Statistical methods for river runoff prediction

Methods used to analyze one type of nonstationary stochastic processes?the periodically correlated process?are considered. Two methods of one-step-forward prediction of periodically correlated time series are examined. One-step-forward predictions made in accordance with an autoregression model and a model of an artificial neural network with one latent neuron layer and with an adaptation mechanism of network parameters in a moving time window were compared in terms of efficiency. The comparison showed that, in the case of prediction for one time step for time series of mean monthly water discharge, the simpler autoregression model is more efficient.

Tide And River Runoff Interactions In The Cochin Estuary

Hydrodynamic characteristics of an estuary resulting from interaction of tide and river runoff are important since problems regarding flood, salinity intrusion, water quality, ecosystem and sedimentation are ubiquitous. The present study focuses on such hydrodynamic aspects in the Cochin estuary. Most of the estuaries that come under the influence of Indian Summer Monsoon and for which the salinity is never in a steady state at any time of the year are generally shallow and convergent, i.e. the width decreases rapidly from mouth to head. In contrast, Cochin estuary is wider towards the upstream and has no typical river mouth, where the rivers are joining the estuary along the length of its channel .Adding to the complexity it has dual inlets and the tidal range is 1 m which is lower than other Indian estuaries along west coast. These typical physical features lead to its unique hydrodynamic characteristics. Therefore the thesis objectives are: I) to study the influence of river runoff on tidal propagation using observations and a numerical model ii) to study stratification and property distributions in Cochin estuary iii) to understand salinity distributions and flushing characteristics iv) to understand the influence of saltwater barrage on tides and salinity v) To evaluate several classification schemes for the estuary

Simulating current global river runoff with a global hydrological model: model revisions, validation, and sensitivity analysis

Global hydrological models (GHMs) model the land surface hydrologic dynamics of continental-scale river basins. Here we describe one such GHM, the Macro-scale - Probability-Distributed Moisture model.09 (Mac-PDM.09). The model has undergone a number of revisions since it was last applied in the hydrological literature. This paper serves to provide a detailed description of the latest version of the model. The main revisions include the following: (1) the ability for the model to be run for n repetitions, which provides more robust estimates of extreme hydrological behaviour, (2) the ability of the model to use a gridded field of coefficient of variation (CV) of daily rainfall for the stochastic disaggregation of monthly precipitation to daily precipitation, and (3) the model can now be forced with daily input climate data as well as monthly input climate data. We demonstrate the effects that each of these three revisions has on simulated runoff relative to before the revisions were applied. Importantly, we show that when Mac-PDM.09 is forced with monthly input data, it results in a negative runoff bias relative to when daily forcings are applied, for regions of the globe where the day-to-day variability in relative humidity is high. The runoff bias can be up to - 80% for a small selection of catchments but the absolute magnitude of the bias may be small. As such, we recommend future applications of Mac-PDM.09 that use monthly climate forcings acknowledge the bias as a limitation of the model. The performance of Mac-PDM.09 is evaluated by validating simulated runoff against observed runoff for 50 catchments. We also present a sensitivity analysis that demonstrates that simulated runoff is considerably more sensitive to method of PE calculation than to perturbations in soil moisture and field capacity parameters.

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty. We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues.

Climate and human forcing of Alpine river flow

River flow in Alpine environments is likely to be highly sensitive to climate change because of the effects of warming upon snow and ice, and hence the intra-annual distribution of river runoff. It is also likely to be influenced strongly by human impacts both upon hydrology (e.g. flow abstraction) and river regulation. This paper compares the river flow and sediment flux of two Alpine drainage basins over the last 5 to 7 decades, one that is largely unimpacted by human activities, one strongly impacted by flow abstraction for hydroelectricity. The analysis shows that both river flow and sediment transport capacity are strongly dependent upon the effects of temperature and precipitation availability upon snow accumulation. As the latter tends to increase annual maximum flows, and given the non-linear form of most sediment transport laws, current warming trends may lead to increased sedimentation in Alpine rivers. However, extension to a system impacted upon by flow abstraction reveals the dominant effect that human activity can have upon river sedimentation but also how human response to sediment management has co-evolved with climate forcing to make disentangling the two very difficult.

Nutrient Mobility in Chalakudy River,Typified With Riparian Buffer Zone and Its Adjoining Estuary:Spatiotemporal Manifestation

This study was aimed at to characterize the spatio-temporal trends in the distributional characteristics of various species of nitrogen and phosphorus as well as to elucidate the factors and processes aflecting these nutrients in the dissolved, particulate and sedimentary phases of a river estuarine system. The main area of study is Chalakudy river in Kerala, which is a fresh water system originating from Anamalai hills and ending at Arabian Sea. Its basin is between I00 05 ’ to I00 35’ North latitude and 76” 15 ’ to 760 55’ East longitude. Being a riparian bufler zone, the dynamics of nutrient mobility tend to be more complex and variable in this river-estuarine system.The diflerent species of nitrogen estimated from the filtrate were nitrite-N, nitrateN, ammonia-N, urea-N, total nitrogen and residual nitrogen. The diflerent forms of phosphorus estimated from the filtrate were phosphate-P, total-P and residualP. Pre weighed sediments as well as particulate matter were analysed for quantijying nitrite-N, nitrate-N, ammonia-N and urea-N. Total nitrogen was estimated after digestion with potassium persulfate. Fractionation of phosphorus in sediment/particulate matter was performed by applying sequential extraction procedure. The dijferent forms of phosphorus thus estimated were loosely bound (exchangeable) P, Fe/Al bound P, polyphosphates, Ca bound P and refractory P. Sedimental total P was also measured directly by applying digestion method.The analyses carried out in this bimonthly annual survey have revealed specific information on the latent factors influencing the water quality pattern ofthe river. There was dependence among the chemical components of the river sediment and suspended matter, reflecting the water quality. A period of profound environmental change occurred and changes in various species had been noted in association with seasonal variations in the waterway, especially following enhanced river runoff during the monsoon. The results also successfully represented the distribution trend of nutrients during the rainy as well as dry season. Thus, the information gathered in this work will also be beneficial for those interested or involved in river management, conservation, regulation and policy making in regional and national levels.

Global runoff routing with the hydrological component of the ECMWF NWP system

A global river routing scheme coupled to the ECMWF land surface model is implemented and tested within the framework of the Global Soil Wetness Project II, to evaluate the feasibility of modelling global river runoff at a daily time scale. The exercise is designed to provide benchmark river runoff predictions needed to verify the land surface model. Ten years of daily runoff produced by the HTESSEL land surface scheme is input into the TRIP2 river routing scheme in order to generate daily river runoff. These are then compared to river runoff observations from the Global Runoff Data Centre (GRDC) in order to evaluate the potential and the limitations. A notable source of inaccuracy is bias between observed and modelled discharges which is not primarily due to the modelling system but instead of to the forcing and quality of observations and seems uncorrelated to the river catchment size. A global sensitivity analysis and Generalised Likelihood Uncertainty Estimation (GLUE) uncertainty analysis are applied to the global routing model. The ground water delay parameter is identified as being the most sensitive calibration parameter. Significant uncertainties are found in results, and those due to parameterisation of the routing model are quantified. The difficulty involved in parameterising global river discharge models is discussed. Detailed river runoff simulations are shown for the river Danube, which match well observed river runoff in upstream river transects. Results show that although there are errors in runoff predictions, model results are encouraging and certainly indicative of useful runoff predictions, particularly for the purpose of verifying the land surface scheme hydrologicly. Potential of this modelling system on future applications such as river runoff forecasting and climate impact studies is highlighted. Copyright © 2009 Royal Meteorological Society.

Detection of solar dimming and brightening effects on Northern Hemisphere river flow

Anthropogenic aerosols in the atmosphere have the potential to affect regional-scale land hydrology through solar dimming. Increased aerosol loading may have reduced historical surface evaporation over some locations, but the magnitude and extent of this effect is uncertain. Any reduction in evaporation due to historical solar dimming may have resulted in an increase in river flow. Here we formally detect and quantify the historical effect of changing aerosol concentrations, via solar radiation, on observed river flow over the heavily industrialized, northern extra-tropics. We use a state-of-the-art estimate of twentieth century surface meteorology as input data for a detailed land surface model, and show that the simulations capture the observed strong inter-annual variability in runoff in response to climatic fluctuations. Using statistical techniques, we identify a detectable aerosol signal in the observed river flow both over the combined region, and over individual river basins in Europe and North America. We estimate that solar dimming due to rising aerosol concentrations in the atmosphere around 1980 led to an increase in river runoff by up to 25% in the most heavily polluted regions in Europe. We propose that, conversely, these regions may experience reduced freshwater availability in the future, as air quality improvements are set to lower aerosol loading and solar dimming.

Zoobenthos and oceanographical parameters in the Kemskaya Guba (Bay) - estuary of the Kem' River entering the Onega Bay, White Sea

Data on distribution of zoobenthos in the Kemskaya Guba (or Kemskaya Bay - the estuary of the Kem' River entering the Onega Bay of the White Sea), which is strongly influenced by river runoff, are presented. The number of species at sampling stations varied from 4 to 65. Density of communities and zoobenthos biomass varied from 342±68 to 4293±96 #/m**2 and from 0.418±0.081 to 1975.22±494.36 g/m**2, respectively. Shannon index values varied between 1.19 to 4.7 bit/ind. At the upper part of the estuary, detritivores dominated, while in the central part and at outlets sestonophages prevailed. Changes in quantitative parameters of the zoobenthos along gradient of water salinity were traced, and relations of these parameters with seven other environmental factors were revealed. It was found that species composition, biodiversity, and trophic structure of the zoobenthos significantly correlated with some of parameters mentioned above. Multiple regression analysis was used to assess combined effect of factors, and it revealed which of them played a determining role in Kemskaya Guba: for species composition - depth, water color, and total concentration of suspended matter; for number of species - contents of <0.01 mm grain size (pelite) fraction and organic carbon in bottom sediments. Biomass depended on water salinity, water chromaticity, and organic carbon contents in bottom sediments and suspended matter. Values of the Shannon index of diversity are determined by water color, and contents of organic carbon and pelite fraction in bottom sediments. Calculations of ecological stress values revealed two zones with unstable state of the zoobenthos.

E-RUN version 1.1: Observational gridded runoff estimates for Europe, link to data in NetCDF format (69 MB)

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950 - December 2015) on a 0.5° x 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

E-RUN version 1.0: Observational gridded runoff estimates for Europe, link to data in NetCDF format (68 MB)

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first collect an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 11) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950-December 2014) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

Feeding ecology and trophic relationships of fish species in the lower Guadiana River Estuary and Castro Marim e Vila Real de Santo Antonio Salt Marsh

In this study we analyze the feeding ecology and trophic relationships of some of the main fish species (Soleidae, Moronidae, Mullidae, Sparidae, Mugilidae, and Batrachoididae) of the lower Estuary of the Guadiana River and the Castro Marim e Vila Real de Santo Antonio Salt Marsh. We examined the stomachs of 1415 fish caught monthly between September 2000 and August 2001. Feeding indices and coefficients were determined and used along with the results of multivariate analysis to develop diagrams of trophic interactions (food webs). Results show that these species are largely opportunistic predators. The most important prey items are amphipods, gobies (Gobiidae), shrimps (Palaemon serratus and Crangon crangon), and polychaete worms. The lower Estuary and associated salt marshes are important nurseries and feeding grounds for the species studied. In this area, it is therefore important to monitor the effects of changes in river runoff, nutrient input, and temperature that result from construction of the Alqueva Dam upstream. (c) 2006 Elsevier Ltd. All rights reserved.