The commonly used discretization approaches for distributed hydrological models can be broadly categorized into four types,based on the nature of the discrete components:Regular Mesh,Triangular Irregular Networks(TINs...The commonly used discretization approaches for distributed hydrological models can be broadly categorized into four types,based on the nature of the discrete components:Regular Mesh,Triangular Irregular Networks(TINs),Representative Elementary Watershed(REWs) and Hydrologic Response Units(HRUs).In this paper,a new discretization approach for landforms that have similar hydrologic properties is developed and discussed here for the Integrated Hydrologic Model(IHM),a combining simulation of surface and groundwater processes,accounting for the interaction between the systems.The approach used in the IHM is to disaggregate basin parameters into discrete landforms that have similar hydrologic properties.These landforms may be impervious areas,related areas,areas with high or low clay or organic fractions,areas with significantly different depths-to-water-table,and areas with different types of land cover or different land uses.Incorporating discrete landforms within basins allows significant distributed parameter analysis,but requires an efficient computational structure.The IHM integration represents a new approach interpreting fluxes across the model interface and storages near the interface for transfer to the appropriate model component,accounting for the disparate discretization while rigidly maintaining mass conservation.The discretization approaches employed in IHM will provide some ideas and insights which are helpful to those researchers who have been working on the integrated models for surface-groundwater interaction.展开更多
The study of snow and ice melt （SIM） is important in water-scarce arid regions for the assessment of water supply and quality. These studies involve unique difficulties, especially in the calibration of hydro-models...The study of snow and ice melt （SIM） is important in water-scarce arid regions for the assessment of water supply and quality. These studies involve unique difficulties, especially in the calibration of hydro-models because there is no direct way to continuously measure the SIM at hydrostations. The recursive digital filter （RDF） and the isotopic hydro-geochemical method （IHM） were coupled to separate the SIM from eight observed series of alpine streamflows in northwestern China. Validation of the calibrated methods suggested a good capture of the SIM characteristics with fair accuracy in both space and time. Applications of the coupled methods in the upper reaches of the Hei River Basin （HRB） suggested a double peak curve of the SIM fraction to streamflow for the multi-component recharged （MCR） rivers, while a single peak curve was suggested for the rainfall-dominant recharged （RDR） rivers. Given inter-annual statistics of the separation, both types of the alpine rivers have experienced an obvious decrease of SIM since 196os. In the past 10 years, the SIM in the two types of rivers has risen to the levels of the 1970s, but has remained lower than the level of the 1960s. The study provided a considerable evidence to quantify the alpine SIMbased on the separation of observed data series at gauge stations. Application of the coupled method could be helpful in the calibration and validation of SIM-related hydro-models in alpine regions.展开更多
To maximize the aggregate throughput achieved in heterogeneous networks, this paper investigates inter-session network coding for the distribution of layered source data. We define inter-layer hierarchical random line...To maximize the aggregate throughput achieved in heterogeneous networks, this paper investigates inter-session network coding for the distribution of layered source data. We define inter-layer hierarchical random linear network codes （IHRLNC）, which not only take the flexibility of intersession network coding for layer mixing but also consider the strict priority inherent in the layered source data. Furthermore, we propose the inter-layer hierarchical multicast （IHM）, which performs IHRLNC in the network such that each sink can recover some source layers according to its individu- al capacity. To determine the optimal type of IHRLNC that should be performed on each edge in IHM, we formulate an optimization problem based on 0-1 integer linear programming, and propose a heuristic approach to approximate the optimal solution in polynomial time. Simulation results show that the proposed IHM can achieve throughput gains over the layered muhicast schemes.展开更多
Air entrapment is an important consideration in environments with shallow water tables and sandy soil, like the condition of highly conductive sandy soils and flat topography in Florida, USA. It causes water table ris...Air entrapment is an important consideration in environments with shallow water tables and sandy soil, like the condition of highly conductive sandy soils and flat topography in Florida, USA. It causes water table rises in soils, which are significantly faster and higher than those in soils without air entrapment. Two numerical models, Integrated Hydrologic Model (IHM) and HYDRUS-1D (a single-phase, one-dimensional Richards′ equation model) were tested at an area of west central Florida to help further understanding the shallow water table behavior during a long term air entrapment. This investigation employed field data with two modeling approaches to quantify the variation of air pressurization values. It was found that the air pressurization effect was responsible at time up to 40 cm of water table rise being recorded by the observation well for these two models. The values of air pressurization calculated from IHM and HYDRUS-1D match the previously published values. Results also indicated that the two numerical models did not consider air entrapment effect (as the predictive parameters remain uncertain) and thus results of depth to water table from these models did not compare to the observations for these selected periods. Incorporating air entrapment in prediction models is critical to reproduce shallow water table observations.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.40901026)Beijing Municipal Science & Technology New Star Project Funds(No.2010B046)+1 种基金Beijing Municipal Natural Science Foundation(No.8123041)Southwest Florida Water Management District(SFWMD) Project
文摘The commonly used discretization approaches for distributed hydrological models can be broadly categorized into four types,based on the nature of the discrete components:Regular Mesh,Triangular Irregular Networks(TINs),Representative Elementary Watershed(REWs) and Hydrologic Response Units(HRUs).In this paper,a new discretization approach for landforms that have similar hydrologic properties is developed and discussed here for the Integrated Hydrologic Model(IHM),a combining simulation of surface and groundwater processes,accounting for the interaction between the systems.The approach used in the IHM is to disaggregate basin parameters into discrete landforms that have similar hydrologic properties.These landforms may be impervious areas,related areas,areas with high or low clay or organic fractions,areas with significantly different depths-to-water-table,and areas with different types of land cover or different land uses.Incorporating discrete landforms within basins allows significant distributed parameter analysis,but requires an efficient computational structure.The IHM integration represents a new approach interpreting fluxes across the model interface and storages near the interface for transfer to the appropriate model component,accounting for the disparate discretization while rigidly maintaining mass conservation.The discretization approaches employed in IHM will provide some ideas and insights which are helpful to those researchers who have been working on the integrated models for surface-groundwater interaction.
基金supported by the following grants:National Key Research and Development Program of China (Grant No. 2009CB421306)the NSFC Project (Grant Nos. 41001014, 51209119) NSFC Projects (Grant Nos. 41240002, 91225301)+1 种基金the NSFC Key Project (Grant No. 91125010)the MAIRS Project funded by the NASA LCLUC Program (Grant No. NNX08AH50G)
文摘The study of snow and ice melt （SIM） is important in water-scarce arid regions for the assessment of water supply and quality. These studies involve unique difficulties, especially in the calibration of hydro-models because there is no direct way to continuously measure the SIM at hydrostations. The recursive digital filter （RDF） and the isotopic hydro-geochemical method （IHM） were coupled to separate the SIM from eight observed series of alpine streamflows in northwestern China. Validation of the calibrated methods suggested a good capture of the SIM characteristics with fair accuracy in both space and time. Applications of the coupled methods in the upper reaches of the Hei River Basin （HRB） suggested a double peak curve of the SIM fraction to streamflow for the multi-component recharged （MCR） rivers, while a single peak curve was suggested for the rainfall-dominant recharged （RDR） rivers. Given inter-annual statistics of the separation, both types of the alpine rivers have experienced an obvious decrease of SIM since 196os. In the past 10 years, the SIM in the two types of rivers has risen to the levels of the 1970s, but has remained lower than the level of the 1960s. The study provided a considerable evidence to quantify the alpine SIMbased on the separation of observed data series at gauge stations. Application of the coupled method could be helpful in the calibration and validation of SIM-related hydro-models in alpine regions.
基金Supported by the National Natural Science Foundation of China （ No. 60832001 ）.
文摘To maximize the aggregate throughput achieved in heterogeneous networks, this paper investigates inter-session network coding for the distribution of layered source data. We define inter-layer hierarchical random linear network codes （IHRLNC）, which not only take the flexibility of intersession network coding for layer mixing but also consider the strict priority inherent in the layered source data. Furthermore, we propose the inter-layer hierarchical multicast （IHM）, which performs IHRLNC in the network such that each sink can recover some source layers according to its individu- al capacity. To determine the optimal type of IHRLNC that should be performed on each edge in IHM, we formulate an optimization problem based on 0-1 integer linear programming, and propose a heuristic approach to approximate the optimal solution in polynomial time. Simulation results show that the proposed IHM can achieve throughput gains over the layered muhicast schemes.
基金Under the auspices of National Natural Science Foundation of China (No. 40901026)International Cooperation Project of Ministry of Science and Technology of China (No. 2010DFA92400)Tampa Bay Water and South Florida Water Management District (TBW and SFWMD) Project
文摘Air entrapment is an important consideration in environments with shallow water tables and sandy soil, like the condition of highly conductive sandy soils and flat topography in Florida, USA. It causes water table rises in soils, which are significantly faster and higher than those in soils without air entrapment. Two numerical models, Integrated Hydrologic Model (IHM) and HYDRUS-1D (a single-phase, one-dimensional Richards′ equation model) were tested at an area of west central Florida to help further understanding the shallow water table behavior during a long term air entrapment. This investigation employed field data with two modeling approaches to quantify the variation of air pressurization values. It was found that the air pressurization effect was responsible at time up to 40 cm of water table rise being recorded by the observation well for these two models. The values of air pressurization calculated from IHM and HYDRUS-1D match the previously published values. Results also indicated that the two numerical models did not consider air entrapment effect (as the predictive parameters remain uncertain) and thus results of depth to water table from these models did not compare to the observations for these selected periods. Incorporating air entrapment in prediction models is critical to reproduce shallow water table observations.
