A combined rainfall infiltration model based on Green–Ampt and SCS‐curve number

The Green–Ampt infiltration equation is an incomplete governing equation for rainfall infiltration due to the absence of an inertia term. The estimation of the capillary pressure head at the wetting front is difficult to determine. Thus, a major limitation of the Green–Ampt model is the constant, non‐zero surface ponding depth. This paper proposes an integrated rainfall infiltration model based on the Green–Ampt model and the SCS‐CN model. It achieves a complete governing equation for rainfall infiltration by momentum balance and the water budget based on the Green–Ampt assumption, and uses the curve number from the SCS‐CN method to calculate the initial abstraction, which is used as a basic parameter for the governing equation of the intensity of rainfall loss during the runoff period. The integrated rainfall infiltration model resolves the dilemma for capillary pressure head estimation, overcomes the limitation of constant, non‐zero surface ponding depth, and facilitates the calculation of runoff for individual flood simulations. Copyright © 2014 John Wiley & Sons, Ltd.     

Discharge and water table predictions using a generalised TOPMODEL formulation

A simple, generalized saturated zone formulation is presented in this paper to relax the assumption of an exponential function originally made in TOPMODEL. This saturated zone model is based on the concept of a ‘discharge:relative storage’ (QΔS) function which is derived empirically, using recession curve analysis, and may be of arbitrary form. The generalized formulation is applied to the Seternbekken MINIFELT catchment in Norway, where detailed distributed water table data have been measured. These water table data are used to suggest an empirical, power law modification of the topographic a/tan β index. Results for the simulation through time of discharges and water table depths at a few locations show that the generalized saturated zone formulation is as efficient a simulator of the observed data as a conventional TOPMODEL, but requires one parameter less to be calibrated. The simulation of detailed water table distributions is only approximate in both cases. The modified power law index shows only a small improvement but provides a basis for a discussion of possible sources of error in the TOPMODEL assumptions for this site. © 1997 John Wiley & Sons, Ltd.     

Green‐Ampt Curve‐Number mixed procedure as an empirical tool for rainfall–runoff modelling in small and ungauged basins

The Soil Conservation Service Curve Number (SCS‐CN) method is a popular rainfall–runoff model that is widely used to estimate direct runoff from small and ungauged basins. The SCS‐CN is a simple and valuable approach to quantify the total streamflow volume generated by storm rainfall, but its use is not appropriate for estimating the sub‐daily incremental rainfall excess. To overcome this drawback, we propose to include the Green‐Ampt (GA) infiltration model into a mixed procedure, which is referred to as Curve Number for Green‐Ampt (CN4GA), aiming to distribute in time the information provided by the SCS‐CN method. For a given storm, the computed SCS‐CN total net rainfall amount is employed to calibrate the soil hydraulic conductivity parameter of the GA model. The proposed procedure is evaluated by analysing 100 rainfall–runoff events that were observed in four small catchments of varying size. CN4GA appears to provide encouraging results for predicting the net rainfall peak and duration values and has shown, at least for the test cases considered in this study, better agreement with the observed hydrographs than the classic SCS‐CN method. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling to analyse the impacts of animal treading effects on soil infiltration

Animal treading can change soil physical properties, and thus is an important factor in hydrological modelling. We investigated the impacts of animal treading on infiltration by using a series of rainfall simulation experiments at Whatawhata Research Center, Waikato, New Zealand. The study identified significant variables for estimating soil steady‐state infiltration at a micro‐site (0·5 m²) and fitted the Green and Ampt equation by modifying or including variables for soil and water parameters and animal activities on grazing paddocks. A regression function for estimating steady‐state infiltration rate was created for each of four scenarios: between tracks (inter‐track), track, easy slope with ash soil, and easy slope with clay soil. Significant variables included the number of days after treading, antecedent soil moisture, field capacity, percentage of bare ground, bulk density, and the high degree of soil damage (damage not compacted). Regression models explained more than 71% of the variance in steady‐state infiltration for three scenarios, but only 53% for the easy slope with clay soil. The remodified Green and Ampt equation provided satisfactory estimation of infiltration for all scenarios (accuracy > 80%), and thus enables us to use the modified model for Waikato hill country pastures of different topography, soil physical condition, season and grazing management. Copyright © 2006 John Wiley & Sons, Ltd.     

ESTIMATING INFILTRATION PARAMETERS FROM BASIC SOIL PROPERTIES

Infiltration data were collected on two rectangular grids with 25 sampling points each. Both experimental grids were located in tropical rain forest (Guyana), the first in an Arenosol area and the second in a Ferralsol field. Four different infiltration models were evaluated based on their performance in describing the infiltration data. The model parameters were estimated using non-linear optimization techniques. The infiltration behaviour in the Ferralsol was equally well described by the equations of Philip, Green–Ampt, Kostiakov and Horton. For the Arenosol, the equations of Philip, Green–Ampt and Horton were significantly better than the Kostiakov model. Basic soil properties such as textural composition (percentage sand, silt and clay), organic carbon content, dry bulk density, porosity, initial soil water content and root content were also determined for each sampling point of the two grids. The fitted infiltration parameters were then estimated based on other soil properties using multiple regression. Prior to the regression analysis, all predictor variables were transformed to normality. The regression analysis was performed using two information levels. The first information level contained only three texture fractions for the Ferralsol (sand, silt and clay) and four fractions for the Arenosol (coarse, medium and fine sand, and silt and clay). At the first information level the regression models explained up to 60% of the variability of some of the infiltration parameters for the Ferralsol field plot. At the second information level the complete textural analysis was used (nine fractions for the Ferralsol and six for the Arenosol). At the second information level a principal components analysis (PCA) was performed prior to the regression analysis to overcome the problem of multicollinearity among the predictor variables. Regression analysis was then carried out using the orthogonally transformed soil properties as the independent variables. Results for the Ferralsol data show that the parameters of the Green–Ampt and Kostiakov model were estimated relatively accurately (maximum R² = 0.76). For the Arenosol, use of the second information level together with PCA produced regression models with an R² value ranging from 0.38 to 0.68. For the Ferralsol, most of the variance was explained by the root content and organic matter content. In the Arenosol plot, the fractions medium and fine sand explained most of the observed variance.     

Curve‐Number/Green–Ampt mixed procedure for streamflow predictions in ungauged basins: Parameter sensitivity analysis

A procedure combining the Soil Conservation Service‐Curve Number (SCS‐CN) method and the Green–Ampt (GA) infiltration equation was recently developed to overcome some of the drawbacks of the classic SCS‐CN approach when estimating the volume of surface runoff at a sub‐daily time resolution. The rationale of this mixed procedure, named Curve Number for Green–Ampt (CN4GA), is to use the GA infiltration model to distribute the total volume of the net hyetograph (rainfall excess) provided by the SCS‐CN method over time. The initial abstraction and the total volume of rainfall given by the SCS‐CN method are used to identify the ponding time and to quantify the hydraulic conductivity parameter of the GA equation. In this paper, a sensitivity analysis of the mixed CN4GA parameters is presented with the aim to identify conditions where the mixed procedure can be effectively used within the Prediction in Ungauged Basin perspective. The effects exerted by changes in selected input parameters on the outputs are evaluated using rectangular and triangular synthetic hyetographs as well as 100 maximum annual storms selected from synthetic rainfall time series. When applied to extreme precipitation events, which are characterized by predominant peaks of rainfall, the CN4GA appears to be rather insensitive to the input hydraulic parameters of the soil, which is an interesting feature of the CN4GA approach and makes it an ideal candidate for the rainfall excess estimation at sub‐daily temporal resolution at ungauged sites. Copyright © 2013 John Wiley & Sons, Ltd.     

On the estimation of antecedent wetness conditions in rainfall–runoff modelling

The analysis of the physical processes involved in a conceptual model of soil water content balance is addressed with the objective of its application as a component of rainfall–runoff modelling. The model uses routinely measured meteorological variables (rainfall and air temperature) and incorporates a limited number of significant parameters. Its performance in estimating the soil moisture temporal pattern was tested through local measurements of volumetric water content carried out continuously on an experimental plot located in central Italy. The analysis was carried out for different periods in order to test both the representation of infiltration at the short time‐scale and drainage and evapotranspiration processes at the long time‐scale. A robust conceptual model was identified that incorporated the Green–Ampt approach for infiltration and a gravity‐driven approximation for drainage. A sensitivity analysis was performed for the selected model to assess the model robustness and to identify the more significant parameters involved in the principal processes that control the soil moisture temporal pattern. The usefulness of the selected model was tested for the estimation of the initial wetness conditions for rainfall–runoff modelling at the catchment scale. Specifically, the runoff characteristics (runoff depth and peak discharge) were found to be dependent on the pre‐event surface soil moisture. Both observed values and those estimated by the model gave good results. On the contrary, with the antecedent wetness conditions furnished by two versions of the antecedent precipitation index (API), large errors were obtained. Copyright © 2007 John Wiley & Sons, Ltd.     

Modeling scale-dependent runoff generation in a small semi-arid watershed accounting for rainfall intensity and water depth

Observed scale effects of runoff on hillslopes and small watersheds derive from complex interactions of time-varying rainfall rates with runoff, infiltration and macro- and microtopographic structures. A little studied aspect of scale effects is the concept of water depth-dependent infiltration. For semi-arid rangeland it has been demonstrated that mounds underneath shrubs have a high infiltrability and lower lying compacted or stony inter-shrub areas have a lower infiltrability. It is hypothesized that runoff accumulation further downslope leads to increased water depth, inundating high infiltrability areas, which increases the area-averaged infiltration rate. A model was developed that combines the concepts of water depth-dependent infiltration, partial contributing area under variable rainfall intensity, and the Green–Ampt theory for point-scale infiltration. The model was applied to rainfall simulation data and natural rainfall–runoff data from a small sub-watershed (0.4 ha) of the Walnut Gulch Experimental Watershed in the semi-arid US Southwest. Its performance to reproduce observed hydrographs was compared to that of a conventional Green–Ampt model assuming complete inundation sheet flow, with runon infiltration, which is infiltration of runoff onto pervious downstream areas. Parameters were derived from rainfall simulations and from watershed-scale calibration directly from the rainfall–runoff events. The performance of the water depth-dependent model was better than that of the conventional model on the scale of a rainfall simulator plot, but on the scale of a small watershed the performance of both model types was similar. We believe that the proposed model contributes to a less scale-dependent way of modeling runoff and erosion on the hillslope-scale.     

不同尺度流域地表径流氮、磷浓度比较

选择太湖上游为研究对象,采集了1-400 km2不同尺度小流域产出径流TN、TP浓度实测数据,结合前期开展的地表坡面流人工暴雨实验监测结果,开展不同尺度流域水质监测对水体面源污染产出浓度估算影响的比较研究,探讨流域尺度之间入渗、汇流以及伴随的流域生态系统营养盐调节机制的差异．结果表明,流域监测尺度对土地利用面源污染产出浓度估算有较大影响．地表坡面流由于未经过流域汇流过程伴随的下渗滤过与吸附等过程,产出径流TN、TP浓度一般高于小流域．小流域林地生态系统具有较强的入渗机制、接近自然的生态沟谷汇流网络,对面源污染TN、TP有较强的削减作用．农业生态系统较弱的入渗机制、人工沟渠汇流网络对面源污染TN、TP的削减作用较弱．现代农业造成流域面源污染增加不仅仅是因为人类农业活动对流域局部土体及养分的改变,农业生态系统改变流域自然生态系统整体水文过程及营养盐调节机制也是面源污染增加的重要因素之一,恢复小尺度的生态沟谷网络系统对削减流域面源污染具有重要的意义．     

Development and parameterization of an infiltration model accounting for water depth and rainfall intensity

Experimental work has clearly shown that the effective hydraulic conductivity (K_e) or effective infiltration rate (f_e) on the local scale of a plot cannot be considered as constant but are dependent on water depth and rainfall intensity because non‐random microtopography‐related variations in hydraulic conductivity occur. Rainfall–runoff models generally do not account for this: models assume that excess water is uniformly spread over the soil surface and within‐plot variations are neglected. In the present study, we propose a model that is based on the concepts of microtopography‐related water depth‐dependent infiltration and partial contributing area. Expressions for the plot scale K_e and f_e were developed that depend on rainfall intensity and runon from upslope (and thus on water depth). To calibrate and validate the model, steady state infiltration experiments were conducted on maize fields on silt loam soils in Belgium, with different stages and combinations of rainfall intensity and inflow, simulating rainfall and runon. Water depth–discharge and depth–inundation relationships were established and used to estimate the effect of inundation on K_e. Although inflow‐only experiments were found to be unsuitable for calibration, the model was successfully calibrated and validated with the rainfall simulation data and combined rainfall–runon data (R²: 0.43–0.91). Calibrated and validated with steady state infiltration experiments, the model was combined with the Green–Ampt infiltration equation and can be applied within a two‐dimensional distributed rainfall–runoff model. The effect of water depth–dependency and rainfall intensity on infiltration was illustrated for a hillslope. Copyright © 2012 John Wiley & Sons, Ltd.     

An approach to analysing plot scale infiltration and runoff responses to rainfall of fluctuating intensity

Simulated rainfall of fluctuating intensity was applied to runoff plots on bare dryland soils in order to explore a new method for analysing the non‐steady‐state responses of infiltration and overland flow. The rainfall events all averaged 10 mm/h but included intensity bursts of up to 70 mm/h and lasting 5–15 min, as well as periods of low intensity and intermittency of up to 25 min. Results were compared with traditional steady‐state estimates of infiltrability made under simulated rainfall sustained at a fixed intensity of 10 mm/h. Mean event infiltration rate averaged 13.6% higher under fluctuating intensities, while runoff ratios averaged only 63% of those seen under constant intensity. In order to understand the changing soil infiltrability, up to three affine Horton infiltration equations were fitted to segments of each experiment. All equations had the same final infiltrability f_c, but adjusted values for coefficients f₀ (initial infiltrability) and K_f (exponential decay constant) were fitted for periods of rainfall that followed significant hiatuses in rainfall, during which subsurface redistribution allowed near‐surface soil suction to recover. According to the fitted Horton equations, soil infiltrability recovered by up 10–24 mm/h during intra‐event rainfall hiatuses of 15 to 20‐min duration, contributing to higher overall event infiltration rates and to reduced runoff ratios. The recovery of infiltrability also reduced the size of runoff peaks following periods of low intensity rainfall, compared with the predictions based on single Horton infiltration equations, and in some cases, no runoff at all was recorded from late intensity peaks. The principal finding of this study is that, using a set of affine equations, the intra‐event time variation of soil infiltrability can be tracked through multiple intensity bursts and hiatuses, despite the lack of steady‐state conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

Green–Ampt approximations

The solution to the Green and Ampt infiltration equation is expressible in terms of the Lambert W₋₁ function. Approximations for Green and Ampt infiltration are thus derivable from approximations for the W₋₁ function and vice versa. An infinite family of asymptotic expansions to W₋₁ is presented. Although these expansions do not converge near the branch point of the W function (corresponds to Green–Ampt infiltration with immediate ponding), a method is presented for approximating W₋₁ that is exact at the branch point and asymptotically, with interpolation between these limits. Some existing and several new simple and compact yet robust approximations applicable to Green–Ampt infiltration and flux are presented, the most accurate of which has a maximum relative error of 5 × 10⁻⁵%. This error is orders of magnitude lower than any existing analytical approximations.     

A new baseflow separation method based on analytical solutions of the Horton infiltration capacity curve

The separation of baseflow is an important issue in hydrology. The objective of this paper is to develop a new baseflow separation method based on the Horton infiltration capacity curve. For this purpose, the mathematical expressions of three parameters for the Horton infiltration capacity curve were derived in terms of rainfall and runoff data, and the lag time of the effective rainfall in the unsaturated zone and the groundwater flow routing equation are also presented. With these equations, the baseflow hydrographs at the outlet of the basin can be separated. The flow chart of the proposed method for baseflow hydrograph separation is given. Three recent baseflow separation methods, i.e. digital filter, non‐linear reservoir and the Boussinesq equation, were chosen as parallel schemes to compare with the proposed method. Rainfall‐runoff data from four watersheds located in different climatic regions in China were selected and used as case studies. Test and application results indicate that the proposed baseflow hydrograph separation method is in accordance with the hydrological physical process. The proposed method is comparable with current available methods and reduces some of the subjective aspects for the rising limb of the baseflow hydrograph, and it is useful for unit hydrograph analysis and for the study of the rainfall‐runoff relationship. Copyright © 2006 John Wiley & Sons, Ltd.     

A distributed monthly hydrological model for integrating spatial variations of basin topography and rainfall

Hydrological models at a monthly time‐scale are important tools for hydrological analysis, such as in impact assessment of climate change and regional water resources planning. Traditionally, monthly models adopt a conceptual, lumped‐parameter approach and cannot account for spatial variations of basin characteristics and climatic inputs. A large requirement for data often severely limits the utility of physically based, distributed‐parameter models. Based on the variable‐source‐area concept, we considered basin topography and rainfall to be two major factors whose spatial variations play a dominant role in runoff generation and developed a monthly model that is able to account for their influences in the spatial and temporal dynamics of water balance. As a hybrid of the Xinanjiang model and TOPMODEL, the new model is constructed by innovatively making use of the highly acclaimed simulation techniques in the two existing models. A major contribution of this model development study is to adopt the technique of implicit representation of soil moisture characteristics in the Xinanjiang model and use the TOPMODEL concept to integrate terrain variations into runoff simulation. Specifically, the TOPMODEL topographic index ln(a/tanβ) is converted into an index of relative difficulty in runoff generation (IRDG) and then the cumulative frequency distribution of IRDG is used to substitute the parabolic curve, which represents the spatial variation of soil storage capacity in the Xinanjiang model. Digital elevation model data play a key role in the modelling procedures on a geographical information system platform, including basin segmentation, estimation of rainfall for each sub‐basin and computation of terrain characteristics. Other monthly data for model calibration and validation are rainfall, pan evaporation and runoff. The new model has only three parameters to be estimated, i.e. watershed‐average field capacity WM, pan coefficient η and runoff generation coefficient α. Sensitivity analysis demonstrates that runoff is least sensitive to WM and, therefore, it can be determined by a prior estimation based on the climate and soil properties of the study basin. The other two parameters can be determined using optimization methods. Model testing was carried out in a number of nested sub‐basins of two watersheds (Yuanjiang River and Dongjiang River) in the humid region in central and southern China. Simulation results show that the model is capable of describing spatial and temporal variations of water balance components, including soil moisture content, evapotranspiration and runoff, over the watershed. With a minimal requirement for input data and parameterization, this terrain‐based distributed model is a valuable contribution to the ever‐advancing technology of hydrological modelling. Copyright © 2006 John Wiley & Sons, Ltd.     

Incremental distributed modelling investigation in a small agricultural catchment: 1. Overland flow with comparison with the unit hydrograph model

A distributed overland flow model is presented and the test results compared with those of the unit hydrograph (UH) model. Infiltration excess in the overland model was calculated using both a modified Green and Ampt (G–A) method and a more complicated method that keeps track of the soil moisture content. The two‐dimensional partial differential flow equations with kinematic flow approximation were solved using both backward‐central explicit and implicit finite‐difference schemes. Moreover, a baseflow component was added to the flow model. Each part of the model was built by replacing a process by a parallel process or by adding a completely new component. When the model was developed and validated in small agricultural fields in southern Finland, comparisons were made between corresponding processes and the significance of added components were estimated in order to find out whether increased model complexity improves the model performance. Apart from the basic model, all the other distributed models outperformed the UH approach. The implicit scheme was clearly more accurate than the explicit scheme, and the baseflow component improved the results significantly. There was no major difference between the performances of the infiltration models, but the G–A method was more stable and much faster. The approaches that were best in the calibration were also the best in the verification. The full distributed model provides a potential method for running water‐quality models and testing their different processes. Copyright © 2006 John Wiley & Sons, Ltd.     

A statistically based runoff‐yield model coupling infiltration excess and saturation excess mechanisms

A statistically based runoff‐yield model is proposed in this paper. The model considers spatial heterogeneities of rainfall, soil infiltration capacity and soil water storage capacity that are main factors controlling runoff‐yield process. It assumes that the spatial variation of rainfall intensity at each time step can be characterized by a probability density function, which is estimated by matching the hyetograph through goodness‐of‐fit measure, whereas the spatial heterogeneities of soil infiltration capacity and soil water storage capacity are described by parabola‐type functions. Surface runoff is calculated according to infiltration excess mechanism; the statistical distribution of surface runoff rate can be deduced with the joint distribution of rainfall intensity and soil infiltration rate, thus obtaining a quasi‐analytical solution for surface runoff. Based on saturation excess mechanism, the groundwater flow (flows below the ground are collectively referred to as groundwater flow) is calculated by infiltration and the probability distribution of soil water storage capacity. Consequently, the total runoff is composed of infiltration excess and saturation excess runoff components. As an example, this model is applied to flood event simulation in Dongwan catchment, a semi‐humid region and a tributary of Yellow River in China. It indicates that the proposed runoff‐yield model could achieve acceptable accuracy. Copyright © 2011 John Wiley & Sons, Ltd.     

Improvement and comparison of the rainfall–runoff methods in SWAT at the monsoonal watershed of Baocun,Eastern China

ABSTRACT

A new physics-based rainfall–runoff method of the Soil and Water Assessment Tool (SWAT) was developed, which integrates a water balance (WB) approach with the variable source area (WB-VSA). This approach was further compared with four methods—soil-water-dependent curve number (CN-Soil), evaporation-dependent curve number (CN-ET), Green and Ampt equation (G&A) and WB—in a monsoonal watershed, Eastern China. The regional sensitivity analysis shows that volumetric efficiency coefficient (VE) with river discharges is sensitive to the most parameters of all approaches. The results of model calibration against VE demonstrate that WB-VSA is the most accurate owing to its reflection of the spatial variation of runoff generation as affected by topography and soil properties. Other methods can also mimic baseflow well, but the G&A and CN-ET simulate floods much worse than the saturation excess runoff approaches (WB-VSA, WB and CN-Soil). Meanwhile, CN-Soil as an empirical method fails to simulate groundwater levels. By contrast, WB-VSA captures them best.

Editor M.C. Acreman; Associate editor S. Kanae     

TOPMODEL在珠江流域布柳河流域的应用及其与新安江模型的比较

TOPMODEL是一种以地形为基础的半分布式流域水文模型.对珠江流域布柳河流域的DEM信息进行处理,提取流域的水系、子流域边界、地形指数及水流路径距离的分布,将TOPMODEL应用于该流域中.另外将新安江模型也应用于该流域进行比较.此外,分析了两种模型结构差异所带来的模拟功能差异.两种模型模拟结果精度差异不大,而TOPMODEL实现了空间产流面积分布的可视化.     

A new modeling approach for simulating microtopography-dominated,discontinuous overland flow on infiltrating surfaces

Realistic modeling of discontinuous overland flow on irregular topographic surfaces has been proven to be a challenge. This study is aimed to develop a new modeling framework to simulate the discontinuous puddle-to-puddle (P2P) overland flow dynamics for infiltrating surfaces with various microtopographic characteristics. In the P2P model, puddles were integrated in a well-delineated, cascaded drainage system to facilitate explicit simulation of their dynamic behaviors and interactions. Overland flow and infiltration were respectively simulated by using the diffusion wave model and a modified Green–Ampt model for the DEM-derived flow drainage network that consisted of a series of puddle-based units (PBUs). The P2P model was tested by using a series of data from laboratory overland flow experiments for various microtopography, soil, and rainfall conditions. The modeling results indicated that the hierarchical relationships and microtopographic properties of puddles significantly affected their connectivity, filling–spilling dynamics, and the associated threshold flow. Surface microtopography and rainfall characteristics also exhibited strong influences on the spatio-temporal distributions of infiltration rates, runoff fluxes, and unsaturated flow. The model tests demonstrated its applicability in simulating microtopography-dominated overland flow on infiltrating surfaces.     

Pattern‐process relationships in surface hydrology: hydrological connectivity expressed in landscape metrics

The degree of hydrological connectivity is mainly determined by the spatial organisation of heterogeneity. A meaningful and aggregate abstraction of spatial patterns is one of the promising means to gain fundamental insights into this complex interaction and can, moreover, be used as a tool to acquire a profound understanding of the major controls of catchment hydrology. In order to disclose such controls, pattern‐process relationships and the explanatory power of landscape metrics were tested by simulating the runoff of differently patterned virtual basins, generated by neutral landscape models and fractal networks and solved by a surface hydrological model composed of kinematic wave routing and Green‐Ampt infiltration. A total of 23 landscape metrics quantified the spatial patterns and were subsequently related to the functional connectivity, assessed as the proportion of internal runoff generation constituting the hydrological response at the outlet. Landscape metrics allowed the identification of dominant features of heterogeneity that explained the observed connectivity, and to disclose changes in control with class abundance. Therefore, landscape metrics are a useful tool for basin comparison and classification in terms of the dominant processes and the corresponding model structure requirements. Copyright © 2011 John Wiley & Sons, Ltd.