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Journal of Hydrology
Elsevier
Journal of Hydrology

Elsevier

0022-1694

Journal of Hydrology/Journal Journal of HydrologySCIISTPEIAHCI
正式出版
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    A distributed domain model coupling open channel flow and groundwater flow to quantify the impact of lateral hydrologic exchange on hydrograph

    Wei, SongZheng, YiLiang, XiuyuTian, Yong...
    16页
    查看更多>>摘要：Hydrologic exchange flows (HEFs) of river-aquifer systems are known to affect water flow, but the quantitative influences of lateral HEFs and the riparian zone's hydraulic conductivity (K) distribution on stream fluxes remain obscure under varying hydrologic conditions. To fill this knowledge gap, this study proposed a physical based, distributed domain, coupled (open channel and groundwater) flow model (DDCM) to quantify the effect of lateral HEFs on hydrograph characteristics, including especially the peak discharge and tailing decay which are practically important. Numerical experiments showed that (1) the interaction between the lateral HEFs and river hydrodynamics reduced the peak discharge and flood flow rates, (2) a heterogeneous K field of the riparian zone generated multi-rate HEFs (which then changed flow response) represented by the hydrographs with various declining rates (varying from exponential to power-law), significantly expanding the flow process, and (3) the probability density function of K also affected the tailing and peak of the hydrograph. A preliminary test showed that the DDCM captured the overall pattern of hydrographs observed from a catchment in the Wadi Ahin West, Oman. This study, therefore, provided a model-based quantification of the mechanisms and factors of the lateral HEFs affecting the hydrograph pattern in flood events, and further applications are needed to test the applicability of the DDCM in capturing real-world hydrographs affected by the lateral HEFs.
      原文链接:
    • NSTL
    • Elsevier

    Contrasting water use characteristics of riparian trees under different water tables along a losing river

    Li, YueMa, YingSong, XianfangWang, Lixin...
    11页
    查看更多>>摘要：Rivers losing flow into surrounding aquifers ('losing' rivers) are common under changing climates and groundwater overexploitation. The riparian plant-water relations under various water table dynamics along a losing river remain unclear. In this study, the water isotopes (delta H-2 and delta O-18), leaf delta C-13, and MixSIAR model were used combinedly for determining the root water uptake patterns and leaf water use efficiency (WUE) of Salix babylonica (L.) at three sites (A, B, and C) with different water table depths (WTDs) in the riparian zone of Jian and Chaobai River in Beijing, China. The correlations of water source contributions with WTD and WUE were quantified. The riparian S. babylonica primarily took up upper (0-80 cm) soil water (71.5%) with the lowest leaf delta C-13 (-28.8 +/- 1.1 %o) at site A under deep WTD (20.5 +/- 0.5 m). In contrast, deep water below 80 cm depth including groundwater contributed 55.1% to S. babylonica at site B with fluctuated shallow WTD (1.9 & PLUSMN; 0.4 m), where leaf 813C was highest (-27.9 +/- 1.0 %o). The S. babylonica mainly used soil water in 30-170 cm layer (56.9%) with mean leaf 813C of -28.2 %o +/- 0.7 %o at site C with stable shallow WTD (1.5 +/- 0.1 m). It was found that both the contributions of upper soil water in 0-80 cm and deep water below 80 cm had significantly quadratic correlations with WTD under shallow water table conditions (p < 0.05). Leaf delta C-13 was negatively correlated with contributions of upper soil water above 80 cm depth, but it was positively related to the con-tributions of deep water below 80 cm in linear functions (p < 0.001). The results indicated that 2.1 m was the optimum WTD for riparian trees, because they maximized the use of deep water sources to get the highest WUE. This study provides insights into managing groundwater, surface water resources and riparian afforestation in losing rivers.
      原文链接:
    • NSTL
    • Elsevier

    Seasonal fog enhances crop water productivity in a tropical rubber plantation

    Gnanamoorthy, PalingamoorthySong, QinghaiZhao, JunbinZhang, Yiping...
    14页
    查看更多>>摘要：The rapid conversion of tropical rainforests into monoculture plantations of rubber (Hevea brasiliensis) in Southeast Asia (SEA) necessitates understanding of rubber tree physiology under local climatic conditions. Frequent fog immersion in the montane regions of SEA may affect the water and carbon budgets of the rubber trees and the plantation ecosystems. We studied the effect of fog on various plant physiological parameters in a mature rubber plantation in southwest China over 3 years. During the study period, an average of 141 fog events occurred every year, and the majority occurred during the dry season, when the temperature was relatively low. In addition to the low temperature, fog events were also associated with low vapor pressure deficit, atmospheric water potential, relative humidity and frequent wet-canopy conditions. We divided the dry season into cool dry (November-February) and hot dry (March-April) seasons and classified days into foggy (FG) and non-foggy (nonFG) days. During the FG days of the cool dry season, the physiological activities of the rubber trees were suppressed where carbon assimilation and evapotranspiration showed reductions of 4% and 15%, respectively, compared to the cool dry non-FG days. Importantly, the unequal declines in carbon assimilation and evapotranspiration led to enhanced crop water productivity (WPc) on cool dry FG days but insignificant WPc values were found between FG and non-FG days of the hot dry season. Our results suggest that, by regulating plant physiology, fog events during the cool dry season significantly reduce water demand and alleviate water stress for the trees through improved WPc.
      原文链接:
    • NSTL
    • Elsevier

    Developing a quantitative framework to track the fate and transport of estrogens on a watershed scale

    Zhao, XiaominLung, Wu-Seng
    12页
    查看更多>>摘要：The risks associated with estrogens in detectable concentrations in the aquatic environment underscore the need to best manage the release of estrogenic compounds. Modeling work can effectively help to understand the variation of estrogens in the natural water bodies at low costs. This study developed a modeling framework based on the Hydrological Simulation Program - FORTRAN (HSPF) code to simulate the fate and transport of three dominant estrogens, estrone (E1), 178-estradiol (E28), and 17 alpha-estradiol (E2 alpha) in surface water by integrating their excretion, transport, interconversion, and attenuation processes. This work focused on estrogens from sewage systems, failing septic systems, grazing animals, and manure land application. The developed modeling framework was applied to the Redwood River Watershed in Minnesota to model the in-stream estradiol equivalents (EEQs). The modeled EEQs were comparable to the values measured at three sampling sites along the Redwood River in 2007. The modeling results indicate that wastewater treatment plant discharges elevate estrogen levels on dry days, and surface runoff caused by storms or snow melting after the manure land application and/or cattle grazing can drastically spike EEQs levels, suggesting the application of buffer stripes and manure storage/composting for estrogen control. The case study shows that the modeling framework can be used to characterize the temporal and spatial variation of estrogens in streams, evaluate their risk to aquatic animals, and determine the best management practices for estrogen control.
      原文链接:
    • NSTL
    • Elsevier

    Contaminant source identification in groundwater by means of artificial neural network

    Molino, LauraZanini, AndreaSecci, Daniele
    11页
    查看更多>>摘要：In a desired environmental protection system, groundwater may not be excluded. In addition to the problem of over-exploitation, in total disagreement with the concept of sustainable development, another not negligible issue concerns the groundwater contamination. Mainly, this aspect is due to intensive agricultural activities or industrialized areas. In literature, several papers have dealt with transport problem, especially for inverse problems in which the release history or the source location are identified. The innovative aim of the paper is to develop a data-driven model that is able to analyze multiple scenarios, even strongly non-linear, in order to solve forward and inverse transport problems, preserving the reliability of the results and reducing the uncertainty. Furthermore, this tool has the characteristic of providing extremely fast responses, essential to identify remediation strategies immediately. The advantages produced by the model were compared with literature studies. In this regard, a feedforward artificial neural network (ANN), which has been trained to handle different cases, represents the data-driven model. Firstly, to identify the concentration of the pollutant at specific observation points in the study area (forward problem); secondly, to deal with inverse problems identifying the release history at known source location (also in the case with multiple sources); then, in case of one contaminant source, identifying the release history and, at the same time, the location of the source in a specific sub-domain of the investigated area. At last, the observation error is investigated and estimated. The results are satisfactorily achieved, highlighting the capability of the ANN to deal with multiple scenarios by approximating nonlinear functions without the physical point of view that describes the phenomenon, providing reliable results, with very low computational burden and uncertainty.
      原文链接:
    • NSTL
    • Elsevier

    Large-scale dynamic flood monitoring in an arid-zone floodplain using SAR data and hybrid machine-learning models

    Panahi, MahdiRahmati, OmidKalantari, ZahraDarabi, Hamid...
    15页
    查看更多>>摘要：Although the growing number of synthetic aperture radar (SAR) satellites has increased their application in flood-extent mapping, predictive models for the analysis of flood dynamics that are independent of sensor characteristics must be developed to fully extract information from SAR images for flood mitigation. This study aimed to develop hybrid machine-learning models for flood mapping in the Ahvaz region, Iran, based on SAR data. Each hybrid model consists of a support vector machine (SVM) algorithm coupled with one of the following metaheuristic optimization procedures: grey wolf optimization (GWO), differential evolution, and the imperialist competitive algorithm. Sentinel-1 acquired SAR images before and during flooding between 20 March and 26 May of 2019. The goodness-of-fit level and predictive capability of each model were scrutinized using overall accuracy, producer accuracy, and user accuracy. The SVM-GWO approach yielded the highest accuracy with overall accuracies of 96.07% and 93.39% in the training and validation steps, respectively. Furthermore, this hybrid model provided the most accurate classification of water-inundation class based on producer accuracy (96.67%) and user accuracy (95.05%). The results highlight that wetland is the last land-use/land-cover type to return to normal conditions due to the many previously dry oxbow lakes that could trap water for a long time. Furthermore, the nine most suitable sites for flood-protection structures (e.g., embankments and levees) were identified based on floodwater distribution analysis. This work describes a robust, data-parsimonious approach that will benefit flood mitigation studies seeking to identify the most suitable locations for embankments based on spatio-temporal flood dynamics.
      原文链接:
    • NSTL
    • Elsevier

    Impact of emergency drawdown in off-stream brackish reservoirs - The case of La Loteta dam in Spain

    Mateo Lazaro, JesusCastillo Mateo, JorgeGarcia Gil, AlejandroSanchez Navarro, Jose Angel...
    12页
    查看更多>>摘要：Reservoirs are the main component of regulation of water resources in basins. Off-stream reservoirs are a particular solution where water is stored in a secondary catchment other than the basin that produces the water resource. This under certain conditions can modify the water regime of the downstream secondary catchment. Although uncommon, one of the reservoir management operations is emergency emptying in the event of possible incidents that could put proper reservoir management at risk. One of the environmental requirements of the drawdown operation of reservoirs is the study of environmental impacts in the event of a complete discharging event from a full reservoir state, given the huge amount of water to be emptied and the duration of the operation, which can last for days. Logically, the impact will be greater when it comes to diversion basins. It is imperative to evaluate the physical impact of prolonged flooding in downstream areas, especially in areas of special ecosystem sensitivity. Additionally, on certain occasions, a physicochemical impact can be produced on flooded areas when the chemical composition of the discharged water differs from the usual concentrations. Exceedance probability curves for conductivity allow identification and assessment of potential impacts of offstream reservoirs. This article presents a practical case assessment of the impact of an off-stream reservoir located in evaporitic soils with a high content of salts increasing the chemical concentration of stored water that is distributed in different compositional strata. The emptying is carried out on a wetland with important ecological value, and the impact of extension and duration of the flood on the wetland are studied, as well as exposure to the presence of water with different chemical concentrations over the time the incident lasts.
      原文链接:
    • NSTL
    • Elsevier

    Hydrologic impacts of sewershed-scale green infrastructure retrofits: Outcomes of a four-year paired watershed monitoring study

    Boening-Ulman, Kathryn M.Winston, Ryan J.Wituszynski, David M.Smith, Joseph S....
    15页
    查看更多>>摘要：Cities across the world are implementing green infrastructure (GI) retrofits to manage stormwater, but limited research has been performed to quantify the hydrologic impact of these efforts at the watershed-scale. To fill this knowledge gap, this study aimed to monitor and evaluate the impact of GI stormwater control measures (SCMs) on sewershed-scale runoff hydrology across multiple treatment sewersheds with varying GI implementation. A paired watershed approach was applied in which a control (i.e., no GI), and three treatment sewersheds (208 bioretention cells and 8,400 m(2) of permeable pavement in total) were monitored from 2016 to 2019 in Columbus, Ohio, USA. Further infrastructure changes, such as lining sanitary sewer laterals to prevent infiltration and inflow of stormwater, were anticipated to counterbalance the hydrologic improvements provided by the GI retrofits by routing more stormwater to the storm sewers. Significant decreases in runoff depths and peak flow rates (35-62% and 40-58% respectively) and increases in lag-to-peak (6-64%) were observed in the treatment sewersheds following the installation of GI retrofits. Compared to the control sewershed, the treatment sewersheds had slight increases (1-3 mm) in runoff thresholds and lower runoff coefficients post-GI. Following additional infrastructure changes, increases in volume and rate of flows were observed, but hydrologic indicators did not significantly differ from pre-GI levels (i.e., no net impact of the overall project on runoff hydrology). These responses indicated that sewershed-scale GI implementation successfully mitigated peak flow rates; however, the additional infrastructure improvement projects appear to have neutralized volume reductions by routing additional stormwater to the GI. Results confirm the impacts of sewershed-scale GI retrofits; however, research investigating the optimization of GI retrofit location, climate change impacts, and GI design, construction, and maintenance to maximize benefits of distributed SCMs in urban areas should be further explored.
      原文链接:
    • NSTL
    • Elsevier

    Estimating hydrological consequences of vegetation greening

    Luan, JinkaiMiao, PingTian, XiaoqiangLi, Xiaojie...
    14页
    查看更多>>摘要：Large-scale afforestation program has alleviated environmental problems to some extent in China. However, the response of hydrological processes to vegetation greening at different catchments remains unclear. This study identified the impact of vegetation changes on runoff (Q), evapotranspiration (ET), and soil water storage (SW), as well as their relationships and sensitivities based on a coupled SWAT-PML model for 23 catchments from 2000 to 2018 in the Yellow River Basin (YRB). Results show that leaf area index (LAI) was significantly (p < 0.05) increased in 72.2% of the YRB area. Vegetation greening decreased SW and Q, but increased ET in all catchments. The effects of vegetation greening on Q and ET were contrasting with axisymmetric fluctuation distribution. The changes in SW, ET, and Q were strongly correlated with the changes in LAI. Sensitivity of the changes in ET and Q to LAI changes increased when the climate becomes drier. Our study suggests that the vegetation greening followed by the afforestation policy implementation has caused gradually increasing impacts on Q and ET. However, such effects are spatially heterogeneous due to different degrees of increase in LAI and aridity conditions. Given the water crisis problem in the YRB, afforestation activity should be taken into consideration of the increasing water demand and the negative effects of vegetation greening on water resources in the future.
      原文链接:
    • NSTL
    • Elsevier

    Multi-scale evaluation of global evapotranspiration products derived from remote sensing images: Accuracy and uncertainty

    Zhu, WenbinTian, ShengrongWei, JiaxingJia, Shaofeng...
    20页
    查看更多>>摘要：Advances in satellite remote sensing (RS) techniques have greatly prompted the development of large-scale evapotranspiration (ET) models, yielding several freely available global ET products. A comprehensive evaluation on these products is necessary for selecting the most suitable ET products and developing large-scale ET models step forward. In this study, the accuracy and uncertainty of five RS-based global ET products (MOD16, SSEBop, GLEAM, AVHRR, and BESS) were evaluated at multi scales. At point scale their accuracy was evaluated through a direct comparison with in-situ observations from 94 worldwide flux towers. Results indicate that accuracy differences of these five products vary with statistical metrics and land cover types. The combination of all statistics illustrates that GLEAM and AVHRR outperform three other products, which is consistent with the findings of most previous continental-scale studies. The accuracy at basin scale was assessed through water balance analysis across 19 big river basins. BESS is found to be the product that is superior to four other ET products at both monthly and multi-annual scale, which may be related with its low random error at point scale. The uncertainty of these five products at pixel scale was assessed by the three-cornered hat (TCH) method and comparison analysis. The TCH outputs reveal that BESS and SSEBop are the two products with the lowest and largest relative uncertainty, respectively. That explains the good performance of BESS at basin scale from another perspective. As for the two MODIS-based ET products (MOD16 and SSEBop), their accuracy at FLUXNET site scale is comparable in monthly ET estimation. However, SSEBop has special advantage in the capture of multiyear ET patterns. The comparison analysis indicates that SSEBop is the product that agrees best with the ensemble mean not only on a global scale but also in four of the six continents. Our results imply that it is difficult or even impossible to figure out the best ET product in all respects. The selection of ET products for scientific research should consider their performance difference in spatial scale as well as the influence of land cover and climate conditions.
      原文链接:
    • NSTL
    • Elsevier