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Hydrological data are the foundation of hydrological research, as well as effective water management. Hydrological data are therefore of pivotal importance to any drought or low flow study. While there have been significant advances in hydrological data acquisition, analysis and dissemination in recent decades, it is still crucially important to ensure data are of suitable quality to support analysis and decision-making. In this chapter, key concepts in hydrological data are first reviewed, and then main types of hydrological data (river flow and groundwater level) are explored, giving due attention to how they are derived, including challenges and limitations. Key supporting datasets are also considered, such as hydrometeorological datasets (e.g., precipitation, evaporation, soil moisture) and spatial datasets available at different scales (local, regional and global) that provide important context for hydrological observations. Example datasets containing flow data are provided that cover different scales (international, regional and local). Local datasets also include groundwater and meteorological data.

Conventional practices of rating curve computation fall short in many aspects. They are data-intensive and are notoriously inaccurate in high-flow regimes as a result of extrapolation of low-flow curve fitting. By making use of a simple commercial UAV, a physically-based rating curve is computed that is substantiated by a detailed representation of the section's geometry. Discharge data is still required for calibration of the roughness coefficient and determination of the stage at zero flow. The physically-based rating curve improves the accuracy of the rating curve in the high flows and allows for an easy separation between flow regimes.

Conventional practices of rating curve computation fall short in many aspects. They are data-intensive and are notoriously inaccurate in high-flow regimes as a result of extrapolation of low-flow curve fitting. By making use of a simple commercial UAV, a physically-based rating curve is computed that is substantiated by a detailed representation of the section's geometry. Discharge data is still required for calibration of the roughness coefficient and determination of the stage at zero flow. The physically-based rating curve improves the accuracy of the rating curve in the high flows and allows for an easy separation between flow regimes.

A rating curve provides a functional relationship between water height (i.e. stage) and discharge at a specified cross-section in a river. Used in combination with a time series of stage, rating curves become one of the central components for generating continuous records of streamflow. Since developing and maintaining rating curves can be time consuming, hydraulic models have shown potential to reduce the effort required for developing rating curves. A central challenge with modeling procedures, however, is the acquisition of accurate stream channel and floodplain topography. From this perspective, this thesis focuses on the real-world application of close-range remote sensing techniques such as laser-based ranging technologies (i.e. Light detection and ranging or LiDAR) or acoustic based ranging technologies (i.e. acoustic Doppler current profiler or ADCP) to capture topographic information for hydraulic modeling applications across various spatial scales. First, a review of the current LiDAR literature was carried out to identify potential ways to take full advantage of these novel data and technologies in the future. This was followed by four interconnected studies whereby: (i) a low-cost custom laser scanning system was designed to capture grain size distributions for a small stream; (ii) synthetically thinned airborne laser scanning (ALS) data was applied in a physically-based hydraulic modelling framework to develop rating curves; (iii) low-resolution national-scale ALS was coupled with ADCP bathymetry to be used in conjunction with a hydraulic model to develop rating curves; and (iv) the impact of measurement uncertainties on generating rating curves with a hydraulic model were investigated. This thesis highlights the potential of close-range remote sensing techniques for capturing accurate stream channel topography and derive from these data, the necessary parameters required for hydraulic modeling applications., En avbördningskurva tillhandahåller ett funktionellt förhållande mellan vattendjup (dvs. vattenstånd) och flöde vid ett specifikt tvärsnitt i ett vattendrag. Avbördningskurvan blir en central komponent för generering av kontinuerliga tidsserier av vattenföring från tidsserier av vattenstånd. Eftersom det är tidskrävande att utveckla och underhålla avbördningskurvor erbjuder hydrauliska modeller attraktiva möjligheter att minska den insats som krävs för att utveckla avbördningskurvorna. En central utmaning för sådana modelleringsförfaranden är emellertid tillgången till noggrann topografidata av strömfåran och de omgivande stränderna. Den här avhandlingen fokuserar på tillämpningen av fjärranalystekniker för avståndsmätning på nära håll, såsom laserbaserade teknik (dvs. Light detection and ranging eller LiDAR) och akustisk baserat teknik (dvs. acoustic Doppler current profiler eller ADCP), för att fånga topografisk information för hydraulisk modellering av vattendrag i olika rumsliga skalor. Först presenteras en litteraturstudie av den nuvarande LiDAR-litteratur för att identifiera potentiella sätt att dra full nytta av dessa nya data och tekniker i framtiden. Detta följs av fyra sammanlänkade studier: (i) tillämpning av ett lågkostnads-laseravsökningssystem för att fånga kornstorleksfördelningar i ett litet vattendrag, (ii) syntetiskt förtunnad flygburen laserskanningsdata (ALS) applicerad i en fysiskt baserad hydraulisk modell för att utveckla avbördningskurvor, (iii) lågupplösta ALS från Svensk nationell höjdmodell kopplade med ADCP-batymetri för att ta fram en avbördningskurva med en hydraulisk modell, och (iv) undersökning av effekterna av osäkerheter på mätdata för att generera avbördningskurvor med en hydraulisk modell. Denna avhandling belyser potentialen för fjärranalystekniker för avståndsmätning på nära håll, för att fånga strömfårans exakta topografi och ifrån dessa data härleda de parametrar som krävs för hydrauliska modelleringstillämpningar., At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.

A rating curve provides a functional relationship between water height (i.e. stage) and discharge at a specified cross-section in a river. Used in combination with a time series of stage, rating curves become one of the central components for generating continuous records of streamflow. Since developing and maintaining rating curves can be time consuming, hydraulic models have shown potential to reduce the effort required for developing rating curves. A central challenge with modeling procedures, however, is the acquisition of accurate stream channel and floodplain topography. From this perspective, this thesis focuses on the real-world application of close-range remote sensing techniques such as laser-based ranging technologies (i.e. Light detection and ranging or LiDAR) or acoustic based ranging technologies (i.e. acoustic Doppler current profiler or ADCP) to capture topographic information for hydraulic modeling applications across various spatial scales. First, a review of the current LiDAR literature was carried out to identify potential ways to take full advantage of these novel data and technologies in the future. This was followed by four interconnected studies whereby: (i) a low-cost custom laser scanning system was designed to capture grain size distributions for a small stream; (ii) synthetically thinned airborne laser scanning (ALS) data was applied in a physically-based hydraulic modelling framework to develop rating curves; (iii) low-resolution national-scale ALS was coupled with ADCP bathymetry to be used in conjunction with a hydraulic model to develop rating curves; and (iv) the impact of measurement uncertainties on generating rating curves with a hydraulic model were investigated. This thesis highlights the potential of close-range remote sensing techniques for capturing accurate stream channel topography and derive from these data, the necessary parameters required for hydraulic modeling applications., En avbördningskurva tillhandahåller ett funktionellt förhållande mellan vattendjup (dvs. vattenstånd) och flöde vid ett specifikt tvärsnitt i ett vattendrag. Avbördningskurvan blir en central komponent för generering av kontinuerliga tidsserier av vattenföring från tidsserier av vattenstånd. Eftersom det är tidskrävande att utveckla och underhålla avbördningskurvor erbjuder hydrauliska modeller attraktiva möjligheter att minska den insats som krävs för att utveckla avbördningskurvorna. En central utmaning för sådana modelleringsförfaranden är emellertid tillgången till noggrann topografidata av strömfåran och de omgivande stränderna. Den här avhandlingen fokuserar på tillämpningen av fjärranalystekniker för avståndsmätning på nära håll, såsom laserbaserade teknik (dvs. Light detection and ranging eller LiDAR) och akustisk baserat teknik (dvs. acoustic Doppler current profiler eller ADCP), för att fånga topografisk information för hydraulisk modellering av vattendrag i olika rumsliga skalor. Först presenteras en litteraturstudie av den nuvarande LiDAR-litteratur för att identifiera potentiella sätt att dra full nytta av dessa nya data och tekniker i framtiden. Detta följs av fyra sammanlänkade studier: (i) tillämpning av ett lågkostnads-laseravsökningssystem för att fånga kornstorleksfördelningar i ett litet vattendrag, (ii) syntetiskt förtunnad flygburen laserskanningsdata (ALS) applicerad i en fysiskt baserad hydraulisk modell för att utveckla avbördningskurvor, (iii) lågupplösta ALS från Svensk nationell höjdmodell kopplade med ADCP-batymetri för att ta fram en avbördningskurva med en hydraulisk modell, och (iv) undersökning av effekterna av osäkerheter på mätdata för att generera avbördningskurvor med en hydraulisk modell. Denna avhandling belyser potentialen för fjärranalystekniker för avståndsmätning på nära håll, för att fånga strömfårans exakta topografi och ifrån dessa data härleda de parametrar som krävs för hydrauliska modelleringstillämpningar., At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.

A rating curve provides a functional relationship between water height (i.e. stage) and discharge at a specified cross-section in a river. Used in combination with a time series of stage, rating curves become one of the central components for generating continuous records of streamflow. Since developing and maintaining rating curves can be time consuming, hydraulic models have shown potential to reduce the effort required for developing rating curves. A central challenge with modeling procedures, however, is the acquisition of accurate stream channel and floodplain topography. From this perspective, this thesis focuses on the real-world application of close-range remote sensing techniques such as laser-based ranging technologies (i.e. Light detection and ranging or LiDAR) or acoustic based ranging technologies (i.e. acoustic Doppler current profiler or ADCP) to capture topographic information for hydraulic modeling applications across various spatial scales. First, a review of the current LiDAR literature was carried out to identify potential ways to take full advantage of these novel data and technologies in the future. This was followed by four interconnected studies whereby: (i) a low-cost custom laser scanning system was designed to capture grain size distributions for a small stream; (ii) synthetically thinned airborne laser scanning (ALS) data was applied in a physically-based hydraulic modelling framework to develop rating curves; (iii) low-resolution national-scale ALS was coupled with ADCP bathymetry to be used in conjunction with a hydraulic model to develop rating curves; and (iv) the impact of measurement uncertainties on generating rating curves with a hydraulic model were investigated. This thesis highlights the potential of close-range remote sensing techniques for capturing accurate stream channel topography and derive from these data, the necessary parameters required for hydraulic modeling applications., En avbördningskurva tillhandahåller ett funktionellt förhållande mellan vattendjup (dvs. vattenstånd) och flöde vid ett specifikt tvärsnitt i ett vattendrag. Avbördningskurvan blir en central komponent för generering av kontinuerliga tidsserier av vattenföring från tidsserier av vattenstånd. Eftersom det är tidskrävande att utveckla och underhålla avbördningskurvor erbjuder hydrauliska modeller attraktiva möjligheter att minska den insats som krävs för att utveckla avbördningskurvorna. En central utmaning för sådana modelleringsförfaranden är emellertid tillgången till noggrann topografidata av strömfåran och de omgivande stränderna. Den här avhandlingen fokuserar på tillämpningen av fjärranalystekniker för avståndsmätning på nära håll, såsom laserbaserade teknik (dvs. Light detection and ranging eller LiDAR) och akustisk baserat teknik (dvs. acoustic Doppler current profiler eller ADCP), för att fånga topografisk information för hydraulisk modellering av vattendrag i olika rumsliga skalor. Först presenteras en litteraturstudie av den nuvarande LiDAR-litteratur för att identifiera potentiella sätt att dra full nytta av dessa nya data och tekniker i framtiden. Detta följs av fyra sammanlänkade studier: (i) tillämpning av ett lågkostnads-laseravsökningssystem för att fånga kornstorleksfördelningar i ett litet vattendrag, (ii) syntetiskt förtunnad flygburen laserskanningsdata (ALS) applicerad i en fysiskt baserad hydraulisk modell för att utveckla avbördningskurvor, (iii) lågupplösta ALS från Svensk nationell höjdmodell kopplade med ADCP-batymetri för att ta fram en avbördningskurva med en hydraulisk modell, och (iv) undersökning av effekterna av osäkerheter på mätdata för att generera avbördningskurvor med en hydraulisk modell. Denna avhandling belyser potentialen för fjärranalystekniker för avståndsmätning på nära håll, för att fånga strömfårans exakta topografi och ifrån dessa data härleda de parametrar som krävs för hydrauliska modelleringstillämpningar., At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.

A rating curve provides a functional relationship between water height (i.e. stage) and discharge at a specified cross-section in a river. Used in combination with a time series of stage, rating curves become one of the central components for generating continuous records of streamflow. Since developing and maintaining rating curves can be time consuming, hydraulic models have shown potential to reduce the effort required for developing rating curves. A central challenge with modeling procedures, however, is the acquisition of accurate stream channel and floodplain topography. From this perspective, this thesis focuses on the real-world application of close-range remote sensing techniques such as laser-based ranging technologies (i.e. Light detection and ranging or LiDAR) or acoustic based ranging technologies (i.e. acoustic Doppler current profiler or ADCP) to capture topographic information for hydraulic modeling applications across various spatial scales. First, a review of the current LiDAR literature was carried out to identify potential ways to take full advantage of these novel data and technologies in the future. This was followed by four interconnected studies whereby: (i) a low-cost custom laser scanning system was designed to capture grain size distributions for a small stream; (ii) synthetically thinned airborne laser scanning (ALS) data was applied in a physically-based hydraulic modelling framework to develop rating curves; (iii) low-resolution national-scale ALS was coupled with ADCP bathymetry to be used in conjunction with a hydraulic model to develop rating curves; and (iv) the impact of measurement uncertainties on generating rating curves with a hydraulic model were investigated. This thesis highlights the potential of close-range remote sensing techniques for capturing accurate stream channel topography and derive from these data, the necessary parameters required for hydraulic modeling applications., En avbördningskurva tillhandahåller ett funktionellt förhållande mellan vattendjup (dvs. vattenstånd) och flöde vid ett specifikt tvärsnitt i ett vattendrag. Avbördningskurvan blir en central komponent för generering av kontinuerliga tidsserier av vattenföring från tidsserier av vattenstånd. Eftersom det är tidskrävande att utveckla och underhålla avbördningskurvor erbjuder hydrauliska modeller attraktiva möjligheter att minska den insats som krävs för att utveckla avbördningskurvorna. En central utmaning för sådana modelleringsförfaranden är emellertid tillgången till noggrann topografidata av strömfåran och de omgivande stränderna. Den här avhandlingen fokuserar på tillämpningen av fjärranalystekniker för avståndsmätning på nära håll, såsom laserbaserade teknik (dvs. Light detection and ranging eller LiDAR) och akustisk baserat teknik (dvs. acoustic Doppler current profiler eller ADCP), för att fånga topografisk information för hydraulisk modellering av vattendrag i olika rumsliga skalor. Först presenteras en litteraturstudie av den nuvarande LiDAR-litteratur för att identifiera potentiella sätt att dra full nytta av dessa nya data och tekniker i framtiden. Detta följs av fyra sammanlänkade studier: (i) tillämpning av ett lågkostnads-laseravsökningssystem för att fånga kornstorleksfördelningar i ett litet vattendrag, (ii) syntetiskt förtunnad flygburen laserskanningsdata (ALS) applicerad i en fysiskt baserad hydraulisk modell för att utveckla avbördningskurvor, (iii) lågupplösta ALS från Svensk nationell höjdmodell kopplade med ADCP-batymetri för att ta fram en avbördningskurva med en hydraulisk modell, och (iv) undersökning av effekterna av osäkerheter på mätdata för att generera avbördningskurvor med en hydraulisk modell. Denna avhandling belyser potentialen för fjärranalystekniker för avståndsmätning på nära håll, för att fånga strömfårans exakta topografi och ifrån dessa data härleda de parametrar som krävs för hydrauliska modelleringstillämpningar., At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.

A rating curve provides a functional relationship between water height (i.e. stage) and discharge at a specified cross-section in a river. Used in combination with a time series of stage, rating curves become one of the central components for generating continuous records of streamflow. Since developing and maintaining rating curves can be time consuming, hydraulic models have shown potential to reduce the effort required for developing rating curves. A central challenge with modeling procedures, however, is the acquisition of accurate stream channel and floodplain topography. From this perspective, this thesis focuses on the real-world application of close-range remote sensing techniques such as laser-based ranging technologies (i.e. Light detection and ranging or LiDAR) or acoustic based ranging technologies (i.e. acoustic Doppler current profiler or ADCP) to capture topographic information for hydraulic modeling applications across various spatial scales. First, a review of the current LiDAR literature was carried out to identify potential ways to take full advantage of these novel data and technologies in the future. This was followed by four interconnected studies whereby: (i) a low-cost custom laser scanning system was designed to capture grain size distributions for a small stream; (ii) synthetically thinned airborne laser scanning (ALS) data was applied in a physically-based hydraulic modelling framework to develop rating curves; (iii) low-resolution national-scale ALS was coupled with ADCP bathymetry to be used in conjunction with a hydraulic model to develop rating curves; and (iv) the impact of measurement uncertainties on generating rating curves with a hydraulic model were investigated. This thesis highlights the potential of close-range remote sensing techniques for capturing accurate stream channel topography and derive from these data, the necessary parameters required for hydraulic modeling applications., En avbördningskurva tillhandahåller ett funktionellt förhållande mellan vattendjup (dvs. vattenstånd) och flöde vid ett specifikt tvärsnitt i ett vattendrag. Avbördningskurvan blir en central komponent för generering av kontinuerliga tidsserier av vattenföring från tidsserier av vattenstånd. Eftersom det är tidskrävande att utveckla och underhålla avbördningskurvor erbjuder hydrauliska modeller attraktiva möjligheter att minska den insats som krävs för att utveckla avbördningskurvorna. En central utmaning för sådana modelleringsförfaranden är emellertid tillgången till noggrann topografidata av strömfåran och de omgivande stränderna. Den här avhandlingen fokuserar på tillämpningen av fjärranalystekniker för avståndsmätning på nära håll, såsom laserbaserade teknik (dvs. Light detection and ranging eller LiDAR) och akustisk baserat teknik (dvs. acoustic Doppler current profiler eller ADCP), för att fånga topografisk information för hydraulisk modellering av vattendrag i olika rumsliga skalor. Först presenteras en litteraturstudie av den nuvarande LiDAR-litteratur för att identifiera potentiella sätt att dra full nytta av dessa nya data och tekniker i framtiden. Detta följs av fyra sammanlänkade studier: (i) tillämpning av ett lågkostnads-laseravsökningssystem för att fånga kornstorleksfördelningar i ett litet vattendrag, (ii) syntetiskt förtunnad flygburen laserskanningsdata (ALS) applicerad i en fysiskt baserad hydraulisk modell för att utveckla avbördningskurvor, (iii) lågupplösta ALS från Svensk nationell höjdmodell kopplade med ADCP-batymetri för att ta fram en avbördningskurva med en hydraulisk modell, och (iv) undersökning av effekterna av osäkerheter på mätdata för att generera avbördningskurvor med en hydraulisk modell. Denna avhandling belyser potentialen för fjärranalystekniker för avståndsmätning på nära håll, för att fånga strömfårans exakta topografi och ifrån dessa data härleda de parametrar som krävs för hydrauliska modelleringstillämpningar., At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.

A rating curve provides a functional relationship between water height (i.e. stage) and discharge at a specified cross-section in a river. Used in combination with a time series of stage, rating curves become one of the central components for generating continuous records of streamflow. Since developing and maintaining rating curves can be time consuming, hydraulic models have shown potential to reduce the effort required for developing rating curves. A central challenge with modeling procedures, however, is the acquisition of accurate stream channel and floodplain topography. From this perspective, this thesis focuses on the real-world application of close-range remote sensing techniques such as laser-based ranging technologies (i.e. Light detection and ranging or LiDAR) or acoustic based ranging technologies (i.e. acoustic Doppler current profiler or ADCP) to capture topographic information for hydraulic modeling applications across various spatial scales. First, a review of the current LiDAR literature was carried out to identify potential ways to take full advantage of these novel data and technologies in the future. This was followed by four interconnected studies whereby: (i) a low-cost custom laser scanning system was designed to capture grain size distributions for a small stream; (ii) synthetically thinned airborne laser scanning (ALS) data was applied in a physically-based hydraulic modelling framework to develop rating curves; (iii) low-resolution national-scale ALS was coupled with ADCP bathymetry to be used in conjunction with a hydraulic model to develop rating curves; and (iv) the impact of measurement uncertainties on generating rating curves with a hydraulic model were investigated. This thesis highlights the potential of close-range remote sensing techniques for capturing accurate stream channel topography and derive from these data, the necessary parameters required for hydraulic modeling applications., En avbördningskurva tillhandahåller ett funktionellt förhållande mellan vattendjup (dvs. vattenstånd) och flöde vid ett specifikt tvärsnitt i ett vattendrag. Avbördningskurvan blir en central komponent för generering av kontinuerliga tidsserier av vattenföring från tidsserier av vattenstånd. Eftersom det är tidskrävande att utveckla och underhålla avbördningskurvor erbjuder hydrauliska modeller attraktiva möjligheter att minska den insats som krävs för att utveckla avbördningskurvorna. En central utmaning för sådana modelleringsförfaranden är emellertid tillgången till noggrann topografidata av strömfåran och de omgivande stränderna. Den här avhandlingen fokuserar på tillämpningen av fjärranalystekniker för avståndsmätning på nära håll, såsom laserbaserade teknik (dvs. Light detection and ranging eller LiDAR) och akustisk baserat teknik (dvs. acoustic Doppler current profiler eller ADCP), för att fånga topografisk information för hydraulisk modellering av vattendrag i olika rumsliga skalor. Först presenteras en litteraturstudie av den nuvarande LiDAR-litteratur för att identifiera potentiella sätt att dra full nytta av dessa nya data och tekniker i framtiden. Detta följs av fyra sammanlänkade studier: (i) tillämpning av ett lågkostnads-laseravsökningssystem för att fånga kornstorleksfördelningar i ett litet vattendrag, (ii) syntetiskt förtunnad flygburen laserskanningsdata (ALS) applicerad i en fysiskt baserad hydraulisk modell för att utveckla avbördningskurvor, (iii) lågupplösta ALS från Svensk nationell höjdmodell kopplade med ADCP-batymetri för att ta fram en avbördningskurva med en hydraulisk modell, och (iv) undersökning av effekterna av osäkerheter på mätdata för att generera avbördningskurvor med en hydraulisk modell. Denna avhandling belyser potentialen för fjärranalystekniker för avståndsmätning på nära håll, för att fånga strömfårans exakta topografi och ifrån dessa data härleda de parametrar som krävs för hydrauliska modelleringstillämpningar., At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

Several attempts to estimate the suspended load and the sediment deficit caused by the reservoirs have been carried out in the lower Ebro River. However, existing data are scarce, scattered along time and space, and obtained under different hydrological conditions and methods. This study estimate the presently suspended sediment load of the lowermost Ebro River, using field data collected during three consecutive years at different verticals of a cross-section and covering a large range of discharges. In addition, the daily suspended load for the last 30 years has been reconstructed and validated. The suspended load for the period 2007-2010 has been estimated at 84,000 t/y (+/- 9800 t) while 99,500 t/y (+/- 18,000 t) accounted for 1981-2010 period. Approximately, 80% of the total suspended load (period 2007-2010) has been transferred as inorganic load. A significant seasonal variability in the total (organic and inorganic) suspended load is observed. Therefore, two distinct cycling phases in the suspended load production and transfer has been inferred: an initial phase in which the sediment was prepared into the basin followed by a second phase in which most of the load was transferred downstream. These two phases are governed by the relative temporal location of the natural floods and the river regulation from the reservoirs. Nowadays, less than 1% of suspended load is transferred compared to pre-dams construction. The current levels of suspended load are very low and not enough to supply the material needed to maintain the delta elevation and avoid coastal retreat. The sustainability of the lower Ebro River and its delta could only be guaranteed by the implementation of a new reservoir management concept with the allocation of an appropriate liquid and solid flow regime., Peer Reviewed, Postprint (author's final draft)

Variation in fluvial suspended sediment-discharge behavior is generally thought to be the product of changes in processes governing the delivery of sediment and water to the channel. The objective of this study was to infer sediment supply dynamics from the response of suspended sediment behavior to antecedent hydrologic factors. The Salinas River (California) is seasonally active, moderately sized, and potentially susceptible to lasting impacts of hydrologic event history because of aridity, high discharge variability, and in-channel terminating flows. Forty-five years of suspended sediment data from the lower Salinas and 80. years of hydrologic data were used to construct hydrologic descriptors of basin preconditioning and to test the effects of these preconditions on suspended sediment behavior. Hydrologic precondition factors - including change in mean daily discharge and increasing elapsed time since the last moderate discharge event (~. 10-20 times mean discharge (Qmean)) - were found to have significant positive effects on discharge-corrected, fine suspended-sediment concentrations. Conversely, increased elapsed time since the last low discharge event (~. 0.1-0.4 times Qmean), and the sum of low flow conditions over interannual time scales were found to cause significant negative trends in fine suspended sediment concentration residuals. Suspended sand concentrations are suppressed by increased elapsed time after threshold discharges of ~. 0.1-2 and 5-100 times Qmean, and increased low to no flow days over time scales from 1 to 2000. days. Current and previous year water yield and precipitation magnitudes correlate positively with sand concentration. Addition of fine sediment from lower Salinas hillslope or channel sources on the rising limb of the hydrograph is the major mechanism behind an overall positive hysteretic pattern, which was forensically supported by the annual occurrence of in-channel suspended sediment deposition by early season, channel termin

Variation in fluvial suspended sediment-discharge behavior is generally thought to be the product of changes in processes governing the delivery of sediment and water to the channel. The objective of this study was to infer sediment supply dynamics from the response of suspended sediment behavior to antecedent hydrologic factors. The Salinas River (California) is seasonally active, moderately sized, and potentially susceptible to lasting impacts of hydrologic event history because of aridity, high discharge variability, and in-channel terminating flows. Forty-five years of suspended sediment data from the lower Salinas and 80. years of hydrologic data were used to construct hydrologic descriptors of basin preconditioning and to test the effects of these preconditions on suspended sediment behavior. Hydrologic precondition factors - including change in mean daily discharge and increasing elapsed time since the last moderate discharge event (~. 10-20 times mean discharge (Qmean)) - were found to have significant positive effects on discharge-corrected, fine suspended-sediment concentrations. Conversely, increased elapsed time since the last low discharge event (~. 0.1-0.4 times Qmean), and the sum of low flow conditions over interannual time scales were found to cause significant negative trends in fine suspended sediment concentration residuals. Suspended sand concentrations are suppressed by increased elapsed time after threshold discharges of ~. 0.1-2 and 5-100 times Qmean, and increased low to no flow days over time scales from 1 to 2000. days. Current and previous year water yield and precipitation magnitudes correlate positively with sand concentration. Addition of fine sediment from lower Salinas hillslope or channel sources on the rising limb of the hydrograph is the major mechanism behind an overall positive hysteretic pattern, which was forensically supported by the annual occurrence of in-channel suspended sediment deposition by early season, channel termin

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage-discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics-based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m-wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90-m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a hybrid model rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see below the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics-based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote locations