Dry Catchments Research Articles

Precipitation, soil moisture and runoff variability in a small river catchment (Ardèche, France) during HyMeX Special Observation Period 1

Flash flooding is a potentially destructive natural hazard known to occur in the Cevennes-Vivarais region in southern France. HyMeX (Hydrological Cycle in the Mediterranean Experiment) is an international program focused on understanding the hydrological cycle in the Mediterranean basin. Soil moisture is known to be a useful indicator of catchment response, however, establishing a meaningful estimation of soil moisture at the catchment level can be difficult due to its high variability in space and time. In a small gauged catchment in the Cevennes-Vivarais region in southern France, a series of manual soil moisture measurements was taken from September to December 2012 at both the field and catchment scale during the Special Observation Period 1 (SOP1) as part of the HyMeX program. Six plots were selected along a trajectory of a microwave link installed in the catchment and were chosen to represent different elevations in the catchment. Within each field plot, surface soil moisture was measured along a 50 m transect at 2 m intervals. This allowed the study of changes in within-field variability as well as between-field variability in response to precipitation events and during the drying out phase. Several precipitation events occurred over this autumn 2012 period which caused a significant wetting-up of the catchment, allowing the study of soil moisture processes over a wide range of wetness conditions. The influence of antecedent catchment conditions (soil moisture) on rainfall–runoff dynamics is demonstrated through the comparison of storm hydrographs for the various events. Dry catchment conditions result in minimal response in event flow, whereas large precipitation events occurring during wetter conditions produce much stronger responses in event flow. This further confirms the importance of quantifying catchment initial conditions to enhance the prediction of flash flood occurrences.

The influence of conceptual model structure on model performance: a comparative study for 237 French catchments

Abstract. Models with a fixed structure are widely used in hydrological studies and operational applications. For various reasons, these models do not always perform well. As an alternative, flexible modelling approaches allow the identification and refinement of the model structure as part of the modelling process. In this study, twelve different conceptual model structures from the SUPERFLEX framework are compared with the fixed model structure GR4H, using a large set of 237 French catchments and discharge-based performance metrics. The results show that, in general, the flexible approach performs better than the fixed approach. However, the flexible approach has a higher chance of inconsistent results when calibrated on two different periods. When analysing the subset of 116 catchments where the two approaches produce consistent performance over multiple time periods, their average performance relative to each other is almost equivalent. From the point of view of developing a well-performing fixed model structure, the findings favour models with parallel reservoirs and a power function to describe the reservoir outflow. In general, conceptual hydrological models perform better on larger and/or wetter catchments than on smaller and/or drier catchments. The model structures performed poorly when there were large climatic differences between the calibration and validation periods, in catchments with flashy flows, and in catchments with unexplained variations in low flow measurements.

Comparative analysis of the response of various land covers to an exceptional rainfall event in the central Spanish Pyrenees, October 2012

ABSTRACTThe hydrological and geomorphological effects of an exceptional rainstorm event that occurred in the central Spanish Pyrenees during 19–21 October 2012 were studied in five experimental catchments under various land covers: (i) subhumid badlands; (ii) dense forest; (iii) an abandoned farmland area recolonized by shrubs and forest patches; and (iv) subalpine grasslands. Hydrographs and sedigraphs demonstrated that vegetation cover is a major factor affecting the control of floods even during exceptional rainstorms, at least at the spatial scale at which the phenomenon was studied (catchment sizes: 0.3–2.8 km2) and under dry catchment conditions. The combined precipitation over the two days (c. 250 mm) was the greatest for any two‐day event recorded since 1950 in the central‐western Pyrenees for all but one of the stations in the study. Five pulses of most intense rainfall were recorded. The forested catchment did not react to the two most intense rainfall pulses, because of the very low antecedent level of the water table. The main peak flow occurred only when at least a part of the catchment was saturated. The abandoned farmland catchment had two small peak discharges at the beginning of the event, which were produced by infiltration excess overland flow from eroded areas close to the main stream. During the third most intense rainfall period a large part of this catchment contributed to runoff and a relatively high peak discharge was produced. The badland catchment reacted immediately from the beginning of the rainstorm, yielding very high discharges accompanied by high suspended sediment concentrations. The subalpine catchment showed a hydrograph mirroring the hyetograph, with brief but intense hydrological responses to increased precipitation, because of the marked gradients and the presence of bare rock in the headwaters. A high volume of bedload was carried during the peak discharge. Copyright © 2013 John Wiley & Sons, Ltd.

Future variability of droughts in three Mediterranean catchments

In the present study, we analyze the magnitude and frequency of long-term droughts throughout the present century in Catalonia in the north-eastern Iberian Peninsula (Spain). In fact, this western Mediterranean region has recently suffered one of the most extreme dry episodes (2006–2008) in the last decades. This calls for further study of future perspectives of drought variability at the local scale. We selected three medium-sized catchments on the Catalan littoral: Fluvia, Tordera and Siurana. We employed both instrumental and simulated temperature and rainfall data to calculate two multi-scalar drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Instrumental data consisted of several weather stations for a recent period: 1984–2008. Future projections covering the 2001–2100 period were extracted from a dynamical downscaling procedure at a 15-km horizontal grid resolution, nesting the mesoscale model MM5 into the atmosphere–ocean coupled model ECHAM5/MPI-OM, performed by the Meteorological Service of Catalonia. We calculated 24-month SPI and SPEI values for the instrumental and simulated periods, and no changes were found in drought variability for the early twenty-first century. For the mid-century, high climatic variability was detected, as extremely dry and wet periods might alternate according to the SPI values. At the end of the present century, we generally detected, particularly in the dry catchment of southern Catalonia, Siurana, more severe and longer droughts than the last extreme drought (2006–2008). There is a need to implement appropriate and specific adaptation strategies for water management of each catchment over the next decades to reduce the risk of the forecasted drought conditions.

Improving runoff estimates using remote sensing vegetation data for bushfire impacted catchments

Rainfall-runoff modelling is widely used for runoff estimation at the catchment scale. However, its simulation capability is sometimes influenced because of rapid land cover changes occurring in catchments. This paper investigates whether modification of a rainfall-runoff model, Xinanjiang, by the incorporation of dynamic remote sensing data (MODIS leaf area index (LAI) and albedo) can improve runoff estimates for four south-east Australian catchments which experienced severe bushfire impacts. The results show that incorporation of remote sensing LAI and albedo data into the modified Xinanjiang model can improve model performance in three wetter bushfire impacted catchments, compared to the modified model using mean annual vegetation data as model inputs. The improvement is indicated by a slight increase (0.01–0.07) in the Nash–Sutcliffe efficiency of daily runoff and noticeable decrease (3–11%) in volumetric errors. However, use of vegetation dynamics does not improve runoff time series simulation in a dry catchment for which mean annual runoff is only 38mm/yr. It indicates that incorporation of vegetation dynamic data into Xinanjiang model may show more benefits for catchments located in the wet regions

Climate change and river flooding: Part 2 sensitivity characterisation for british catchments and example vulnerability assessments

This paper is the second of a series describing a scenario-neutral methodology to assess the sensitivity and vulnerability of British catchments to changes in flooding due to climate change. In paper one, nine flood sensitivity types were identified from response surfaces generated for 154 catchments. The response surfaces describe changes in 20-year return period flood peaks (RP20) in response to a large set of changes in precipitation, temperature and potential evapotranspiration. In this paper, a recursive partitioning algorithm is used to link families of sensitivity types to catchment properties, via a decision tree. The tree shows 85 % success characterising the four sensitivity families, using five properties and nine paths. Catchment annual average rainfall is the primary partitioning factor, with drier catchments having a more variable response to climate (precipitation) change than wetter catchments and higher catchment losses and permeability being aggravating factors. The full sensitivity-exposure-vulnerability methodology is illustrated for two catchments: sensitivity is estimated by using the decision tree to identify the sensitivity family (and its associated average response surface); exposure is defined from a set of climate model projections and combined with the response surface to estimate the resulting impacts (changes in RP20); vulnerability under a range of adaptive capacity thresholds is estimated from the set of impacts. Even though they are geographically close, the two catchments show differing vulnerability to climate change, due to their differing properties. This demonstrates that generalised response surfaces characterised by catchment properties are useful screening tools to quantify the vulnerability of catchments to climate change without the need to undertake a full climate change impact study.

Inferring catchment precipitation by doing hydrology backward: A test in 24 small and mesoscale catchments in Luxembourg

The complexity of hydrological systems and the necessary simplification of models describing these systems remain major challenges in hydrological modeling. Kirchner's (2009) approach of inferring rainfall and evaporation from discharge fluctuations by “doing hydrology backward” is based on the assumption that catchment behavior can be conceptualized with a single storage‐discharge relationship. Here we test Kirchner's approach using a densely instrumented hydrologic measurement network spanning 24 geologically diverse subbasins of the Alzette catchment in Luxembourg. We show that effective rainfall rates inferred from discharge fluctuations generally correlate well with catchment‐averaged precipitation radar estimates in catchments ranging from less than 10 to more than 1000 km2in size. The correlation between predicted and observed effective precipitation was 0.8 or better in 23 of our 24 catchments, and prediction skill did not vary systematically with catchment size or with the complexity of the underlying geology. Model performance improves systematically at higher soil moisture levels, indicating that our study catchments behave more like simple dynamical systems with unambiguous storage‐discharge relationships during wet conditions. The overall mean correlation coefficient for all subbasins for the entire data set increases from 0.80 to 0.95, and the mean bias for all basins decreases from –0.61 to –0.35 mm d−1. We propose an extension of Kirchner's approach that uses in situ soil moisture measurements to distinguish wet and dry catchment conditions.

Less bluster ahead? Ecohydrological implications of global trends of terrestrial near‐surface wind speeds

ABSTRACTWhy, in a globally warming climate, have observed rates of atmospheric evaporative demand (AED) declined at many sites over recent decades? The answer is that the evaporative process is primarily driven by radiative and aerodynamic components (the latter mainly influenced by wind speed and atmospheric humidity). So, although increases in air temperatures in isolation would result in increases of both pan evaporation (Epan) observations, and fully physically based model estimates of potential evapotranspiration (ETp), results show that changes in the other meteorological variables governing AED are currently exerting a greater opposing influence. Widespread declines in wind speed (denoted ‘stilling’) of ~−0.014 m s−1 a−1 have recently been reported. In studies assessing the relative contribution of the four primary meteorological variables on AED dynamics, wind speed trends are often indentified as being important. Stilling reduces AED, but its impact on actual evapotranspiration and streamflow is situation dependant. For wet catchments under steady state conditions, stilling‐induced declines in actual evapotranspiration will result in an approximate complementary increase in streamflow. In contrast, for dry catchments, actual evapotranspiration dynamics more closely follow precipitation dynamics so stilling has negligible impact on streamflow. In ‘equitant’ catchments (i.e. those that straddle the energy–water limitation divide), the likely impact of stilling on the catchment water balance depends on sub‐annual processes and requires that new approaches (either top–down or bottom–up) be developed to allow better predictions to be made. Copyright © 2012 Commonwealth of Australia

Synthetic monthly flow duration curves for the Cape Floristic Region, South Africa

A flow duration curve (FDC) provides a valuable planning and management tool since it describes the entire flow regime of a river. Water resource planning in South Africa is often based on monthly river flow data and synthetic FDCs are required for applications in ungauged catchments. The objective of this study was to derive 11 monthly FDC percentile flows and the mean annual flow (MAQ) for catchments in the Cape Floristic Region of South Africa using regression equations with readily measureable catchment variables, including vegetation indices from Moderate Resolution Imaging Spectrometer (MODIS) satellite imagery. An ‘all-models’ approach with 10-fold validation was adopted to identify the ‘best’ regression models. Predictions of percentile flows above the median flow and MAQ were generally good but poor for low flows. Overall predictive uncertainty had a tendency to be larger in drier catchments. The most important predictive variables were catchment mean annual precipitation, physiography and soils. MODIS vegetation indices were significant predictors in equations for 6 percentile flows and MAQ, and predictive uncertainty increased if the MODIS indices were excluded from model development. The regression approach implemented in this study may be appropriate for other regionalisation studies that are based on a small sample of gauged catchments.

Regionalising a meso-catchment scale conceptual model for river basin management in the semi-arid environment

Meso-scale catchments are often of great interest for water resources development and for development interventions aimed at uplifting rural livelihoods. However, in Sub-Saharan Africa IWRM planning in such catchments, and the basins they form part of, are often ungauged or constrained by poor data availability. Regionalisation of a hydrological model presents opportunities for prediction in ungauged basins and catchments. This study regionalises HBVx, derived from the conceptual hydrological model HBV, in the semi-arid Mzingwane Catchment, Limpopo Basin, Zimbabwe. Fifteen meso-catchments were studied, including three that were instrumented during the study. Discriminant analysis showed that the characteristics of catchments in the arid agro-ecological Region V were significantly different from those in semi-arid Region IV. Analysis of flow duration curves statistically separated sub-perennial catchments from (sub-)ephemeral catchments. Regionalised parameter sets for HBVx were derived from means of parameters from the sub-perennial catchments, the (sub-)ephemeral catchments and all catchments. The parameter sets that performed best in the regionalisation are characterised by slow infiltration with moderate/fast “overland flow”. These processes appear more extreme in more degraded catchments. This is points to benefits to be derived from conservation techniques that increase infiltration rate and from runoff farming. Faster, and possibly greater, sub-surface contribution to streamflow is expected from catchments underlain by granitic rocks. Calibration and regionalisation were more successful at the dekad (10days) time step than when using daily or monthly data, and for the sub-perennial catchments than the (sub-)ephemeral catchments. However, none of the regionalised parameter sets yielded CNS⩾0.3 for half of the catchments. The HBVx model thus does offer some assistance to river basin planning in semi-arid basins, particularly for predicting flows in ungauged catchments at longer time steps, such as for water allocation purposes. However, the model is unreliable for more ephemeral and drier catchments. Without more reliable and longer rainfall and runoff data, regionalisation in semi-arid ephemeral catchments will remain highly challenging.

Development of a formal likelihood function for improved Bayesian inference of ephemeral catchments

The application of formal Bayesian inferential approaches in hydrologic modeling is often criticized for requiring explicit assumptions to be made about the distribution of the errors via the likelihood function. These assumptions can be adequate in some situations, but often little attention is paid to the selection of an appropriate likelihood function. This paper investigates the application of Bayesian methods in modeling ephemeral catchments. We consider two modeling case studies, including a synthetically generated data set and a real data set of an arid Australian catchment. The case studies investigate some typical forms of the likelihood function which have been applied widely by previous researchers, as well as introducing new implementations aimed at better addressing likelihood function assumptions in dry catchments. The results of the case studies indicate the importance of explicitly accounting for model residuals that are highly positively skewed due to the presence of many zeros (zero inflation) arising from the dry spells experienced by the catchment. Specifically, the form of the likelihood function was found to significantly impact the calibrated parameter posterior distributions, which in turn have the potential to greatly affect the uncertainty estimates. In each application, the likelihood function that explicitly accounted for the nonconstant variance of the errors and the zero inflation of the errors resulted in (1) equivalent or better fits to the observed discharge in both timing and volume, (2) superior estimation of the uncertainty as measured by the reliability and sharpness metrics, and (3) more linear quantile‐quantile plots indicating the errors were more closely matched to the assumptions of this form of the likelihood function.

Improving Curve Number Based Storm Runoff Estimates Using Soil Moisture Proxies

Advances in data dissemination and the availability of new remote sensing datasets present both opportunities and challenges for hydrologists in improving flood forecasting systems. The current study investigates the improvement in SCS curve number (CN)-based storm runoff estimates obtained after inclusion of various soil moisture proxies based on additional data on precipitation, baseflow, and soil moisture. A dataset (1980-2007) comprising 186 Australian catchments (ranging from 51 to 1979 km 2 in size) was used. In order to investigate the value of a particular proxy, the observed S (potential maximum retention) was compared to values obtained with different soil moisture proxies using linear regression. An antecedent precipitation index (API) based on gauged precipitation using a decay parameter proved most valuable in improving storm runoff estimates, stressing the importance of high quality precipitation data. An antecedent baseflow index (ABFI) also performed well. Proxies based on remote sensing (TRMM and AMSR-E) gave promising results, particularly when considering the expected arrival of higher accuracy data from upcoming satellites. The five-day API performed poorly. The inclusion of soil moisture proxies resulted in mean modeled versus observed correlation coefficients around 0.75 for almost all proxies. The greatest improvement in runoff estimates was observed in drier catchments with low Enhanced Vegetation Index (EVI) and topographical slope (all intercorrelated parameters). The present results suggest the usefulness of incorporating remotely sensed proxies for soil moisture and catchment wetness in flood forecasting systems.

The influence of preferential flow on hillslope hydrology in a semi‐arid watershed (in the Spanish Dehesas)

AbstractPreferential flow is known to influence hillslope hydrology in many areas around the world. Most research on preferential flow has been performed in temperate regions. Preferential infiltration has also been found in semi‐arid regions, but its impact on the hydrology of these regions is poorly known. The aim of this study is to describe and quantify the influence of preferential flow on the hillslope hydrology from small scale (infiltration) to large scale (subsurface stormflow) in a semi‐arid Dehesa landscape. Precipitation, soil moisture content, piezometric water level and discharge data were used to analyse the hydrological functioning of a catchment in Spain. Variability of soil moisture content during the transition from dry to wet season (September to November) within horizontal soil layers leads to the conclusion that there is preferential infiltration into the soils. When the rainfall intensity is high, a water level rapidly builds up in the piezometer pipes in the area, sometimes even reaching soil surface. This water level also drops back to bedrock within a few hours (under dry catchment conditions) to days (under wet catchment conditions). As the soil matrix is not necessarily wet while this water layer is built up, it is thought to be a transient water table in large connected pores which drain partly to the matrix, partly fill up bedrock irregularities and partly drain through subsurface flow to the channels. When the soil matrix becomes wetter the loss of water from macropores to the matrix and bedrock decreases and subsurface stormflow increases. It may be concluded that the hillslope hydrological system consists of a fine matrix domain and a macropore domain, which have their own flow characteristics but which also interact, depending on the soil matrix and macropore moisture contents. The macropore flow can result in subsurface flow, ranging from 13% contribution to total discharge for a large event of high intensity rainfall or high discharge to 80% of total discharge for a small event with low intensity rainfall or low discharge. During large events the fraction of subsurface stormflow in the discharge is suppressed by the large amount of surface runoff. Copyright © 2008 John Wiley & Sons, Ltd.

Estimation of rainfall elasticity of streamflow in Australia

Estimates of rainfall elasticity of streamflow in 219 catchments across Australia are presented. The rainfall elasticity of streamflow is defined here as the proportional change in mean annual streamflow divided by the proportional change in mean annual rainfall. The elasticity is therefore a simple estimate of the sensitivity of long-term streamflow to changes in long-term rainfall, and is particularly useful as an initial estimate of climate change impact in land and water resources projects. The rainfall elasticity of streamflow is estimated here using a hydrological modelling approach and a nonparametric estimator. The results indicate that the rainfall elasticity of streamflow (ϵ P ) in Australia is about 2.0–3.5 (observed in about 70% of the catchments), that is, a 1% change in mean annual rainfall results in a 2.0–3.5% change in mean annual streamflow. The rainfall elasticity of streamflow is strongly correlated to runoff coefficient and mean annual rainfall and streamflow, where streamflow is more sensitive to rainfall in drier catchments, and those with low runoff coefficients. There is a clear relation-ship between the ϵ P values estimated using the hydrological modelling approach and those estimated using the nonparametric estimator for the 219 catchments, although the values estimated by the hydrological modelling approach are, on average, slightly higher. The modelling approach is useful where a detailed study is required and where there are sufficient data to reliably develop and calibrate a hydrological model. The nonparametric estimator is useful where consistent estimates of the sensitivity of long-term streamflow to climate are required, because it is simple to use and estimates the elasticity directly from the historical data. The nonparametric method, being model independent, can also be easily applied in comparative studies to data sets from many catchments across large regions.

Uncertainty of simulated catchment runoff response in the presence of threshold processes: Role of initial soil moisture and precipitation

This paper examines the effect of spatially variable initial soil moisture and spatially variable precipitation on predictive uncertainty of simulated catchment scale runoff response in the presence of threshold processes. The underlying philosophy is to use a physically based hydrological model named CATFLOW as a virtual landscape, assuming perfect knowledge of the processes. The model, which in particular conceptualizes preferential flow as threshold process, was developed based on intensive process and parameter studies and has already been successfully applied to simulate flow and transport at different scales and catchments. Study area is the intensively investigated Weiherbach catchment. Numerous replicas of spatially variable initial soil moisture or spatially variable precipitation with the same geostatistical properties are conditioned to observed soil moisture and precipitation data and serve as initial and boundary conditions for the model during repeated simulations. The effect of spatially soil moisture on modeling catchment runoff response was found to depend strongly on average saturation of the catchment. Different realizations of initial soil moisture yielded strongly different hydrographs for intermediate initial soil moisture as well as in dry catchment conditions; in other states the effect was found to be much lower. This is clearly because of the threshold nature of preferential flow as well as the threshold nature of Hortonian production of overland flow. It was shown furthermore that the spatial pattern of a key parameter (macroporosity) that determined threshold behavior is of vast importance for the model response. The estimation of these patterns, which is mostly done based on sparse observations and expert knowledge, is a major source for predictive model uncertainty. Finally, it was shown that the usage of biased, i.e. spatially homogenized precipitation, input during parameter estimation yields a biased model structure, which gives poor results when used with highly distributed input. If spatially highly resolved precipitation was used during model parameter estimation, the predictive uncertainty of the model was clearly reduced.

Linking fish assemblages and attributes of mangrove estuaries in tropical Australia: criteria for regional marine reserves

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 305:41-57 (2005) - doi:10.3354/meps305041 Linking fish assemblages and attributes of mangrove estuaries in tropical Australia: criteria for regional marine reserves J. A. Ley Department of Fisheries and Marine Environment, Australian Maritime College, PO Box 21, Beauty Point, Tasmania 7270, Australia *Email: j.ley@amc.edu.au ABSTRACT: Quantifying natural features important in structuring fish assemblages is an essential pre-requisite to implementation of measures to conserve regionally representative whole ecosystems. Tropical estuaries are high in priority for protection, but fish-ecosystem relationships have rarely been analysed at multiple scales. Fishery-independent surveys (gill nets 19 to 152 mm mesh) were replicated seasonally (wet, dry) in 11 large estuaries along 1400 km of coast adjacent to the Great Barrier Reef. Fundamental differences in physical forces (river, wave, tidal) apparently generated variation in abiotic attributes, which distinguished Tide- from Wave-dominated systems. These trends correlated with patterns observed among estuarine fish assemblages, mediated by ecological and biological processes. Tide-dominated systems (n = 7), located in drier catchments, had greater mangrove area, wide deltaic mouths, and muddy substrate; in these systems, diversity was high with Ariidae, Belonidae and Haemulidae characterising the fish assemblages. Wave-dominated systems (n = 4), located in higher rainfall catchments, had constricted mouths, less mangrove area, and sandy substrate. For Wave-dominated systems, deltas (n = 2), had high diversity with Megalopidae characterising the fish assemblages, while true estuaries (n = 2) were relatively depauperate. Notably, none of the estuarine attributes explained the greater catch rates of Carangidae and Carcharhinidae observed in east Cape York. This trend may be attributed to negligible fishing pressure in the remote Cape York region. Overall, a substantial amount of the variation in fish assemblages (42.9%) was related to catchment hydrology, configuration of the estuary mouth, substrate and mangrove area. The results here support management programs incorporating a surrogate approach aimed at conserving the biodiversity of estuarine fish assemblages by combining regional and estuary scales in defining networks of reserve systems. KEY WORDS: Marine reserves · Mangroves · Fish assemblages · Multivariate analysis · Estuaries · Habitat · Great Barrier Reef · Ecosystems Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 305. Online publication date: December 23, 2005 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2005 Inter-Research.

Flood frequency regionalisation—spatial proximity vs. catchment attributes

We examine the predictive performance of various flood regionalisation methods for the ungauged catchment case, based on a jack-knifing comparison of locally estimated and regionalised flood quantiles for 575 Austrian catchments, 122 of which have a record length of 40 years or more. The main result is that spatial proximity is a significantly better predictor of regional flood frequencies than are catchment attributes. A method that combines spatial proximity and catchment attributes yields the best predictive performance. This is a novel method proposed in this paper which is based on kriging and takes differences in the length of the flood records into account. It is shown that short flood records contain valuable information which can be exploited by the proposed method. A method that uses only spatial proximity performs second best. The methods that only use catchment attributes perform significantly poorer than those based on spatial proximity. These are a variant of the Region Of Influence (ROI) approach, applied in an automatic mode, and multiple regressions. It is suggested that better predictive variables and similarity measures need to be found to make these methods more useful. A stratified analysis suggests that in wet catchments all regionalisation methods perform better than they do in dry catchments.

Climate, soil, and vegetation controls upon the variability of water balance in temperate and semiarid landscapes: Downward approach to water balance analysis

Observed differences between water balance for temperate and semiarid catchments can be attributed to variability in the primary controls of the soil profile (soil water storage capacity and permeability), vegetation (surface coverage and water use efficiency), and climate (rainfall and potential evaporation). Motivated by the downward development methodology mooted by Klemes [1983], this paper explores the underlying climate and landscape interactions that cause differences in water balance between a number of temperate and semiarid benchmark catchments around Australia. A systematic parsimonious analysis based around a simple water balance model whose parameters are estimated from available data is used to observe and interpret signatures of annual, intra‐annual, and daily water balance behavior and variability. The essence of the downward analysis is that model complexity evolves from the simplest form to its final quasi‐distributed framework with multiple storages and process interactions in response to inadequacies in signature prediction. Consequently, each step in the process develops insight into local climate and landscape influences and sensitivity to their temporal and spatial variabilities. The results affirm that the relative influence of climate and landscape properties upon catchment response is manifested in a systematic transformation of process sensitivity with increasing timescales (annual, monthly, daily, and hourly). Significantly, drier catchments are shown to be more sensitive to small‐scale perturbation than humid catchments. We conclude that the downward analysis approach is a means to better understand the significance of landscape variability upon catchment response. Consequential knowledge can begin to explain data requirements and requisite model complexity and to provide insight into the ability to reliably predict water balance behavior. These are important first steps toward the longer‐term objective of reliably predicting water balance variability across ungauged basins.

Climate and landscape controls on water balance model complexity over changing timescales

A systematic approach is described for determining the minimum level of model complexity required to predict runoff in New Zealand catchments, with minimal calibration, at decreasing timescales. Starting with a lumped conceptual model representing the most basic hydrological processes needed to capture water balance, model complexity is systematically increased in response to demonstrated deficiencies in model predictions until acceptable accuracy is achieved. Sensitivity and error analyses are performed to determine the dominant physical controls on streamflow variability. It is found that dry catchments are sensitive to a threshold storage parameter, producing inaccurate results with little confidence, while wet catchments are relatively insensitive, producing more accurate results with more confidence. Sensitivity to the threshold parameter is well correlated with climate and timescale, and in combination with the results of two previous studies, this allowed the postulation of a qualitative relationship between model complexity, timescale, and the climatic dryness index (DI). This relationship can provide an a priori understanding of the model complexity required to accurately predict streamflow with confidence in small catchments under given climate and timescales and a conceptual framework for model selection. The objective of the paper is therefore not to present a perfect model for any of the catchments studied but rather to present a systematic approach to modeling based on making inferences from data that can be applied with respect to different model designs, catchments and timescales.

A new approach to estimating Mean Flow in the UK

Abstract. Traditionally, the estimation of Mean Flow (MF) in ungauged catchments has been approached using conceptual water balance models or empirical formulae relating climatic inputs to stream flow. In the UK, these types of models have difficulty in predicting MF in low rainfall areas because the conceptualisation of soil moisture behaviour and its relationship with evaporation rates used is rather simplistic. However, it is in these dry regions where the accurate estimation of flows is most critical to effective management of a scarce resource. A novel approach to estimating MF, specifically designed to improve estimation of runoff in dry catchments, has been developed using a regionalisation of the Penman drying curve theory. The dynamic water balance style Daily Soil Moisture Accounting (DSMA) model operates at a daily time step, using inputs of precipitation and potential evaporation and simulates the development of soil moisture deficits explicitly. The model has been calibrated using measured MFs from a large data set of catchments in the United Kingdom. The performance of the DSMA model is superior to existing established steady state and dynamic water-balance models over the entire data set considered and the largest improvement is observed in very low rainfall catchments. It is concluded that the performance of all models in high rainfall areas is likely to be limited by the spatial representation of rainfall. Keywords: hydrological models, regionalisation, water resources, mean flow, runoff, water balance, Penman drying curve, soil moisture model