Academic literature on the topic 'Hydrometric approaches'

Abstract The issues of forecasting dangerous hydrological phenomena in water bodies in the presence of hydrometrically observed data are considered. The analytical distribution functions of annual excess probabilities are applied - sufficiency curves. The features of calculating the empirical annual probability of exceeding hydrological characteristics, variation coefficients and asymmetries for distribution, the scattering of estimates and other distribution parameters are considered. In the case of heterogeneity of the initial data of hydrometric observations, when the series under consideration consists of heterogeneous elements of the hydrological regime, empirical and analytical distribution curves are set separately for each homogeneous totality. Based on the considered data, a system for monitoring and forecasting emergencies of a hydrological nature at water bodies is being constructed.

Trying to model the rainfall-runoff process is a complex activity as it is influenced by a number of implicit and explicit factors — for example, precipitation distribution, evaporation, transpiration, abstraction, watershed topography, and soil types. However, this kind of forecasting is particularly important as it is used to predict serious flooding, estimate erosion and identify problems associated with low flow. Inductive learning approaches (e.g. decision trees and artificial neural networks) are particularly well suited to problems of this nature as they can often interpret underlying factors (such as seasonal variations) which cannot be modelled by other techniques. In addition, these approaches can easily be trained on the explicit factors (e.g. rainfall) and the inexplicit factors (e.g. abstraction) that affect river flow. Inductive learning approaches can also be extended to account for new factors that emerge over a period of time. This paper evaluates the application of decision trees and two artificial neural network models (the multilayer perceptron and the radial basis function network) to river flow forecasting in two flood prone UK catchments using real hydrometric data. Comparisons are made between the performance of these approaches and conventional flood forecasting systems.

This paper presents a review of water yields for six reservoir schemes within Selangor and Kuala Lumpur. The study was carried out using up-to-date hydrometric database up to 2009. Three approaches were used for yield calculations; namely, (1) Drought Sequence, (2) Longterm records, and (3) Storage-yield-reliability model techniques/methodologies. It was found that the gross yields of various reservoir schemes were agreeable with one another, at least within the margin of difference which is about 5%.

Abstract. Current techniques to disentangle the total evaporative flux from the continental surface into a contribution evaporated from soils and canopy, or transpired by plants are under debate. Many isotope-based studies show that transpiration contributes generally more than 70% to the total moisture fluxes, while other isotope-independent techniques lead to considerably smaller transpiration fractions. This paper provides a perspective on isotope-based vs. non isotope-based partitioning studies. Some partitioning results from isotope-based methods, hydrometric measurements, and modeling are presented for comparison. Moreover, the methodological aspects of the analysis of partitioning are discussed including their limitations, and explanations of possible discrepancies between the methods are briefly discussed. We conclude that every method has its own uncertainties and these may lead to a high bias in the results, e.g. instruments inaccuracy and error, some assumptions used in analyses, parameters calibration. A number of comparison studies using isotope-based methods and hydrometric measurements in the same plants and climatic conditions are consistent within the errors, however, models tend to produce lower transpiration fractions. The relatively low transpiration fractions in current state of the art land surface models calls for a reassessment of the skill of the underlying model parameterizations. The scarcity of global evaporation data makes calibration and validation of global isotope-independent and isotope-based results difficult. However, isotope enabled land-surface and global climate modeling studies allow the evaluation of the parameterization of land surface models by comparing the computed water isotopologue signals in the atmosphere with the available remote sensing and flux-based data sets. Future studies that allow this evaluation could provide a better understanding of the hydrological cycle in vegetated regions.

Abstract. Determining the soil hydraulic properties is a prerequisite to physically model transient water flow and solute transport in the vadose zone. Estimating these properties by inverse modelling techniques has become more common within the last two decades. While these inverse approaches usually fit simulations to hydrometric data, we expanded the methodology by using independent information about the stable isotope composition of the soil pore water depth profile as a single or additional optimization target. To demonstrate the potential and limits of this approach, we compared the results of three inverse modelling strategies where the fitting targets were (a) pore water isotope concentrations, (b) a combination of pore water isotope concentrations and soil moisture time series, and (c) a two-step approach using first soil moisture data to determine water flow parameters and then the pore water stable isotope concentrations to estimate the solute transport parameters. The analyses were conducted at three study sites with different soil properties and vegetation. The transient unsaturated water flow was simulated by numerically solving the Richards equation with the finite-element code of Hydrus-1D. The transport of deuterium was simulated with the advection-dispersion equation, and the Hydrus code was modified to allow for deuterium loss during evaporation. The Mualem–van Genuchten and the longitudinal dispersivity parameters were determined for two major soil horizons at each site. The results show that approach (a) using only the pore water isotope content cannot substitute hydrometric information to derive parameter sets that reflect the observed soil moisture dynamics, but gives comparable results when the parameter space is constrained by pedotransfer functions. Approaches (b) and (c) using both, the isotope profiles and the soil moisture time series resulted in satisfying model performances and good parameter identifiability. However, approach (b) has the advantage that it considers the isotope data not only for the solute transport parameters, but also for water flow, and thus increases parameter realism. Approaches (b) and (c) both outcompeted simulations run with parameters derived from pedotransfer functions, which did not result in satisfying model efficiencies. Overall, parameters based on this new approach that includes isotope data lead to similar model performances regarding the water balance and soil moisture dynamics and better parameter identifiability than the conventional inverse model approaches limited to hydrometric fitting targets. If only data from isotope profiles in combination with textural information is available, the results are still satisfactory. This method has the additional advantage that it will not only allow us to estimate water balance and response times, but also site specific time variant transit times or solute breakthrough within the soil profile.

Abstract. Current techniques to disentangle the evaporative fluxes from the continental surface into a contribution evaporated from soils and canopy, or transpired by plants, are under debate. Many isotope-based studies show that transpiration contributes generally more than 70% to the total evaporation, while other isotope-independent techniques lead to considerably smaller transpiration fractions. This paper provides a perspective on isotope-based versus non-isotope-based partitioning studies. Some partitioning results from isotope-based methods, hydrometric measurements, and modeling are presented for comparison. Moreover, the methodological aspects of the partitioning analysis are considered, including their limitations, and explanations of possible discrepancies between the methods are discussed. We suggest sources of systematic error that may lead to biases in the results, e.g., instruments inaccuracy, assumptions used in analyses, and calibration parameters. A number of comparison studies using isotope-based methods and hydrometric measurements in the same plants and climatic conditions are consistent within the errors; however, models tend to produce lower transpiration fractions. The relatively low transpiration fraction in current state-of-the-art land-surface models calls for a reassessment of the skill of the underlying model parameterizations. The scarcity of global evaporation data makes calibration and validation of global isotope-independent and isotope-based results difficult. However, isotope-enabled land-surface and global climate modeling studies allow for the evaluation of the parameterization of land-surface models by comparing the computed water isotopologue signals in the atmosphere with the available remote sensing and flux-based data sets. Future studies that allow for this evaluation could provide a better understanding of the hydrological cycle in vegetated regions.

Abstract. Determining the soil hydraulic properties is a prerequisite to physically model transient water flow and solute transport in the vadose zone. Estimating these properties by inverse modelling techniques has become more common within the last 2 decades. While these inverse approaches usually fit simulations to hydrometric data, we expanded the methodology by using independent information about the stable isotope composition of the soil pore water depth profile as a single or additional optimization target. To demonstrate the potential and limits of this approach, we compared the results of three inverse modelling strategies where the fitting targets were (a) pore water isotope concentrations, (b) a combination of pore water isotope concentrations and soil moisture time series, and (c) a two-step approach using first soil moisture data to determine water flow parameters and then the pore water stable isotope concentrations to estimate the solute transport parameters. The analyses were conducted at three study sites with different soil properties and vegetation. The transient unsaturated water flow was simulated by solving the Richards equation numerically with the finite-element code of HYDRUS-1D. The transport of deuterium was simulated with the advection-dispersion equation, and a modified version of HYDRUS was used, allowing deuterium loss during evaporation. The Mualem–van Genuchten and the longitudinal dispersivity parameters were determined for two major soil horizons at each site. The results show that approach (a), using only the pore water isotope content, cannot substitute hydrometric information to derive parameter sets that reflect the observed soil moisture dynamics but gives comparable results when the parameter space is constrained by pedotransfer functions. Approaches (b) and (c), using both the isotope profiles and the soil moisture time series, resulted in good simulation results with regard to the Kling–Gupta efficiency and good parameter identifiability. However, approach (b) has the advantage that it considers the isotope data not only for the solute transport parameters but also for water flow and root water uptake, and thus increases parameter realism. Approaches (b) and (c) both outcompeted simulations run with parameters derived from pedotransfer functions, which did not result in an acceptable representation of the soil moisture dynamics and pore water stable isotope composition. Overall, parameters based on this new approach that includes isotope data lead to similar model performances regarding the water balance and soil moisture dynamics and better parameter identifiability than the conventional inverse model approaches limited to hydrometric fitting targets. If only data from isotope profiles in combination with textural information is available, the results are still satisfactory. This method has the additional advantage that it will not only allow us to estimate water balance and response times but also site-specific time variant transit times or solute breakthrough within the soil profile.

Abstract Streamflow forecasting, as one of the most important issues in hydrological studies, plays a vital role in several aspects of water resources management such as reservoir operation, water allocation, and flood forecasting. In this study, wavelet-gene expression programming (WGEP) and wavelet-M5 prime (WM5P) techniques, as two robust artificial intelligence (AI) models, were applied for forecasting the monthly streamflow in Khoshkroud and Polroud Rivers located in two basins with the same names. Results of hybrid AI techniques were compared with those achieved by two stand-alone models of GEP and M5P. Seven combinations of hydrological (H) and meteorological (M) variables were considered to investigate the effect of climatic variables on the performance of the proposed techniques. Moreover, the performance of both stand-alone and hybrid models were evaluated by statistical criteria of correlation of coefficient, root-mean-square error, index of agreement, the Nash–Sutcliffe model efficiency coefficient, and relative improvement. The statistical results revealed that there is a dependency between ‘the M5P and GEP performance’ and ‘the geometric properties of basins (e.g., area, shape, slope, and river network density)’. It was found that a preprocessed technique could increase the performance of M5P and GEP models. Compared to the stand-alone techniques, the hybrid AI models resulted in higher performance. For both basins, the performance of the WM5P model was higher than the WGEP model, especially for extreme events. Overall, the results demonstrated that the proposed hybrid AI approaches are reliable tools for forecasting the monthly streamflow, while the meteorological and hydrometric variables are taken into account.

Abstract Streamflow forecasting, as one of the most important issues in hydrological studies, plays a vital role in several aspects of water resources management such as reservoir operation, water allocation, and flood forecasting. In this study, wavelet-gene expression programming (WGEP) and wavelet-M5 prime (WM5P) techniques, as two robust artificial intelligence (AI) models, were applied for forecasting the monthly streamflow in Khoshkroud and Polroud Rivers located in two basins with the same names. Results of hybrid AI techniques were compared with those achieved by two stand-alone models of GEP and M5P. Seven combinations of hydrological (H) and meteorological (M) variables were considered to investigate the effect of climatic variables on the performance of the proposed techniques. Moreover, the performance of both stand-alone and hybrid models were evaluated by statistical criteria of correlation of coefficient, root-mean-square error, index of agreement, the Nash–Sutcliffe model efficiency coefficient, and relative improvement. The statistical results revealed that there is a dependency between ‘the M5P and GEP performance’ and ‘the geometric properties of basins (e.g., area, shape, slope, and river network density)’. It was found that a preprocessed technique could increase the performance of M5P and GEP models. Compared to the stand-alone techniques, the hybrid AI models resulted in higher performance. For both basins, the performance of the WM5P model was higher than the WGEP model, especially for extreme events. Overall, the results demonstrated that the proposed hybrid AI approaches are reliable tools for forecasting the monthly streamflow, while the meteorological and hydrometric variables are taken into account.

The paper presents the spatial distribution of the mean annual river runoff in the Ukrainian Carpathians in the form of a map. The methodological approaches concerning the river runoff mapping and the technological stages of map creation by applying the geographic information system (GIS) analytical functions are considered. The accuracy assessment of the calculation of the mean annual river runoff water based on the data from the hydrometric stations for the whole observation period was performed. The mapping reliability of the mean annual runoff and their territorial variability over the main basins in the Ukrainian Carpathians are analysed.

This thesis presents studies of the heterogeneous nature of groundwater-surface water (GW-SW) interactions at the hillslope and catchment scale in the 3.2km2 Bruntland Burn, UK. GW fluctuations were measured within three contrasting hydropedological units. Synoptic hydrogeochemical surveys were carried out (major ions, stable isotopes) to capture the increased influence of GW to the stream during a 10year return period drought. The catchment was shown to have highly dynamic GW stores, with each landscape unit translating into different rainfall-runoff processes. Soil characteristics were shown to be the strongest predictors for variability in GW dynamics. Each soil type was characterised by a unique storage-discharge relationship and threshold response with a certain GW level above which lateral flow dominated. On the lower hillslope, predominating lateral flow and little recharge to depth is supported by hydrologically responsive soils. Connectivity between the steeper slopes and the valley bottom, however, needed persistent wet periods to overcome storage thresholds. Here, vertical flow paths recharging deeper GW dominated, with GW levels falling below the soil layer into the underlying drift. It was found that relatively well mixed, near-surface sources of stream flow predominated in wetter conditions, whilst baseflows are variable and reflect a diverse range of GW stores. Geophysics (ERT) and GW level measurements were integrated into MODFLOW-NWT to simulate GW-SW interactions along a representative 2D-hillslope transect. Although only a preliminary model, it was shown that shallow pathways have much shorter residence times, thus maintaining high water tables in the riparian peatlands, than deeper flow paths discharging through the drift and directly into the stream. Largest sources of GW are located within the drift, resulting in complex spatial patterns of runoff generation. This work illustrated the utility of a basic model to predict GW flow paths, highlighting how water and solutes are stored and released in montane headwater catchments.

The interaction between groundwater and surface water systems is a key component of the hydrological cycle and an understanding of their connectivity is fundamental for sustainable water resource management. Water is a vehicle for mobilising dissolved constituents, including nutrients, between surface and subsurface waters and between terrestrial and marine systems. Therefore, knowledge of surface-subsurface linkages is critical not only for water quantity allocation, but also for water quality and its implications for ecosystem health. In particular, ascertaining the significance of groundwater fluxes for river nitrogen budgets is an important motivation for characterising river-groundwater connectivity. This overarching theme is developed through the course of the thesis. The marked seasonality of tropical river systems provides a unique opportunity to investigate groundwater contributions to surface waters, especially when there are minimal overland flows. The Herbert River in northeast Queensland represents a useful case study in the Australian tropics for assessing the potential for transport of agricultural contaminants, such as dissolved forms of nitrogen, between surface and subsurface waters, and between terrestrial and marine systems, including the ecologically significant Great Barrier Reef World Heritage Area. Whilst the lower Herbert River catchment, dominated by sugarcane production, is the focus for this thesis, the research methodology and policy implications for nutrient monitoring and management are applicable to other tropical catchments. An extensive water quality sampling program was instigated to collect river and groundwater samples during low flow conditions, for analysis of a range of conservative and nonconservative environmental tracers including major ions, stable isotopes of water, radon, and dissolved inorganic forms of nitrogen. Grab samples were collected during months representing the beginning and end of the dry season to compare connectivity relationships at contrasting stages of the stream hydrograph. Hydrochemical data at the end of the dry season is particularly useful for isolating the groundwater signal in the river and its tributaries. Existing physical and chemical datasets are also an important source of high temporal resolution information to supplement the more detailed water quality data collected specifically for this investigation. An understanding of the dynamics of water movement between river and aquifer storages is critical for assessing the mobility of dissolved nitrogen between them. A combination of hydrogeological, hydrometric, hydrological and hydrochemical tools are applied to characterise the interaction between the alluvial aquifers and the lower Herbert River at a catchment scale. Specifically, the potential for hydraulic connection and the direction of flux between the aquifer system and the river are evaluated through qualitative hydrometric approaches, including: depth relationships of the river channel with that of the underlying alluvial sediments; historical groundwater elevation-stream stage relationships; and groundwater flow patterns around the river. Hydrological techniques such as stream hydrograph and flow duration curve analysis are utilised to assess the temporal characteristics of flow in the river; the groundwater flux to the river is also quantified by hydrograph separation. Physical understanding of river-aquifer linkages is verified and enriched through analysis of surface water chemistry data, in conjunction with the conceptual hydrogeological model developed from physical and chemical assessment of the aquifers. The significance of groundwater as a vector for nitrogen is then evaluated in light of a conceptual process understanding of the river-aquifer system. This provides a platform for undertaking future catchment-scale nutrient budget studies based on detailed investigations of nitrogen sources and transformations. The research approach used in this thesis highlights the value of combining analytical techniques, not provided by any one method, to inform and verify different aspects of a complex water resource problem involving both surface and groundwater systems. The application of multiple environmental tracers, at varied spatial and temporal resolution, is particularly instructive for distinguishing between the key processes that influence the chemistry of the river in space and time. Furthermore, the spectrum of tracer techniques provides both qualitative and quantitative information regarding the flux of groundwater along the length of the lower Herbert River. Whilst the absolute groundwater fluxes determined have a degree of uncertainty, mass balances of radon and selected solutes highlight the value of quantitative estimates in combination with qualitative trends to characterise river-aquifer relationships. The analyses demonstrate that discharge of groundwater from the alluvial aquifers is a dominant influence on both the flow and chemistry of the lower Herbert River in the dry season. In particular, groundwater is a key vector for the delivery of nitrate to the river during low flow conditions. This provides a new perspective for monitoring and management of nutrients in tropical rivers where there is good connectivity with the underlying groundwater system. Key recommendations arising from this research include: (1) water quality sampling should be undertaken at recognised periods on the stream/groundwater hydrograph, with an understanding of temporal and spatial river-aquifer connectivity relationships; (2) surface and subsurface sources of water and dissolved nutrients must be considered, including identification of nutrient hotpots in both surface water and groundwater systems; (3) sampling locations should capture the longitudinal variation in river nutrient concentrations, not simply end-of-river monitoring; (4) appropriate water quality guideline values must be set to account for seasonal changes in both the sources and forms of nutrients transported to surface waters.

AbstractThe aim of this work is to study the temporal evolution of the rainfall-runoff relations of four basins in northwestern Algeria: the Tafna Maritime, Isser Sikkak, downstream Mouilah and Upper Tafna basins. The adopted approach consists of analyzing hydroclimatic variables using statistical methods and testing the nonstationarity of the rainfall-runoff relation by the cross-simulation method using the GR2M model. The results of the different statistical methods applied to the series of rainfall and hydrometric variables show a decrease due to a break in stationarity detected since the mid-1970s and the beginning of the 1980s. The annual rainfall deficits reached average values of 34.6% during the period of 1941–2006 and 29.1% during the period of 1970–2010. The average annual wadi flows showed average deficits of 61.1% between 1912 and 2000 and 53.1% between 1973 and 2009. The GR2M conceptual model simulated the observed hydrographs in an acceptable manner by providing calculated runoff values in the calibration and validation periods greater or less than the observed runoff values. The application of the cross-simulation method highlighted the nonstationarity of the rainfall-runoff relations in three of the four studied basins, indicating downward trends of monthly runoff.

The study is focused on the assessment of basic flood features using Cavis software for raw data, recorded for a period of 40 years, between 1979 and 2019, at Satu Mare hydrometric station on the Someș River. Using the long term recorded data for the two of the largest floods in each year, we have made a statistical analysis on certain features associated with temporal frequency (monthly and seasonal occurrence), total duration, multi-daily vulnerability, maximum discharge values (in respect with the defense levels at the hydrometric station) and the total volumes of water translated through the river bed during those major flooding events.

Dams play a vital role in supplying fresh water to many cities all over the world. With increasing pressure on and demand for natural resources, water supply remains a scarce resource worldwide. During times of uncertainty, predicting the future availability of water supply by considering various hydrometric and anthropogenic variables will provide a framework for future scenario forecasting and a model-based approach to sustainable water management. To this end, this project proposes a multivariate time-series analysis and forecasting model to both analyse and forecast daily water-level fluctuations in three water-supply dams: Upper Nihotupu, Waitākere and Mangatangi, located in the Tāmaki Makaurau Auckland and Waikato regions of Aotearoa New Zealand.

Drought can be defined in meteorological terms or in relative terms with respect to hydrology and ecosystems. Meteorological drought is not a necessary or a sufficient condition for fire, because fires burn during conditions of normal seasonal aridity. Drought occurs without wildfires in the absence of ignitions. However, when drought occurs, both live and dead fuels can dry out and become more flammable. Hydrologic drought as natural event is the result of long-lasting rainfall in the catchment area leading to the gradual depletion of water resources in the river network and the occurrence of a drought. Typically, hydrological drought is recorded as a river runoff below acceptable critical value. The authors explore the relationship between hydrological drought and forest fires. They present projections of fire-related drought indicators: the hydrologic indicator 7Q10 (the lowest 7-day average flow that occurs on average once every 10 years). The implementation of the hydrological drought as an approach for fire risk assessment has just started in Bulgaria. For this purpose, the assessment of the feasibility of using the hydrological 7Q10 drought index as a fire hazard indicator in real time is based on archive information on the variation of hydrological characteristics in the river network before and during an actual fire in an accepted pilot catchment. The Hydrologic Index 7Q10 for the pilot catchment of the Struma River was determined according to the rules for the last 15 years (2003-2017) using the daily water flows from all hydrometric stations The results of the presented study confirm the possibility of using the hydrological 7Q10 drought index to assess the risk of real-time fires by information on runoff from operational hydrological stations. One of the largest fires in the Struma River in 2017 occurred in an area identified as a fire on a highly hazard area according to the hydrological drought index 7Q10.