ALBERT

Description: In this study we propose an uspcaling approach to derive time series of (a) REW scale state variables, and (b) effective REW scale soil hydraulic functions to test and parameterise models based on the REW approach. To this end we employed a physically based hydrological model, that represents the typical patterns and structures in the study catchment, and has previously been shown to reproduce observed runoff response and state dynamics well. This landscape- and process-compatible model is used to simulate numerical drainage and wetting experiments. The effective soil water retention curve and soil hydraulic conductivity curve are derived using the spatially averaged saturation and capillary pressure as well as averaged fluxes. When driven with observed boundary conditions during a one year simulation the model is used to estimate how the spatial pattern of soil moisture evolved during this period in the catchment. The time series of the volume integrated soil moisture is deemed as best estimate for the average catchment scale soil moisture. The approach is applied to the extensively monitored Weiherbach catchment in Germany. A sensitivity analysis showed that catchment scale model structures different from the landscape- and process compatible one yielded different times series of average catchment scale soil moisture and where not able to reproduce the observed rainfall runoff response. Hence, subscale typical heterogeneity leaves a clear fingerprint in the time series of average catchment scale saturation. In case of the Weiherbach catchment local scale heterogeneity of ks could be neglected and a simple representation of the typical hillslope scale patterns of soil types and macroporosity was sufficient for obtaining effective REW scale soil hydraulic functions. Both the effective soil hydraulic functions and time series of catchment scale saturation turned out to be useful to parameterise and test the CREW model, which is based on the REW approach and was applied to the Weiherbach catchment in a companion study Lee et al. (2006, this issue).

Description: This study explores the dominant processes that may be responsible for the observed streamflow response in Seventeen Mile Creek, a tropical catchment located in a monsoonal climate in Northern Territory, Australia. The hydrology of this vast region of Australia is poorly understood due to the low level of information and gauging that are available. Any insights that can be gained from the few well gauged catchments that do exist can be valuable for predictions and water resource assessments in other poorly gauged or ungauged catchments in the region. To this end, the available rainfall and runoff data from Seventeen Mile Creek catchment are analyzed through the systematic and progressive development and testing of rainfall-runoff models of increasing complexity, by following the "downward" or "top-down" approach. This procedure resulted in a multiple bucket model (4 buckets in parallel). Modelling results suggest that the catchment's soils and the landscape in general have a high storage capacity, generating a significant fraction of delayed runoff, whereas saturation excess overland flow occurs only after heavy rainfall events. The sensitivity analyses carried out with the model with regard to soil depth and temporal rainfall variability revealed that total runoff from the catchment is more sensitive to rainfall variations than to soil depth variations, whereas the partitioning into individual components of runoff appears to be more influenced by soil depth variations. The catchment exhibits considerable inter-annual variability in runoff volumes and the greatest determinant of this variability turns out to be the seasonality of the climate, the timing of the wet season, and temporal patterns of the rainfall. The water balance is also affected by the underlying geology, nature of the soils and the landforms, and the type, density and dynamics of vegetation, although information pertaining to these is lacking.

Description: The aim of this paper is to illustrate the effects of selected catchment storage thresholds upon runoff behaviour, and specifically their impact upon flood frequency. The analysis is carried out with the use of a stochastic rainfall model, incorporating rainfall variability at intra-event, inter-event and seasonal timescales, as well as infrequent summer tropical cyclones, coupled with deterministic rainfall-runoff models that incorporate runoff generation by both saturation excess and subsurface stormflow mechanisms. Changing runoff generation mechanisms (i.e. from subsurface flow to surface runoff) associated with a given threshold (i.e. saturation storage capacity) is shown to be manifested in the flood frequency curve as a break in slope. It is observed that the inclusion of infrequent summer storm events increases the temporal frequency occurrence and magnitude of surface runoff events, in this way contributing to steeper flood frequency curves, and an additional break in the slope of the flood frequency curve. The results of this study highlight the importance of thresholds on flood frequency, and provide insights into the complex interactions between rainfall variability and threshold nonlinearities in the rainfall-runoff process, which are shown to have a significant impact on the resulting flood frequency curves.

Description: The episodic nature of hydrological flows such as surface runoff and preferential flow is a result of the nonlinearity of their triggering and the intermittency of rainfall. In this paper we examine the temporal dynamics of threshold processes that are triggered by either an infiltration excess (IE) mechanism when rainfall intensity exceeds a specified threshold value, or a saturation excess (SE) mechanism governed by a storage threshold. We use existing and newly derived analytical results to describe probabilistic measures of the time between successive events in each case, and in the case of the SE triggering, we relate the statistics of the time between events (the inter-event time, denoted IET) to the statistics of storage and the underlying water balance. In the case of the IE mechanism, the temporal dynamics of flow events is found to be simply scaled statistics of rainfall timing. In the case of the SE mechanism the time between events becomes structured. With increasing climate aridity the mean and the variance of the time between SE events increases but temporal clustering, as measured by the coefficient of variation (CV) of the IET, reaches a maximum in deep stores when the climatic aridity index equals 1. In very humid and also very arid climates, the temporal clustering disappears, and the pattern of triggering is similar to that seen for the IE mechanism. In addition we show that the mean and variance of the magnitude of SE events decreases but the CV increases with increasing aridity. The CV of IETs is found to be approximately equal to the CV of the magnitude of SE events per storm only in very humid climates with the CV of event magnitude tending to be much larger than the CV of IETs in arid climates. In comparison to storage the maximum temporal clustering was found to be associated with a maximum in the variance of soil moisture. The CV of the time till the first saturation excess event was found to be greatest when the initial storage was at the threshold.

Description: Budyko (1974) postulated that long-term catchment water balance is controlled to first order by the available water and energy. This leads to the interesting question of how do landscape characteristics (soils, geology, vegetation) and climate properties (precipitation, potential evaporation, number of wet and dry days) interact at the catchment scale to produce such a simple and predictable outcome of hydrological partitioning? Here we use a physically-based hydrologic model separately parameterized in 12 US catchments across a climate gradient to decouple the impact of climate and landscape properties to gain insight into the role of climate-vegetation-soil interactions in long-term hydrologic partitioning. The 12 catchment models (with different paramterizations) are subjected to the 12 different climate forcings, resulting in 144 10 yr model simulations. The results are analyzed per catchment (one catchment model subjected to 12 climates) and per climate (one climate filtered by 12 different model parameterization), and compared to water balance predictions based on Budyko's hypothesis (E/P = ϕ (Ep/P); E: evaporation, P: precipitation, Ep: potential evaporation). We find significant anti-correlation between average deviations of the evaporation index (E/P) computed per catchment vs. per climate, compared to that predicted by Budyko. Catchments that on average produce more E/P have developed in climates that on average produce less E/P, when compared to Budyko's prediction. Water and energy seasonality could not explain these observations, confirming previous results reported by Potter et al. (2005). Next, we analyze which model (i.e., landscape filter) characteristics explain the catchment's tendency to produce more or less E/P. We find that the time scale that controls subsurface storage release explains the observed trend. This time scale combines several geomorphologic and hydraulic soil properties. Catchments with relatively longer subsurface storage release time scales produce significantly more E/P. Vegetation in these catchments have longer access to this additional groundwater source and thus are less prone to water stress. Further analysis reveals that climates that give rise to more (less) E/P are associated with catchments that have vegetation with less (more) efficient water use parameters. In particular, the climates with tendency to produce more E/P have catchments that have lower % root fraction and less light use efficiency. Our results suggest that their exists strong interactions between climate, vegetation and soil properties that lead to specific hydrologic partitioning at the catchment scale. This co-evolution of catchment vegetation and soils with climate needs to be further explored to improve our capabilities to predict hydrologic partitioning in ungauged basins.

Description: This paper presents a historical socio-hydrological analysis of the Tarim River basin (TRB), Xinjiang Uyghur Autonomous Region, in Western China, from the time of the opening of the Silk Road to the present. The analysis is aimed at exploring the historical co-evolution of coupled human–water systems and at identifying common patterns or organizing principles underpinning socio-hydrological systems (SHS). As a self-organized entity, the evolution of the human–water system in the Tarim Basin reached stable states for long periods of time, but then was punctuated by sudden shifts due to internal or external disturbances. In this study, we discuss three stable periods (i.e., natural, human exploitation, and degradation and recovery) and the transitions in between during the past 2000 years. During the "natural" stage that existed pre-18th century, with small-scale human society and sound environment, evolution of the SHS was mainly driven by natural environmental changes such as river channel migration and climate change. During the human exploitation stage, especially in the 19th and 20th centuries, it experienced rapid population growth, massive land reclamation and fast socio-economic development, and humans became the principal players of system evolution. By the 1970s, the Tarim Basin had evolved into a new regime with a vulnerable eco-hydrological system seemingly populated beyond its carrying capacity, and a human society that began to suffer from serious water shortages, land salinization and desertification. With intensified deterioration of river health and increased recognition of unsustainability of traditional development patterns, human intervention and recovery measures have since been adopted. As a result, the basin has shown a reverse regime shift towards some healing of the environmental damage. Based on our analysis within TRB and a common theory of social development, four general types of SHSs are defined according to their characteristic spatio-temporal variations of historical co-evolution, including primitive agricultural, traditional agricultural, industrial agricultural, and urban SHSs. These co-evolutionary changes have been explained in the paper in terms of the Taiji–Tire model, a refinement of a special concept in Chinese philosophy, relating to the co-evolution of a system because of interactions among its components.

Description: The goal of this paper is to explore the process controls underpinning regional patterns of variations of streamflow regime behavior, i.e., the mean seasonal variation of streamflow within the year, across the continental United States. The ultimate motivation is to use the resulting process understanding to generate insights into the physical controls of another signature of streamflow variability, namely the flow duration curve (FDC). The construction of the FDC removes the time dependence of flows. Thus in order to better understand the physical controls in regions that exhibit strong seasonal dependence, the regime curve (RC), which is closely connected to the FDC, is studied in this paper and later linked back to the FDC. To achieve these aims a top-down modeling approach is adopted; we start with a simple two-stage bucket model, which is systematically enhanced through addition of new processes on the basis of model performance assessment in relation to observations, using rainfall-runoff data from 197 United States catchments belonging to the MOPEX dataset. Exploration of dominant processes and the determination of required model complexity are carried out through model-based sensitivity analyses, guided by a performance metric. Results indicated systematic regional trends in dominant processes: snowmelt was a key process control in cold mountainous catchments in the north and north-west, whereas snowmelt and vegetation cover dynamics were key controls in the north-east; seasonal vegetation cover dynamics (phenology and interception) were important along the Appalachian mountain range in the east. A simple two-bucket model (with no other additions) was found to be adequate in warm humid catchments along the west coast and in the south-east, with both regions exhibiting strong seasonality, whereas much more complex models are needed in the dry south and south-west. Agricultural catchments in the mid-west were found to be difficult to predict with the use of simple lumped models, due to the strong influence of human activities. Overall, these process controls arose from general east-west (seasonality) and north-south (aridity, temperature) trends in climate (with some exceptions), compounded by complex dynamics of vegetation cover and to a less extent by landscape factors (soils, geology and topography).

Description: The paper reports on a four-pronged study of the physical controls on regional patterns of the flow duration curve (FDC). This involved a comparative analysis of long-term continuous data from nearly 200 catchments around the US, encompassing a wide range of climates, geology, and ecology. The analysis was done from three different perspectives – statistical analysis, process-based modeling, and data-based classification – followed by a synthesis, which is the focus of this paper. Streamflow data were separated into fast and slow flow responses, and associated signatures, and both total flow and its components were analyzed to generate patterns. Regional patterns emerged in all aspects of the study. The mixed gamma distribution described well the shape of the FDC; regression analysis indicated that certain climate and catchment properties were first-order controls on the shape of the FDC. In order to understand the spatial patterns revealed by the statistical study, and guided by the hypothesis that the middle portion of the FDC is a function of the regime curve (RC, mean within-year variation of flow), we set out to classify these catchments, both empirically and through process-based modeling, in terms of their regime behavior. The classification analysis showed that climate seasonality and aridity, either directly (empirical classes) or through phenology (vegetation processes), were the dominant controls on the RC. Quantitative synthesis of these results determined that these classes were indeed related to the FDC through its slope and related statistical parameters. Qualitative synthesis revealed much diversity in the shapes of the FDCs even within each climate-based homogeneous class, especially in the low-flow tails, suggesting that catchment properties may have become the dominant controls. Thus, while the middle portion of the FDC contains the average response of the catchment, and is mainly controlled by climate, the tails of the FDC, notably the low-flow tails, are mainly controlled by catchment properties such as geology and soils. The regime behavior explains only part of the FDC; to gain a deeper understanding of the physical controls on the FDC, these extremes must be analyzed as well. Thus, to completely separate the climate controls from the catchment controls, the roles of catchment properties such as soils, geology, topography etc. must be explored in detail.

Description: The flow duration curve (FDC) is a classical method used to graphically represent the relationship between the frequency and magnitude of streamflow. In this sense it represents a compact signature of temporal runoff variability that can also be used to diagnose catchment rainfall-runoff responses, including similarity and differences between catchments. This paper is aimed at extracting regional patterns of the FDCs from observed daily flow data and elucidating the physical controls underlying these patterns, as a way to aid towards their regionalization and predictions in ungauged basins. The FDCs of total runoff (TFDC) using multi-decadal streamflow records for 197 catchments across the continental United States are separated into the FDCs of two runoff components, i.e., fast flow (FFDC) and slow flow (SFDC). In order to compactly display these regional patterns, the 3-parameter mixed gamma distribution is employed to characterize the shapes of the normalized FDCs (i.e., TFDC, FFDC and SFDC) over the entire data record. This is repeated to also characterize the between-year variability of "annual" FDCs for 8 representative catchments chosen across a climate gradient. Results show that the mixed gamma distribution can adequately capture the shapes of the FDCs and their variation between catchments and also between years. Comparison between the between-catchment and between-year variability of the FDCs revealed significant space-time symmetry. Possible relationships between the parameters of the fitted mixed gamma distribution and catchment climatic and physiographic characteristics are explored in order to decipher and point to the underlying physical controls. The baseflow index (a surrogate for the collective impact of geology, soils, topography and vegetation, as well as climate) is found to be the dominant control on the shapes of the normalized TFDC and SFDC, whereas the product of maximum daily precipitation and the fraction of non-rainy days was found to control the shape of the FFDC. These relationships, arising from the separation of total runoff into its two components, provide a potential physical basis for regionalization of FDCs, as well as providing a conceptual framework for developing deeper process-based understanding of the FDCs.

Description: Predictions of hydrological responses in ungauged catchments can benefit from a classification scheme that can organize and pool together catchments that exhibit a level of hydrologic similarity, especially similarity in some key variable or signature of interest. Since catchments are complex systems with a level of self-organization arising from co-evolution of climate and landscape properties, including vegetation, there is much to be gained from developing a classification system based on a comparative study of a population of catchments across climatic and landscape gradients. The focus of this paper is on climate seasonality and seasonal runoff regime, as characterized by the ensemble mean of within-year variation of climate and runoff. The work on regime behavior is part of an overall study of the physical controls on regional patterns of flow duration curves (FDCs), motivated by the fact that regime behavior leaves a major imprint upon the shape of FDCs, especially the slope of the FDCs. As an exercise in comparative hydrology, the paper seeks to assess the regime behavior of 428 catchments from the MOPEX database simultaneously, classifying and regionalizing them into homogeneous or hydrologically similar groups. A decision tree is developed on the basis of a metric chosen to characterize similarity of regime behavior, using a variant of the Iterative Dichotomiser 3 (ID3) algorithm to form a classification tree and associated catchment classes. In this way, several classes of catchments are distinguished, in which the connection between the five catchments' regime behavior and climate and catchment properties becomes clearer. Only four similarity indices are entered into the algorithm, all of which are obtained from smoothed daily regime curves of climatic variables and runoff. Results demonstrate that climate seasonality plays the most significant role in the classification of US catchments, with rainfall timing and climatic aridity index playing somewhat secondary roles in the organization of the catchments. In spite of the tremendous heterogeneity of climate, topography, and runoff behavior across the continental United States, 331 of the 428 catchments studied are seen to fall into only six dominant classes.