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Discharge monitoring stations are often costly and difficult to install, operate, and maintain, especially in small streams. The purpose of this study was to evaluate a low-cost method for remotely monitoring streamflow in small-scale watersheds to provide continuous discharge measurements across multiple sites and flow conditions. Within the Upper Poteau River Watershed (UPRW) in Arkansas, 12 sites were selected at bridge crossings near the outflow of HUC-12 or HUC-14 subwatersheds. A HOBO water level logger was deployed at each site to obtain continuous stage records, and HOBO barometric pressure transducers were installed within 16 km of each sample site to account for fluctuations in atmospheric pressure. SonTek-IQ acoustic Doppler instruments were deployed to measure discharge during high-flow events, and roving discharge monitoring stations were installed at each site to allow easy rotation of the SonTek-IQ instruments among sites between flood events. Once the roving discharge monitoring stations were installed at each site, one or more SonTek-IQ instruments could be rotated among sites to capture high-flow discharge measurements; therefore, a Son-Tek-IQ instrument was not required for every site of interest. The high-flow data captured during SonTek-IQ deployment, and baseflow discharge measurements collected on a monthly basis, were used to develop rating curves with a combination of simple linear regression, LOESS regression, and Manning's equation. The rating curves well represented the measured flows, with Nash-Sutcliffe efficiencies ranging between 0.87 and 0.98. This method provides an opportunity to collect continuous records of flow across multiple, remote, small-scale watersheds, and in conjunction with constituent concentrations and load estimations, can be used to calibrate and validate watershed models. [ABSTRACT FROM AUTHOR]

Understanding suspended sediment dynamics and their driving factors is essential for effective watershed management. In this study, the spatiotemporal patterns of suspended sediment were identified for 11 sub‐watersheds of the Goodwin Creek, Mississippi, USA, for the period 1982–2002 using wavelet transforms. The continuous wavelet transform (CWT) results of streamflow time series showed that a near‐continuous annual periodicity influenced all stations over the study period, yet an overall decline occurred in wavelet spectral power of sediment load during the 1990s. This decline in sediment load is a result of the indirect effect of decreased cultivation on reducing the rate of peak flow and thus fluvial erosion processes. The CWTs of fine sediment (clays and silts) concentration (FSC) time series showed that factors other than land‐use (e.g., ponds, ephemeral gullies, and bed composition) better explain the variations in FSC. A comparison of CWTs of FSC at two stations with different bed composition in their channels showed that sandy channels are less responsive to erosion control measures compared to gravely channels indicating that they are major sources of sediment. A change in phase relationship between flow and FSC for the gravel‐dominated channel was associated with the transition in upland land‐use indicating a change in sediment supply mechanisms. The CWTs of sand concentrations reflected the spatiotemporal impact of bank materials, the growth cycle of riparian vegetation, and in‐channel sand availability on sand dynamics. While CWT‐based analysis is sensitive to input conditions, the method is able to provide valuable outcomes for distinguishing patterns in complex temporal datasets. Key Points: An overall decline in fine sediment load occurred across all time scales during the period of land‐use change and in‐channel stabilizationStreambed composition and the locations of ponds and upland sediment sources explain the spatiotemporal patterns of suspended finesThe spatiotemporal patterns of sand dynamics reflect both the state of channel stability and the availability of in‐channel sand [ABSTRACT FROM AUTHOR]

Having a river basin as the study site, it is of fundamental importance to comprehend the sediment dynamics of river systems, in order to diagnose and understand them, aiming to carry out predictions. The observance of the sediment supply carried by the river systems is related to the erosion, transport and deposition, through rainfall and dynamic land use and cover in hillside environments. The Purus River basin is part of this context, the study area of this paper and it is located in the Amazon biome. This study aims to start the first steps to understand the suspended sediment dynamics of that basin, because of its expressive environmental variations. For this purpose was considered the sediment present in the river systems as an indicator which can be understood and used in order to support soil and water conservation measures in the Purus River basin, distinguishing the natural dynamics and anthropogenic dynamics. Thus, this study has the objective of evaluating the suspended sediments discharge in the Purus River basin, in order to collaborate with action planning and watershed management, with the objective of generating knowledge about the suspended sediment dynamics of that spring. [ABSTRACT FROM PUBLISHER]

The honey-bees mating programming (HBMP) algorithm is introduced as a novel tool for predicting suspended sediment concentration for the Mad River catchment near Arcata, USA. The paper also applies gene expression programming (GEP) as a comparison and shows that these two approaches can the produce transparent, nonlinear relationships between the independent and dependent variables. Some modifications have been made to the HBMP algorithm to improve its capability and efficiency. The results achieved from this method and GEP are compared with two different sediment rating curves based on regression techniques. The findings show that the results from both the HBMP and GEP methods are promising and outperform the results obtained from the sediment rating curves.Editor D. Koutsoyiannis; Associate editor L. See [ABSTRACT FROM AUTHOR]

An empirical framework for assisting with water quality management is proposed that relies on open-source hydrologic data. Such data are measured periodically at fixed water stations and commonly available in time-series form. To fully exploit the data, we suggest that observations from multiple stations should be combined into a single long-panel data set, and an econometric model developed to estimate upstream management effects on downstream water quality. Selection of the model's functional form and explanatory variables would be informed by rating curves, and idiosyncrasies across and within stations handled in an error term by testing contemporary correlation, serial correlation, and heteroskedasticity. Our proposed approach is illustrated with an application to the Nakdong River basin in South Korea. Three alternative policies to achieve downstream BOD level targets are evaluated: upstream water treatment, greater dam discharge, and development of a new water source. Upstream water treatment directly cuts off incoming pollutants, thereby presenting the smallest variation in its downstream effects on BOD levels. Treatment is advantageous when reliability of water quality is a primary concern. Dam discharge is a flexible tool, and may be used strategically during a low-flow season. We consider development of a new water corridor from an extant dam as our third policy option. This turns out to be the most cost-effective way for securing lower BOD levels in the downstream target city. Even though we consider a relatively simple watershed to illustrate the usefulness of our approach, it can be adapted easily to analyze more complex upstream-downstream issues. [ABSTRACT FROM AUTHOR]

Abstract: 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 80years 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 2000days. 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 terminating flows and by the flushing function of moderate hydrologic events found in this study. The importance of hillslope and/or channel fine sediment contributions proximal to the lower Salinas are further highlighted by the lack of control exerted by upper subbasin water provenance on fine suspended sediment concentration, while sand behavior is differentiated by upper basin water provenance. Investigation of suspension of bed-sized sediment showed that the channel bed could exert significant effects on fine and sand-sized suspended sediment dynamics, but this mediation for fine sediment was most likely small in terms of decadal-scale sediment budgets. The magnitude of the effects of hydrologic variables on sediment dynamics remains uncertain, but the factors identified here may play a significant role in water quality, if not long-term sediment flux to the ocean. [Copyright &y& Elsevier]

This study focuses on the impact of changes in winter streamflow on in-stream turbidity in the Esopus Creek watershed, one of the New York City water supply watersheds. Projected changes in daily precipitation and air temperature from a suite of five global climate models and three emission scenarios for future periods 2046-2065 and 2081-2100 were downscaled for the study region. The simulated climate scenarios were used to project future streamflows using the Generalized Watershed Loading Functions - Variable Source Area watershed model. Seasonal turbidity rating curves based on measured historical streamflow and stream turbidity were used in combination with the simulated streamflow for generating future stream turbidity scenarios. Results indicate an increase in future ambient stream turbidity from November to March and a decrease during April. These results are the effects of increased winter rainfall, reduced snowfall, and a shift to early timing of spring snowmelt runoff, causing an increase in streamflow during early winter. It also suggests a reduction in the traditional peak streamflow around April that is expected to occur in this region. As a result, our models simulate a consistent increase in the low to medium percentile range of turbidity values associated with low to medium range of streamflows and no apparent change in high-percentile turbidity values associated with high streamflows. Our results may be applicable in regions where snowmelt runoff is an important process and turbidity caused by the suspension of fine clay particles is a water quality concern. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Nestos River flows through Bulgaria and Greece and discharges into the North Aegean Sea. Its total catchment area is around 6,200 km, while the mean annual precipitation and runoff are 680 mm and 40 m/s, respectively. The Hellenic part of the catchment has undergone a substantial hydroelectric development, since two dams associated with major hydropower pumped-storage facilities are in operation. The main objective of the paper is to assess the expected sediment delivery of Nestos R. at the uppermost Thisavros reservoir site. This has been carried out by implementing the Universal Soil Loss Equation in a GIS environment for determining the mean annual soil erosion in conjunction with a suspended sediment measurement program (114 measurements in total) accomplished between 1965 and 1983 adjacent to the dam site. The sediment discharge rating curve between sediment and river discharges in a power form has been constructed using five alternative techniques, namely (a) the linear regression of the log-transformed variables, (b) the same as (a) but with the Ferguson correction, (c) different ratings for the dry and wet seasons of the year, (d) the nonlinear regression, and (e) the broken line interpolation that utilizes different rating parameters for two discharge classes. It is shown that the mean annual sediment yield is almost equal for all rating curve formulations and varies between 178.5 t km and 203.4 t km and the highest value results from the broken line interpolation method. Accordingly, the sediment delivery ratios vary slightly between 17% and 19% of the upstream soil erosion. [ABSTRACT FROM AUTHOR]

This paper illustrates the importance of taking into account the potential errors in discharge estimation in the assessment of extreme floods. First, a summary of the main difficulties encountered in extrapolating rating curves for flood discharge is provided. Then a sensitivity analysis is carried out using a hydraulic modelling approach, applied to eight Mediterranean catchments, and yielding an envelope curve for the stage-discharge relationship, Q(H). To assess the influence of errors in the flood discharge on the uncertainty in estimating extreme floods, a Bayesian framework including a multiplicative error on the rating curve was applied. Its application on two catchments for which historical data are available for the period (1741-2004) shows that ignoring the rating curve errors may lead to an unduly optimistic reduction in the final uncertainty in estimation of flood discharge quantiles. Moreover, the quantile values are also affected by taking into account the rating curve errors. Citation Lang, M., Pobanz, K., Renard, B., Renouf, E. & Sauquet, E. (2010) Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis. Hydrol. Sci. J. 55(6), 883-898. [ABSTRACT FROM AUTHOR]

Abstract: Using data from two very large watersheds and five smaller, this paper explores the use of Bayesian methods for fitting rating curves. Posterior distribution of rating-curve parameters were calculated using Markov Chain Monte Carlo (MCMC) methods, and 95% credible intervals were calculated for predicted discharges, given stage. Expected discharge was related to stage using a link function. For the five smaller watersheds, the assumptions were (a) that the distribution of discharge Q, given stage h, is Normal, with variance proportional to h; (b) that a log link function relates μ Q , the mean of Q∣h, to a function of stage, of the form μ Q = β(h + α) λ . For the two large watersheds, however, a better fit was obtained by taking the distribution of Q to be log-Normal, and the link function as ln μ Q = β 0 + β 1 h. For the two large watersheds, priors for all three parameters were taken as uninformative; for the five smaller, the prior for parameter λ was taken as Normally distributed, N(2,0.5). Acceptable ratings were obtained for all seven sites. It is argued that distributions of derived variables (such as annual maximum discharge) can be derived directly from (a) the posterior distribution of rating-curve parameters, and (b) the stage record, without recourse to additional assumptions. Estimates thus obtained for the T-year event will incorporate rating-curve uncertainty. It is argued that Bayesian methods are appropriate for rating-curve calculation because their inherent flexibility (a) allows the incorporation of prior information about the nature of a rating curve; (b) yields credible intervals for predicted discharges and quantities derived from them; (c) can be extended to allow for uncertainty in stage measurements. [Copyright &y& Elsevier]

Niamey, the capital of Niger, is particularly prone to floods, since it is on the banks of the Niger River, which in its middle basin has two flood peaks: one in summer (the red flood) and one in winter (the black flood). In 2020, the Niger River in Niamey reached its all-time highest levels following an abundant rainy season. On the other hand, the floods in Niamey have been particularly frequent in the last decade, a symptom of a change in hydroclimatic behaviour already observed since the end of the great droughts of the 1970s and 1980s and which is identified with the name of Sahelian Paradox. This study, starting from the analysis of the 2020 flood and from the update of the rating curve of the Niamey hydrometric station, analyses the rainfall–runoff relationship on the Sahelian basins of the Medium Niger River Basin (MNRB) that are at the origin of the local flood. The comparative analysis of runoffs, annual maximum flows (AMAX) and runoff coefficients with various rainfall indices calculated on gridded datasets allowed to hydroclimatically characterise the last decade as a different period from the wet one before the drought, the dry one and the post-drought one. Compared to the last one, the current period is characterised by a sustained increase in hydrological indicators (AMAX +27%) consistent with the increase in both the accumulation of precipitation (+11%) and the number (+51%) and magnitude (+54%) of extreme events in the MNRB. Furthermore, a greater concentration of rainfall and extremes (+78%) in August contributes to reinforcing the red flood's positive anomalies (+2.23 st.dev in 2020). The study indicates that under these conditions the frequency of extreme hydrological events in Niamey will tend to increase further also because of the concurrence of drivers such as river-bed silting and levee effects. Consequently, the study concludes with the need for a comprehensive flood-risk assessment on the Niamey city that considers both recent hydroclimatic trends and urbanisation dynamics in flood zones hence defining the most appropriate risk-reduction strategies. [ABSTRACT FROM AUTHOR]

The Sahelian regions are affected by an increasing number of catastrophic floods in recent years as a consequence of climate and land use/land cover changes. River flow data is key to understanding river behavior and develop flood mitigation and prevention strategies. The present study provides a revision and an update of the existing discharge dataset of the Sirba River with the aim of enhancing the reliability of these data. The revision also includes the recalibration of the Garbey Kourou rating curves. The analysis of the revised discharge time series strengthens the previous findings, evidencing a positive trend in flood frequency and intensity over the entire analyzed period of 1956–2018. This positive trend is more pronounced for the last 40 years due to a significant underestimation of the rating curves used. A relevant finding is a new changepoint in the time series, detected for 2008, which represents the beginning of the period in which the highest flood magnitudes were registered. The effect of land use/land cover changes and climate changes on the water resource is depicted using flow duration curves. This research produces a revised and more reliable discharge time series that will be a new starting point for future hydrological analyses. [ABSTRACT FROM AUTHOR]

Recent floods from intense storms in the southern United States and the unusually active 2017 Atlantic hurricane season have highlighted the need for real‐time flood inundation mapping using high‐resolution topography. High‐resolution topographic data derived from lidar technology reveal unprecedented topographic details and are increasingly available, providing extremely valuable information for improving inundation mapping accuracy. The enrichment of terrain details from these data sets, however, also brings challenges to the application of many classic approaches designed for lower‐resolution data. Advanced methods need to be developed to better use lidar‐derived terrain data for inundation mapping. We present a new workflow, GeoFlood, for flood inundation mapping using high‐resolution terrain inputs that is simple and computationally efficient, thus serving the needs of emergency responders to rapidly identify possibly flooded locations. First, GeoNet, a method for automatic channel network extraction from high‐resolution topographic data, is modified to produce a low‐density, high‐fidelity river network. Then, a Height Above Nearest Drainage (HAND) raster is computed to quantify the elevation difference between each land surface cell and the stream bed cell to which it drains, using the network extracted from high‐resolution terrain data. This HAND raster is then used to compute reach‐average channel hydraulic parameters and synthetic stage‐discharge rating curves. Inundation maps are generated from the HAND raster by obtaining a water depth for a given flood discharge from the synthetic rating curve. We evaluate our approach by applying it in the Onion Creek Watershed in Central Texas, comparing the inundation extent results to Federal Emergency Management Agency 100‐yr floodplains obtained with detailed local hydraulic studies. We show that the inundation extent produced by GeoFlood overlaps with 60%~90% of the Federal Emergency Management Agency floodplain coverage demonstrating that it is able to capture the general inundation patterns and shows significant potential for informing real‐time flood disaster preparedness and response. Plain Language Summary: Simple and computationally efficient flood inundation mapping methods are needed to take advantage of increasingly available high‐resolution topography data. In this work, we present a new approach, called GeoFlood, for flood inundation mapping using high‐resolution topographic data. This approach combines GeoNet, an advanced method for high‐resolution terrain data analysis, and the Height Above Nearest Drainage. GeoFlood can rapidly convert real‐time forecasted river flow conditions to corresponding flood maps. A case study in central Texas demonstrated that the flood maps generated with our approach capture the majority of the inundated extent reported by detailed Federal Emergency Management Agency flood studies. Our results show that GeoFlood is a valuable solution for rapid inundation mapping. Key Points: A simple and computationally efficient approach was developed for real‐time flood inundation mappingThe approach, called GeoFlood, combines nonlinear filtering, geodesic minimization principles, prior information from low‐resolution products, and the Height Above Nearest DrainageWith simple hydraulic assumptions and approximate roughness estimation, GeoFlood rapidly generates flood maps corresponding well with those of detailed local models [ABSTRACT FROM AUTHOR]