On the identification of ENSO-induced rainfall and runoff variability: a comparison of methods and indices

Abstract

It is known that the El Niño Southern Oscillation (ENSO) phenomenon induces marked climate variability across many parts of the world. However, in seeking useful relationships between ENSO and climate, several indices are available. In addition to the choice of index, previous studies assessing ENSO effects have employed a range of different methods to classify periods as El Niño, La Niña or Neutral. It is therefore clear that significant subjectivity exists in the adoption of ENSO classification schemes. In this study, several ENSO classification methods are applied to a range of ENSO indices. Each method-index combination is investigated to determine which provides the strongest relationship with rainfall and runoff in the Williams River catchment, New South Wales, Australia. The results demonstrate substantial differences between the methods and indices. The Multivariate ENSO Index (or MEI) is found to provide the best classification irrespective of method. The potential for forecasting ENSO-related effects on rainfall, runoff and river abstractions is then investigated. A “rise rule” to account for dynamic ENSO trends is also assessed. Strong relationships were found to exist with runoff (rainfall) up to nine (eight) months in advance of the Summer/autumn period. Implications for improved forecasting of potential river abstractions are apparent.     

RELATIONSHIPS BETWEEN CATCHMENT ATTRIBUTES AND HYDROLOGICAL RESPONSE CHARACTERISTICS IN SMALL AUSTRALIAN MOUNTAIN ASH CATCHMENTS

Sixteen small catchments in the Maroondah region of Victoria, Australia were analysed using rainfall, temperature and streamflow time series with a rainfall–runoff model whose parameters efficiently characterize the hydrological response of a catchment. A set of catchment attributes for each of these catchments was then compared with the associated set of hydrological response characteristics of the catchments as estimated by the model. The time constant governing quickflow recession of streamflow (τ_q) was related to the drainage network and catchment area. The time constant governing slowflow recession of streamflow (τ_s) was related to the slope and shape of the catchment. The parameter governing evapotranspirative losses ( f ) was related to catchment gradient and vegetative water use. Forestry activities in the catchments changed evapotranspirative losses and thus total volume of streamflow, but did not affect the rate of streamflow recession.     

Simulating temporal variability in catchment response using a monthly rainfall–runoff model

Abstract

Temporal variability can result from shifts in climate, or from changes in the runoff response due to land- or water-use changes, and represents a potential source of uncertainty in calibrating hydrological models. Parameter values were determined using Monte Carlo parameter sampling methods for a monthly rainfall–runoff model (Pitman model) for different sub-periods on four catchments, with different types and degrees of temporal variability, in Australia and Africa. For some catchments, parameters were not dependent upon the sub-period used and fell within expected ranges given the relatively high degree of model equifinality. In other catchments, dependencies can be identified that are associated with signals contained within the sub-periods. While the Pitman model is relatively robust in the face of temporal variability, it is concluded that better simulations will always be obtained from calibration data that include signals representing the total variability in climate, land-use change and catchment responses.     

Modelling streamflow trends for a watershed with limited data: case of the Litani basin,Lebanon

Abstract

Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m³/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m³/s per decade in January for the Upper and Lower basin, respectively.

Editor D. Koutsoyiannis; Associate editor Sheng Yue

Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.     

Impacts of El Niño–southern oscillation on global runoff: Characteristic signatures and potential mechanisms

Runoff signatures, including low flow, high flow, mean flow and flow variability, have important implications on the environment and society, predominantly through drought, flooding and water resources. Yet, the response of runoff signatures has not been previously investigated at the global scale, and the influencing mechanisms are largely unclear. Hence, this study makes a global assessment of runoff signature responses to the El Niño and La Niña phases using daily streamflow observations from 8217 gauging stations during 1960–2015. Based on the Granger causality test, we found that ~15% of the hydrological stations of multiple runoff signatures show a significant causal relationship with El Niño–southern oscillation (ENSO). The quantiles of all runoff signatures were larger during the El Niño phase than during the La Niña phase, implying that the entire flow distribution tends to shift upward during El Niño and downward during La Niña. In addition, El Niño has different effects on low and high flows: it tends to increase the low and mean flow signatures but reduces the high flow and flow variability signatures. In contrast, La Niña generally reduces all runoff signatures. We highlight that the impacts of ENSO on streamflow signatures are manifested by its effects on precipitation (P), potential evaporation (PET) and leaf area index (LAI) through ENSO-induced atmospheric circulation changes. Overall, our study provides a comprehensive picture of runoff signature responses to ENSO, with valuable insights for water resources management and flood and drought disaster mitigation.     

Hydrological system analysis and modelling of the Kara River basin (West Africa) using a lumped metric conceptual model

This paper discusses the analysis and modelling of the hydrological system of the basin of the Kara River, a transboundary river in Togo and Benin, as a necessary step towards sustainable water resources management. The methodological approach integrates the use of discharge parameters, flow duration curves and the lumped conceptual model IHACRES. A Sobol sensitivity analysis is performed and the model is calibrated by applying the shuffled complex evolution algorithm. Results show that discharge generation in three nested catchments of the basin is affected by landscape physical characteristics. The IHACRES model adequately simulates the rainfall–runoff dynamics in the basin with a mean modified Nash-Sutcliffe efficiency measure of 0.6. Modelling results indicate that parameters controlling rainfall transformation to effective rainfall are more sensitive than those routing the streamflow. This study provides insights into understanding the catchment’s hydrological system. Nevertheless, further investigations are required to better understand detailed runoff generation processes.

EDITOR M.C. Acreman; ASSOCIATE EDITOR N Verhoest     

Hydrological response of a humid agroforestry catchment at different time scales

Using data collected at the Mero catchment during three hydrological years (2005/06–2007/08), an analysis of rainfall–runoff relationships was performed at annual, seasonal, monthly, and event scales. At annual scale, the catchment showed low runoff coefficients (23–35%), due to high water storage capacity soils as well as high runoff inter‐annual variability. Rainfall variability was the main responsible for the differences in the inter‐annual runoff. At seasonal and monthly scales, there was no simple relationship between rainfall and runoff. Seasonal dynamics of rainfall and potential evapotranspiration in conjunction with different rainfall distribution during the study years could be the key factors explaining the complex relationship between rainfall and runoff at monthly and seasonal scale. At the event scale, the results revealed that the hydrological response was highly dependent on initial conditions and, to a lesser extent, on rainfall amount. The shapes of the different hydrographs, regardless of the magnitude, presented similar characteristics: a moderate rise and a prolonged recession, suggesting that subsurface flow was the dominant process in direct runoff. Moreover, all rainfall–runoff events had a higher proportion of baseflow than of direct runoff. A cluster‐type analysis discriminated three types of events differentiated mainly by rainfall amount and antecedent rainfall conditions. The study highlights the role of the antecedent rainfall and the need for caution in extrapolating relationships between rainfall amount and hydrological response of the catchment. Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluation of rainfall–runoff model performance under non-stationary hydroclimatic conditions

ABSTRACT

Understanding of rainfall–runoff model performance under non-stationary hydroclimatic conditions is limited. This study compared lumped (IHACRES), semi-distributed (HEC-HMS) and fully-distributed (SWATgrid) hydrological models to determine which most realistically simulates runoff in catchments where non-stationarity in rainfall–runoff relationships exists. The models were calibrated and validated under different hydroclimatic conditions (Average, Wet and Dry) for two heterogeneous catchments in southeast Australia (SEA). SWATgrid realistically simulates runoff in the smaller catchment under most hydroclimatic conditions but fails when the model is calibrated in Dry conditions and validated in Wet. All three models perform poorly in the larger catchment irrespective of hydroclimatic conditions. This highlights the need for more research aimed at improving the ability of hydrological models to realistically incorporate the physical processes causing non-stationarity in rainfall–runoff relationships. Although the study is focussed on SEA, the insights gained are useful for all regions which experience large hydroclimatic variability and multi-year/decadal droughts.     

Estimation of rainfall elasticity of streamflow in Australia

Abstract

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 (? _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 ? _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.     

Modelling the impacts of land-cover change on streamflow dynamics of a tropical rainforest headwater catchment

Abstract

A modelling experiment is used to examine different land-use scenarios ranging from extreme deforestation (31% forest cover) to pristine (95% forest cover) conditions and related Payment for Ecosystem Services (PES) schemes to assess whether a change in streamflow dynamics, discharge extremes and mean annual water balance of a 73.4-km² tropical headwater catchment in Costa Rica could be detected. A semi-distributed, conceptual rainfall–runoff model was adapted to conceptualize the empirically-based, dominant hydrological processes of the study area and was multi-criteria calibrated using different objective functions and empirical constraints on model simulations in a Monte Carlo framework to account for parameter uncertainty. The results suggest that land-use change had relatively little effect on the overall mean annual water yield (<3%). However, streamflow dynamics proved to be sensitive in terms of frequency, timing and magnitude of discharge extremes. For low flows and peak discharges of return periods greater than one year, land use had a minor influence on the runoff response. Below these thresholds (<1-year return period), forest cover potentially decreased runoff peaks and low flows by as much as 10%, and non-forest cover increased runoff peaks and low flows by up to 15%. The study demonstrated the potential for using hydrological modelling to help identify the impact of protection and reforestation efforts on ecosystem services.

Editor Z.W. Kundzewicz

Citation Birkel, C., Soulsby, C., and Tetzlaff, D., 2012. Modelling the impacts of land-cover change on streamflow dynamics of a tropical rainforest headwater catchment. Hydrological Sciences Journal, 57 (8), 1543–1561.     

Simulated response of an intermittent stream to rainfall frequency patterns

The response of intermittent catchments to rainfall is complex and difficult to model. This study uses the spatially distributed CATchment HYdrology (CATHY) model to explore how the frequency of daily rainfall (λ) can affect the hydrologic regime of intermittent catchments. After a multi-objective calibration and validation of CATHY against experimental measurements of streamflow and groundwater levels in a catchment used as a pasture, the role of λ in affecting streamflow characteristics was explored using different scenarios. With different values of λ for the dry and wet periods of the year, CATHY showed that a series of frequent rainfall events was often associated with incipient streamflow, independent of the season. Activation of streamflow during the wet season was related to multiple factors and was not often associated with the shallow groundwater levels near the outlet of the catchment. The interplay between rainfall depth and intensity acted as the most important factor for the generation of streamflow. Using the difference between accumulated rainfall and evapotranspiration as a measure of wetness, saturated subsurface flow mechanism generated streamflow in simulations with wetness at least three times larger than mean wetness of other simulations. Although groundwater uprise near the outlet did not effectively contribute to streamflow in the initial days of flow, it strongly correlated with the magnitude of the runoff coefficient. Values of λ close or equal to the maximum value in the wet season can sustain the connectivity between groundwater and streamflow in the riparian zone. This connectivity increases the catchment wetness, which consequently results in an increase of the generated streamflow. Our study showed that rainfall regimes characterized by different λ were able to identify distinct flow regimes typical of either intermittent, ephemeral, or nonflowing catchments. Decrease of λ in the wet season is likely associated with a reduction of streamflow, with a shift of flow regime from intermittent to ephemeral or no-flow.     

MODELLING RAINFALL-RUNOFF FROM LARGE CATCHMENT TO BASIN SCALE: THE GOULBURN VALLEY,VICTORIA

A lumped parameter dynamic rainfall-runoff model, IHACRES, is applied to the large upland area (more than 4500 km²) of the Goulburn Valley Basin, Victoria, Australia to predict streamflow under different climatic conditions. This paper presents the first evaluation of a rainfall–runoff model at large catchment scale, which is comprehensive in terms of the number of catchments investigated and the number of calibration and simulation periods used. The basin is subdivided into 12 catchments (from 100 to 700 km²), each of which is calibrated separately. High values of model efficiency and low bias are consistently obtained for different calibration sub-periods for all catchments in the basin. Simulation or so-called validation tests are used to select the best models for each catchment. This allows simulation of the water regime during long historical (approximately 90 year) periods when only climatological (rainfall and temperature) data were available. This procedure is extremely important for the estimation of the effect of climate variability and of the possible impact of climate change on the hydrological regime in the region and, in particular, for supporting irrigation management of the basin. Analysis of a composite catchment (2417 km²) and its five separate subcatchments indicates that the information content in the rainfall–streamflow data is independent of catchment size. Dynamic modelling of the daily water balance at the macroscale is limited principally by the adequacy of the precipitation gauging network. When a good estimate of areal precipitation is available for a catchment, it is not necessary to consider subcatchment-scale variability for modelling if the only interest is the daily discharge and evaporation losses from the catchment.     

Assessment of the effectiveness of a multi-site stochastic weather generator on hydrological modelling in the Red Deer River watershed,Canada

ABSTRACT

To improve the convergence of multiple-site weather generators (SWGs) based on the brute force algorithm (MBFA), a genetic algorithm (GA) is proposed to search the overall optimal correlation matrix. Precipitation series from weather generators are used as input to the hydrological model, the soil and water assessment tool (SWAT), to generate runoff over the Red Deer watershed, Canada for further runoff analysis. The results indicate that the SWAT model using SWG-generated data accurately represents the mean monthly streamflow for most of the months. The multi-site generators were capable of better representing the monthly streamflow variability, which was notably underestimated by the single-site version. In terms of extreme flows, the proposed method reproduced the observed extreme flow with smaller bias than MBFA, while the single-site generator significantly underestimated the annual maximum flows due to its poor capability in addressing partial precipitation correlations.     

Rainfall–runoff response and event-based runoff coefficients in a humid area (northwest Spain)

Abstract

The hydrological response of a small agroforestry catchment in northwest Spain (Corbeira catchment, 16 km²) is analysed, with particular focus on rainfall events. Fifty-four rainfall–runoff events, from December 2004 to September 2007, were used to analyse the principal hydrological patterns and show which factors best explain the hydrological response. The nonlinearity between rainfall and runoff showed that the variability in the hydrological response of the catchment was linked to the seasonal dynamics of the rainfall and, to a lesser extent, to evapotranspiration. The runoff coefficient, estimated as the ratio between direct runoff and rainfall volume, on an event basis, was analysed as a function of rainfall characteristics (amount and intensity) and the initial catchment state conditions prior to an event, such as pre-event baseflow and antecedent rainfall index. The results revealed that the hydrological response depends both on the soil humidity conditions at the start of the event and on rainfall amount, whereas rainfall intensity presented only a significant correlation with discharge increment. The antecedent conditions seem to be a key point in runoff production, and they explain much of the response. The hydrographs are characterized by a steep rising limb, a relatively narrow peak discharge and slow recession limb. These data and the observations suggest that the subsurface flow is the dominant runoff process.

Editor Z.W. Kundzewicz; Associate editor T. Wagener

Citation Rodríguez-Blanco, M.L., Taboada-Castro, M.M. and Taboada-Castro, M.T., 2012. Rainfall–runoff response and event-based runoff coefficients in a humid area (northwest Spain). Hydrological Sciences Journal, 57 (3), 445–459.     

Modelling nitrogen dynamics for a mesoscale catchment using a minimum information requirement (MIR) concept / Modélisation des dynamiques de l'azote pour un bassin versant de taille moyenne,utilisant le concept de besoin minimum d'information

Abstract

Based on the water balance model LARSIM (Large Area Simulation Model), a model for the simulation of nitrogen transport was developed in a mesoscale catchment in southwest Germany. To meet the needs and constraints in river basin management, the nitrogen model was developed following the concept of minimum information requirement (MIR). The modelling concept uses only few calibration parameters and only easily accessible input data. Water balance, runoff generation and nitrogen transport were simulated on a 1-km² grid of sub-areas in which different land-use classes and soil characteristics were accounted. Temporal variability of the storage of mobile nitrogen were described using a monthly based mass balance. Nitrogen mobilization and transport was simulated using monthly values of different runoff components and data for soil properties, topography, hydrogeology and river network. The simulation was calibrated and validated using streamflow from two gauging stations and observed nitrogen concentrations at the catchment outlet, showing reasonable results for both streamflow and nitrogen dynamics. The results of the model application are discussed in the context of uncertainty problems and their implications for water management.     

MODELLING RUNOFF GENERATION ON SMALL AGRICULTURAL CATCHMENTS: CAN REAL WORLD RUNOFF RESPONSES BE CAPTURED?

This paper focuses on the problem of quantifying real world catchment response using a distributed model and discusses the ability of the model to capture that response. The rainfall–runoff responses of seven small agricultural catchments in the eastern wheatbelt region of south-western Australia are examined. The variability in runoff generation and the factors that contribute to that variability (i.e. rainfall intensity, soil properties and topography) are investigated to determine if their influence can be captured in a mathematical model. The spatially distributed rainfall–runoff model used in this study is based on the TOPMODEL concepts of Beven and Kirkby (1979), and simulates runoff generation by both the infiltration excess and saturation excess mechanisms. Simulations with the model revealed the highly complex nature of catchment response to rainfall events. Runoff generation was highly heterogeneous in both space and time, with the runoff response being governed by the spatial variability of soil properties and topography, and by the temporal variation in rainfall intensity. Although the model proved capable of simulating catchment response for many events, the investigation has demonstrated that not all aspects of the variability associated with agricultural catchments (particularly the effects of land management) can be captured using this relatively simple model. © 1997 by John Wiley & Sons, Ltd     

Temporal variability in hydrological response within a small catchment with badland areas,central Pyrenees

Abstract

The lower Araguás catchment, central Pyrenees, is characterized by extensive badlands (25% of the total catchment), whereas the upper catchment is covered by dense plantation forest. The catchment (45 ha) has been monitored since October 2005 with the aim of studying its hydrological response. The 44 floods recorded over this period were analysed to identify the factors that control the rainfall—runoff relationship. The first relevant feature of the catchment was its responsiveness. The catchment reacted to all rainfall events, but the irregular nature of the hydrological response was the most characteristic feature of the response. No single variable could explain the response of the Araguás catchment. It was found that stormflow coefficients mainly depend on the combination of rainfall volume and antecedent baseflow. A significant correlation was observed between maximum rainfall intensity and peak flow values. The shapes of the different hydrographs are very similar, regardless of the peak flow magnitude; they show a short time lag, relatively narrow peak flow, and steep recession limb. This indicates a large contribution by overland flow, resulting mainly from the generation of infiltration excess runoff in badland areas.     

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.     

Combining regression and spatial proximity for catchment model regionalization: a comparative study

Abstract

Spatial error regression is employed to regionalize the parameters of a rainfall–runoff model. The approach combines regression on physiographic watershed characteristics with a spatial proximity technique that describes the spatial dependence of model parameters. The methodology is tested for the monthly abcd model at a network of gauges in southeast United States and compared against simpler regression and spatial proximity approaches. Unlike other comparative regionalization studies that only evaluate the skill of regionalized streamflow predictions in ungauged catchments, this study also examines the fit between regionalized parameters and their optimal (i.e. calibrated) values. Interestingly, the spatial error model produces parameter estimates that better resemble the optimal parameters than either of the simpler methods, but the spatial proximity method still yields better hydrologic simulations. The analysis suggests that the superior streamflow predictions of spatial proximity result from its ability to better preserve correlations between compensatory hydrological parameters.

Editor D. Koutsoyiannis; Associate editor Y. Gyasi-Agyei     

Seasonal changes in the fraction of global radiation retained as net all-wave radiation and their hydrological implications

Abstract

High linear correlation between concurrent measurements of net all-wave radiation Q*, and global incoming short-wave radiation E_g↓ was found for hourly, daytime and 24-h totals measured over a grassland catchment in the subhumid climate region of southeastern Australia. Five years of daily measurements were used to study the temporal variability in the fraction of incoming short-wave radiation retained at the surface as net all-wave radiation. When values of ξ = [Sgrave]Q*/[Sgrave]E_g↓ are calculated from 24-h totals and are plotted against date, the results reveal strong day-to-day and seasonal variability in ξ. Analysis indicated that the ξ ratio was largely determined by data, latitude and cloudiness, whilst the nature of the underlying surface appeared to play a less important role. Data from four other grassland sites in Australia, New Caledonia, Denmark and Ireland yielded a general relationship for estimating ξ from day length. Values of [Sgrave]Q* may thus be obtained from [Sgrave]E_g↓ observations using (a) a single regression between [Sgrave]Q* and [Sgrave]E_g↓ (b) monthly ξ values derived from measurements; or (c) monthly ξ values estimated from day length. All three approaches give estimates of [Sgrave]Q* with error terms similar to those of measurements of net all-wave radiation and those found when [Sgrave]Q* was estimated climatologically from the individual elements of the surface radiation balance—the standard method of obtaining this rarely measured but hydrologically important parameter. The hydrological impact of different methods of obtaining [Sgrave]Q* was demonstrated using the semi-distributed VIC catchment model to compute potential evapotranspiration for the 26 km² Lockyersleigh catchment near Goulburn, New South Wales, Australia. The limited hydrological impact found is attributed to the fact that actual evapotranspiration in this subhumid catchment is limited by the strength of the soil water source rather than that of the atmospheric sink-potential evapotranspiration.