SEASONAL METEOROLOGICAL EFFECTS UPON STREAMFLOW IN NORTHERN UTAH

Abstract

A watershed's seasonal streamflow fluctuations are caused by meteorological conditions as they are modified by the watershed's inherent characteristics such as size, shape, aspect, geology, and plant cover. Records from Halfway Creek watershed, a perennial tributary to Farmington Creek located on the Wasatch Mountains in northern Utah, show that winter streamflow comprises only a small portion of the total annual yield. The winter contribution, which is low but constant, originates as drainage from deep aquifers. A much greater portion of the water yield comes in the spring as seepage flow derived from melting snow and spring rains, although the highest instantaneous spring peak so far recorded is only 24 csm (cubic feet per second per square mile). Initial recession of the flow of Halfway Creek from its spring peak is rapid, but in a short time its decrease becomes so gradual that in late summer the hydrograph becomes an almost flat line. The summer recession ends when climatic conditions in the autumn cause cessation of plant growth. Rainstorms often interrupt the normal summer recession. Most of these interruptions are brief, but the height of the peak varies widely. For instance, in the 24-year period 1923–1947 when the vegetation cover was depleted, overland flow from short duration intense summer rainstorms caused mud-rock floods from Halfway Creek watershed that had instantaneous peaks 100 to 200 times greater than the spring peak. The relations presented in this report were determined for a small area and are based on specific records. They apply in a general way to a much greater area in northern Utah and the Intermountain West of which they are representative.     

Refined conceptualization of TOPMODEL for shallow subsurface flows

The TOPMODEL framework was used to derive expressions that account for saturated and unsaturated flow through shallow soil on a hillslope. The resulting equations were the basis for a shallow‐soil TOPMODEL (STOPMODEL). The common TOPMODEL theory implicitly assumes a water table below the entire watershed and this does not conceptually apply to systems hydrologically controlled by shallow interflow of perched groundwater. STOPMODEL provides an approach for extending TOPMODEL's conceptualization to apply to shallow, interflow‐driven watersheds by using soil moisture deficit instead of water table depth as the state variable. Deriving STOPMODEL by using a hydraulic conductivity function that changes exponentially with soil moisture content results in equations that look very similar to those commonly associated with TOPMODEL. This alternative way of conceptualizing TOPMODEL makes the modelling approach available to researchers, planners, and engineers who work in areas where TOPMODEL was previously believed to be unsuited, such as the New York City Watershed in the Catskills region of New York State. Copyright © 2002 John Wiley & Sons, Ltd.     

Generalization of TOPMODEL for a power law transmissivity profile

A generalization of the TOPMODEL equations for a power law vertical profile of hydraulic conductivity is introduced. The exponential profile of TOPMODEL is obtained as a limit case of the new general form. © 1997 John Wiley & Sons, Ltd.     

A network‐index‐based version of TOPMODEL for use with high‐resolution digital topographic data

This paper describes the preliminary development of a network‐index approach to modify and to extend the classic TOPMODEL. Application of the basic Beven and Kirkby form of TOPMODEL to high‐resolution (2·0 m) laser altimetric data (based upon the UK Environment Agency's light detection and ranging (LIDAR) system) to a 13·8 km² catchment in an upland environment identified many saturated areas that remained unconnected from the drainage network even during an extreme flood event. This is shown to be a particular problem with using high‐resolution topographic data, especially over large appreciable areas. To deal with the hydrological consequences of disconnected areas, we present a simple network index modification in which saturated areas are only considered to contribute when the topographic index indicates continuous saturation through the length of a flow path to the point where the path becomes a stream. This is combined with an enhanced method for dealing with the problem of pits and hollows, which is shown to become more acute with higher resolution topographic data. The paper concludes by noting the implications of the research as presented for both methodological and substantive research that is currently under way. Copyright © 2004 John Wiley & Sons, Ltd.     

Analytical solution to a bias in the TOPMODEL framework balance

The increasing need for distributed hydrological modelling leads to an intense use of spatially distributed predictions of physically based models, such as TOPMODEL as addressed here. The ability of these models to reproduce the internal behaviour of catchments physically is increasingly tested through field experiments (geochemical investigation, distributed measurements network, etc.). This paper will show that, in the case of TOPMODEL, an implicit approximation remains in the classic derivation of the equations that consists in neglecting the surface of saturated areas with respect to the total surface of the catchment. This simplifying, though unnecessary, approximation leads to a systematic underestimation of the catchment water storage deficit and to divergence in the water budget accounting. This may also significantly change the predicted ratio between subsurface and surface water fluxes in the total discharge. An analytical solution is suggested that leads to water balance accounting which is better defined, and more consistent in comparison with field water storage recording. It is expected that this work will ensure more accurate TOPMODEL predictions, consistent with the assumptions of the model. This will then improve the interpretation of comparisons between results of simulation and field experiments. Copyright © 2004 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.     

Multi‐criterial validation of TOPMODEL in a mountainous catchment

The need for powerful validation methods for hydrological models including the evaluation of internal stages and spatially distributed simulations has often been emphasized. In this study a multi‐criterial validation scheme was used for validation of TOPMODEL, a conceptual semi‐distributed rainfall–runoff model. The objective was to test TOPMODEL's capability of adequately representing dominant hydrological processes by simple conceptual approaches. Validation methods differed in the type of data used, in their target and in mode. The model was applied in the humid and mountainous Brugga catchment (40 km²) in south‐west Germany. It was calibrated by a Monte Carlo method based on hourly runoff data. Additional information for validation was derived from a recession analysis, hydrograph separation with environmental tracers and from field surveys, including the mapping of saturated areas. Although runoff simulations were satisfying, inadequacies of the model structure compared with the real situation with regard to hydrological processes in the study area were found. These belong mainly to the concept of variable contributing areas for saturation excess overland flow and their dynamics, which were overestimated by the model. The simple TOPMODEL approach of two flow components was found to be insufficient. The multi‐criterial validation scheme enables not only to demonstrate limitations with regard to process representation, but also to specify where and why these limitations occur. It may serve as a valuable tool for the development of physically sound model modifications. Copyright © 1999 John Wiley & Sons, Ltd.     

Power function decay of hydraulic conductivity for a TOPMODEL‐based infiltration routine

TOPMODEL rainfall‐runoff hydrologic concepts are based on soil saturation processes, where soil controls on hydrograph recession have been represented by linear, exponential, and power function decay with soil depth. Although these decay formulations have been incorporated into baseflow decay and topographic index computations, only the linear and exponential forms have been incorporated into infiltration subroutines. This study develops a power function formulation of the Green and Ampt infiltration equation for the case where the power n = 1 and 2. This new function was created to represent field measurements in the New York City, USA, Ward Pound Ridge drinking water supply area, and provide support for similar sites reported by other researchers. Derivation of the power‐function‐based Green and Ampt model begins with the Green and Ampt formulation used by Beven in deriving an exponential decay model. Differences between the linear, exponential, and power function infiltration scenarios are sensitive to the relative difference between rainfall rates and hydraulic conductivity. Using a low‐frequency 30 min design storm with 4·8 cm h^?1 rain, the n = 2 power function formulation allows for a faster decay of infiltration and more rapid generation of runoff. Infiltration excess runoff is rare in most forested watersheds, and advantages of the power function infiltration routine may primarily include replication of field‐observed processes in urbanized areas and numerical consistency with power function decay of baseflow and topographic index distributions. Equation development is presented within a TOPMODEL‐based Ward Pound Ridge rainfall‐runoff simulation. Copyright © 2006 John Wiley & Sons, Ltd.     

Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models

This paper analyses the effect of rain data uncertainty on the performance of two hydrological models with different spatial structures: a semidistributed and a fully distributed model. The study is performed on a small catchment of 19.6 km² located in the north‐west of Spain, where the arrival of low pressure fronts from the Atlantic Ocean causes highly variable rainfall events. The rainfall fields in this catchment during a series of storm events are estimated using rainfall point measurements. The uncertainty of the estimated fields is quantified using a conditional simulation technique. Discharge and rain data, including the uncertainty of the estimated rainfall fields, are then used to calibrate and validate both hydrological models following the generalized likelihood uncertainty estimation (GLUE) methodology. In the storm events analysed, the two models show similar performance. In all cases, results show that the calibrated distribution of the input parameters narrows when the rain uncertainty is included in the analysis. Otherwise, when rain uncertainty is not considered, the calibration of the input parameters must account for all uncertainty in the rainfall–runoff transformation process. Also, in both models, the uncertainty of the predicted discharges increase in similar magnitude when the uncertainty of rainfall input increase.     

A MATLAB implementation of TOPMODEL

The MATLAB SIMULINK programming language is applied to the TOPMODEL rainfall–runoff model. SIMULINK requires a good recognition of model dynamics, which has been achieved here in a version based on the first TOPMODEL (Beven and Kirkby, 1979). Introducing the topographic index distribution in a vector form allows the generalization and simplification of the SIMULINK structure. The SIMULINK version of TOPMODEL has a very easy to understand graphical representation, which shows, in a straightforward way, all the physical interactions that take place in the model. Moreover, owing to its modular structure it is easy to add new and/or develop old submodels, depending on the available data and the goal of the modelling. In the example given here TOPMODEL was extended by two submodels representing the soil moisture and evaporation distribution in the catchment. Preparation of the data and presentation of the results is done in MATLAB. Discharge predictions and spatial patterns of hydrological response are demonstrated for a separate validation period. © 1997 John Wiley & Sons, Ltd.     

A digital elevation analysis: a spatially distributed flow apportioning algorithm

An integrated flow determination algorithm is proposed to calculate the spatial distribution of the topographic index to the channel network. The advantages of a single flow direction algorithm and other multiple flow direction schemes are selectively considered in order to address the drawbacks of existing algorithms. A spatially varying flow apportioning factor is introduced to distribute the contributing area from upslope cells to downslope cells. The channel initiation threshold concept is expanded and integrated into a spatially distributed flow apportioning algorithm to delineate a realistic channel network. The functional relationships between the flow apportioning factors and the expanded channel initiation threshold (ECIT) are developed to address the spatially varied flow distribution patterns considering the permanent channel locations. A genetic algorithm (GA) is integrated into the spatially distributed flow apportioning algorithm (SDFAA) with the objective function of river cell evaluation. An application of a field example suggests that the spatially distributed flow apportioning scheme provides several advantages over the existing approaches; the advantages include the relaxation of overdissipation problems near channel cells, the connectivity feature of river cells and the robustness of the parameter determination procedure over existing algorithms. Copyright © 2004 John Wiley & Sons, Ltd.     

Hydrological model sensitivity to parameter and radar rainfall estimation uncertainty

Radar estimates of rainfall are being increasingly applied to flood forecasting applications. Errors are inherent both in the process of estimating rainfall from radar and in the modelling of the rainfall–runoff transformation. The study aims at building a framework for the assessment of uncertainty that is consistent with the limitations of the model and data available and that allows a direct quantitative comparison between model predictions obtained by using radar and raingauge rainfall inputs. The study uses radar data from a mountainous region in northern Italy where complex topography amplifies radar errors due to radar beam occlusion and variability of precipitation with height. These errors, together with other error sources, are adjusted by applying a radar rainfall estimation algorithm. Radar rainfall estimates, adjusted and not, are used as an input to TOPMODEL for flood simulation over the Posina catchment (116 km²). Hydrological model parameter uncertainty is explicitly accounted for by use of the GLUE (Generalized Likelihood Uncertainty Estimation). Statistics are proposed to evaluate both the wideness of the uncertainty limits and the percentage of observations which fall within the uncertainty bounds. Results show the critical importance of proper adjustment of radar estimates and the use of radar estimates as close to ground as possible. Uncertainties affecting runoff predictions from adjusted radar data are close to those obtained by using a dense raingauge network, at least for the lowest radar observations available. Copyright © 2004 John Wiley & Sons, Ltd.     

Discussion of “Perceptual models of uncertainty for socio-hydrological systems: a flood risk change example”*

ABSTRACT

Dealing with uncertainty is key in socio-hydrological analysis. As such, thinking through what uncertainties mean for whom and when is key. This discussion contribution introduces three issues related to defining uncertainties. The first issue deals with the problem of defining uncertainty as a given external reality. The second issue deals with who decides about relevant uncertainties. The third issue deals with the issue whether coupled human-hydrological systems can be seen as existing on their own. Finally, the text provides two examples of hydrological research that try to be explicit about our dealing with multiple (interpretations of) realities.     

Temporal sampling strategies and uncertainty in calibrating a conceptual hydrological model for a small boreal catchment

How much data is needed for calibration of a hydrological catchment model? In this paper we address this question by evaluating the information contained in different subsets of discharge and groundwater time series for multi‐objective calibration of a conceptual hydrological model within the framework of an uncertainty analysis. The study site was a 5·6‐km² catchment within the Forsmark research site in central Sweden along the Baltic coast. Daily time series data were available for discharge and several groundwater wells within the catchment for a continuous 1065‐day period. The hydrological model was a site‐specific modification of the conceptual HBV model. The uncertainty analyses were based on a selective Monte Carlo procedure. Thirteen subsets of the complete time series data were investigated with the idea that these represent realistic intermittent sampling strategies. Data subsets included split‐samples and various combinations of weekly, monthly, and quarterly fixed interval subsets, as well as a 53‐day ‘informed observer’ subset that utilized once per month samples except during March and April—the months containing large and often dominant snow melt events—when sampling was once per week. Several of these subsets, including that of the informed observer, provided very similar constraints on model calibration and parameter identification as the full data record, in terms of credibility bands on simulated time series, posterior parameter distributions, and performance indices calculated to the full dataset. This result suggests that hydrological sampling designs can, at least in some cases, be optimized. Copyright © 2009 John Wiley & Sons, Ltd.     

Discussion of “Perceptual models of uncertainty for socio-hydrological systems: a flood risk change example”*

ABSTRACT

Dealing with uncertainty is key in socio-hydrological analysis. As such, thinking through what uncertainties mean for whom and when is key. This discussion contribution introduces three issues related to defining uncertainties. The first issue deals with the problem of defining uncertainty as a given external reality. The second issue deals with who decides about relevant uncertainties. The third issue deals with the issue whether coupled human-hydrological systems can be seen as existing on their own. Finally, the text provides two examples of hydrological research that try to be explicit about our dealing with multiple (interpretations of) realities.     

A two-stage sensitivity analysis for parameter identification and calibration of a physically-based distributed model in a river basin

Hydrological models demand large numbers of input parameters, which are to be optimally identified for better simulation of various hydrological processes. Identifying the most relevant parameters and their values using efficient sensitivity analysis methods helps to better understand model performance. In this study, the physically-based distributed model SHETRAN is used for hydrological simulation on the Netravathi River Basin in south India and the most important parameters are identified using the Morris screening method. Further, the influence of a particular model parameter on streamflow is quantified using local sensitivity analysis and optimal parameters are obtained for calibration of the SHETRAN model. The results demonstrate the capability of two-stage sensitivity analysis, combining qualitative and quantitative methods in the initial screening-out of insignificant model parameters, identifying parameter interactions and quantifying the contribution of each model parameter to the streamflow. The results of the sensitivity analysis simplified the calibration procedure of SHETRAN for the study area.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

Modelling the hydrologic effects of dynamic land‐use change using a distributed hydrologic model and a spatial land‐use allocation model

This study develops a novel approach for modelling and examining the impacts of time–space land‐use changes on hydrological components. The approach uses an empirical land‐use change allocation model (CLUE‐s) and a distributed hydrological model (DHSVM) to examine various land‐use change scenarios in the Wu‐Tu watershed in northern Taiwan. The study also uses a generalized likelihood uncertainty estimation approach to quantify the parameter uncertainty of the distributed hydrological model. The results indicate that various land‐use policies—such as no change, dynamic change and simultaneous change—have different levels of impact on simulating the spatial distributions of hydrological components in the watershed study. Peak flow rates under simultaneous and dynamic land‐use changes are 5·71% and 2·77%, respectively, greater than the rate under the no land‐use change scenario. Using dynamic land‐use changes to assess the effect of land‐use changes on hydrological components is more practical and feasible than using simultaneous land‐use change and no land‐use change scenarios. Furthermore, land‐use change is a spatial dynamic process that can lead to significant changes in the distributions of ground water and soil moisture. The spatial distributions of land‐use changes influence hydrological processes, such as the ground water level of whole areas, particularly in the downstream watershed. Copyright © 2010 John Wiley & Sons, Ltd.     

A BTOP model to extend TOPMODEL for distributed hydrological simulation of large basins

Topography is a dominant factor in hillslope hydrology. TOPMODEL, which uses a topographical index derived from a simplified steady state assumption of mass balance and empirical equations of motion over a hillslope, has many advantages in this respect. Its use has been demonstrated in many small basins (catchment areas of the order of 2–500 km²) but not in large basins (catchment areas of the order of 10 000–100 000 km²). The objective of this paper is to introduce the Block‐wise TOPMODEL (BTOP) as an extension of the TOPMODEL concept in a grid based framework for distributed hydrological simulation of large river basins. This extension was made by redefining the topographical index by using an effective contributing area af(a) (0?f(a)?1) per unit grid cell area instead of the upstream catchment area per unit contour length and introducing a concept of mean groundwater travel distance. Further the transmissivity parameter T₀ was replaced by a groundwater dischargeability D which can provide a link between hill slope hydrology and macro hydrology. The BTOP model uses all the original TOPMODEL equations in their basic form. The BTOP model has been used as the core hydrological module of an integrated distributed hydrological model YHyM with advanced modules of precipitation, evapotranspiration, flow routing etc. Although the model has been successfully applied to many catchments around the world since 1999, there has not been a comprehensive theoretical basis presented in such applications. In this paper, an attempt is made to address this issue highlighted with an example application using the Mekong basin. Copyright © 2007 John Wiley & Sons, Ltd.