Evaluating sources of uncertainty in Australian runoff projections

Generating estimates of the future impacts of climate change on human and natural systems is confounded by cascading uncertainties which propagate through the impact assessment. Here, a simple stochastic rainfall–runoff model representing 238 river basins on the Australian continent was used to assess the sensitivity of the risk of runoff changes to various sources of uncertainty. Uncertainties included global mean temperature change, greenhouse gas stabilisation targets, catchment sensitivities to climatic change, and the seasonality of runoff, rainfall, and evaporation. Model simulations provided estimates of the first-order risk of climate change to Australian catchments, with several regions having high likelihoods of experiencing significant reductions in future runoff. Climate uncertainty (at global and regional scales) was identified as the dominant driving force in hydrological risk assessments. Uncertainties in catchment sensitivities to climatic changes also influenced risk, provided they were sufficiently large, whereas structural assumptions of the model were generally negligible. Collectively, these results indicate that rigorous assessment of climate risk to water resources over relatively long time-scales is largely a function of adequately exploring the uncertainty space of future climate changes.     

Many-year variations of river runoff in the Selenga basin

Many-year variations of river runoff in the Selenga basin are analyzed along with precipitation, potential evapotranspiration, and basin water storages. Data of ground-based (1932–2015) and satellite observations, as well as the analysis of literature data suggest the presence of within-century cycles in the series of annual and minimum runoff. Compared with 1934–1975, the Selenga Basin shows a general tendency toward a decrease in the maximum (by 5–35%) and mean annual (up to 15%) runoff at an increase in the minimum runoff (by 30%), a decrease in the mean annual precipitation (by 12%), and an increase in potential evapotranspiration by 4% against the background of a decrease in evaporation because of lesser soil moisture content and an increase in moisture losses for infiltration because of permafrost degradation. The observed changes in water balance may have unfavorable environmental effects.     

On in-series correlation of minimum river runoff

Field data are used to assess the autocorrelation coefficient between successive terms in the series of minimal 30-day sums of river runoff in the winter and summer-autumn low-flow periods in the Russian territory. Zoning of the autocorrelation coefficient of winter and summer-autumn runoff is carried out within this territory, and the character of its dependence on the module and coefficient of variation of minimal runoff is studied.     

Mechanism of wetting and river runoff in the east european plain

The general picture of wetting the East European Plain in 1966–1985 is established by studying the trajectories of more than 5000 cyclones in the Northern Hemisphere. The role of the Arctic High as a regulator of the paths of the Atlantic cyclones is established. It is shown that the majority of rivers of the East European Plain feature higher rate of streamflow in the years with the El Nino effect.Translated from Vodnye Resursy, Vol. 32, No. 1, 2005, pp. 108–114.Original Russian Text Copyright © 2005 by Babkin, Klige.     

Discrete dynamic-stochastic model of long-term river runoff variations

A model of long-term river runoff variations is proposed. The model is based on a difference stochastic equation of water balance on a watershed. Precipitation and evaporation on the watershed are simulated by stochastic, dependent, non-Gaussian Markov processes. Long-term river runoff variations are described by a component of three-dimensional non-Gaussian Markov process. It is shown that the autocorrelation and skewness coefficients for river runoff can be negative. The proposed model can be used to assess the effect of climate-induced variations in precipitation and evaporation regimes in a watershed on long-term river runoff variations.     

Quantifying the sources of simulation uncertainty in natural catastrophe models

The risk from natural catastrophes is typically estimated using complex simulation models involving multiple stochastic components in a nested structure. This risk is principally assessed via the mean annual loss, and selected quantiles of the annual loss. Determining an appropriate simulation strategy is important in order to achieve satisfactory convergence of these statistics, without excessive computation time and data storage requirements. This necessitates an understanding of the relative contribution of each of the stochastic components to the total variance of the statistics. A simple framework using random effects models and analysis of variance is used to partition the variance of the annual loss, which permits calculation of the variance of the mean annual loss with varying numbers of samples of each of the components. An extension to quantiles is developed using the empirical distribution function in combination with bootstrapping. The methods are applied to a European flood model, where the primary stochastic component relates to the frequency and severity of flood events, and three secondary components relate to defence levels, exposure locations and building vulnerability. As expected, it is found that the uncertainty due to the secondary components increases as the size of the portfolio of exposures decreases, and is higher for industrial and commercial business, compared with residential for all statistics of interest. In addition, interesting insights are gained as to the impact of flood defences on convergence.     

Estimating the necessary duration of observation period in studying winter river runoff

A procedure for determining the minimal representative observation period at hydrological gages is proposed as required for studying the regularities in river runoff formation in rivers in the drainage basin of the Votkinsk Reservoir. Data of hydrological gages with long observational series were used as an example to show, by the division of these series into intervals and analysis of the obtained deviations from long-term mean values, that such minimal period can be taken to be 40 years long.     

Discharge of biogenic substances with river runoff in Selenga basin

Averaged many-year measurement data on the concentrations of mineral forms of biogenic elements are analyzed, and their total concentrations in the rivers of Selenga, Chikoi, Khilok, Uda, Dzhida, and Temnik are evaluated. The monthly variations of the concentrations of major biogenic substances are characterized, and their ratios within a year are determined. Characteristics of river water runoff and biogenic substance concentrations are used to evaluate their within-year discharge by rivers. Characteristic variations in the ratios between the total and mineral forms of biogenic elements discharged by rivers have been revealed. It is established that the share of mineral components in the total input into the Selenga delta N_tot and P_tot are 82 and 22%, respectively.     

Estimation of monthly runoff from small catchments in India

Abstract

Data from 31 non-snowfed catchments in India having catchment areas less than 1515 km² have been analysed to develop a simple method for the estimation of monthly runoff for the monsoon months of June to October. One of the parameters of this method was found to vary with the catchment area, the percentage of forest cover in the catchment and the monthly average temperature. The value of another parameter of the proposed method was found to be constant during any one month in a hydrologically homogeneous region. The method proposed herein is useful for estimating the monthly runoff during the monsoon period from catchments having scarce data.     

Year-to-year and many-year river runoff variations in Baikal drainage basin

New approaches, methods, and formulas, proposed by the author, are used to study many-year and year-to-year variations of the annual, maximal, and minimal runoff of rivers in Baikal Lake drainage basin. The stationary character of most changes in the annual and maximal runoff (including major Baikal tributaries at the gages nearest to the lake) is demonstrated and the percentage of transient changes in the minimal runoff is shown to be close to the mean world characteristics. Some effects found in Baikal Basin have been generally recorded only in the data of runoff observations in much larger basins or globally: “the law of the power of minus 0.5” for the dependence of the coefficient of variation and the correlation between neighboring years on the mean runoff depth, a fixed structure of the orders of stochastic (autoregression models), the effect of bifurcation of the models of maximal and minimal runoff at the passage from drier to wetter watersheds.     

On some sources of uncertainty in the Lyman-α ionization-rate calculation

Summary The effect of the uncertainty and variability in the absorption cross-section, ionization cross-section and the Lyman- line shape on the Lyman- ionization-rate calculation is studied. The effect of the variability of the Lyman- line shape seems to be negligible. The effect of the ionization cross-section is rather small. The greatest and very significant effect, particularly at lower altitudes, is due to the discrepancy in the absorption cross-section data. Some ionospheric and atmospheric consequences are briefly discussed.     

Application of Generalized Likelihood Uncertainty Estimation (GLUE) at different temporal scales to reduce the uncertainty level in modelled river flows

ABSTRACT

In this study, the distributed catchment-scale model, DiCaSM, was applied on five catchments across the UK. Given its importance, river flow was selected to study the uncertainty in streamflow prediction using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology at different timescales (daily, monthly, seasonal and annual). The uncertainty analysis showed that the observed river flows were within the predicted bounds/envelope of 5% and 95% percentiles. These predicted river flow bounds contained most of the observed river flows, as expressed by the high containment ratio, CR. In addition to CR, other uncertainty indices – bandwidth B, relative bandwidth RB, degrees of asymmetry S and T, deviation amplitude D, relative deviation amplitude RD and the R factor – also indicated that the predicted river flows have acceptable uncertainty levels. The results show lower uncertainty in predicted river flows when increasing the timescale from daily to monthly to seasonal, with the lowest uncertainty associated with annual flows.     

Climatic and geographic patterns of river runoff formation in Northern Eurasia

Siberian rivers are of global importance as they impact on the freshwater budget of the Arctic Ocean, which affects the Thermo-Haline circulation in the North Atlantic Ocean. Siberian rivers, in particular the tributaries to the larger rivers, are under-represented in the international river-regime databases. The runoff of three Russian rivers in the Central Siberian taiga (Kureyka, Karabula and Erba) is modelled to analyse the relative influence of climate. In addition three rivers (Rhine, Maas and Odra) in Western Europe are similarly assessed as a control. The results show that the role of precipitation and autocorrelation as factors in the formation of river runoff is stronger under oceanic climate conditions, increasing from the central regions of Northern Eurasia towards the Arctic Ocean in the North and the Atlantic in the West. At the same time the influence of summer temperatures is weakened. The formation of Northern Eurasian river runoff appears to be influenced by periodically thawing top horizons of permafrost soil. Time served as an indicator for land use change after inclusion of meteorological data in the models. Maas and Erba showed a significant influence of the time factor. For the Erba the onset of agricultural land use in the catchment coincides with a drop in runoff. A similar causal relationship is suggested for the Maas. Land use can change the formation of runoff, which in turn can be used as an environmental indicator for sustainable land use.     

Assessment of uncertainty sources in water quality modeling in the Niagara River

This paper presents a framework to quantify the overall variability of the model estimations of Total Polychlorinated Biphenyls (Total PCBs) concentrations in the Niagara River on the basis of the uncertainty of few model parameters and the natural variability embedded in some of the model input variables. The results of the uncertainty analysis are used to understand the importance of stochastic model components and their effect on the overall reliability of the model output and to evaluate multiple sources of uncertainty that might need to be further studied. The uncertainty analysis is performed using a newly developed point estimate method, the Modified Rosenblueth method. The water quality along the Niagara River is simulated by coupling two numerical models the Environmental Fluid Dynamic Code (EFDC) – for the hydrodynamic portion of the study and the Water Quality Analysis and Simulation Program (WASP) – for the fate and transport of contaminants. For the monitoring period from May 1995 to March 1997, the inflow Total PCBs concentration from Lake Erie is the stochastic component that most influences the variability of the modeling results for the simulated concentrations at the exit of the Niagara River. Other significant stochastic components in order are as follows: the suspended sediments concentration, the point source loadings and to a minor degree the atmospheric deposition, the flow and the non-point source loadings. Model results that include estimates of uncertainty provide more comprehensive information about the variability of contaminant concentrations, such as confidence intervals, and, in general offer a better approach to compare model results with measured data.     

Spatial uncertainty in bias corrected climate change projections and hydrogeological impacts

The question of which climate model bias correction methods and spatial scales for correction are optimal for both projecting future hydrological changes as well as removing initial model bias has so far received little attention. For 11 climate models (CMs), or GCM/RCM – Global/Regional Climate Model pairing, this paper analyses the relationship between complexity and robustness of three distribution‐based scaling (DBS) bias correction methods applied to daily precipitation at various spatial scales. Hydrological simulations are forced by CM inputs to assess the spatial uncertainty of groundwater head and stream discharge given the various DBS methods. A unique metric is devised, which allows for comparison of spatial variability in climate model bias and projected change in precipitation. It is found that the spatial variability in climate model bias is larger than in the climate change signals. The magnitude of spatial bias seen in precipitation inputs does not necessarily correspond to the magnitude of biases seen in hydrological outputs. Variables that integrate basin responses over time and space are more sensitive to mean spatial biases and less so on extremes. Hydrological simulations forced by the least parameterized DBS approach show the highest error in mean and maximum groundwater heads; however, the most highly parameterised DBS approach shows less robustness in future periods compared with the reference period it was trained in. For hydrological impacts studies, choice of bias correction method should depend on the spatial scale at which hydrological impacts variables are required and whether CM initial bias is spatially uniform or spatially varying. Copyright © 2015 John Wiley & Sons, Ltd.     

Land management impacts on runoff sources in small Amazon watersheds

Forest clearing and conversion to cattle pasture in the lowland Amazon region has been linked to soil compaction and increased soil water storage, which combine to diminish soil infiltration, enhance quick lateral flows and increase the stream flow response to precipitation. Quantifying the importance of quick surficial flow in response to this land use change requires identification of water sources within catchments that contribute to stream flow. Using an end member mixing analysis approach, potential contributing sources of stream flow were evaluated during an entire rainy season in a forest and a pasture watershed drained by ephemeral‐to‐intermittent streams in the south‐western Amazon. Water yield was 17% of precipitation in the pasture and 0·8% of precipitation in the forest. During the early rainy season, throughfall, groundwater, and soil water contributed 79%, 18%, and 3%, respectively, to total forest stream flow. Over the entire rainy season, throughfall, groundwater, and shallow soil water provided 57%, 24%, and 19%, respectively, of stream flow. In the pasture watershed, overland flow dominated stream flow both in the early (67%) and late (57%) rainy season, with a mean contribution of 60% overland flow, 35% groundwater, and 5% soil water. The uncertainty associated with those estimates was studied using a Monte Carlo approach. In addition to large changes in total surface flow, marked differences were found in the proportions of total stream flow in the second half of the rainy season between the forest and pasture watershed. These results suggest that (1) there is great potential for alteration of the hydrological budgets of larger watersheds as the proportion of deforested land in the Amazon increases, and (2) as more rainfall is diverted into fast flowpaths to streams in established pastures, the potential to deliver water with higher solute concentrations generated by erosion or by bypassing sites of solute removal increases. Copyright © 2007 John Wiley & Sons, Ltd.     

Impact of changes in the conditions of European Russia forests on annual river runoff

Based on the methods of O.I. Krestovskii and recent information on the forestry of European Russia, the article offers the assessment of the impact of transformations in the structure of forests in the recent decades on the river runoff and evaporation. The accompanying changes in the runoff are shown to be relatively insignificant; however, in the XXI century they may become more significant and manifest themselves not only at the local but also at the regional level.