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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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    Parallel cooperation search algorithm and artificial intelligence method for streamflow time series forecasting

    Feng, Zhong-kaiShi, Peng-feiYang, TaoNiu, Wen-jing...
    14页
    查看更多>>摘要：Reliable streamflow prediction is an important productive information in the hydrology and water resources management fields. As used to forecast the nonlinear streamflow time series, the conventional artificial intelligence model may suffer from local convergence defect and fail to track the dynamic changes of the hydrological process when the model parameters and network structure are not well identified. Thus, this research develops a practical hydrological forecasting model based on parallel cooperation search algorithm (PCSA) and extreme learning machine (ELM), where the standard ELM method is chosen as the basic forecasting model, and then the PCSA method using several smaller and independent subswarms for parallel computation is used to determine satisfying input-hidden weights and hidden biases of the ELM model. The proposed model is used to forecast the nonlinear streamflow time series of several real-world hydrological stations in China. The results demonstrate that the proposed model outperforms the standard ELM model in various evaluation indicators. Thus, the key contributions of this study lie in two aspects: (1) for the first time, the parallel computing technique is developed to improve the global search ability and resources utilization efficiency of the emerging cooperation search algorithm; (2) an artificial intelligence model coupled with parallel evolutionary optimizer is proposed to improve the prediction accuracy of hydrological time series.
      原文链接:
    • NSTL
    • Elsevier

    Developing pedotransfer functions using Sentinel-2 satellite spectral indices and Machine learning for estimating the surface soil moisture

    Sedaghat, AzadehShahrestani, Mahmoud ShabanpourNoroozi, Ali AkbarNosratabad, Alireza Fallah...
    17页
    查看更多>>摘要：To estimate the surface soil moisture (SM) using a combination of new spectral indices and methods of Random Forrest (RF) and Multiple Linear Regression (MLR), 11 pedotransfer functions (PTF1-11) were developed by combining basic soil properties (clay, silt/sand, and bulk density) and spectral indices of Sentinel-2 satellite. In this study, 124 surface soil samples were randomly taken from three regions including Telo in Tehran province, Ivaneki in Semnan province, and Borujerd in Lorestan province, Iran. The results showed that the accuracy of the RF method was considerably higher compared to the MLR method. The SM was better estimated using water spectral indices (such as Normalized Difference Water Index (NDWI) and Surface Water Capacity Index (SWCI)), along with the basic properties of soil as inputs of PTF7. In the training and testing steps, the Root Mean Square Error (RMSE) decreased from 0.041 and 0.05 (cm3 cm-3) in PTF1 to 0.028 and 0.039 in PTF7, respectively. The average values of RMSE, Akaike Information Criterion (AIC), coefficient of determination (R2) and Relative Improvement (RI) of the RF method were 0.028 (cm3 cm-3), -559, 0.79 and 0.001, and 0.038 (cm3 cm-3), -279, 0.73 and -0.006 for the training and testing steps of all PTFs, respectively. While, these values for the MLR method were 0.032 (cm3 cm-3), -542, 0.69 and 0.0003, and 0.043 (cm3 cm-3), -269, 0.63 and 0.002 for the training and testing steps, respectively. Due to the low values of MBE, it was possible to disregard the overestimation of the results. The evaluation of results for predictor importance indicated that among the basic properties, clay percent has a significant effect on estimation of SM. These results show that spectral indices alone are not suitable estimators for SM estimation. It suggests using basic soil properties and spectral indices to estimate the SM.
      原文链接:
    • NSTL
    • Elsevier

    Runoff and sediment response to deforestation in a large Southeast Asian monsoon watershed

    Zhao, BaoxuLei, HuiminYang, DawenYang, Shuyu...
    13页
    查看更多>>摘要：Deforestation has been reported to increase annual streamflow, baseflow, and sediment load in many parts of the world. However, studies about the hydrological effects of deforestation are scant in the tropical monsoon region. In this study, these effects were examined in the Upper Chao Phraya River basin (UCPRB) which is a typical tropical monsoon basin and is an important area of water resources in Thailand. A significant breakpoint for annual streamflow and annual precipitation in the entire UCPRB is identified as 1993, and this breakpoint is also identified for annual baseflow in most upstream sub-basins during the past decades (1981-2015). Significant increasing trend is detected in the annual suspended sediment load of the Wang River sub-basin. Land use maps generated by a CA-Markov model suggest that continuous deforestation occurred during the study period. The contributions of climate change and deforestation to the hydrological and sedimentary changes are then attributed within the Budyko Framework. Precipitation increment dominates the annual streamflow increment in the entire UCPRB and the annual baseflow increment in the Ping River sub-basin, and deforestation dominates the annual streamflow increment in the upstream sub-basins, the annual baseflow increment in most of the upstream sub-basins, and the increasing suspended sediment load in the Wang River sub-basin. The hydrological and sedimentary response to deforestation is then quantified. In the entire UCPRB, one percent reduction of the forest cover can increase the annual streamflow by 1.9%. In the upstream sub-basins, one percent reduction of the forest cover can increase the annual streamflow and annual baseflow by 2.5%-5.4% and 2.6%-6.7%, respectively. One percent reduction of the forest cover can increase the annual suspended sediment load by 8.7%. These findings will help develop better understanding of land use management in the UCPRB for water-soil conservation.
      原文链接:
    • NSTL
    • Elsevier

    Groundwater table fluctuations in a coastal unconfined aquifer with depth-varying hydraulic properties

    Yang, MingzheZheng, YihaoXu, XinghuaLiu, Haijiang...
    8页
    查看更多>>摘要：While many analytical studies have been carried out to examine groundwater table fluctuations in tidallyinfluenced coastal unconfined aquifers, they generally focused on homogeneous aquifers and overlooked actual field situations with sound physical underpinnings. Taking the inelastic intergranular movement into account, this study presented a new governing equation under the Dupuit assumption, in which the compressibility factor was considered to incorporate the vertical variations of both effective porosity and hydraulic conductivity. An analytical solution was derived using Taylor expansion and the perturbation method. Timevarying groundwater table from the present model lies in between the homogeneous solutions predicted using grain parameters in the upper and bottom aquifer layers, which is almost overlapped with the homogeneous solution if applying the grain parameters in the middle layer. Effects of depth-varying hydraulic properties were further examined with respect to the total fluctuation range and phase shift of the groundwater table, which quantitatively present the differences between the present solution and Nielsen (1990) homogeneous solution. Such differences become significant for the large compressibility factor. In addition, it was mathematically proved that compressibility factor has no effect on the mean water surface as landward distance approaches infinity.
      原文链接:
    • NSTL
    • Elsevier

    Multi-objective risk analysis for flood control operation of a complex reservoir system under multiple time-space correlated uncertainties

    Lu, QingwenZhong, Ping-anXu, BinHuang, Xin...
    17页
    查看更多>>摘要：Many uncertainties are involved in flood control operation of a multi-reservoir system and result in risks for the system. Risk analysis for reservoir flood control operation is essential for decision making. Traditional flood control risk analysis only takes flood forecast error as the main risk source, ignoring the influence of dynamic control of flood-limited water level on reservoir initial water level for flood regulation. In this study, the spatial correlation of reservoir initial water level errors and the spatiotemporal correlation of flood forecast errors are identified via copula function. A risk analysis model considering both upstream and downstream is established for multi-objective flood control operation of a complex reservoir system, coupling multi-dimensional uncertainties of reservoir initial water levels, flood forecast errors, reservoir capacity curve errors, reservoir discharge curve errors and river flood routing errors. The impact of multiple risk sources with spatiotemporal correlations on reservoir flood control operation is then evaluated and the competitive tradeoff between flood control risks in upstream and downstream analyzed. The model is applied to a mixed four-reservoir system in Pi River Basin in China. Results indicated that 1) there is a strong correlation between the reservoir initial water level errors in space and also between the flood forecast errors in space and time, which can be effectively described by copula function, and ignoring the correlations will underestimate the flood control risk; 2) the two objective values of upstream and downstream show a clear competitive relationship, and the solution that prefers one objective has low risk marginal benefit, thus choosing a compromise solution can balance risks; 3) coupling the initial water level uncertainty reduces the flood control risk caused by the flood forecast errors to a certain extent, but also lead to the increase of extreme risk loss.
      原文链接:
    • NSTL
    • Elsevier

    Non-point contaminant source identification in an aquifer using the ensemble smoother with multiple data assimilation

    Xu, TengZhang, WenjunJaime Gomez-Hernandez, J.Xie, Yifan...
    17页
    查看更多>>摘要：Proper identification of groundwater contaminant sources is vital to assess groundwater contamination. However, the majority of previous studies focuses on point source identification; only a few works have been conducted for non-point source parameter identification. Here, we employ the ensemble smoother with multiple data assimilation (ES-MDA) to simultaneously identify the spatial architecture of non-point contaminant sources and the related release information. Three different shapes of non-point contaminant sources are considered, an ellipse, a circle, and an irregular shape. We test the applicability of the ES-MDA for the simultaneous identification using three scenarios in a synthetic confined aquifer by assimilating concentration observations from alltime steps multiple times. The results demonstrate that the ES-MDA is capable to accurately identify both regular and irregular non-point contaminant source information; the accuracy of the identification can be improved by increasing the number of iterations.
      原文链接:
    • NSTL
    • Elsevier

    A hybrid deep learning framework with physical process description for simulation of evapotranspiration

    Chen, HanHuang, Jinhui JeanneDash, Sonam SandeepWei, Yizhao...
    15页
    查看更多>>摘要：Evapotranspiration (ET) estimation models can be broadly classified as statistical or physical process based models. However, assuming the limitation of individual approaches, the integration of these two approaches has become a challenging task for ET simulation under varying surface and climatic conditions. To address this issue, a revised Penman-Monteith (PM) formula that uses a non-linear exponential Clausius-Clapeyron relationship was proposed in this study. The improved PM formula was further coupled into the loss function of the deep learning (DL) model, and subsequently, a hybrid DL model was formulated. The hybrid DL model with improved physical conceptualization considered the constraints of surface energy balance and turbulent diffusion processes in the ET simulation. The performance of the hybrid DL model was verified at 212 flux sites from the FLUXNET that contain ten types of underlying surfaces across the globe. The results revealed that as compared to the original DL model, the hybrid DL model improved the predictive capability of ET. The average root-mean-square-error (RMSE) and mean absolute percentage difference (MAPD) reduced by 12.1 W/m(2) and 5.7%, respectively for latent heat flux (LE) simulation. Furthermore, the hybrid DL model also performed better than the original DL model in predicting the extreme events (such as ET under drought and heatwave conditions) which justifying its improved generalization capability. Sensitivity analysis outcomes showed that the vegetation parameters highest influence for ET simulations at the 212 flux sites, followed by soil parameters and meteorological parameters. The hybrid DL model was further applied to map the inter-seasonal distribution of global ET across twelve months of the year 2015 with five global ET products as the benchmark. Certainly, this research achieved the seamless integration of machine learning-based ET model and physical mechanism-based ET model and provided a new dimension for ET simulation. The hybrid DL model could be adopted to generate continuous ET datasets across regional and global scales.
      原文链接:
    • NSTL
    • Elsevier

    Simultaneous observations revealed the non-steady state effects of a tropical storm on the export of particles and inorganic nitrogen through a river-estuary continuum

    Lin, JingjieKrom, Michael D.Wang, FenfangCheng, Peng...
    13页
    查看更多>>摘要：An important consequence of storms in river-estuary systems is major changes in hydrology and nutrients being fluxed from the land to the coastal ocean. However, the impacts of storms on the nature and amount of dissolved inorganic nitrogen (DIN) in the river-estuary continuum are poorly understood. In this study, two week's continuous observations on two lower riverine fixed stations and an estuarine fixed station in the Jiulong River (SE China) were carried out during a complete storm event in June 10th to 23rd 2019. Suspended particulate matter (SPM), nitrogen species and their isotopic ratios, nitrifying and denitrifying functional genes were measured. The increased river discharge caused the freshwater-brackish water boundary to move downstream and altered the pattern of particle distribution and the location of the estuarine turbidity maximum. The increased river SPM and inorganic nitrogen was associated with watershed soil erosion, sediment scour and land use. Both in the river and estuary, the peak concentration of ammonium arrived faster than nitrate. Apart from river inputs, there was an additional increase of 40 +/- 8% of DIN supplied within the tidal river and estuary. The additional DIN mostly came from resuspended sediments and catchment runoff, while increased nitrate also came from soil and ground waters, increased nitrification and decreased denitrification in the estuary. These results suggest that during baseflow conditions the wetlands in the upper estuary acts as a temporary nutrient trap and biogeochemical incubator, while in storms the transformed pollutant N was fluxed from the river-estuary continuum to the adjacent coastal areas.
      原文链接:
    • NSTL
    • Elsevier

    Rainfall estimation from surface soil moisture using SM2RAIN in cold mountainous areas

    Lai, YaoTian, JieKang, WeimingGao, Chao...
    13页
    查看更多>>摘要：Rainfall across mountainous areas is vital for the water supply and ecosystem services of arid watersheds. Rain gauges are the most common method to measure rainfall, but these are sparse in mountainous areas. Satellite and reanalysis products can provide rainfall information over a large area but often have large uncertainty in high elevation environments. A recently developed "bottom-up" approach (SM2RAIN, Soil Moisture to Rain) estimates rainfall from soil moisture dynamics and provides a novel method to estimate rainfall. However, the reliability and accuracy of this method in high-altitude mountainous areas are currently not well understood. This study evaluates the SM2RAIN method under different environmental conditions based on data from 9 in-situ soil moisture and rainfall observation stations in the Qilian Mountains in Northwest China. Subsequently, we compare the Rsim (rainfall estimated using the SM2RAIN in-situ), the global SM2RAIN rainfall product (SM2RAIN-ASCAT) and the reanalysis rainfall product (China Meteorological Forcing Dataset, CMFD) with the in-situ rainfall observations. Results show that the performance of SM2RAIN decreases with increasing elevation. SM2RAIN performs well in alpine meadows, but underestimates rainfall in forestland due to strong interception, and overestimates rainfall in farmland due to irrigation. Meanwhile, SM2RAIN has the potential to evaluate the interception capacity of forestland and the irrigation of farmland. The SM2RAIN-ASCAT and CMFD have similar performances in estimating daily rainfall in the study area. Calibration of SM2RAIN using high spatio-temporal resolution soil moisture products and an advanced bias-correction method can significantly improve rainfall estimation performance in data-scarce mountainous areas.
      原文链接:
    • NSTL
    • Elsevier

    Streamflow decline threatens water security in the upper Yangtze river

    Shi, RuijieWang, TaihuaYang, DawenYang, Yuting...
    12页
    查看更多>>摘要：The annual streamflow in the upper Yangtze River (UYR) declined by 36.6 billion m3 from 1961 to 2015. However, the contributions to this streamflow decline from different tributaries and the underlying causes remain unclear. Here we quantify the streamflow decline in the UYR and the impacts of climate change and human activities using a distributed hydrological model and statistical methods. Results show that the streamflow decline increased from the upstream to downstream regions. Combining hydrological simulation and statistical analysis, the contributions of climate change, human water consumption, reservoir impoundment and human-induced vegetation change on streamflow decline are estimated to be 62.5%, 19.7%, 18.4% and 1.8%, respectively. Specifically, human water consumption growth is consistent with the spatial pattern of population growth and industrial development, and the reservoir impoundments are mainly located in the middle and lower parts of the mainstream. In the Jialingjiang, the tributary with the largest drainage area in the UYR, human activities account for 63.6% of the streamflow decline, with the largest decline induced by human water consumption growth. Under climate change and population growth, the population under water stress (water resources available less than 1000 m3/capita/yr) increases in the Mintuojiang and Jialingjiang, where the major cities are centralized and the population density is high. This study provides a new perspective for understanding the status of water resources in the UYR and offers insights into the sustainable utilization of water resources in the future.
      原文链接:
    • NSTL
    • Elsevier