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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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    Assessing multi-year-drought vulnerability in dense Mediterranean-climate forests using water-balance-based indicators

    Cui, GuotaoMa, QinBales, Roger
    18页
    查看更多>>摘要：Water availability in mountain forests affects vegetation response to drought, which in turn changes evapotranspiration (ET). We investigated water-balance indicators based on precipitation (P) minus ET to assess Mediterranean-climate forest vulnerability to multi-year droughts. We used the drought-vulnerable dense mixed-conifer forests of California's Sierra Nevada, which includes 78 groves of giant sequoia as study area. With long-term Landsat-based ET data during 1985-2018, water-stress patterns at 30-m resolution during two historical droughts (1987-92 and 2012-15) were analyzed. Canopy moisture loss and tree mortality were used as indices of drought vulnerability. Using cumulative multi-year P-ET as an indicator, groves that were water stressed in 1987-92 were more vulnerable in California's unprecedented 2012-15 drought. Historical-minimum annual P-ET is an indicator of water stress, explaining 32% and 29% of the variances of canopy moisture loss and tree mortality, respectively. As an extreme test to explore potential vegetation response, we trained a deep-learning Long Short-Term Memory (LSTM) model to project ET during hypothetical extended-drought scenarios. The LSTM model reasonably predicted ET with r(2) of 0.72 for the testing period. Annual P-ET using LSTM-based ET agreed (r(2) = 0.99) with that using ET values from Landsat. Historical water-stress-prone areas were projected to suffer larger ET decreases and to experience more-severe stress during a 12-yr drought scenario. Water stress is more severe in lower-elevation forests, versus mid-to-high areas that have higher precipitation and shorter growing season under current climate. Our study provides water-balance-based indicators to project drought vulnerability and assess effects of disturbance in forests in a warming climate.
      原文链接:
    • NSTL
    • Elsevier

    Long-term succession of Microcystis genotypes is driven by hydrological conditions and anthropogenic nutrient loading in a large shallow lake

    Huo, ShouliangXiao, ZheLi, XiaochuangZhang, Hanxiao...
    8页
    查看更多>>摘要：Microcystis blooms that are caused by intensified human activities and global warming have become a challenging environmental problem in global lakes and reservoirs. Research has focused on Microcystis genotypes to understand their proliferation and the development of blooms, although knowledge gaps exist regarding how Microcystis genotype succession occurs over long-term time scales. In this study, high-throughput sequencing was used to investigate decade-long successional patterns of Microcystis genotypes in the large shallow Lake Chaohu that has long suffered from Microcystis blooms. Microcystis populations exhibited high overall genetic diversity, with 11,431 genotypes, and these were relatively stable over the last similar to 70 years, with 339 shared core genotypes and 1 dominant genotype. Microcystis genotype succession exhibited three distinct historical phases corresponding to 1944-1960, 1964-1973, and 1976-2015. These successional patterns were clearly influenced by dam construction in 1963, and subsequent nutrient enrichment following the 1970s. After dam construction, increased hydraulic retention times and slowing of hydrodynamic conditions influenced Microcystis genotype diversity by altering population composition and decreasing genotype richness. Populations and dominant genotypes rapidly returned after dam construction, combined with increased inferred interactions among genotypes. Network analysis also indicated that low abundance Microcystis genotypes, rather than dominant genotypes, may be keystone taxa across the decadal-scale co-occurrence network of Microcystis population.
      原文链接:
    • NSTL
    • Elsevier

    A hybrid approach for integrated surface and subsurface hydrologic simulation of baseflow with Iterative Ensemble Smoother

    Delottier, H.Therrien, R.Young, N. L.Paradis, D....
    19页
    查看更多>>摘要：Integrated surface and subsurface hydrologic models are particularly well suited for the simulation of baseflow as exchange fluxes does not rely on boundary conditions. Regional scale hydrologic models are of particular interest as they can provide guidance to stakeholders toward sustainable water resources management. However, integrated hydrologic models are rarely considered at the regional scale because their computational costs usually prevent efficient model calibration and predictive uncertainty analysis. Moreover, estimation of baseflow and each water budget component usually requires additional post-processing steps. In this paper, we thus aim here to provide a hybrid approach for the application of an integrated hydrologic model at the regional scale when low-flow processes are of primary concern. A surface water mass balance module has been developed to solve the hydrological mass balance from precipitations and temperature datasets. This module calculates potential infiltration fluxes that are used as input to the integrated modeling platform HydroGeoSphere (HGS). This approach provides a computationally tractable integrated model where low-flow processes are explicitly considered, baseflows generated in an integrated fashion, and each water budget component accessible. The model is applied to a region covering 36 900 km(2) in the Southeastern part of the province of Quebec, Canada. Thanks to the computational efficiency of the approach, a rigorous mathematical parameter estimation, the Levenberg-Marquardt form of the Iterative Ensemble Smoother, can be considered to calibrate the model to baseflow of eight main rivers, snow water equivalent and evapotranspiration. An ensemble of 187 equally-probable realizations was used for history matching of observations and for the non-linear uncertainty analysis. An improved representation of baseflow can be linked to an appropriate non-linear uncertainty quantification through an efficient integrated surface and subsurface hydrologic model to support managing water resources at the regional scale.
      原文链接:
    • NSTL
    • Elsevier

    Distributed ANN-bi level two-stage stochastic fuzzy possibilistic programming with Bayesian model for irrigation scheduling management

    Wang, YouzhiYin, HuijuanGuo, XinweiZhang, Wenge...
    14页
    查看更多>>摘要：To optimize irrigation amount and date, and water allocation target across spatially distributed crops under uncertainties and risks, the framework of the distributed ANN-bi level two-stage stochastic fuzzy possibilistic programming with Bayesian (distributed ANN-BLTSFPPB) model was established by integrating bi-level programming, two stochastic programming (TSP), fuzzy possibilistic programming, Bayesian, downside risk with the distributed ANN model. Decisions making of distributed crops were conducted by building distributed model to optimize decisions at several spatially heterogeneous units. The risks of economic benefit and water productivity were considered and measured by the downside risk approach, and uncertainties of runoff were presented as fuzzy normal distribution numbers to reduce uncertainties and improve robustness of decisions. Besides, tradeoffs between economic benefit and risks in the upper layers, and contradictory relationships across objectives at the upper and lower layers were balanced by the BLTSFPPB model. Moreover, effects of water right trading on economic benefit with considerations of subjectivities of managers under different hydrological years were quantified by Bayesian approach. Calculation efficiencies of the distributed AquaCrop-optimization model were effectively improved by establishing the distributed ANN-BLTSFPPB, making it easy-to-use and expanding its applications. The developed model was applied to Yingke district to verify its application. The results disclosed that economic benefit and yield enlarged, and water productivity and risks lessened when the water right trading was considered. The results could offer insight into how to establish the distributed ANN model to replace distributed simulation model and further couple with optimization model to conduct spatially distributed decisions and improve calculation efficiencies for managers. They can reach key tradeoffs across economic benefit, yield and risks, and support in-depth analysis about how water right trading affects system outcomes.
      原文链接:
    • NSTL
    • Elsevier

    Sediment transport and morphological changes in shallow flows modelled with the lattice Boltzmann method

    Stipic, DaniloBudinski, LjubomirFabian, Julius
    15页
    查看更多>>摘要：A novel form of the lattice Boltzmann method for sediment transport and morphological changes is developed and implemented. The depth averaged shallow water equations (SWE) have been used to reach the flow pattern, the advection-diffusion equation (ADE) was exploited to determine sediment concentration in the water, bed load was determined by the active layer mass conservation equation (ALMC), while the morphological changes of the river bed were determined by the global active layer mass conservation equation (GALMC), the Exner equation. The SWE are solved by the multiple-relaxation-time lattice Boltzmann method, (MRT-LBM), while the Bhatnagar-Gross-Krook (BGK-LBM) approach has been used for solving the ADE, ALMC and GALMC. New forms of the equilibrium function for solving the ALMC and GALMC are presented, using the D2Q9 lattice. Dedicated sediment-related equations are created for each sediment-size class. Additional dedicated terms in the transport equations take care of particle exchange between the suspension and the river bed, as well as of river bed deformation. The model has been verified on a experimental section of the Danube river. The results have been compared to the measured ones, and to the results obtained by the finite difference method (FDM). Very good agreement between the results is achieved, indicating that the LBM can be successfully used for simulation of flow and sediment related processes in natural watercourses, characterized by complex geometry and morphology, and lack of uniformity in sediment composition.
      原文链接:
    • NSTL
    • Elsevier

    Comparison of different quantile delta mapping schemes in frequency analysis of precipitation extremes over mainland Southeast Asia under climate change

    Qin, XiaoshengDai, Chao
    16页
    查看更多>>摘要：This study investigated the frequency analysis of precipitation indices of maximum daily precipitation amount (Rx1day), maximum 5-day cumulative precipitation amount (Rx5day), and maximum length of consecutive dry days (CDD) using various bias-correction schemes over mainland Southeast Asia (MSEA). The bias-correction schemes were based on quantile delta mapping (QDM) with different strategies in selecting the data series, including monthly correction (MC), annual correction (AC), peak correction using annual raw data (PCRAW), and annual correction using extreme-index data series (ACEX). Two regional climate model (RCM) outputs from CORDEX-SEA and APHRODITE rainfall datasets were used as modelled and observed data for methodology verification. The study first compared four frequency analysis methods based on generalized extreme value (GEV), Gumbel (GB), Log-Pearson Type III (LP3), and Lognormal (LOGN) distributions, at 9 selected sites over MSEA, and found that LP3 was the best choice for frequency analysis for the study region. Then, the study compared the four bias-correction schemes at both individual sites and all grids over the entire MSEA and indicated that the PCRAW was the best performer in terms of bias-correction for frequency information. Finally, the study gave an ensembled projection of future extreme indices with 200-yr return based on seven CORDEXSEA RCMs and suggested a general increasing trend of all indices over MSEA. The study explored the effect of uncertainty originated from adopting various bias-correction schemes in mapping future frequency of precipitation indices and is valuable in revealing the spatiotemporal distribution of precipitation extremes over large areas under climate change which is important for flood/drought risk assessment and adaptation planning.
      原文链接:
    • NSTL
    • Elsevier

    The sensitivity of snow hydrology to changes in air temperature and precipitation in three North American headwater basins

    Rasouli, KabirPomeroy, John W.Whitfield, Paul H.
    19页
    查看更多>>摘要：Whether or not the impact of warming on mountain snow and runoff can be offset by precipitation increases has not been well examined, but it is crucially important for future downstream water supply. Using the physically based Cold Regions Hydrological Modelling Platform (CRHM), elasticity (percent change in runoff divided by change in a climate forcing) and the sensitivity of snow regimes to perturbations were investigated in three well-instrumented mountain research basins spanning the northern North American Cordillera. Hourly meteorological observations were perturbed using air temperature and precipitation changes and were then used to force hydrological models for each basin. In all three basins, lower temperature sensitivities of annual runoff volume (<= 6% degrees C-1) and higher sensitivities of peak snowpack (-17% C-1) showed that annual runoff was far less sensitive to temperature than the snow regime. Higher and lower precipitation elasticities of annual runoff (1.5 - 2.1) and peak snowpack (0.7 - 1.1) indicated that the runoff change is primarily attributed to precipitation change and, secondarily, to warming. A low discrepancy between observed and simulated precipitation elasticities showed that the model results are reliable, and one can conduct sensitivity analysis. The air temperature elasticities, however, must be interpreted with care as the projected warmings range beyond the observed temperatures and, hence, it is not possible to test their reliability. Simulations using multiple elevations showed that the timing of peak snowpack was most sensitive to temperature. For the range of warming expected from North American climate model simulations, the impacts of warming on annual runoff, but not on peak snowpack, can be offset by the size of precipitation increases projected for the near-future period 2041-2070. To offset the impact of 2 degrees C warming on annual runoff, precipitation would need to increase by less than 5% in all three basins. To offset the impact of 2 degrees C warming on peak snowpack, however, precipitation would need to increase by 12% in Wolf Creek in Yukon Territory, 18% in Marmot Creek in the Canadian Rockies, and an amount greater than the maximum projected at Reynolds Mountain in Idaho. The role of increased precipitation as a compensator for the impact of warming on snowpack is more effective at the highest elevations and higher latitudes. Increased precipitation leads to resilient and strongly coupled snow and runoff regimes, contrasting sharply with the sensitive and weakly coupled regimes at low elevations and in temperate climate zones.
      原文链接:
    • NSTL
    • Elsevier

    Simulation of dew point temperature in different time scales based on grasshopper algorithm optimized extreme gradient boosting

    Zeng, WenzhiLei, GuoqingWu, LifengChen, Haorui...
    15页
    查看更多>>摘要：Dew point temperature (Tdew) plays an important role in hydrology, meteorology, and other related research. This study evaluated the ability of a new machine learning model (hybrid extreme gradient boosting with grasshopper optimization algorithm (GOA-XGBoost)) to estimate Tdew and compared it with two other tree-based models (XGBoost and random forest (RF)). We collected meteorological data namely actual vapor pressure (ea), maximum air temperature (Tmax), minimum air temperature (Tmin), maximum relative humidity (RHmax), minimum relative humidity (RHmin), atmospheric pressure (Pa), 2 m high wind speed (Ud), during 2016-2019 on daily and hourly time scales from the Sijiqinglin station in China to train, test, and validate each model. The results showed that the GOA-XGBoost model performed best, and the RF model had severe over-fitting problems during the validation phase at daily time scale. The models showed the best accuracy and stability when the input was ea (on average R2 =1.000, RMSE = 0.296 degrees C, MBE = 0.001 degrees C, MAE = 0.167 degrees C, and KGE = 0.991). The models had more significant errors when the inputs were Tmax, Tmin (on average R2 = 0.721, RMSE = 6.756 degrees C, MBE = -0.101 degrees C, MAE = 5.071 degrees C, and KGE = 0.771). The estimation loss exhibited by the models were similar for the hourly and daily scale patterns. T and RH were the most basic meteorological factors and adding extraneous factors would affect the estimation accuracy of the model. The variability of meteorological data varied less on an hourly scale than on a daily scale. Therefore, the accuracy of the models was higher, but the data set and the volume of operations became larger. This led to a possible reduction in model stability, but the hourly scales are better suited for assessing the effects of simulations in extreme situations. Taking accuracy and stability into account, the GOA-XGBoost model was the best model and the most practical input for both time scales was ea. Therefore, in subsequent studies, the GOA-XGBoost model can be combined with the input ea to estimate Tdew accurately.
      原文链接:
    • NSTL
    • Elsevier

    Influence of low-frequency variability on groundwater level trends

    Baulon, LisaAllier, DelphineMassei, NicolasBessiere, Helene...
    20页
    查看更多>>摘要：Estimating groundwater level evolution is a major issue in the context of climate change. Groundwater is a key resource and can even account in some countries for more than half of the water supply. Groundwater trend estimates are often used for describing this evolution. However, the estimated trend obviously strongly depends on available time series length, which may be caused by the existence of long-term variability of groundwater resources. In this paper, using a groundwater level database in Metropolitan France as an example, we address this issue by exploring how much trend estimates are sensitive to low-frequency variability of groundwater levels. Database consists of relatively undisturbed groundwater level time series regarding anthropogenic influence (water abstraction by either continuous or periodic pumping). Frequent changes in trend direction and magnitude are detected according to time series length, which can eventually lead to contradictory interpretations of the groundwater resource evolution, as presented in first part of this article. To assess whether low-frequency variability - known to originate from climate variability - can induce such modifications of trends, we explored in a second step the multi-time scale variability of groundwater levels using a methodology based on discrete wavelet transform. Most of the time series displaying changing trends depending on time series length corresponded to aquifers with high-amplitude low-frequency variability of groundwater levels. Two predominant low-frequency components were detected: multi-annual (-7 years) and decadal (-17 years). We finally examined how much those two low-frequency components may affect trend estimates on the longer time period available. For this purpose, we individually removed each of both components from the original times series by discrete wavelet filtering and re-estimated trends in the filtered groundwater level time series. The results showed that the groundwater level trends were highly sensitive to the presence of any of these low frequency components, which may then strongly influence the estimated trends either by exaggerating or mitigating them. These results emphasize that i) attributing the estimated trends only to climate change would be hazardous given the large influence of low-frequency variability on groundwater level trends, ii) estimation of trends in hydrological projections resulting from General Circulation Models (GCM) outputs in which low frequency variability is not well represented would be subject to strong uncertainty, iii) a potential change in the amplitude of internal climate variability - e.g. increasing or decreasing low-frequency variability - in the next decades may lead to substantial changes in groundwater level trends.
      原文链接:
    • NSTL
    • Elsevier

    Hydrogeochemical characteristics and processes of groundwater in an over 2260 year irrigation district: A comparison between irrigated and nonirrigated areas

    Gao, YanyanChen, JieQian, HuiWang, Haike...
    15页
    查看更多>>摘要：A comprehensive understanding of groundwater chemistry and its evolution in irrigation districts is essential for irrigation management. In this study, with emphasis on a comparison between irrigated and nonirrigated areas, the groundwater chemistry and hydrogeochemical processes of a typical irrigation district with an irrigation history of over 2260 years were studied to clarify the effects of long-term irrigation on groundwater quality. Based on 107 water samples collected from across the study area, a comprehensive analysis was conducted using multivariate statistics, stable isotope analysis, and hydrogeochemical modeling. The results showed that the variation range and average concentrations of almost all the ions in the irrigation district are much greater than those in the nonirrigated areas. The groundwater in the nonirrigated areas could be characterized by low TDS and HCO3 or HCO3 center dot SO4 types, whereas the groundwater in the irrigation district could be characterized by complex water types and high TDS. Stable isotopes of hydrogen and oxygen indicated that the groundwater in the irrigation district experienced strong evaporation. The calculated groundwater residence time showed that it takes approximately 2180 years for the groundwater to flow through the irrigation district. Some old irrigation water was present, and it influenced the current groundwater chemistry in the study area. The processes forming the current groundwater chemistry in the irrigation district can be formulated as: mixing -> evaporation -> water-rock interaction. For mixing, the proportions of rainfall, irrigation water from the Jing River, and lateral recharge from the nonirrigated areas were found to be approximately 30%, 49%, and 21%, respectively. For evaporation, the ratio based on the TDS was 3.83 when comparing the groundwater in the irrigation district with the mixed water after evaporation. Hydrogeochemical modeling showed that the irrigation area is a potential carbon source. The dissolution of halite and gypsum, the precipitation of calcite and dolomite, CO2 degassing and Na-Ca exchange are the main chemical reactions in the geochemical evolution of groundwater. The lesson learned from this irrigation district is that long-term irrigation will lead to salinization and complexity of the groundwater. Hence, in the water resource management of irrigation districts, attention should not only be paid to the balance of water quantity, but also to the balance of salts and the hydrochemical evolution of groundwater.
      原文链接:
    • NSTL
    • Elsevier