查看更多>>摘要：To explore the impact of climate change on snow cover and spring soil moisture (SM) in areas with seasonally frozen soil, snow cover parameters and spring SM for different land use types in Northeast China are extracted based on remote sensing snow cover and SM products. Snow cover parameters include snow days (SD), first day of snow cover (FSD), last day of snow cover (LSD), maximum snow depth (MSD) and average snow depth (ASD). The spatiotemporal variations and correlations between snow cover parameters and spring SM for different land use types are analyzed. The results showed that the average spring SM for different land use types was ordered woodland > farmland > grassland, with obvious woodland and farmland increases. Woodlands had many SD and large snow depths (MSD and ASD) that eventually decreased. Farmland SM increased significantly in spring, which aided crop development. The decrease in grassland spring SM was not obvious, but the snow cover parameters of certain areas decreased notably. Snow cover significantly impacted farmland SM, and correlation coefficients were highest between all snow cover parameters and SM in spring. The correlations between grassland snow cover parameters and SM in April were higher than those in May, but woodland snow cover parameters and spring SM were not correlated. Among the five snow parameters, FSD had the lowest correlation with spring SM, and SD had the greatest impact on SM. These results show the significant relationship between snow cover and SM and reveal relevant patterns. As future climate warming may introduce drought risk to woodland and grassland areas, advance preparations should be made. Farmland areas will continue to maintain appropriate SM, which is beneficial for agricultural development.
查看更多>>摘要：Several versions of the Complementary Relationship (CR) between actual regional evaporation and apparent potential evaporation have recently been proposed. Few studies have compared multiple CR versions side-by-side using datasets spanning various climates and land surfaces. Filling this lack is one purpose of this project. It also investigates how various CR versions respond to changes in spatial and temporal averaging. This study uses multiple years of data from seven eddy-covariance flux stations in Australia, representing a wide range of biomes, along with global ERA5 reanalysis data products. Daily and monthly averages were used for both datasets, and the Australian observations also used weekly and yearly averages. The ERA5 data represent a scale of about 30 km, much larger than the scale represented by the flux station data. A set of five questions regarding the impact of spatial and temporal scaling on CR parameter values and performance are asked and assessed using the two datasets. Four recent CR versions are considered in answering the questions. Due to important differences between FLUXNET and ERA5 data, questions regarding temporal scaling were answered with greater confidence than those regarding spatial scaling. With these data, rescaled versions of the CR performed best overall.
查看更多>>摘要：Streamflow prediction plays a crucial role in water resources systems planning and the mitigation of hydrological extremes such as floods and droughts. Since a variety of uncertainties exist in streamflow prediction, it is necessary to enhance our efforts to robustly address uncertainties and their interactions for improving the reliability of streamflow prediction. This paper presents a stochastic hydrological modeling system (SHMS) for improving daily streamflow prediction by explicitly addressing uncertainties in error and model parameters as well as in forcing data and model outputs. Specifically, the SHMS merges the strengths of the ensemble Kalman filter and the particle filter algorithms for improving the effectiveness and robustness of daily streamflow assimilation. Factorial analysis of variance and variance-based global sensitivity analysis are performed to reveal parameter interactions affecting predictive performance and temporal dynamics of parameter sensitivities, maximizing the accuracy of streamflow prediction. The SHMS has been applied to the Guadalupe River basin located in Texas of the United States to demonstrate feasibility and applicability. Our findings indicate that the SHMS improves upon the well-known ensemble Kalman filter for sequential estimation of hydrological model parameters through a more rapid and accurate convergence of model parameters in streamflow simulation. The SHMS also demonstrates a higher level of skill in streamflow prediction compared to the conditional vine copula model. The proposed SHMS can be applied straightforwardly to other river basins for probabilistic hydrological prediction.
查看更多>>摘要：Water inrush is a typical geological disaster in the process of underground mining. It is crucial to depict potential water inrush areas for mining safety. In this study, mining activity in Dongtan coal mine is under the water inrush threat from deep Ordovician limestone confined aquifers. Tomographic water releasing tests and simultaneous successive linear estimator (SimSLE) were conducted to characterize aquifer heterogeneity by stimulating hundreds of square kilometers. An artificial injection well was firstly introduced to alleviate the influence from identified recharge channels. The estimated parameter distributions indicated that the study area was divided into two separately hydrogeological compartments. Transmissivity (T) and storativity (S) in the north were relatively higher due to water-conducting structures, and more attention should be paid to this region which may develop into water inrush incidents. The southern area is occupied with lower T and S, which indicated relatively worse flow conditions. Auxiliary drawdown recovery data, borehole chemistry variations, drilling fluid losses, and existing geological features further confirmed the estimated parameter distributions. In the end, we concluded that Hydraulic Tomography technique (HT) could obtain aquifer parameter information in large scales and provide supports to formulate reasonably effective water prevention and control schemes before mining deep coal seams.
查看更多>>摘要：This paper presents an investigation on the effect of dam operation on the ensemble Kalman filter (EnKF) performance in a distributed hydrological model based on kinematic wave theory. For this purpose, two flood events in a mountainous catchment in Japan are selected, and the model error parameters for the EnKF implementation are first determined through a series of experiments by varying the input error magnitude, state variable perturbation, and its correlation length. Then, through the assimilation of dam outflow observations, it is shown that special treatment of such measurements is critical in ensuring the success of the filter when flood control operation significantly changes the flow hydrograph and when the covariances between distant grids are high. Localization methods based on Euclidean distance, flow accumulation values, and river distance are all able to limit the deleterious updates to model states at distant grids and improve filter efficacy. However, no single localization approach is found to be consistently optimal for varying noise configurations, number (and type) of assimilated stations, or flood events. Separate localization of dam outflows from streamflow measurements by assuming the dam grids to be only related to their downstream grids shows potential in improving prediction at locations near the dams themselves while minimizing disruptions at long distances.
查看更多>>摘要：The standard exponential and logarithmic laws for flow velocity evaluation cannot be applied for gravel-bed streams due to the effect of large-scale roughness. An analytical model based on a two-layer subdivision approach was developed to predict flow velocity over a gravel array with different densities. The velocity distribution in the gravel layer was derived by solving the Darcy-Forchheimer-Brinkman (DFB) differential equation based on the concept of porous medium flows. The velocity in the surface layer was modeled by the mixing length theory with the length scale modified by taking into account the porous effect of the gravel (ball) arrays. To assess the model, flow velocities over gravel beds simulated by Ping-Pong ball arrays with different densities (or porosities) were measured in a laboratory flume. The results show that the predicted velocities by this subdivision model agree well with experimental data, reflecting that the porosity of the gravel array essentially impacts the flows both in the gravel layer and surface layer. In comparison with the existing models not considering the porous effect of the gravel bed, this model can effectively predict vertical velocity distributions and thereby flow resistances in gravel streams. The permeable interface velocity atop the gravel layer, as the boundary condition for the two-layer model, is sensitive to the bed context effect rather than the hydraulic effect, suggesting that the inflection point of the full velocity profile might be vital in determining the accuracy of the model. Moreover, with other data sources over dense gravel-bed, our model is suitable for data pre-dealt with the spatially averaging, where the spatial non-uniformity effect is great.
查看更多>>摘要：Soil moisture (SM) is a key variable in the surface energy balance and water cycle, and its spatiotemporal dynamics are of great significance to climate, agriculture and other fields. Optical remote sensing has been widely used to estimate SM with relatively fine spatial resolution. However, optical observations are easily contaminated by clouds, making it difficult to obtain spatially continuous SM over large regions. In the present study, a semimonthly SM dataset over the study area of the entire Inner Mongolia region with nearly full spatial coverage was derived from the synergistic use of China's Feng-Yun (FY) geostationary (FY-4A) and polar-orbit (FY-3D) observations, following a previously developed trapezoid feature space in a pixel-to-pixel manner. A preliminary assessment was conducted to evaluate the performances of the proposed method over two main dominant land cover types (grassland and cropland) in the study region, where the China Meteorological Administration Land Data Assimilation System (CLDAS) and the Soil Moisture Active Passive (SMAP) SM products were provided as references. The results indicated that the estimated SM was well correlated to the referenced SM datasets, with a significant correlation coefficient varying from 0.5 to 0.8. Furthermore, for the grassland (cropland), unbiased root mean square errors of approximately 0.062 (0.097) m(3)/m(3) and 0.055 (0.069) m(3)/m(3) can be found when comparing the estimated SM with the CLDAS and the SMAP product, respectively.
查看更多>>摘要：Water shortage has severely threatened the North China Plain (NCP), a typical grain bowl and highly populated and urbanized area in China. As surface water body area (SWA) is a critical variable for measuring regional water resources, understanding its changes and driving mechanisms is important for sustainable water management. Here, we examine the interannual variations and trends of SWA in the NCP during 1987-2020 by using all the available Landsat imagery, the water indices-and threshold-based water mapping algorithm, and cloud computing platform Google Earth Engine (GEE). The results show that SWA of the NCP significantly (p < 0.05) expanded by 68.0% (from 4740.0 km(2) in 1987 to 7963.7 km(2) in 2020) at a rate of 101.9 km(2)/yr. The most remarkable expansion of SWA happened in Shandong Province (75.0 km(2)/yr), which is an increasingly important aquaculture production region. We find that the increasing artificial reservoirs/lakes due to the implementation of water projects, together with aquaculture development, are the main drivers for the expansion of SWA in the NCP. The expansion of SWA caused a significant increase in water evaporation (0.09 km(3)/yr) in the NCP as the shallow nature of these artificial reservoirs/lakes and aquaculture ponds could lead to excess evaporation because of the frequent heating and cooling cycles due to their limited abilities to store energy. Similarly, Shandong Province experienced the most rapid increase in water evaporation (0.03 km(3)/yr), which could accelerate the loss of water storage at a rate of 8.4-14.4 mm/yr in the regions covered by surface water bodies. Continuous temperature rise (0.02-0.06 ?/yr) in the future, as predicted by the climate models (CMIP5) under the two Representative Concentration Pathway (RCP) scenarios of medium (RCP 4.5) and high (RCP 8.5) greenhouse gas emission, could further increase water evaporation, which may add more pressure to regional water shortage. This study warns that, despite an observed significant SWA expansion, water shortage remains a major concern in the NCP.
查看更多>>摘要：Reliable distributed hydrological modeling, especially in semi-arid areas, must consider the inclusion of surface soil moisture (SSM) spatial information during the calibration process. This variable plays a key role in the evapotranspiration processes that determine the hydrological cycle. The coarse resolution of the SSM estimates by satellite remote sensing has restricted the application of this approach to only large basins, focusing most of the studies in the consideration of simply the temporal dynamics of this variable. The growing efforts in providing higher spatial resolution through disaggregating methodologies or new sensor estimates facilitates the application of this spatial approach to small basins. This paper explores the applicability of the currently available satellite surface soil moisture estimates for distributed eco-hydrological modelling in Mediterranean forest basins. On one hand, this study contributes to fill the existing research gap on the use of remote sensing SSM spatial patterns within the distributed hydrological modelling framework in small basins. On the other hand, it serves as an indirect validation method for the spatial performance of satellite SSM products. To achieve this goal, we implemented the eco-hydrological model TETIS in three case studies named: Hozgarganta (southern Spain), Ceira (western Portugal) and Carraixet (eastern Spain). The SSM estimates selected for comparison were Sentinel-1 SSM provided by the Copernicus Global Land Services (CGLS), SMAP SSM disaggregated using Sentinel-1 (SPL2SMAP_S) provided by the National Aeronautics and Space Administration (NASA), SMOS SSM provided by the Barcelona Expert Center (BEC), and SMOS and SMAP SSM disaggregated using the DISPATCH algorithm provided by Lobelia Earth. The methodology employed involved a multi-objective and multi-variable calibration in terms of remote sensing SSM spatial patterns and in-situ streamflow, using the Spatial Efficiency Metric (SPAEF) and the Nash-Sutcliffe efficiency index (NSE) respectively. Before model calibration a sensitivity analysis of the most influent variables was performed. The temporal and spatial comparison of the reference SSM products revealed inconsistencies amongst products. The disaggregating methodology determined the spatial agreement to a greater degree than the sensor itself (i.e. SMAP, SMOS). In spite of the differences amongst products, the multi-objective calibration approach proposed increased the robustness of the hydrological modelling.
查看更多>>摘要：Assessing the impact of ecological water diversion on oasis restoration is critical for water resources and environmental management in arid inland basins. This study proposed a copula incorporated cellular automata (CA) module for modeling the oasis's spatial distribution driven by ecological water diversion. Given the effects of groundwater depth and community expansion on oasis evolution, a water availability index and a neighbor vegetation index were proposed. These two indices were joint using the Clayton copula function, producing a vegetation suitability index that quantified vegetation growth's habitat quality and provided the CA module's basis to identify cellular categories. The CA module was integrated into a previously developed conceptual lumped ecohydrological model (CLEM), resulting in an improved CA-CLEM that outputted groundwater depth, oasis area, oasis NDVI, and oasis distribution data. The CLEM provided the oasis area changes for the CA module, which specified the spatial distribution of these changes. The CA-CLEM had a simple structure, low computation cost, and good performance, indicated by the application in the Shiyang River basin in Northwest China. Results show that an ecological water diversion of 30 million m(3), with an average groundwater depth of 2.95 m, an oasis area of 25 km(2), and an oasis NDVI of 0.36, would successfully recover the terminal Qingtu Oasis in 2020. The oasis distribution and its dynamic evolution processes were irregular because of the spatial heterogeneity of vegetation habitat suitability. The present Qingtu Oasis was fragile, and its sustainability relied on ecological water diversion. The reduction in water diversion would cause water table decline, oasis area shrinkage, vegetation degradation, and oasis fragmentation. The CA-CLEM combined with scenario analysis provides practical and reliable implications for managers and policymakers to improve ecological water diversion strategies.
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Elsevier