A review of continental scale hydrological models and their suitability for drought forecasting in (sub-Saharan) Africa

The aim of this review is to provide a basis for selecting a suitable hydrological model, or combination of models, for hydrological drought forecasting in Africa at different temporal and spatial scales; for example short and medium range (1–10 days or monthly) forecasts at medium to large river basin scales or seasonal forecasts at the Pan-African scale. Several global hydrological models are currently available with different levels of complexity and data requirements. However, most of these models are likely to fail to properly represent the water balance components that are particularly relevant in arid and semi-arid basins in sub-Saharan Africa. This review critically looks at weaknesses and strengths in the representation of different hydrological processes and fluxes of each model. The major criteria used for assessing the suitability of the models are (1) the representation of the processes that are most relevant for simulating drought conditions, such as interception, evaporation, surface water-groundwater interactions in wetland areas and flood plains and soil moisture dynamics; (2) the capability of the model to be downscaled from a continental scale to a large river basin scale model; and (3) the applicability of the model to be used operationally for drought early warning, given the data availability of the region. This review provides a framework for selecting models for hydrological drought forecasting, conditional on spatial scale, data availability and end-user forecast requirements. Among 16 well known hydrological and land surface models selected for this review, PCR-GLOBWB, GWAVA, HTESSEL, LISFLOOD and SWAT show higher potential and suitability for hydrological drought forecasting in Africa based on the criteria used in this evaluation.     

Investigating the use of spatial discretization of hydrological processes in conceptual rainfall runoff modelling: a case study for the meso‐scale

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.     

Interactions and connectivity between runoff generation processes of different spatial scales

Monitoring runoff generation processes in the field is a prerequisite for developing conceptual hydrological models and theories. At the same time, our perception of hydrological processes strongly depends on the spatial and temporal scale of observation. Therefore, the aim of this study is to investigate interactions between runoff generation processes of different spatial scales (plot scale, hillslope scale, and headwater scale). Different runoff generation processes of three hillslopes with similar topography, geology and soil properties, but differences in vegetation cover (grassland, coniferous forest, and mixed forest) within a small v‐shaped headwater were measured: water table dynamics in wells with high spatial and temporal resolution, subsurface flow (SSF) of three 10 m wide trenches at the bottom of the hillslopes subdivided into two trench sections each, overland flow at the plot scale, and catchment runoff. Bachmair et al. ( 2012 ) found a high spatial variability of water table dynamics at the plot scale. In this study, we investigate the representativity of SSF observations at the plot scale versus the hillslope scale and vice versa, and the linkage between hillslope dynamics (SSF and overland flow) and streamflow. Distinct differences in total SSF within each 10 m wide trench confirm the high spatial variability of the water table dynamics. The representativity of plot scale observations for hillslope scale SSF strongly depends on whether or not wells capture spatially variable flowpaths. At the grassland hillslope, subsurface flowpaths are not captured by our relatively densely spaced wells (3 m), despite a similar trench flow response to the coniferous forest hillslope. Regarding the linkage between hillslope dynamics and catchment runoff, we found an intermediate to high correlation between streamflow and hillslope hydrological dynamics (trench flow and overland flow), which highlights the importance of hillslope processes in this small watershed. Although the total contribution of SSF to total event catchment runoff is rather small, the contribution during peak flow is moderate to substantial. Additionally, there is process synchronicity between spatially discontiguous measurement points across scales, potentially indicating subsurface flowpath connectivity. Our findings stress the need for (i) a combination of observations at different spatial scales, and (ii) a consideration of the high spatial variability of SSF at the plot and hillslope scale when designing monitoring networks and assessing hydrological connectivity. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessing effects of model complexity and structure on predictions of hydrological responses using serial and parallel model design

By utilizing functional relationships based on observations at plot or field scales, water quality models first compute surface runoff and then use it as the primary governing variable to estimate sediment and nutrient transport. When these models are applied at watershed scales, this serial model structure, coupling a surface runoff sub-model with a water quality sub-model, may be inappropriate because dominant hydrological processes differ among scales. A parallel modeling approach is proposed to evaluate how best to combine dominant hydrological processes for predicting water quality at watershed scales. In the parallel scheme, dominant variables of water quality models are identified based entirely on their statistical significance using time series analysis. Four surface runoff models of different model complexity were assessed using both the serial and parallel approaches to quantify the uncertainty on forcing variables used to predict water quality. The eight alternative model structures were tested against a 25-year high-resolution data set of streamflow, suspended sediment discharge, and phosphorous discharge at weekly time steps. Models using the parallel approach consistently performed better than serial-based models, by having less error in predictions of watershed scale streamflow, sediment and phosphorus, which suggests model structures of water quantity and quality models at watershed scales should be reformulated by incorporating the dominant variables. The implication is that hydrological models should be constructed in a way that avoids stacking one sub-model with one set of scale assumptions onto the front end of another sub-model with a different set of scale assumptions.     

半干旱地区洪水模拟效果差异性分析及影响因子响应评估

中国北方半干旱地区的降水与下垫面条件具有明显的时空异质性,如何完整准确地描述该类区域的水文过程是当代水文学研究的难点之一.选择半干旱地区水文实验区域——绥德流域和曹坪流域,通过构建不同时空规律的降水场,并结合3种不同产流机制的水文模型,进行大型数值模拟实验,去探究时间、空间、产流机制等因素对半干旱地区洪水模拟的影响,为该类地区水文模型的研制工作提供借鉴.结果 表明:1)半干旱地区中小流域的产流对降雨强度较为敏感,因此降水输入的时间步长对洪水模拟效果的影响程度较大;相比之下,流域雨量站数量的增减,仅体现在降雨分布场的暴雨中心缺失以及面平均降雨量的微小差别,对洪水模拟效果的影响程度较小.2)水文模型能否准确描述主导水文过程是半干旱地区洪水模拟效果优良的关键,流域的尺度效应及其下垫面条件的空间异质性是半干旱地区不同水文模型研制和调整应当优先考虑的问题,无论时间步长、雨量站数量怎么组合,产流结构适宜的模型其模拟效果总是趋于较好的结果.     

An analysis of the impact of spatial variability in rainfall on runoff and sediment predictions from a distributed model

This paper investigates the effect of introducing spatially varying rainfall fields to a hydrological model simulating runoff and erosion. Pairs of model simulations were run using either spatially uniform (i.e. spatially averaged) or spatially varying rainfall fields on a 500‐m grid. The hydrological model used was a simplified version of Thales which enabled runoff generation processes to be isolated from hillslope averaging processes. Both saturation excess and infiltration excess generation mechanisms were considered, as simplifications of actual hillslope processes. A 5‐year average recurrence interval synthetic rainfall event typical of temperate climates (Melbourne, Australia) was used. The erosion model was based on the WEPP interrill equation, modified to allow nonlinear terms relating the erosion rate to rainfall or runoff‐squared. The model results were extracted at different scales to investigate whether the effects of spatially varying rainfall were scale dependent. A series of statistical metrics were developed to assess the variability due to introducing the spatially varying rainfall field. At the catchment (approximately 150 km²) scale, it was found that particularly for saturation excess runoff, model predictions of runoff were insensitive to the spatial resolution of the rainfall data. Generally, erosion processes at smaller sub‐catchment scales, particularly when the sediment generation equation had non linearity, were more sensitive to spatial rainfall variability. Introducing runon infiltration reduced the total runoff and sediment yield at all scales, and this process was also most sensitive to the rainfall resolution. Copyright © 2011 John Wiley & Sons, Ltd.     

Spatial and temporal variability of the hydrological response in a small Mediterranean research catchment (Vallcebre,Eastern Pyrenees)

This paper analyses the spatial and temporal variability of the hydrological response in a small Mediterranean catchment (Cal Rodó). The first part of the analysis focuses on the rainfall–runoff relationship at seasonal and monthly scale, using an 8‐year data set. Then, using storm‐flow volume and coefficient, the temporal variability of the rainfall–runoff relationship and its relationship with several hydrological variables are analysed at the event scale from hydrographs observed over a 3‐year period. Finally, the spatial non‐linearity of the hydrological response is examined by comparing the Cal Rodó hydrological response with the Can Vila sub‐catchment response at the event scale. Results show that, on a seasonal and monthly scale, there is no simple relationship between rainfall and runoff depths, and that evapotranspiration is a factor that introduced some non‐linearity in the rainfall–runoff relationship. The analysis of monthly values also reveals the existence of a threshold in the relationship between rainfall and runoff depths, denoting a more contrasted hydrological response than the one usually observed in humid catchments. At the event scale, the storm‐flow coefficient has a clear seasonal pattern with an alternance between a wet period, when the catchment is hydrologically responsive, and a dry summer period, when the catchment is much less reactive to any rainfall. The relationship between the storm‐flow coefficient and rainfall depth, rainfall maximum intensity and base‐flow shows that observed correlations are the same as those observed for humid conditions, even if correlation coefficients are notably lower. Comparison with the Can Vila sub‐catchment highlights the spatial heterogeneity of the rainfall‐runoff relationship at the small catchment scale. Although interpretation in terms of runoff processes remains delicate, heterogeneities between the two catchments seem to be related to changes in the ratio between infiltration excess and saturation processes in runoff formation. Copyright © 2007 John Wiley & Sons, Ltd.     

Investigation of the model complexity required in runoff simulation at different time scales / Etude de la complexité de modélisation requise pour la simulation d'écoulement à différentes échelles temporelles

Abstract

The “optimal” model complexity is defined as the minimum watershed model structure required for realistic representation of runoff processes. This paper examines the effects of model complexity at different time scales, daily and hourly. Two watershed models with different levels of complexity were constructed and their capability to simulate runoff from a watershed was evaluated. Both models were tested on the same watershed using identical meteorological input, thereby assuring that any difference between model outputs is due only to their model structure. It is demonstrated that, at a daily time scale, a simple model gives good results. For the mountain situation, in which snowmelt is a dominant influence, the nonlinearity of the runoff processes is moderate, and therefore a simple model works well. The model produced good results over a period of 28 years of continuous simulation. However, this simpler model was inadequate when tested on an hourly time scale due to greater nonlinear effects, especially when modelling high-intensity rainfall events. Therefore, the hourly simulation benefited from the more complex model structure. These model results show that optimal watershed model complexity depends on temporal resolution, namely the simulation period and the computational time step. It was shown that certain process representations and model parameters that appeared unimportant during the long-term simulation had significant effects on the short-term extreme event model simulation.     

Advancing understanding of runoff and sediment transfers in agricultural catchments through simultaneous observations across scales

Our understanding of the effect of scale on runoff and sediment transfers within catchments is currently limited by a lack of available data. A multi‐scale dataset of 17 rainfall events collected simultaneously at four spatial scales within a small agricultural catchment in 2005–2006 is presented. Analysis using exploratory techniques and a two‐step, zero‐inflated lognormal mixed‐effects regression model, has demonstrated that event responses, and event response characteristics representing runoff and sediment peaks and area‐normalized yields, are scale dependent, and hence cannot be transferred directly between scales. Runoff and sediment yields increase as scale increases, and it is proposed that this effect, which differs from that observed in the few other studies of scale effects undertaken, is due to increasing connectivity within the catchment, and the dominance of preferential flow pathways including through macropores and field drains. The processes contributing to scale dependence in the data, and the possibility that certain processes dominate at particular scales, are discussed. The data presented here help to improve our spatial understanding of runoff and sediment transport in small agricultural catchments, and provide examples of the type of spatial dataset and the type of analysis that are essential if we are to develop models which are able to predict runoff and soil erosion accurately, and allow us to manage runoff and sediment transport effectively across scales. Copyright © 2011 John Wiley & Sons, Ltd.     

Modelling the water balance of a mesoscale catchment basin using remotely sensed land cover data

Hydrological modelling of mesoscale catchments is often adversely affected by a lack of adequate information about specific site conditions. In particular, digital land cover data are available from data sets which were acquired on a European or a national scale. These data sets do not only exhibit a restricted spatial resolution but also a differentiation of crops and impervious areas which is not appropriate to the needs of mesoscale hydrological models. In this paper, the impact of remote sensing data on the reliability of a water balance model is investigated and compared to model results determined on the basis of CORINE (Coordination of Information on the Environment) Land Cover as a reference. The aim is to quantify the improved model performance achieved by an enhanced land cover representation and corresponding model modifications. Making use of medium resolution satellite imagery from SPOT, LANDSAT ETM+ and ASTER, detailed information on land cover, especially agricultural crops and impervious surfaces, was extracted over a 5-year period (2000–2004). Crop-specific evapotranspiration coefficients were derived by using remote sensing data to replace grass reference evapotranspiration necessitated by the use of CORINE land cover for rural areas. For regions classified as settlement or industrial areas, degrees of imperviousness were derived. The data were incorporated into the hydrological model GROWA (large-scale water balance model), which uses an empirical approach combining distributed meteorological data with distributed site parameters to calculate the annual runoff components. Using satellite imagery in combination with runoff data from gauging stations for the years 2000–2004, the actual evapotranspiration calculation in GROWA was methodologically extended by including empirical crop coefficients for actual evapotranspiration calculations. While GROWA originally treated agricultural areas as homogeneous, now a consideration and differentiation of the main crops is possible. The accuracy was determined by runoff measurements from gauging stations. Differences in water balances resulting from the use of remote sensing data as opposed to CORINE were analysed in this study using a representative subcatchment. Resulting Nash–Sutcliff model efficiencies improved from 0.372 to 0.775 and indicate that the enhanced model can produce thematically more accurate and spatially more detailed local water balances. However, the proposed model enhancements by satellite imagery have not exhausted the full potential of water balance modelling, for which a higher temporal resolution is required.     

Advances in the use of observed spatial patterns of catchment hydrological response

Over the past two decades there have been repeated calls for the collection of new data for use in developing hydrological science. The last few years have begun to bear fruit from the seeds sown by these calls, through increases in the availability and utility of remote sensing data, as well as the execution of campaigns in research catchments aimed at providing new data for advancing hydrological understanding and predictive capability. In this paper we discuss some philosophical considerations related to model complexity, data availability and predictive performance, highlighting the potential of observed patterns in moving the science and practice of catchment hydrology forward. We then review advances that have arisen from recent work on spatial patterns, including in the characterisation of spatial structure and heterogeneity, and the use of patterns for developing, calibrating and testing distributed hydrological models. We illustrate progress via examples using observed patterns of snow cover, runoff occurrence and soil moisture. Methods for the comparison of patterns are presented, illustrating how they can be used to assess hydrologically important characteristics of model performance. These methods include point-to-point comparisons, spatial relationships between errors and landscape parameters, transects, and optimal local alignment. It is argued that the progress made to date augers well for future developments, but there is scope for improvements in several areas. These include better quantitative methods for pattern comparisons, better use of pattern information in data assimilation and modelling, and a call for improved archiving of data from field studies to assist in comparative studies for generalising results and developing fundamental understanding.     

The use of agent based modelling techniques in hydrology: determining the spatial and temporal origin of channel flow in semi‐arid catchments

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

IV. Water resource modelling using remote sensing and object-oriented simulation

Remote sensing technology has matured significantly over the past decade. Operational satellites provide reliable, periodic coverage for all areas of the Earth. Data from these satellites are in a digital format that provides enhanced flexibility in hydrological modelling. Considerable advances in acquiring hydrological data from airborne and in situ sensors have also been achieved. Additionally, data from non-traditional remote sources such as weather radar from which spatial and temporal rainfall rates may be estimated are widely available. These new data acquisition capabilities have been paralleled by equal advancements in digital array processing and geographic information systems, which allow the effective extraction of both temporal and spatial information. This paper examines the use of object-oriented programming techniques to create dynamic hydrological models, and explores their potential to receive real and near real-time data from remote sensors as input to improve hydrological forecasting. In particular, the COE SSARR model is used to illustrate how an established hydrological model may be adapted to create a dynamic object model.     

Regional‐scale mapping of groundwater discharge zones using thermal satellite imagery

Mapping groundwater discharge zones at broad spatial scales remains a challenge, particularly in data sparse regions. We applied a regional scale mapping approach based on thermal remote sensing to map discharge zones in a complex watershed with a broad diversity of geological materials, land cover and topographic variation situated within the Prairie Parkland of northern Alberta, Canada. We acquired winter thermal imagery from the USGS Landsat archive to demonstrate the utility of this data source for applications that can complement both scientific and management programs. We showed that the thermally determined potential discharge areas were corroborated with hydrological (spring locations) and chemical (conservative tracers of groundwater) data. This study demonstrates how thermal remote sensing can form part of a comprehensive mapping framework to investigate groundwater resources over broad spatial scales. Copyright © 2013 John Wiley & Sons, Ltd.     

Two‐dimensional continuous simulation of spatiotemporally varied hydrological processes using the time‐area method

Distributed, continuous hydrologic models promote better understanding of hydrology and enable integrated hydrologic analyses by providing a more detailed picture of water transport processes across the varying landscape. However, such models are not widely used in routine modelling practices, due in part to the extensive data input requirements, computational demands, and complexity of routing algorithms. We developed a two‐dimensional continuous hydrologic model, HYSTAR, using a time‐area method within a grid‐based spatial data model with the goal of providing an alternative way to simulate spatiotemporally varied watershed‐scale hydrologic processes. The model calculates the direct runoff hydrograph by coupling a time‐area routing scheme with a dynamic rainfall excess sub‐model implemented here using a modified curve number method with an hourly time step, explicitly considering downstream ‘reinfiltration’ of routed surface runoff. Soil moisture content is determined at each time interval based on a water balance equation, and overland and channel runoff is routed on time‐area maps, representing spatial variation in hydraulic characteristics for each time interval in a storm event. Simulating runoff hydrographs does not depend on unit hydrograph theory or on solution of the Saint Venant equation, yet retains the simplicity of a unit hydrograph approach and the capability of explicitly simulating two‐dimensional flow routing. The model provided acceptable performance in predicting daily and monthly runoff for a 6‐year period for a watershed in Virginia (USA) using readily available geographic information about the watershed landscape. Spatial and temporal variability in simulated effective runoff depth and time area maps dynamically show the areas of the watershed contributing to the direct runoff hydrograph at the outlet over time, consistent with the variable source area overland flow generation mechanism. The model offers a way to simulate watershed processes and runoff hydrographs using the time‐area method, providing a simple, efficient, and sound framework that explicitly represents mechanisms of spatially and temporally varied hydrologic processes. Copyright © 2015 John Wiley & Sons, Ltd.     

Using integrated modelling to understand seasonal vegetation dynamics and its relationship to runoff generation

Vegetation dynamics and hydrological processes are major components of terrestrial ecosystems, and they interact strongly with each other. Studies of hydrological responses to vegetation dynamics are usually conducted on a long-term scale, whereas the hydrological responses within a single year have rarely been studied. In the present study, Poyang Lake runoff (PYL-R) model, a new hydrological model coupled with leaf area index (LAI) remote sensing products, was established and applied to simulate the runoff process in the Poyang Lake Watershed. The simulation results obtained in three sub-watersheds of the Poyang Lake Watershed (Ganjiang Watershed, Xinjiang Watershed, and Fuhe Watershed) agreed well with the observations (Nash efficiency coefficient values and R values exceeded 0.6 and 0.9, respectively). The PYL-R experiment (PYL-R-E) model was designed as a contrast model without considering the impact of LAI. The simulated monthly runoff results obtained using the PYL-R and PYL-R-E models were compared, and the within-year changes in the differences between the two results were analysed to evaluate and quantify the impact of vegetation dynamic on runoff. From January to July, when LAI values increased by around 2.6 m² m⁻², monthly runoff depth differences between PYL-R and PYL-R-E results increased by 35.25, 27.98, and 29.14 mm in the Ganjiang, Xinjiang, and Fuhe watersheds, respectively. Dense vegetation caused high interception and evapotranspiration during summer, which largely reduced runoff. By contrast, during winter, the effect of vegetation was weaker on runoff process whereas the impacts of other factors (e.g., precipitation) were higher. The sensitivity of monthly runoff to vegetation dynamics varied greatly throughout the whole year. In particular, during August and September, the LAI-caused runoff changes were very high, accounting for 28–42% of monthly runoff in the sub-watersheds. Our findings clarify the effects of changes in vegetation on hydrological processes over short time scales, thereby providing insights into the effects of scale on eco-hydrological processes.     

Complexity analysis of rainfall and runoff time series based on sample entropy in different temporal scales

This study applied sample entropy (SampEn) to rainfall and runoff time series to investigate the complexity of different temporal scales. Rainfall and runoff time series with intervals of 1, 10, 30, 90, and 365 days for the Wu-Tu upstream watershed were used. Thereafter, SampEn was computed for the five rainfall and runoff time series. The results show that for the various temporal scales, comparisons of the complexity between the rainfall and runoff time series based on the SampEn are inconsistent. Calculating the dynamic SampEn further elucidated variations of the complexity in the rainfall and runoff time series. In addition, the results show that SampEn measures of the rainfall and runoff time series are typically higher than the approximate entropy measures of the rainfall and runoff time series for a specific temporal scale. The complexity increases when the sample size increases for a specific temporal scale. Furthermore, temporal scales with low complexity and high predictability are obtained from the variations of SampEn for the rainfall and runoff time series with different temporal scales, thereby providing a reference for determining the appropriate temporal scale for rainfall and runoff time series forecasting.     

Water balance modeling over variable time scales based on the Budyko framework – Model development and testing

Partitioning of precipitation into evapotranspiration and runoff is controlled by climate and catchment characteristics. The degree of control exerted by these factors varies with the spatial and temporal scales of processes modeled. The Budyko framework or the “limits” concept was used to model water balance at four temporal scales (mean annual, annual, monthly and daily). The method represents a top-down approach to hydrologic modeling and is expected to achieve parsimony of model parameters. Daily precipitation, potential evapotranspiration, and streamflow from 265 catchments in Australia were used. On a mean annual basis, the index of dryness defined as the ratio of potential evapotranspiration to precipitation was confirmed to be a dominant factor in determining the water balance with one model parameter. Analysis of the data, however, suggested increased model complexity is necessary on finer time scale such as monthly. In response, the Budyko framework for mean annual water balance was extended to include additional factors and this resulted in a parsimonious lumped conceptual model on shorter-time scale. The model was calibrated and tested against measured streamflow at variable time scales and showed promising results. The strengths of the model are consistent water balance relationships across different time scales, and model parsimony and robustness. As result, the model has the potential to be used to predict streamflow for ungauged catchments.     

大尺度水文模型TOPX构建及其与区域环境系统集成模式RIEMS的耦合

基于改进型SIMTOP参数化径流方案和新安江模型的三层土壤水量平衡计算方法,本文构建了一个输入数据和率定参数较少、同时具有地形指数尺度转换机制、较好描述二维水文过程的简单高效的大尺度水文模型TOPX,并将其与区域环境系统集成模式RIEMS紧密耦合,以增强区域气候模式对大尺度流域径流量的定量数值模拟能力．TOPX模型在酉水河流域和泾河流域的离线测试表明：该模型对小尺度流域的径流量模拟精度较高,能够较好地描述流域水文变化过程;同时,该模型在大尺度上具有较强的分布式模拟能力,能够捕捉陆面水文过程的主要特征和时空演变特点．TOPX与RIEMS的耦合模式在泾河流域进行了在线测试,借助TOPX模型中的地形指数降尺度转换和水文过程产汇流机制,耦合模式实现了利用区域气候模式模拟的气象资料来驱动水文模型进行大尺度流域日径流量的模拟．进一步分析还表明：区域气候模式RIEMS模拟的降水时空分布数据的精度是影响耦合模式对径流量模拟效果的关键因素．