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1.
The solution of many practical water problems is strictly connected to the availability of reliable and widespread information about runoff. The estimation of mean annual runoff and its interannual variability for any basin over a wide region, even if ungauged, would be fundamental for both water resources assessment and planning and for water quality analysis. Starting from these premises, the main aim of this work is to show a new approach, based on the Budyko's framework, for mapping the mean annual surface runoff and deriving the probability distribution of the annual runoff in arid and semiarid watersheds. As a case study, the entire island of Sicily, Italy, is here proposed. First, time series data of annual rainfall, runoff, and reconstructed series of potential evapotranspiration have been combined within the Budyko's curve framework to obtain regional rules for rainfall partitioning between evapotranspiration and runoff. Then this knowledge has been used to infer long‐term annual runoff at the point scale by means of interpolated rainfall and potential evapotranspiration. The long‐term annual runoff raster layer has been obtained at each pixel of the drainage network, averaging the upstream runoff using advanced spatial analysis techniques within a GIS environment. Furthermore, 2 alternative methods are here proposed to derive the distribution of annual runoff, under the assumption of negligible interannual variations of basin water storage. The first method uses Monte Carlo simulations, combining rainfall and potential evapotranspiration randomly extracted from independent distributions. The second method is based on a simplification of the Budyko's curve and analytically provides the annual runoff distribution as the derived distribution of annual rainfall and potential evapotranspiration. Results are very encouraging: long‐term annual runoff and its distribution have been derived and compared with historical records at several gauged stations, obtaining satisfactory matching.  相似文献   

2.
J. Vaze  A. Davidson  J. Teng  G. Podger 《水文研究》2011,25(16):2597-2612
The impact of future climate on runoff generation and the implications of these changes for management of water resources in a river basin are investigated by running these changes through catchment and river system models. Two conceptual daily rainfall‐runoff models are used to simulate runoff across the Macquarie‐Castlereagh region for historical (1895–2006) and future (~2030) climate based on outputs from 15 of the 23 IPCC AR4 GCMs for the A1B global warming scenario. The estimates of future runoff are used as inputs to the river system model. The mean annual historical rainfall averaged across the Macquarie‐Castlereagh region is 544 mm and the simulated runoff is 34 and 30 mm for SIMHYD and Sacramento rainfall‐runoff models, respectively. The mean annual future rainfall and runoff across the region are projected to decrease. The modelling results show a median estimate of a 5% reduction for SIMHYD (50% confidence interval ? 11 to + 7%) and a 7% reduction for Sacramento (50% confidence interval ? 15 to + 8%) in mean annual runoff under a ~2030 climate for the region. The results from the river system modelling indicate that under the ~2030 climate scenario, the median of general security and supplementary diversions are projected to decrease by 4% (50% confidence interval ? 10 to + 5%) and 2% (50% confidence interval ? 5 to + 3%) respectively for the SIMHYD inflows and 8% (50% confidence interval ? 17 to + 6%) and 5% (50% confidence interval ? 11 to + 3%) for the Sacramento inflows. The future annual and seasonal storage volumes for the Burrendong Dam and inflows at all major locations across the region are projected to be lower than the historical records. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

3.
An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable.  相似文献   

4.
5.
C. Fleurant  B. Kartiwa  B. Roland 《水文研究》2006,20(18):3879-3895
The rainfall‐runoff modelling of a river basin can be divided into two processes: the production function and the transfer function. The production function determines the proportion of gross rainfall actually involved in the runoff. The transfer function spreads the net rainfall over time and space in the river basin. Such a transfer function can be modelled using the approach of the geomorphological instantaneous unit hydrograph (GIUH). The effectiveness of geomorphological models is actually revealed in rainfall‐runoff modelling, where hydrologic data are desperately lacking, just as in ungauged basins. These models make it possible to forecast the hydrograph shape and runoff variation versus time at the basin outlet. This article is an introduction to a new GIUH model that proves to be simple and analytical. Its geomorphological parameters are easily available on a map or from a digital elevation model. This model is based on general hypotheses on symmetry that provide it with multiscale versatile characteristics. After having validated the model in river basins of very different nature and size, we present an application of this model for rainfall‐runoff modelling. Since parameters are determined relying on real geomorphological data, no calibration is necessary, and it is then possible to carry out rainfall‐runoff simulations in ungauged river basins. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

6.
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   

7.
This study examines the role of rainfall variability on the spatial scaling structure of peak flows using the Whitewater River basin in Kansas as an illustration. Specifically, we investigate the effect of rainfall on the scatter, the scale break and the power law (peak flows vs. upstream areas) regression exponent. We illustrate why considering individual hydrographs at the outlet of a basin can lead to misleading interpretations of the effects of rainfall variability. We begin with the simple scenario of a basin receiving spatially uniform rainfall of varying intensities and durations and subsequently investigate the role of storm advection velocity, storm variability characterized by variance, spatial correlation and intermittency. Finally, we use a realistic space–time rainfall field obtained from a popular rainfall model that combines the aforementioned features. For each of these scenarios, we employ a recent formulation of flow velocity for a network of channels, assume idealized conditions of runoff generation and flow dynamics and calculate peak flow scaling exponents, which are then compared to the scaling exponent of the width function maxima. Our results show that the peak flow scaling exponent is always larger than the width function scaling exponent. The simulation scenarios are used to identify the smaller scale basins, whose response is dominated by the rainfall variability and the larger scale basins, which are driven by rainfall volume, river network aggregation and flow dynamics. The rainfall variability has a greater impact on peak flows at smaller scales. The effect of rainfall variability is reduced for larger scale basins as the river network aggregates and smoothes out the storm variability. The results obtained from simple scenarios are used to make rigorous interpretations of the peak flow scaling structure that is obtained from rainfall generated with the space–time rainfall model and realistic rainfall fields derived from NEXRAD radar data.  相似文献   

8.
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.  相似文献   

9.
Lateral inflows control the spatial distribution of river discharge, and understanding their patterns is fundamental for accurately modelling instream flows and travel time distributions necessary for evaluating impacts of climate change on aquatic habitat suitability, river energy budgets, and fate of dissolved organic carbon. Yet, little is known about the spatial distribution of lateral inflows in Arctic rivers given the lack of gauging stations. With a network of stream gauging and meteorological stations within the Kuparuk River watershed in northern Alaska, we estimated precipitation and lateral inflows for nine subcatchments from 1 July to 4 August,2013, 2014, and 2015. Total precipitation, lateral inflows, runoff ratios (area-normalized lateral inflow divided by precipitation), percent contribution to total basin discharge, and lateral inflow per river kilometre were estimated for each watershed for relatively dry, moderate, or wet summers. The results show substantial variability between years and subcatchments. Total basin lateral inflow depths ranged 24-fold in response to a threefold change in rainfall between dry and wet years, whereas within-basin lateral inflows varied fivefold from the coastal plain to the foothills. General spatial trends in lateral inflows were consistent with previous studies and mean summer precipitation patterns. However, the spatially distributed nature of these estimates revealed that reaches in the vicinity of a spring-fed surficial ice feature do not follow general spatial trends and that the coastal plain, which is typically considered to produce minimal runoff, showed potential to contribute to total river discharge. These findings are used to provide a spatially distributed understanding of lateral inflows and identify watershed characteristics that influence hydrologic responses.  相似文献   

10.
Tropical river basins are experiencing major hydrological alterations as a result of climate variability and deforestation. These drivers of flow changes are often difficult to isolate in large basins based on either observations or experiments; however, combining these methods with numerical models can help identify the contribution of climate and deforestation to hydrological alterations. This paper presents a study carried out in the Tapaj?s River (Brazil), a 477,000 km2 basin in South‐eastern Amazonia, in which we analysed the role of annual land cover change on daily river flows. Analysis of observed spatial and temporal trends in rainfall, forest cover, and river flow metrics for 1976 to 2008 indicates a significant shortening of the wet season and reduction in river flows through most of the basin despite no significant trend in annual precipitation. Coincident with seasonal trends over the past 4 decades, over 35% of the original forest (140,000 out of 400,000 km2) was cleared. In order to determine the effects of land clearing and rainfall variability to trends in river flows, we conducted hindcast simulations with ED2 + R, a terrestrial biosphere model incorporating fine scale ecosystem heterogeneity arising from annual land‐use change and linked to a flow routing scheme. The simulations indicated basin‐wide increases in dry season flows caused by land cover transitions beginning in the early 1990s when forest cover dropped to 80% of its original extent. Simulations of historical potential vegetation in the absence of land cover transitions indicate that reduction in rainfall during the dry season (mean of ?9 mm per month) would have had an opposite and larger magnitude effect than deforestation (maximum of +4 mm/month), leading to the overall net negative trend in river flows. In light of the expected increase in future climate variability and water infrastructure development in the Amazon and other tropical basins, this study presents an approach for analysing how multiple drivers of change are altering regional hydrology and water resources management.  相似文献   

11.
Basin landscapes possess an identifiable spatial structure, fashioned by climate, geology and land use, that affects their hydrologic response. This structure defines a basin's hydrogeological signature and corresponding patterns of runoff and stream chemistry. Interpreting this signature expresses a fundamental understanding of basin hydrology in terms of the dominant hydrologic components: surface, interflow and groundwater runoff. Using spatial analysis techniques, spatially distributed watershed characteristics and measurements of rainfall and runoff, we present an approach for modelling basin hydrology that integrates hydrogeological interpretation and hydrologic response unit concepts, applicable to both new and existing rainfall‐runoff models. The benefits of our modelling approach are a clearly defined distribution of dominant runoff form and behaviour, which is useful for interpreting functions of runoff in the recruitment and transport of sediment and other contaminants, and limited over‐parameterization. Our methods are illustrated in a case study focused on four watersheds (24 to 50 km2) draining the southern coast of California for the period October 1988 though to September 2002. Based on our hydrogeological interpretation, we present a new rainfall‐runoff model developed to simulate both surface and subsurface runoff, where surface runoff is from either urban or rural surfaces and subsurface runoff is either interflow from steep shallow soils or groundwater from bedrock and coarse‐textured fan deposits. Our assertions and model results are supported using streamflow data from seven US Geological Survey stream gauges and measured stream silica concentrations from two Santa Barbara Channel–Long Term Ecological Research Project sampling sites. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

12.
Australian arid zone ephemeral rivers are typically unregulated and maintain a high level of biodiversity and ecological health. Understanding the ecosystem functions of these rivers requires an understanding of their hydrology. These rivers are typified by highly variable hydrological regimes and a paucity, often a complete absence, of hydrological data to describe these flow regimes. A daily time‐step, grid‐based, conceptual rainfall–runoff model was developed for the previously uninstrumented Neales River in the arid zone of northern South Australia. Hourly, logged stage data provided a record of stream‐flow events in the river system. In conjunction with opportunistic gaugings of stream‐flow events, these data were used in the calibration of the model. The poorly constrained spatial variability of rainfall distribution and catchment characteristics (e.g. storage depths) limited the accuracy of the model in replicating the absolute magnitudes and volumes of stream‐flow events. In particular, small but ecologically important flow events were poorly modelled. Model performance was improved by the application of catchment‐wide processes replicating quick runoff from high intensity rainfall and improving the area inundated versus discharge relationship in the channel sections of the model. Representing areas of high and low soil moisture storage depths in the hillslope areas of the catchment also improved the model performance. The need for some explicit representation of the spatial variability of catchment characteristics (e.g. channel/floodplain, low storage hillslope and high storage hillslope) to effectively model the range of stream‐flow events makes the development of relatively complex rainfall–runoff models necessary for multisite ecological studies in large, ungauged arid zone catchments. Grid‐based conceptual models provide a good balance between providing the capacity to easily define land types with differing rainfall–runoff responses, flexibility in defining data output points and a parsimonious water‐balance–routing model. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

13.
V. Hrissanthou 《水文研究》2006,20(18):3939-3952
The Yermasoyia Reservoir is located northeast of the town of Limassol, Cyprus. The storage capacity of the reservoir is 13·6 × 106 m3. The basin area of the Yermasoyia River, which feeds the reservoir, totals 122·5 km2. This study aims to estimate the mean annual deposition amount in the reservoir, which originates from the corresponding basin. For the estimate of the mean annual sediment inflow into the reservoir, two mathematical models are used alternatively. Each model consists of three submodels: a rainfall‐runoff submodel, a soil erosion submodel and a sediment transport submodel for streams. In the first model, the potential evapotranspiration is estimated for the rainfall‐runoff submodel, and the soil erosion submodel of Schmidt and the sediment transport submodel of Yang are used. In the second model, the actual evapotranspiration is estimated for the rainfall‐runoff submodel, and the soil erosion submodel of Poesen and the sediment transport submodel of Van Rijn are used. The deposition amount in the reservoir is estimated by means of the diagram of Brune, which delivers the trap efficiency of the reservoir. Daily rainfall data from three rainfall stations, and daily values of air temperature, relative air humidity and sunlight hours from a meteorological station for four years (1986–89) were available. The computed annual runoff volumes and mean annual soil erosion rate are compared with the respective measurement data. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

14.
High resolution radar rainfall fields and a distributed hydrologic model are used to evaluate the sensitivity of flood and flash flood simulations to spatial aggregation of rainfall and soil properties at catchment scales ranging from 75 to 983 km2. Hydrologic modeling is based on a Hortonian infiltration model and a network-based representation of hillslope and channel flow. The investigation focuses on three extreme flood and flash flood events occurred on the Sesia river basin, North Western Italy, which are analysed by using four aggregation lengths ranging from 1 to 16 km. The influence of rainfall spatial aggregation is examined by using the flow distance as a spatial coordinate, hence emphasising the role of river network in the averaging of space–time rainfall. The effects of reduced and distorted rainfall spatial variability on peak discharge have been found particularly severe for the flash flood events, with peak errors up to 35% for rainfall aggregation of 16 km and at 983 km2 catchment size. Effects are particularly remarkable when significant structured rainfall variability combines with relatively important infiltration volumes due to dry initial conditions, as this emphasises the non-linear character of the rainfall–runoff relationship. In general, these results confirm that the correct estimate of rainfall volume is not enough for the accurate reproduction of flash flood events characterised by large and structured rainfall spatial variability, even at catchment scales around 250 km2. However, accurate rainfall volume estimation may suffice for less spatially variable flood events. Increasing the soil properties aggregation length exerts similar effects on peak discharge errors as increasing the rainfall aggregation length, for the cases considered here and after rescaling to preserve the rainfall volume. Moreover, peak discharge errors are roughly proportional to runoff volume errors, which indicates that the shape of the flood wave is influenced in a limited way by modifying the detail of the soil property spatial representation. Conversely, rainfall aggregation may exert a pronounced influence on the discharge peak by reshaping the spatial organisation of the runoff volumes and without a comparable impact on the runoff volumes.  相似文献   

15.
Studying the processes responsible for the distribution of water resources in a river basin over space and time is of great importance for spatial planning. In this study a multi-agent simulation approach is applied for exploring the influence of alternative reservoir operation strategies on water use distribution in the semi-arid Jaguaribe basin in case of decreasing rainfall. Water use distribution is analyzed both for one specific subbasin – our study area – and for the river basin level. Agents in this study are farmers that adapt to local variations in water availability. In this way both natural and human influences on water availability are taken into account. This study shows that a decrease in rainfall and runoff in the Jaguaribe basin leads to a transition of water use from the dry season to the wet season. The dry season water use decreases because of reduced water availability in the dry season. This mainly is the result of reduced rainfall and runoff in the wet season and the consequent increased water use for irrigation in the wet season. A decrease in rainfall and runoff also leads to a relative transition of water use from downstream to upstream at the basin scale. Strategic reservoir operation enables local water managers to offset the effect of decreasing rainfall and runoff with regards to water use at the subbasin level, at the cost of further decreasing water availability at the basin level.  相似文献   

16.
This paper compares artificial neural network (ANN), fuzzy logic (FL) and linear transfer function (LTF)‐based approaches for daily rainfall‐runoff modelling. This study also investigates the potential of Takagi‐Sugeno (TS) fuzzy model and the impact of antecedent soil moisture conditions in the performance of the daily rainfall‐runoff models. Eleven different input vectors under four classes, i.e. (i) rainfall, (ii) rainfall and antecedent moisture content, (iii) rainfall and runoff and (iv) rainfall, runoff and antecedent moisture content are considered for examining the effects of input data vector on rainfall‐runoff modelling. Using the rainfall‐runoff data of the upper Narmada basin, Central India, a suitable modelling technique with appropriate model input structure is suggested on the basis of various model performance indices. The results show that the fuzzy modelling approach is uniformly outperforming the LTF and also always superior to the ANN‐based models. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

17.
Huai River Basin, as the sixth largest river basin in China, has a high‐regulated river system and has been facing severe water problems. In this article, the changing patterns of runoff and precipitation at 10 hydrological stations from 1956 to 2000 on the highly regulated river (Shaying River) and less‐regulated river (Huai River) in the basin are evaluated at the monthly, seasonal and annual scales using the Mann–Kendall test and simple linear regression model. The results showed that: (1) No statistically significant trends of precipitation in the upper and middle Huai River Basins were detected at the annual scale, but the trend of annual runoff at Baiguishan, Zhoukou and Fuyang stations in Shaying River decreased significantly, whereas the others were not. Moreover, the decreasing trends of runoff for most months were significant in Shaying River, although the trend of monthly precipitation decreased significantly only in April in the whole research area and the number of months in the dry season having significantly decreasing trends in runoff was more than that in the wet season. (2) The rainfall–runoff relationship was significant in both highly regulated river and less‐regulated river. In regulated river, the reservoirs have larger regulation capacity than the floodgates and thus have the smaller correlation coefficient and t‐value. In Huai River, the correlation coefficients decreased from upper stream to downstream. (3) The regulation of dams and floodgates for flood control and water supply was the principal reason for the decreasing runoff in Huai River Basin, although the decreasing precipitation in April in this basin was statistically significant. The findings are useful for recognizing hydrology variation and will provide scientific foundation to integrated water resources management in Huai River Basin. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

18.
In this study a simple modelling approach was applied to identify the need for spatial complexity in representing hydrological processes and their variability over different scales. A data set of 18 basins was used, ranging between 8 and 4011 km2 in area, located in the Nahe basin (Germany), with daily discharge values for over 30 years. Two different parsimoniously structured models were applied in lumped as well as in spatially distributed according to two distribution classifications: (1) a simple classification based on the lithology expressed in three permeability types and (2) a more complex classification based on seven dominating runoff production processes. The objective of the study was to compare the performances of the models on a local and on a regional scale as well as between the models with a view to identifying the accuracy in capturing the spatial variability of the rainfall‐runoff relationships. It was shown that the presence of a specific basin characteristic or process of the distribution classification was not related with higher model performance; only a larger basin size promoted higher model performance. The results of this study also indicated that the permeability generally contained more useful information on the spatial heterogeneity of the hydrological behaviour of the natural system than did a more detailed classification on dominating runoff generation processes. Although model performance was slightly lower for the model that used permeability as a distribution classification, consistency in its parameter values was found, which was lacking with the more complex distribution classification. The latter distribution classification had a higher flexibility to optimize towards the variability of the runoff, which resulted in higher performance, however, process representation was applied inconsistently. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

19.
There is increasing demand for models that can accurately predict river temperature at the large spatial scales appropriate to river management. This paper combined summer water temperature data from a strategically designed, quality controlled network of 25 sites, with recently developed flexible spatial regression models, to understand and predict river temperature across a 3,000 km2 river catchment. Minimum, mean and maximum temperatures were modelled as a function of nine potential landscape covariates that represented proxies for heat and water exchange processes. Generalised additive models were used to allow for flexible responses. Spatial structure in the river network data (local spatial variation) was accounted for by including river network smoothers. Minimum and mean temperatures decreased with increasing elevation, riparian woodland and channel gradient. Maximum temperatures increased with channel width. There was greater between‐river and between‐reach variability in all temperature metrics in lower‐order rivers indicating that increased monitoring effort should be focussed at these smaller scales. The combination of strategic network design and recently developed spatial statistical approaches employed in this study have not been used in previous studies of river temperature. The resulting catchment scale temperature models provide a valuable quantitative tool for understanding and predicting river temperature variability at the catchment scales relevant to land use planning and fisheries management and provide a template for future studies.  相似文献   

20.
Statistical self-similarity in the spatial and temporal variability of rainfall, river networks, and runoff processes has been observed in many empirical studies. To theoretically investigate the relationships between the various time and space scales of variability in rainfall and runoff process we propose a simplified, yet physically based model of a catchment–rainfall interaction. The channel network is presented as a random binary tree, having topological and hydraulic geometry properties typically observed in real river networks. The continuous rainfall model consists of individual storms separated by dry periods. Each given storm is disaggregated in space and time using the random cascade model. The flow routing is modelled by the network of topologically connected nonlinear reservoirs, each representing a link in the channel network. Running the model for many years of synthetic rainfall time series and a continuous water balance model we generate an output, in the form of continuous time series of water discharge in all links in the channel network. The main subject of study is the annual peak flow as a function of catchment area and various characteristics of rainfall. The model enables us to identify different physical processes responsible for the empirically observed scaling properties of peak flows.  相似文献   

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