Impact of the spatial variability of daily precipitation on hydrological projections: A comparison of GCM‐ and RCM‐driven cases in the Han River basin,Korea

In this study, we investigate the impact of the spatial variability of daily precipitation on hydrological projections based on a comparative assessment of streamflow simulations driven by a global climate model (GCM) and two regional climate models (RCMs). A total of 12 different climate input datasets, that is, the raw and bias‐corrected GCM and raw and bias‐corrected two RCMs for the reference and future periods, are fed to a semidistributed hydrological model to assess whether the bias correction using quantile mapping and dynamical downscaling using RCMs can improve streamflow simulation in the Han River basin, Korea. A statistical analysis of the daily precipitation demonstrates that the precipitation simulated by the GCM fails to capture the large variability of the observed daily precipitation, in which the spatial autocorrelation decreases sharply within a relatively short distance. However, the spatial variability of precipitation simulated by the two RCMs shows better agreement with the observations. After applying bias correction to the raw GCM and raw RCMs outputs, only a slight change is observed in the spatial variability, whereas an improvement is observed in the precipitation intensity. Intensified precipitation but with the same spatial variability of the raw output from the bias‐corrected GCM does not improve the heterogeneous runoff distributions, which in turn regulate unrealistically high peak downstream streamflow. GCM‐simulated precipitation with a large bias correction that is necessary to compensate for the poor performance in present climate simulation appears to distort streamflow patterns in the future projection, which leads to misleading projections of climate change impacts on hydrological extremes.     

Seasonalizing mountain system recharge in semi-arid basins-climate change impacts

Climate variability and change impact groundwater resources by altering recharge rates. In semi-arid Basin and Range systems, this impact is likely to be most pronounced in mountain system recharge (MSR), a process which constitutes a significant component of recharge in these basins. Despite its importance, the physical processes that control MSR have not been fully investigated because of limited observations and the complexity of recharge processes in mountainous catchments. As a result, empirical equations, that provide a basin-wide estimate of mean annual recharge using mean annual precipitation, are often used to estimate MSR. Here North American Regional Reanalysis data are used to develop seasonal recharge estimates using ratios of seasonal (winter vs. summer) precipitation to seasonal actual or potential evapotranspiration. These seasonal recharge estimates compared favorably to seasonal MSR estimates using the fraction of winter vs. summer recharge determined from isotopic data in the Upper San Pedro River Basin, Arizona. Development of hydrologically based seasonal ratios enhanced seasonal recharge predictions and notably allows evaluation of MSR response to changes in seasonal precipitation and temperature because of climate variability and change using Global Climate Model (GCM) climate projections. Results show that prospective variability in MSR depends on GCM precipitation predictions and on higher temperature. Lower seasonal MSR rates projected for 2050-2099 are associated with decreases in summer precipitation and increases in winter temperature. Uncertainty in seasonal MSR predictions arises from the potential evapotranspiration estimation method, the GCM downscaling technique and the exclusion of snowmelt processes.     

The effects of climate change and urbanization on the runoff of the Rock Creek basin in the Portland metropolitan area,Oregon, USA

Climate changes brought on by increasing greenhouse gases in the atmosphere are expected to have a significant effect on the Pacific Northwest hydrology during the 21st century. Many climate model simulations project higher mean annual temperatures and temporal redistribution of precipitation. This is of particular concern for highly urbanized basins where runoff changes are more vulnerable to changes in climate. The Rock Creek basin, located in the Portland metropolitan area, has been experiencing rapid urban growth throughout the last 30 years, making it an ideal study area for assessing the effect of climate and land cover changes on runoff. A combination of climate change and land cover change scenarios for 2040 with the semi‐distributed AVSWAT (ArcView Soil and Water Assessment Tool) hydrological model was used to determine changes in mean runoff depths in the 2040s (2030–2059) from the baseline period (1973–2002) at the monthly, seasonal, and annual scales. Statistically downscaled climate change simulation results from the ECHAM5 general circulation model (GCM) found that the region would experience an increase of 1·2 °C in the average annual temperature and a 2% increase in average annual precipitation from the baseline period. AVSWAT simulation shows a 2·7% increase in mean annual runoff but a 1·6% decrease in summer runoff. Projected climate change plus low‐density, sprawled urban development for 2040 produced the greatest change to mean annual runoff depth (+5·5%), while climate change plus higher‐density urban development for 2040 resulted in the smallest change (+5·2%), when compared with the climate and land cover of the baseline period. This has significant implications for water resource managers attempting to implement adaptive water resource policies to future changes resulting from climate and urbanization. Copyright © 2008 John Wiley & Sons, Ltd.     

Development of a high resolution runoff routing model, calibration and application to assess runoff from the LMD GCM

Large-scale runoff routing models (RRMs) are important as a validation tool for GCMs, and to close the hydrological cycle in fully-coupled climate models. The model RiTHM was developed to simulate the discharge of large rivers from the total runoff simulated by the LMD GCM. It uses a 1024×800 grid, nested in the 64×50 grid of the LMD GCM. The runoff simulated in a GCM grid cell is uniformly distributed over the underlying cells, where a series of two reservoirs accounts for the delay related to infiltration through the unsaturated zone and aquifers. The resulting riverflow is routed assuming pure translation along the drainage network, extracted with a GIS from a 5 min DEM. The transfer time from a cell to the outlet depends on topography, and on a basin-wide parameter, the time of concentration. RiTHM was calibrated in 11 river basins, using a realistic runoff forcing (computed by the land surface model SECHIBA from reanalyzed meteorological forcing). This led to a very satisfactory reproduction of observed hydrographs. The main problems were related to hydraulic processes neglected in RiTHM (reservoirs, diversion of riverflow because of flooding or irrigation). These results helped to validate SECHIBA, except for its snow processes, shown to be too simple. With the same parameters, RiTHM was also forced with runoff from the LMD GCM. This induced an important degradation of the simulated hydrographs, regarding both volume and timing. It was largely explained by errors in precipitation, and more generally climate, in the GCM. The direct calibration of RiTHM under the GCM-runoff forcing markedly improved the timing of simulated discharge, which could be interesting for land–atmosphere–ocean coupling. This work demonstrated that the usefulness of RRMs for GCMs strongly depends on their adequate calibration.     

Modeling river/reservoir system management, water allocation, and supply reliability

The state of Texas has implemented a modeling system for assessing the availability and reliability of water resources that consists of a generalized simulation model called the Water Rights Analysis Package (WRAP) and input datasets for the state's 23 river basins. Reservoir/river system management and water allocation practices are simulated using historical naturalized monthly streamflow sequences to represent basin hydrology. Institutional systems for allocating streamflow and reservoir storage resources among numerous water users are considered in detail in evaluating basinwide impacts of water management decisions. The generalized WRAP model is a flexible tool that may be applied to river basins anywhere. The Texas experience in implementing a statewide modeling system illustrates issues that are relevant to water management in many other regions of the world.     

Long‐term trend of precipitation and runoff in Korean river basins

The spatial and temporal variations of precipitation and runoff for 139 basins in South Korea were investigated for 34 years (1968–2001). The Precipitation‐Runoff Modelling System (PRMS) was selected for the assessment of basin hydrologic response to varying climates and physiology. A non‐parametric Mann–Kendall's test and regression analysis are used to detect trends in annual, seasonal, and monthly precipitation and runoff, while Moran's I is adapted to determine the degree of spatial dependence in runoff trend among the basins. The results indicated that the long‐term trends in annual precipitation and runoff were increased in northern regions and decreased in south‐western regions of the study area during the study period. The non‐parametric Mann–Kendall test showed that spring streamflow was decreasing, while summer streamflow was increasing. April precipitation decreased between 15% and 74% for basins located in south‐western part of the Korean peninsula. June precipitation increased between 18% and 180% for the majority of the basins. Trends in seasonal and monthly streamflow show similar patterns compared to trends in precipitation. Decreases in spring runoff are associated with decreases in spring precipitation which, accompanied by rising temperatures, are responsible for reducing soil moisture. The regional patterns of precipitation and runoff changes show a strong to moderate positive spatial autocorrelation, suggesting that there is a high potential for severe spring drought and summer flooding in some parts of Korea if these trends continue in the future. Copyright © 2008 John Wiley & Sons, Ltd.     

Distributed modelling of future changes in hydrological processes of Spencer Creek watershed

The hydrologic impact of climate change has been largely assessed using mostly conceptual hydrologic models. This study investigates the use of distributed hydrologic model for the assessment of the climate change impact for the Spencer Creek watershed in Southern Ontario (Canada). A coupled MIKE SHE/MIKE 11 hydrologic model is developed to represent the complex hydrologic conditions in the Spencer Creek watershed, and later to simulate climate change impact using Canadian global climate model (CGCM 3·1) simulations. Owing to the coarse resolution of GCM data (daily GCM outputs), statistical downscaling techniques are used to generate higher resolution data (daily precipitation and temperature series). The modelling results show that the coupled model captured the snow storage well and also provided good simulation of evapotranspiration (ET) and groundwater recharge. The simulated streamflows are consistent with the observed flows at different sites within the catchment. Using a conservative climate change scenario, the downscaled GCM scenarios predicted an approximately 14–17% increase in the annual mean precipitation and 2–3 °C increase in annual mean maximum and minimum temperatures for the 2050s (i.e., 2046–2065). When the downscaled GCM scenarios were used in the coupled model, the model predicted a 1–5% annual decrease in snow storage for 2050s, approximately 1–10% increase in annual ET, and a 0·5–6% decrease in the annual groundwater recharge. These results are consistent with the downscaled temperature results. For future streamflows, the coupled model indicated an approximately 10–25% increase in annual streamflows for all sites, which is consistent with the predicted changes in precipitation. Overall, it is shown that distributed hydrologic modelling can provide useful information not only about future changes in streamflow but also changes in other key hydrologic processes such as snow storage, ET, and groundwater recharge, which can be particularly important depending on the climatic region of concern. The study results indicate that the coupled MIKE SHE/MIKE 11 hydrologic model could be a particularly useful tool for understanding the integrated effect of climate change in complex catchment scale hydrology. Copyright © 2010 John Wiley & Sons, Ltd.     

Statistical downscaling of GCM simulations to streamflow using relevance vector machine

General circulation models (GCMs), the climate models often used in assessing the impact of climate change, operate on a coarse scale and thus the simulation results obtained from GCMs are not particularly useful in a comparatively smaller river basin scale hydrology. The article presents a methodology of statistical downscaling based on sparse Bayesian learning and Relevance Vector Machine (RVM) to model streamflow at river basin scale for monsoon period (June, July, August, September) using GCM simulated climatic variables. NCEP/NCAR reanalysis data have been used for training the model to establish a statistical relationship between streamflow and climatic variables. The relationship thus obtained is used to project the future streamflow from GCM simulations. The statistical methodology involves principal component analysis, fuzzy clustering and RVM. Different kernel functions are used for comparison purpose. The model is applied to Mahanadi river basin in India. The results obtained using RVM are compared with those of state-of-the-art Support Vector Machine (SVM) to present the advantages of RVMs over SVMs. A decreasing trend is observed for monsoon streamflow of Mahanadi due to high surface warming in future, with the CCSR/NIES GCM and B2 scenario.     

Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins

In climate‐change studies, a macroscale hydrologic model (MHM) operating over large scales can be an important tool in developing consistent hydrological variability estimates over large basins. MHMs, which can operate at coarse grid resolutions of about 1° latitude by longitude, have been used previously to study climate change impacts on the hydrology of continental scale or global river basins. They can provide a connection between global atmospheric models and water resource systems on large spatial scales and long timescales. In this study, the variable infiltration capacity (VIC) MHM is used to study large scale hydrologic impacts of climate change for Indian river basins. Large‐scale changes in runoff, evapotranspiration and soil moisture for India, as well as station‐scale changes in discharges for three major river basins with distinct climatic and geographic characteristics are examined in this study. Climate model projections for meteorological variables (precipitation, temperature and wind speed) from three general circulation models (GCMs) and three emissions scenarios are used to drive the VIC MHM. GCM projections are first interpolated to a 1° by 1° hydrologic model grid and then bias‐corrected using a quantile–quantile mapping. The VIC model is able to reproduce observed statistics for discharges in the Ganga, Narmada and Krishna basins reasonably well, even at the coarse grid resolution employed using a calibration period for years 1965–1970 and testing period from 1971–1973/1974. An increasing trend is projected for summer monsoon surface runoff, evapotranspiration and soil moisture in most central Indian river basins, whereas a decrease in runoff and soil moisture is projected for some regions in southern India, with important differences arising from GCM and scenario variability. Discharge statistics show increases in mid‐flow and low flow at Farakka station on Ganga River, increased high flows at Jamtara station upstream of Narmada, and increased high, mid‐flow and low flow for Vijayawada station on Krishna River in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessing the effects of precipitation and temperature changes on hydrological processes in a glacier‐dominated catchment

The processes by which climate change affects streamflow in alpine river basins are not entirely understood. This study evaluated the impacts of temperature and precipitation changes on runoff and streamflow using glacier‐enhanced Soil and Water Assessment Tool model. The study used observed and detrended historical meteorological data for recent decades (1961–2005) to analyse individual and combined effects of temperature and precipitation changes on snow and glacier melts and discharges in the Sary‐Djaz‐Kumaric River Basin (SRB), Tianshan Mountains. The results showed a 1.3% increase in annual snowmelt in the basin, mainly because of an increase in precipitation. Snowmelt in the basin varied seasonally, increasing from April through May because of increasing precipitation and decreasing from July through September because of rising temperature. Glacier melt increased by 5.4%, 5.0% of which was due to rising temperature and only 0.4% due to increasing precipitation. Annual streamflow increased by 4.4%, of which temperature and precipitation increases accounted for 2.5% and 1.9%, respectively. The impacts of temperature and precipitation changes on streamflow were especially significant after 1980 and even more so in September. Glacier melt, due to temperature rise, was the dominant driver of increasing streamflow in the glacier‐dominated SRB, Tianshan Mountains. Copyright © 2015 John Wiley & Sons, Ltd.     

Response of streamflow to climate change and human activity in Xitiaoxi river basin in China

In recent years, the Xitiaoxi river basin in China has experienced intensified human activity, including city expansion and increased water demand. Climate change also has influenced streamflow. Assessing the impact of climate variability and human activity on hydrological processes is important for water resources planning and management and for the sustainable development of eco‐environmental systems. The non‐parametric Mann–Kendall test was employed to detect the trends of climatic and hydrological variables. The Mann–Kendall–Sneyers test and the moving t‐test were used to locate any abrupt change of annual streamflow. A runoff model, driven by precipitation and potential evapotranspiration, was employed to assess the impact of climate change on streamflow. A significant downward trend was detected for annual streamflow from 1975 to 2009, and an abrupt change occurred in 1999, which was consistent with the change detected by the double mass curve test between streamflow and precipitation. The annual precipitation decreased slightly, but upward trends of annual mean temperature and potential evapotranspiration were significant. The annual streamflow during the period 1999–2009 decreased by 26.19% compared with the reference stage, 1975–1998. Climate change was estimated to be responsible for 42.8% of the total reduction in annual streamflow, and human activity accounted for 57.2%. Copyright © 2012 John Wiley & Sons, Ltd.     

Parameterizing a hydrological model using a short-term observational dataset to study runoff generation processes and reproduce recent trends in streamflow at a remote mountainous permafrost basin

Recent decades have seen a change in the runoff characteristics of the Suntar River basin in the mountainous, permafrost, hard-to-reach region of Eastern Siberia. This study aims to investigate and simulate runoff formation processes, including the factors driving recent changes in hydrological response of the Suntar River, based on short-term historical observations of a range of hydrological, climatological and landscape measurements conducted in 1957–1959. The hydrograph model is applied as it has the advantage of using observed physical properties of landscapes as its parameters. The developed parametrization of the goltsy landscape (rocky-talus) is verified by comparison of the results of simulations of variable states of snow and frozen ground with observations carried out in 1957–1959. Continuous simulations of streamflow on a daily time step are conducted for the period 1957–2012 in the Suntar River (area 7680 km², altitude 828–2794 m) with mean and median values of Nash–Sutcliff criteria reaching 0.58 and 0.67, respectively. The results of simulations have shown that the largest component of runoff (about 70%) is produced in the high-altitude area which comprises only 44% of the Suntar River basin area. The simulated streamflow reproduces the patterns of recently observed changes, including the increase in low flows, suggesting that the increase in the proportion of liquid precipitation in autumn due to air temperature rise is an important factor in driving streamflow changes in the region. The data presented are unique for the vast mountainous parts of North-Eastern Eurasia which play an important role in the global climate system. The results indicate that parameterizing a hydrological model based on observations allows the model to be used in studying the response of river basins to climate change with greater confidence.     

Merging multi-source precipitation products or merging their simulated hydrological flows to improve streamflow simulation

Satellite and reanalysis precipitation products are widely utilized for streamflow simulation, which is one critical hydrological application, especially for ungauged regions. Possible ways to improve streamflow simulation are investigated in this study by merging multi-source precipitation products, or directly merging streamflow simulated with different precipitation products. Two satellite-based precipitation products, Tropical Rainfall Measuring Mission (3B42 Version 7) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and one reanalysis precipitation product, National Centers for Environment Prediction-Climate Forecast System Reanalysis (NCEP-CFSR) are selected. Bayesian model averaging (BMA) is used to merge multi-source precipitation estimates and streamflow simulations. The results show that merging multi-source precipitation products made little difference to improve streamflow simulation. Merging multi-source streamflow simulations using the BMA generally achieved better performance on streamflow simulation, indicating that this approach is more efficient than merging multi-source precipitation products.     

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

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

UTILIZATION OF THE RESULTS FROM REPRESENTATIVE AND EXPERIMENTAL BASINS WITH A VIEW TO THE MANAGEMENT OF WATER RESOURCES / Utilisation des résultats obtenus sur les bassins représentatifs et expérimentaux en vue de l'aménagement des ressources en eau

Abstract

The management of water resources requires knowledge of the spatial and temporal distribution of surface and groundwater resources, and an assessment of the influence of man on the hydrological regime.

For small water courses regional estimates can be made from representative basins which offer guidelines (1) for the computation of mean annual flow and in some cases for the determination of the statistical distribution of the annual flow; (2) for the computation of the 10-year flood maximum discharge and volume.

An example concerning the tropical African Sahel is given. From a general study of the daily precipitation, a simple rainfall/runoff model used on a daily basis and calibrated on data from representative basins, and also the direct comparison of results from 55 representative basins, statistical distribution curves were established for annual runoff based on mean annual precipitation and the geomorphological characteristics of the basins.

Another example concerning tropical Africa west of Congo presents a methodology for the computation of the 10-year flood (maximum discharge and volume).

The systematic study of 60 representative basins makes it possible to plot the runoff coefficient R/P as a function of basin climate, mean slope and soil permeability. Other curves are used to determine the time of rise and the base time of the hydrograph as a function of the basin area and the mean slope.

The experimental basin is a good tool for the assessment of the influence of man on hydrological parameters. An example shows the influence of land use on the regression between annual precipitation and annual runoff.     

Residence times in river basins as determined by analysis of long-term tritium records

The US Geological Survey has maintained a network of stations to collect samples for the measurement of tritium concentrations in precipitation and streamflow since the early 1960s. Tritium data from outflow waters of river basins draining 4500–75000 km² are used to determine average residence times of water within the basins. The basins studied are the Colorado River above Cisco, Utah; the Kissimmee River above Lake Okeechobee, Florida; the Mississippi River above Anoka, Minnesota; the Neuse River above Streets Ferry Bridge near Vanceboro, North Carolina; the Potomac River above Point of Rocks, Maryland; the Sacramento River above Sacramento, California; the Susquehanna River above Harrisburg, Pennsylvania. The basins are modeled with the assumption that the outflow in the river comes from two sources—prompt (within-year) runoff from precipitation, and flow from the long-term reservoirs of the basin. Tritium concentration in the outflow water of the basin is dependent on three factors: (1) tritium concentration in runoff from the long-term reservoir, which depends on the residence time for the reservoir and historical tritium concentrations in precipitation; (2) tritium concentrations in precipitation (the within-year runoff component); (3) relative contributions of flow from the long-term and within-year components. Predicted tritium concentrations for the outflow water in the river basins were calculated for different residence times and for different relative contributions from the two reservoirs. A box model was used to calculate tritium concentrations in the long-term reservoir. Calculated values of outflow tritium concentrations for the basin were regressed against the measured data to obtain a slope as close as possible to 1. These regressions assumed an intercept of zero and were carried out for different values of residence time and reservoir contribution to maximize the fit of modeled versus actual data for all the above rivers. The final slopes of the fitted regression lines ranged from 0.95 to 1.01 (correlation coefficient > 0.96) for the basins studied. Values for the residence time of waters within the basins and average relative contributions of the within-year and long-term reservoirs to outflow were obtained. Values for river basin residence times ranged from 2 years for the Kissimmee River basin to 20 years for the Potomac River basin. The residence times indicate the time scale in which the basin responds to anthropogenic inputs. The modeled tritium concentrations for the basins also furnish input data for urban and agricultural settings where these river waters are used.     

Cross-spectral analysis of rainfall and runoff for Raritan and Mullica river basins in New Jersey

Cross-correlation and cross-spectral analysis were employed in the analysis of rainfall and runoff in two river basins: the Raritan and Mullica River basins in New Jersey. Cross-covariance and coherence were studied in the correlograms for the following correlation cases: (a) rainfall-runoff for each one basin separately; (b) rainfall-rainfall analysis for two main meteorological stations in each one of the basins; (c) runoff-runoff for two main gaging stations in each one of the basins. From the estimates of the coherence at various frequencies the cross-spectral analysis shows a highly nonlinear relationship between rainfall and runoff in Raritan and Mullica River basins. A poor coherence observed at the annual cycles for each basin makes it difficult to predict the annual oscillations of runoff from those of rain-fall by a linear regression model. The high coherence between rainfall (or runoff) at the first station and rainfall (or runoff) at the second station within the same basin at almost all frequencies establishes an accurate prediction on a linear basis.     

Addressing uncertainty in reflectivity‐rainfall relations in mountain watersheds during summer convection

The use of precipitation estimates from weather radar reflectivity has become widespread in hydrologic predictions. However, uncertainty remains in the use of the nonlinear reflectivity–rainfall (Z‐R) relation, in particular for mountainous regions where ground validation stations are often lacking, land surface data sets are inaccurate and the spatial variability in many features is high. In this study, we assess the propagation of rainfall errors introduced by different Z‐R relations on distributed hydrologic model performance for four mountain basins in the Colorado Front Range. To do so, we compare spatially integrated and distributed rainfall and runoff metrics at seasonal and event time scales during the warm season when convective storms dominate. Results reveal that the basin simulations are quite sensitive to the uncertainties introduced by the Z‐R relation in terms of streamflow, runoff mechanisms and the water balance components. The propagation of rainfall errors into basin responses follows power law relationships that link streamflow uncertainty to the precipitation errors and streamflow magnitude. Overall, different Z‐R relations preserve the spatial distribution of rainfall relative to a reference case, but not the precipitation magnitude, thus leading to large changes in streamflow amounts and runoff spatial patterns at seasonal and event scales. Furthermore, streamflow errors from the Z‐R relation follow a typical pattern that varies with catchment scale where higher uncertainties exist for intermediate‐sized basins. The relatively high error values introduced by two operational Z‐R relations (WSR‐57 and NEXRAD) in terms of the streamflow response indicate that site‐specific Z‐R relations are desirable in the complex terrain region, particularly in light of other uncertainties in the modelling process, such as model parameter values and initial conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Scaling and physiographic controls on streamflow behaviour on the Precambrian Shield, south-central Ontario

Relationships explaining streamflow behaviour in terms of drainage basin physiography greatly assist efforts to extrapolate streamflow metrics from gauged to ungauged basins in the same landscape. The Dorset Environmental Science Centre (DESC) has monitored streamflow from 22 small basins (3.4–190.5 ha) on the Precambrian Shield in south-central Ontario, in some cases since 1976. The basins exhibit regional coherence in their interannual response to precipitation; however, there is often a poor correlation between streamflow metrics from basins separated by as little as 1 km. This study assesses whether inter-basin variations in such metrics can be explained in terms of basin scale and physiography. Several characteristics (annual maximum, minimum and average flow) exhibited simple scaling with basin area, while magnitude, range and timing of annual maximum daily runoff showed scaling behaviour consistent with the Representative Elementary Area (REA) concept. This REA behaviour is partly attributed to convergence of fractional coverage of the two dominant and hydrologically-contrasting land cover types in the DESC region with increasing basin size. Three Principal Components (PCs) explained 82.4% of the variation among basin physiographic properties, and several runoff metrics (magnitude and timing of annual minimum daily runoff, mean number of days per year with 0 streamflow) exhibited significant relationships with one or more PC. Significant relationships were obtained between basin quickflow (QF) production and the PCs on a seasonal and annual basis, almost all of which were superior to simple area-based relationships. Basin physiography influenced QF generation via its control on slope runoff, water storage and hydrologic connectivity; however, this role was minimized during Spring when QF production in response to large rain-on-snow events was relatively uniform across the DESC basins. The PC-based relationships and inter-seasonal changes in their form were consistent with previous research conducted at point, slope and basin scales in the DESC region, and perceptions of key hydrological processes in these small basins may not have been as readily obtained from scaling studies using streamflow from larger basins. This process understanding provides insights into scaling behaviour beyond those derived from simple scaling and REA analyses. The physiography of the study area is representative of large portions of the Precambrian Shield, such that basin streamflow behaviour could potentially be extended across much of south-central Ontario. This would assist predictions of streamflow conditions at ungauged locations, development and testing of hydrological models for this landscape, and interpretation of inter-basin and intra-annual differences in hydrochemical behaviour on the southern Precambrian Shield.     

How informative are stream level observations in different geographic regions?

Simple runoff models with a low number of model parameters are generally able to simulate catchment runoff reasonably well, but they rely on model calibration, which makes their use in ungauged basins challenging. In a previous study it has been shown that a limited number of streamflow measurements can be quite informative for constraining runoff models. In practice, however, instead of performing such repeated flow measurements, it might be easier to install a stream level logger. Here, a dataset of 600+ gauged basins in the USA was used to study how well models perform when only stream level data, rather than streamflow data, are available. A runoff model (the HBV model) was calibrated assuming that only stream level observations were available, and the simulations were evaluated on the full observed streamflow record. The results indicate that stream level data alone can already provide surprisingly good model simulation results in humid catchments, whereas in arid catchments some form of quantitative information (e.g. a streamflow observation or a regional average value) is needed to obtain good results. These results are encouraging for hydrological observations in data scarce regions as level observations are much easier to obtain than streamflow measurements. Based on runoff modelling, it might even be possible to derive streamflow time series from the level data obtained from loggers, satellites or community‐based approaches. Copyright © 2016 John Wiley & Sons, Ltd.