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1.
The non-linear perturbation model based on artificial neural network (NLPM-ANN) takes advantage of the consideration of seasonal information by the linear perturbation model (LPM) and the notable non-linear simulation capability of artificial neural network (ANN). However, this model does not take account of antecedent catchment wetness that may effect the simulation and forecasting accuracy. A modified NLPM-ANN model is proposed and developed to take the consideration of antecedent catchment wetness. The output perturbing terms of the response function in the simple linear model (SLM) in an auxiliary component are taken as inputs of ANN to represent catchment wetness. The simulated total runoff is obtained by integrating the outputs of ANN with that of the seasonal model. The rainfall–runoff data of eight catchments were selected and used to compare the modified NLPM-ANN with the NLPM-ANN models. Results show that the modified NLPM-ANN is significantly superior to the NLPM-ANN, and the model component efficiency index values are 16.82% and 16.74% over the NLPM-ANN during calibration and verification periods, respectively.  相似文献   

2.
The Xinanjiang model, which is a conceptual rainfall‐runoff model and has been successfully and widely applied in humid and semi‐humid regions in China, is coupled by the physically based kinematic wave method based on a digital drainage network. The kinematic wave Xinanjiang model (KWXAJ) uses topography and land use data to simulate runoff and overland flow routing. For the modelling, the catchment is subdivided into numerous hillslopes and consists of a raster grid of flow vectors that define the water flow directions. The Xinanjiang model simulates the runoff yield in each grid cell, and the kinematic wave approach is then applied to a ranked raster network. The grid‐based rainfall‐runoff model was applied to simulate basin‐scale water discharge from an 805‐km2 catchment of the Huaihe River, China. Rainfall and discharge records were available for the years 1984, 1985, 1987, 1998 and 1999. Eight flood events were used to calibrate the model's parameters and three other flood events were used to validate the grid‐based rainfall‐runoff model. A Manning's roughness via a linear flood depth relationship was suggested in this paper for improving flood forecasting. The calibration and validation results show that this model works well. A sensitivity analysis was further performed to evaluate the variation of topography (hillslopes) and land use parameters on catchment discharge. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

3.
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4.
This paper presents preliminary results from the application of a transfer‐function rainfall–runoff model to ephemeral streams in Mediterranean Spain. Flow simulations have been conducted for two small catchments (Carraixet and Poyo basins), located in close proximity to one another yet with significantly different geological characteristics. Analysis of flow simulations for a number of high‐flow events has revealed the dominant influence of the rainfall on the catchment response, particularly for high‐rainfall events. Particular success has been attained modelling the highest magnitude events in both catchments and for all events in the faster responding (Poyo) catchment. In order to investigate the viability of the model for forecasting floods in ungauged catchments, additional investigations have been conducted by calibrating the model for one catchment (donor catchment) and then applying it to another (receptor catchment). The results indicate that this can be successful when either the donor catchment is a fast response catchment or when the model is calibrated using a high‐magnitude event in the donor catchment, providing that the modelled receptor catchment event is of a lower magnitude. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

5.
The rainfall–runoff modelling being a stochastic process in nature is dependent on various climatological variables and catchment characteristics and therefore numerous hydrological models have been developed to simulate this complex process. One approach to modelling this complex non-linear rainfall–runoff process is to combine the outputs of various models to get more accurate and reliable results. This multi-model combination approach relies on the fact that various models capture different features of the data, and hence combination of these features would yield better result. This study for the first time presented a novel wavelet based combination approach for estimating combined runoff The simulated daily output (Runoff) of five selected conventional rainfall–runoff models from seven different catchments located in different parts of the world was used in current study for estimating combined runoff for each time period. Five selected rainfall–runoff models used in this study included four data driven models, namely, the simple linear model, the linear perturbation model, the linearly varying variable gain factor model, the constrained linear systems with a single threshold and one conceptual model, namely, the soil moisture accounting and routing model. The multilayer perceptron neural network method was used to develop combined wavelet coupled models to evaluate the effect of wavelet transformation (WT). The performance of the developed wavelet coupled combination models was compared with their counterpart simple combination models developed without WT. It was concluded that the presented wavelet coupled combination approach outperformed the existing approaches of combining different models without applying input WT. The study also recommended that different models in a combination approach should be selected on the basis of their individual performance.  相似文献   

6.
In this paper, the controls of different indicators on the statistical moments (i.e. mean annual flood (MAF), coefficient of variation (CV) and skewness (CS)) of the maximum annual flood records of 459 Austrian catchments are analysed. The process controls are analysed in terms of the correlation of the flood moments within five hydrologically homogeneous regions to two different types of indicators. Indicators of the first type are static catchment attributes, which are associated with long‐term observations such as mean annual precipitation, the base flow index, and the percentage of catchment area covered by a geological unit or soil type. Indicators of the second type are dynamic catchment attributes that are associated with the event scale. Indicators of this type used in the study are event runoff coefficients and antecedent rainfall. The results indicate that MAF and CV are strongly correlated with indicators characterising the hydro‐climatic conditions of the catchments, such as mean annual precipitation, long‐term evaporation and the base flow index. For the catchments analysed, the flood moments are not significantly correlated with static catchment attributes representing runoff generation, such as geology, soil types, land use and the SCS curve number. Indicators of runoff generation that do have significant predictive power for flood moments are dynamic catchment attributes such as the mean event runoff coefficients and mean antecedent rainfall. The correlation analysis indicates that flood runoff is, on average, more strongly controlled by the catchment moisture state than by event rainfall. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

7.
In the semi‐arid Mediterranean environment, the rainfall–runoff relationships are complex because of the markedly irregular patterns in rainfall, the seasonal mismatch between evaporation and rainfall, and the spatial heterogeneity in landscape properties. Watersheds often display considerable non‐linear threshold behavior, which still make runoff generation an open research question. Our objectives in this context were: to identify the primary processes of runoff generation in a small natural catchment; to test whether a physically based model, which takes into consideration only the primary processes, is able to predict spatially distributed water‐table and stream discharge dynamics; and to use the hydrological model to increase our understanding of runoff generation mechanisms. The observed seasonal dynamics of soil moisture, water‐table depth, and stream discharge indicated that Hortonian overland‐flow was negligible and the main mechanism of runoff generation was saturated subsurface‐flow. This gives rise to base‐flow, controls the formation of the saturated areas, and contributes to storm‐flow together with saturation overland‐flow. The distributed model, with a 1D scheme for the kinematic surface‐flow, a 2D sub‐horizontal scheme for the saturated subsurface‐flow, and ignoring the unsaturated flow, performed efficiently in years when runoff volume was high and medium, although there was a smoothing effect on the observed water‐table. In dry years, small errors greatly reduced the efficiency of the model. The hydrological model has allowed to relate the runoff generation mechanisms with the land‐use. The forested hillslopes, where the calibrated soil conductivity was high, were never saturated, except at the foot of the slopes, where exfiltration of saturated subsurface‐flow contributed to storm‐flow. Saturation overland‐flow was only found near the streams, except when there were storm‐flow peaks, when it also occurred on hillslopes used for pasture, where soil conductivity was low. The bedrock–soil percolation, simulated by a threshold mechanism, further increased the non‐linearity of the rainfall–runoff processes. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

8.
The processes of hillslope runoff and erosion are typically represented at coarse spatial resolution in catchment‐scale models due to computational limitations. Such representation typically fails to incorporate the important effects of topographic heterogeneity on runoff generation, overland flow, and soil erosion. These limitations currently undermine the application of distributed catchment models to understand the importance of thresholds and connectivity on hillslope and catchment‐scale runoff and erosion, particularly in semi‐arid environments. This paper presents a method for incorporating high‐resolution topographic data to improve sub‐grid scale parameterization of hillslope overland flow and erosion models. Results derived from simulations conducted using a kinematic wave overland flow model at 0.5 m spatial resolution are used to parameterize the depth–discharge relationship in the overland flow model when applied at 16 m resolution. The high‐resolution simulations are also used to derive a more realistic parameterization of excess flow shear stress for use in the 16 m resolution erosion model. Incorporating the sub‐grid scale parameterization in the coarse‐resolution model (16 m) leads to improved predictions of overland flow and erosion when evaluated using results derived from high‐resolution (0.5 m) model simulations. The improvement in performance is observed for a range of event magnitudes and is most notable for erosion estimates due to the non‐linear dependency between the rates of erosion and overland flow. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

9.
Linking quickflow response to subsurface state can improve our understanding of runoff processes that drive emergent catchment behaviour. We investigated the formation of non-linear quickflows in three forested headwater catchments and also explored unsaturated and saturated storage dynamics, and likely runoff generation mechanisms that contributed to threshold formation. Our analyses focused on two reference watersheds at the Coweeta Hydrologic Laboratory (CHL) in western North Carolina, USA, and one reference watershed at the Susquehanna Shale Hills Critical Zone Observatory (SHW) in Central Pennsylvania, USA, with available hourly soil moisture, groundwater, streamflow, and precipitation time series over several years. Our study objectives were to characterise (a) non-linear runoff response as a function of storm characteristics and antecedent conditions, (b) the critical levels of shallow unsaturated and saturated storage that lead to hourly flow response, and (c) runoff mechanisms contributing to rapidly increasing quickflow using measurements of soil moisture and groundwater. We found that maximum hourly rainfall did not significantly contribute to quickflow production in our sites, in contrast to prior studies, due to highly conductive forest soils. Soil moisture and groundwater dynamics measured in hydrologically representative areas of the hillslope showed that variable subsurface states could contribute to non-linear runoff behaviour. Quickflow generation in watersheds at CHL were dominated by both saturated and unsaturated pathways, but the relative contributions of each pathway varied between catchments. In contrast, quickflow was almost entirely related to groundwater fluctuations at SHW. We showed that co-located measurements of soil moisture and groundwater supplement threshold analyses providing stronger prediction and understanding of quickflow generation and indicate dominant runoff processes.  相似文献   

10.
The rainfall-runoff modeling is very useful for forecasting purposes. A good methodology for forecasting the future stream flow is a key requirement for designers and operators of water resources systems. A compromise between conceptual and classical time series modeling is applied to model the relationship between rainfall and runoff. The dynamic nonlinear model is composed of a probability distribution describing the observation, a link function relating its mean to the so called state parameters and a system of equations defining the evolution of these parameters. Its Bayesian nature permits to take into account subjective information, making forward intervention, defining monitoring schemes and introducing smoothing facilities. An application using the data of Fartura river's basin is reported. The assessment of the prior distribution is discussed and the predictive performance of the linear and the non-linear models is reported.  相似文献   

11.
In humid upland catchments wetlands are often a prominent feature in the vicinity of streams and have potential implications for runoff generation and nutrient export. Wetland surfaces are often characterized by distinct micro-topography (hollows and hummocks). The effects of such micro-topography on surface–subsurface exchange and runoff generation for a 10 by 20 m synthetic section of a riparian wetland were investigated in a virtual modeling experiment. A reference model with a planar surface was run for comparison. The geostatistically simulated structure of the micro-topography replicates the topography of a peat-forming riparian wetland in a small mountainous catchment in South-East Germany (Lehstenbach). Flow was modeled with the fully-integrated surface–subsurface code HydroGeoSphere. Simulation results showed that the specific structure of the wetland surface resulted in distinct shifts between surface and subsurface flow dominance. Surface depressions filled and started to drain via connected channel networks in a threshold controlled process, when groundwater levels intersected the land surface. These networks expanded and shrunk in a spill and fill mechanism when the shallow water table fluctuated around the mean surface elevation under variable rainfall inputs. The micro-topography efficiently buffered rainfall inputs and produced a hydrograph that was characterized by subsurface flow during most of the year and only temporarily shifted to surface flow dominance (> 80% of total discharge) during intense rainstorms. In contrast the hydrograph in the planar reference model was much “flashier” and more controlled by surface runoff. A non-linear, hysteretic relationship between groundwater level and discharge observed at the study site was reproduced with the micro-topography model. Hysteresis was also observed in the relationship between surface water storage and discharge, but over a relatively narrow range of surface water storage values. Therefore it was concluded that surface water storage was a better predictor for the occurrence of surface runoff than groundwater levels.  相似文献   

12.
A method to improve the calculation of overland flow in distributed groundwater recharge models is presented and applied to two sub‐catchments in the Thames Basin, UK. Recharge calculation studies tend to simulate the runoff flow component of river flow in a simplistic way, often as a fraction of rainfall over a particular period. The method outlined in this study intends to improve the calculation of groundwater recharge estimates in distributed recharge models but does not present an alternative to complex overland flow simulators. This method uses seasonally varying coefficients to calculate runoff for specified hydrogeological classes or runoff zones, which are used to model baseflow index variations across the basin. It employs a transfer function model to represent catchment storage. Monte Carlo simulation was applied to refine the runoff values. Decoupling the runoff zones between the two sub‐catchments produces a better match between the simulated and observed values; however, the difference between observed runoff and the simulated output indicates other factors, such as landuse and topographical characteristics that affect the generation of runoff flow, need to be taken into account when classifying runoff zones. British Geological Survey © NERC 2011. Hydrological Processes © 2011 John Wiley & Sons, Ltd.  相似文献   

13.
Because of high spatial heterogeneity and the degree of uncertainty about hydrological processes in large‐scale catchments of semiarid mountain areas, satisfactory forecasting of daily discharge is seldom available using a single model in many practical cases. In this paper the Takagi–Sugeno fuzzy system (TS) and the simple average method (SAM) are applied to combine forecasts of three individual models, namely, the simple linear model (SLM), the seasonally based linear perturbation model (LPM) and the nearest neighbour linear perturbation model (NNLPM) for modelling daily discharge, and the performance of modelling results is compared in five catchments of semiarid areas. It is found that the TS combination model gives good predictions. The results confirm that better prediction accuracy can be obtained by combining the forecasts of different models with the Takagi–Sugeno fuzzy system in semi‐arid mountain areas. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

14.
Empirically based understanding of streamflow generation dynamics in a montane headwater catchment formed the basis for the development of simple, low‐parameterized, rainfall–runoff models. This study was based in the Girnock catchment in the Cairngorm Mountains of Scotland, where runoff generation is dominated by overland flow from peaty soils in valley bottom areas that are characterized by dynamic expansion and contraction of saturation zones. A stepwise procedure was used to select the level of model complexity that could be supported by field data. This facilitated the assessment of the way the dynamic process representation improved model performance. Model performance was evaluated using a multi‐criteria calibration procedure which applied a time series of hydrochemical tracers as an additional objective function. Flow simulations comparing a static against the dynamic saturation area model (SAM) substantially improved several evaluation criteria. Multi‐criteria evaluation using ensembles of performance measures provided a much more comprehensive assessment of the model performance than single efficiency statistics, which alone, could be misleading. Simulation of conservative source area tracers (Gran alkalinity) as part of the calibration procedure showed that a simple two‐storage model is the minimum complexity needed to capture the dominant processes governing catchment response. Additionally, calibration was improved by the integration of tracers into the flow model, which constrained model uncertainty and improved the hydrodynamics of simulations in a way that plausibly captured the contribution of different source areas to streamflow. This approach contributes to the quest for low‐parameter models that can achieve process‐based simulation of hydrological response. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

15.
Model predictions concerning the endangerment of on‐site and off‐site damages due to runoff, soil erosion and sedimentation under alternative design and operation policies are of particular importance in recent catchment planning and management. By using the raster‐based model approach, linear landscape elements, such as streets and roads, and their impacts on flow paths are often neglected. Therefore, the aim of this study was to analyse the effects of linear landscape elements on patterns of soil erosion, sediment transport and sedimentation. To accomplish this, roads are considered while determining flow paths. Simulations in the well‐investigated catchment of the Wahnbach River (54 km²) in a low mountain range in Germany were carried out using a combination of different models for hydrology and soil erosion. Although the study focuses on the catchment scale of the Wahnbach River, detailed investigations concerning the sub‐catchment scale (21 ha) were also conducted. The simulation results show that these spatial structures mainly affect the pattern of soil erosion and sedimentation. On the sub‐catchment scale, improved identification of active zones for sediment dynamic becomes possible. On the catchment scale, the predicted runoff is about 20% higher, and sediment outputs were four times larger than predicted when roads were considered. Soil erosion increases by 37% whereas sedimentation is reduced by 29%. The model improvement could not be evaluated on the catchment scale because of the high variability and heterogeneity of land use and soils, but road impacts could be explained by simulations on the sub‐catchment scale. It can be concluded that runoff concentration due to rerouted flow paths leads to lower non‐concentrated and higher concentric‐linear surface runoff. Thus, infiltration losses decline and surface runoff and soil erosion increase because sedimentation is reduced. Further, runoff concentration can cause soil erosion hot spots. In the model concept used in this study, buffering of runoff and sediments on the upslope side of roads and in local depressions adjacent to roads cannot be simulated. Flow paths will only be rerouted because of road impacts, but the temporal ponding of water is not simulated. Therefore, the drastic increase of predicted sediment output due to road impact does not seem to be reliable. However, results indicate that the consideration of roads when determining flow paths enabled more detailed simulations of surface runoff, soil erosion and sedimentation. Thus, progress in model‐based decision‐making support for river catchment planning and management can be achieved. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

16.
《水文科学杂志》2013,58(4):567-584
Abstract

Reliable, real-time river flow forecasting in Africa on a time scale of days can provide enormous humanitarian and economic benefits. This study investigates the feasibility of using daily rainfall estimates based on cold cloud duration (CCD) derived from Meteosat thermal infrared imagery as input to a simple rainfall—runoff model and also whether such estimates can be improved by the inclusion of information from numerical weather prediction (NWP) analysis models. The Bakoye catchment in Mali, West Africa has been used as a test area. The data available for the study covered the main months of the rainy season for three years. The rainfall estimates were initially validated against gauge data. Improvements in quality were observed when information relating to African Easterly Wave phase and storm type was included in a multiple linear regression (MR) algorithm. The estimates were also tested by using them as input to a rainfall—runoff model. When contemporaneous calibrations from raingauges were available for calibration, both CCD-only and MR rainfall estimates gave more accurate river flow forecasts than when using raingauge data alone. In the absence of contemporaneous calibrations, the performance was reduced but the MR did better than the CCDonly input in all years. The use of satellite-derived vegetation index did not improve the quality of the river flow forecasts.  相似文献   

17.
C. Valeo  S. M. A. Moin 《水文研究》2000,14(14):2505-2525
The impact of grid‐cell size on calibrated parameters and on the performance of a variable source area model intended for urbanizing catchments is studied in this research. The model uses TOPMODEL concepts that were modified to consider urban areas in both the topographic index and the mechanism of surface runoff generation. The revised model known as TOPURBAN, was applied to a small catchment of roughly 8 km2 in southern Ontario. Ten different grid‐cell sizes ranging from 10 m to 100 m were selected to study scale effects in this catchment with mild to moderate relief, on three separate time periods. The model performed adequately with calibration efficiencies for all three time periods in the range of 0\65 to 0\85. The verification efficiencies were not as high and ranged from 0\4 to 0\6. Larger cell sizes produced higher averages of topographic index, and this resulted in larger calibrated transmissivities. The most important parameter in determining the quantity of urban runoff was slightly affected by grid resolution. During the calibration process, this parameter was also found to interact with important parameters that dealt primarily with rural runoff generation. As cell size increased, contributions from urban areas increased and overland flow contributions from rural areas decreased. Results showed that in this integrated model of urban and rural areas, predicted processes based on calibrated parameters were dependent on grid resolution. Calibration of internal state variables is recommended to draw conclusions on the influences between urban and rural areas on the overall flow. Copyright © 2000 John Wiley & Sons, Ltd.  相似文献   

18.
Information on the spatial and temporal origin of runoff entering the channel during a storm event would be valuable in understanding the physical dynamics of catchment hydrology; this knowledge could be used to help design flood defences and diffuse pollution mitigation strategies. The majority of distributed hydrological models give information on the amount of flow leaving a catchment and the pattern of fluxes within the catchment. However, these models do not give any precise information on the origin of runoff within the catchment. The spatial and temporal distribution of runoff sources is particularly intricate in semi‐arid catchments, where there are complex interactions between runoff generation, transmission and re‐infiltration over short temporal scales. Agents are software components that are capable of moving through and responding to their local environment. In this application, the agents trace the path taken by water through the catchment. They have information on their local environment and on the basis of this information make decisions on where to move. Within a given model iteration, the agents are able to stay in the current cell, infiltrate into the soil or flow into a neighbouring cell. The information on the current state of the hydrological environment is provided by the environment generator. In this application, the Connectivity of Runoff Model (CRUM) has been used to generate the environment. CRUM is a physically based, distributed, dynamic hydrology model, which considers the hydrological processes relevant for a semi‐arid environment at the temporal scale of a single storm event. During the storm event, agents are introduced into the model across the catchment; they trace the flows of water and store information on the flow pathways. Therefore, this modelling approach is capable of giving a novel picture of the temporal and spatial dynamics of flow generation and transmission during a storm event. This is possible by extracting the pathways taken by the agents at different time slices during the storm. The agent based modelling approach has been applied to two small catchments in South East Spain. The modelling approach showed that the two catchments responded differently to the same rainfall event due to the differences in the runoff generation and overland flow connectivity between the two catchments. The model also showed that the time of travel to the nearest flow concentration is extremely important for determining the connectivity of a point in the landscape with the catchment outflow. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

19.
The Process Modelling and Artificial Intelligence for Online Flood Forecasting (PAI-OFF) methodology combines the reliability of physically based, hydrologic/hydraulic modelling with the operational advantages of artificial intelligence. These operational advantages are extremely low computation times and straightforward operation. The basic principle of the methodology is to portray process models by means of ANN. We propose to train ANN flood forecasting models with synthetic data that reflects the possible range of storm events. To this end, establishing PAI-OFF requires first setting up a physically based hydrologic model of the considered catchment and – optionally, if backwater effects have a significant impact on the flow regime – a hydrodynamic flood routing model of the river reach in question. Both models are subsequently used for simulating all meaningful and flood relevant storm scenarios which are obtained from a catchment specific meteorological data analysis. This provides a database of corresponding input/output vectors which is then completed by generally available hydrological and meteorological data for characterizing the catchment state prior to each storm event. This database subsequently serves for training both a polynomial neural network (PoNN) – portraying the rainfall–runoff process – and a multilayer neural network (MLFN), which mirrors the hydrodynamic flood wave propagation in the river. These two ANN models replace the hydrological and hydrodynamic model in the operational mode. After presenting the theory, we apply PAI-OFF – essentially consisting of the coupled “hydrologic” PoNN and “hydrodynamic” MLFN – to the Freiberger Mulde catchment in the Erzgebirge (Ore-mountains) in East Germany (3000 km2). Both the demonstrated computational efficiency and the prediction reliability underline the potential of the new PAI-OFF methodology for online flood forecasting.  相似文献   

20.
The impacts of forest conversion on runoff generation in the tropics have received much interest, but scientific progress is still hampered by challenging fieldwork conditions and limited knowledge about runoff mechanisms. Here, we assessed the runoff generation, flow paths and water source dynamics of a pristine rainforest catchment in Costa Rica using end member mixing analysis (EMMA) and a Bayesian mixing model (MixSIAR). Geochemical tracer data collected over a 4-week field campaign were combined with tritium data used to assess potential deeper groundwater flow pathways to the perennial stream. The streamflow composition was best captured using three end-members, namely throughfall, shallow (5–15 cm) and deeper (15–50 cm) soil water. We estimated the end-member contributions to the main stream and two tributaries using the two mixing approaches and found good agreement between results obtained from EMMA and MixSIAR. The system was overwhelmingly dominated by near-surface sources, with little evidence for deeper and older groundwater as tritium-derived baseflow mean transit time was between 2.0 and 4.4 years. The shallow soil flow pathway dominated streamflow contributions in the main stream (median 39% and 49% based on EMMA and MixSIAR, respectively), followed by the deeper soil (32% and 31%) and throughfall (25% and 19%). The two tributaries had even greater shallow soil water contributions relative to the main stream (83% and 74% for tributary A and 42% and 63% for tributary B). Tributary B had no detectable deep soil water contribution, reflecting the morphology of the hillslope (steeper slopes, shallower soils and lower vegetation density compared to hillslope A). Despite the short sampling campaign and associated uncertainties, this study allowed to thoroughly assess runoff generation mechanisms in a humid tropical catchment. Our results also provide a first comparison of two increasingly used mixing models and suggest that EMMA and MixSIAR yield comparable estimates of water source partitioning in this tropical, volcanic rainforest environment.  相似文献   

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