnitude of N2O reduction (Fr) by denitrification. The results showed that denitrification was dominant pathway of N2O production, although the relative contribution of denitrification and nitrification had a great temporal and spatial variability. There is no distinct linear relationship between the concentrations of dissolved N2O, delta N-15-N2O and environmental variables (DO, DOC, NO3- , and NH4(+)). The non-linear relationship among delta N-15-N2O and delta N-15-NO3-, f, Fr, and environmental variables were explored by regression tree analysis. The results suggested that f and Fr, not DO, DOC, NO(3)(- )and NH4(+), were the primary correlates of dissolved N2O, for which the N2O concentrations were higher when N2O was primarily produced via nitrification (f > 77.5%) or denitrification (f < 8%), and were lower when Fr > 69.5%. It is the first attempt to reveal the connection between production and consumption processes with N2O concentrations directly. In addition, the elevated values of delta N-15-NO3- (4.3 to 29.8%o) and delta N-15-NH4(+) (3.2%o to 9.3%o) in these urban rivers consequence that the nitrogen contamination is predominantly sourced from urban sewage. Regression tree analysis also indicated that intense denitrification and sewage effluent result in enriched delta N-15 in N2O from polluted rivers, for which the delta N-15 values were higher when N2O was primarily produced via denitrification (f < 12%) or delta 15N-NO(3)(- )were higher than 15.6%o. These findings provide a foundation upon which to devise strategies to reducing N2O production and emission in urban rivers.
      原文链接:
    • NSTL
    • Elsevier

    Analytical relationships between normal stress and fluid flow for single fractures based on the two-part Hooke's model

    Ye, ZuyangYang, JianhangXiong, FengHuang, Shibing...
    9页
    查看更多>>摘要：The normal stress-dependent hydraulic properties of single fractures are fundamental in hydro-mechanical coupling for the fractured reservoirs. With increasing normal stress, fluid flow through single fractures de-creases dramatically in the low stress range and then gradually in the high stress range, respectively. In order to describe this heterogeneous hydro-mechanical behavior, analytical relationships between normal stress and fluid flow for single fractures are established based on the two-part Hooke's model (TPHM), in which the fracture aperture is conceptualized into two parts at a macro scale, hard part and soft part. The contributions of soft part and hard part apertures on the hydraulic properties are separately evaluated by the different mechanical properties with normal stress. The validity of the proposed relationships between normal stress and fluid flow is verified by the good agreements between experimental data and theoretical predictions for natural and induced tensile fractures. The significant reductions of permeability and flow rate at low stress are dominated by the soft part and the degree of their nonlinearity highly depends on the spatial correlation of fracture geometry. In addition, the irrecoverable fracture deformation and flow drop between loading cycles are also greatly affected by the soft part while the fracture modulus of the hard part exhibits a weak dependence on loading cycle. The proposed relationships can be used to evaluate the coupled hydro-mechanical processes in fractured rock en-gineering such as geothermal energy development, CO2 geologic sequestration and stability of fractured rock slope.
      原文链接:
    • NSTL
    • Elsevier

    Prediction of the unfrozen water content in soils based on premelting theory

    Wan, XushengPei, WanshengLu, JianguoZhang, Xiong...
    13页
    查看更多>>摘要：The variation of unfrozen water content with temperature has a significant effect on the coupled heat-water transport in freezing soil, which can cause the frost heave and thaw settlement, and thus influence the stability of infrastructures. The premelting theory for water-ice in soils is developed to study the unfrozen water variation in freezing soil. The developed theory integrates the interfacial premelting of contact ice, the soil particles, the melting of the ice surface, and the premelting induced by impurity and curvature. A model to predict the unfrozen water content is then established by considering the change of unfrozen water film. The equivalent grain size is introduced to improve the solving efficiency in the calculation. Finally, the proposed analytical model is verified by the test data. The results indicate that the thickness of water film in soils increases when the surface charge density and the impurity concentration increase under the same supercooling degree. The surface melting on the interfaces of soil particle and the pore ice has key influence on the variation of the liquid water content. Meanwhile, the unfrozen water content increases with the increasing impurity concentration and surface charge on soil particles. Besides, the unfrozen water content also increases with the decreasing radius of soil particles.
      原文链接:
    • NSTL
    • Elsevier

    Geochemical factors controlling natural background levels of phosphate in various groundwater units in a large-scale urbanized area

    Bi, PanHuang, GuanxingLiu, ChunyanLi, Liangping...
    10页
    查看更多>>摘要：Assessing natural background levels (NBLs) of groundwater chemical components is useful to the identification of geochemical factors controlling the origin of high levels of chemical components in groundwater. This study assessed the NBLs of phosphate in various groundwater units in the Pearl River Delta (PRD) where urbanization is a large-scale by the combination of a modified pre-selection method and Grubbs' test, and discussed main geochemical processes controlling the origin of high levels of phosphate in groundwater. Here, the PRD is divided into four groundwater units according to its hydrogeological conditions. The modified pre-selection method consists of detected organic contaminants, the oxidation capacity, as well as the high levels of ammo-nium and nitrate in groundwater. Results showed that the NBL of phosphate in the coastal-alluvial aquifer was abnormal high (1.8 mg/L), and was >4 times that in other groundwater units. This is mainly attributed to the co-release of phosphate, bicarbonate, and Fe(II) accompanied with the elevated pH and decreased Eh, which resulted from the mineralization of organic matter accompanied with the reductive dissolution of Fe(III)-(hydr) oxides as well as the desorption of other secondary minerals such as aluminum oxyhydroxides in the overlaid marine stratum. Besides, unlike other groundwater units, the property of discharge area of the coastal-alluvial aquifer with more reducing environment also contributes the higher NBL of phosphate in the coastal-alluvial aquifer than in other groundwater units.
      原文链接:
    • NSTL
    • Elsevier

    Rainfall extremes on the rise: Observations during 1951-2020 and bias-corrected CMIP6 projections for near- and late 21st century over Indian landmass

    Saha, UpalSateesh, M.
    16页
    查看更多>>摘要：In this study, we provide a comprehensive analysis to identify and quantify spatial patterns of heavy, very heavy and extremely heavy rainfall and their trends that have emerged during the last seven decades (1951 to 2020) of monsoon months (June to September) under warming scenario as well as to project these extreme rainfall counts during the near- (2036-2060) and late-21st century (2075-2099) w.r.t. historical period (1990-2014) using biascorrected Coupled Model Intercomparison Project-6 (CMIP6) multi-model ensemble method. On the basis of daily maximum rainfall occurrences, the Central India, North-East India, Western Ghats and Eastern Ghats are found to be susceptible to extreme rainfall zones over the Indian landmass. The trend distribution during 1951-2020 suggests an increase of 42-63 heavy rainfall events over Orissa, Chattisgarh and parts of Madhya Pradesh and a declination over Uttar Pradesh, Kerala and hilly regions of North-East India. Our study suggests the causal theory for the rise of monsoon rainfall extremes in terms of both dynamics and local-scale thermodynamics over the sub-continent. Moreover, the bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for historic and projected climate for the three scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) using output from 20 General Circulation Models (GCMs) from CMIP6. Hence, the bias-corrected projections suggest that most susceptible places for increasing heavy rainfall extremes likely to be Mumbai, Pune, Panaji in the Western coasts of India (Western Ghats), Itanagar and Shillong in the North-East India, Raipur and Bhopal in the Central India in near- and late-21st century under all scenarios in a warming climate. Thus, the bias-corrected projections from CMIP6-GCMs can be used for hydroclimate impact assessment in Indian region under the changing atmospheric circulation dynamics and warming induced by greenhouse gases.
      原文链接:
    • NSTL
    • Elsevier

    Pluvial flooding: High-resolution stochastic hazard mapping in urban areas by using fast-processing DEM-based algorithms

    Soriano, EnriqueOria, PeioBagli, StefanoCastellarin, Attilio...
    21页
    查看更多>>摘要：Climate change and rapid expansion of urban areas are expected to increase pluvial flood hazard and risk in the near future, and particularly so in large developed areas and cities. Therefore, large-scale and high-resolution pluvial flood hazard mapping is required to identify hotspots where mitigation measures may be applied to reduce flood risk. Depressions or low points in urban areas where runoff volumes can be stored are prone to pluvial flooding. The standard approach based on estimating synthetic design hyetographs assumes, in a given depression, that the T-year design storm generates the T-year pluvial flood. In addition, urban areas usually include several depressions even linked or nested that would require distinct design hyetographs instead of using a unique synthetic design storm. In this paper, a stochastic methodology is proposed to address the limitations of this standard approach, developing large-scale ~ 2 m-resolution pluvial flood hazard maps in urban areas with multiple depressions. The authors present an application of the proposed approach to the city of Pamplona in Spain (68.26 km(2)). The Safer_RAIN fast-processing algorithm based on digital elevation models (DEMs) is compared with the IBER 2D hydrodynamic model in four real storms by using 10-min precipitation fields. Precipitation recorded at rainfall-gauging stations was merged with continuous fields obtained from a meteo-rological radar station. Given the hydrostatic limitations of Safer_RAIN, the benchmarking results are adequate in terms of water depths in depressions. A long set of 10 000 synthetic storms that maintain the statistical properties of observations in Pamplona is generated. Safer_RAIN is used to simulate runoff response, and filling and spilling processes, in depressions for the 10 000 synthetic storms, obtaining the probability distribution of water depths in each cell. Maps of pluvial flood hazards are developed in the Pamplona metropolitan area for 10 return periods in the range from two to 500 years from such pixel-based series of simulated water depths. Bivariate return -period curves are estimated in a set of cells, showing that several storms can generate a given T-year pluvial flood with an increasing precipitation with storm duration that depends on the draining catchment soil char-acteristics. The methodology proposed is useful to develop maps of pluvial flood hazards in large multi-depression urban areas in reasonable computation times, identifying the main pluvial flood hotspots.
      原文链接:
    • NSTL
    • Elsevier