River Discharge Measurements Research Articles

Estimation of inflow discharge to Lake Baikal at upstream section using different satellite-based precipitation and runoff datasets from Upper Angara and Kichera River basins in East Siberia, Russia

Accurate basin-level river discharge estimation is of vital importance across various fields, including water resources, climate change, natural hazards, biodiversity, and energy production. Normally, gauging stations are deemed the most reliable data source for measuring river discharge. However, a significant proportion of the world’s rivers remain ungauged due to a combination of technical, economic, and political constraints. Encouragingly, recent advancements in remote sensing and satellite observation have opened new avenues for global river discharge monitoring, even in ungauged basins, and the availability of extensive datasets and advancements in computing technologies have facilitated the development of numerous modern data-driven techniques. The general objective of this study is to estimate inflow discharge to Lake Baikal at upstream section from Upper Angara and Kichera River Basins using different satellite precipitation and runoff datasets. According to the calculation result, a higher discharge was observed for the power dataset. The obtained results were used to mitigate floods, droughts, bridge design, manage urban drainage systems, and manage the lake ecosystem.

Monitoring river discharge from space: An optimization approach with uncertainty quantification for small ungauged rivers

The number of in-situ stations measuring river discharge, one of the Essential Climate Variables (ECV), is declining steadily, and numerous basins have never been gauged. With the aim of improving data availability worldwide, we propose an easily applicable and transferable approach to estimate reach-scale discharge solely using remote sensing data that is suitable for filling gaps in the in-situ network. We combine 20 years of satellite altimetry observations with high-resolution satellite imagery via a hypsometric function to observe large portions of the reach-scale bathymetry. The high-resolution satellite images, which are classified using deep learning image segmentation, allow for detecting small rivers (narrower than 100m) and can capture small width variations. The unobserved part of the bathymetry is estimated using an empirical width-to-depth function. Combined with precise satellite-derived slope measurements, river discharge is calculated at multiple consecutive cross-sections within the reach. The unknown roughness coefficient is optimized by minimizing the discharge differences between the cross-sections. The approach requires minimal input and approximate boundary conditions based on expert knowledge but is not dependent on calibration. We provide realistic uncertainties, which are crucial for data assimilation, by accounting for errors and uncertainties in the different input quantities. The approach is applied globally to 27 river sections with a median normalized root mean square error of 12% and a Nash–Sutcliffe model efficiency of 0.560. On average, the 90% uncertainty range includes 91% of the in-situ measurements.

A Review on the Video-Based River Discharge Measurement Technique.

The hydrological monitoring of flow data is important for flood prevention and modern river management. However, traditional contact methods are increasingly struggling to meet the requirements of simplicity, accuracy, and continuity. The video-based river discharge measurement is a technique to monitor flow velocity without contacting the water body by using the image-recognition algorithms, which has been verified to have the advantages of full coverage and full automation compared with the traditional contact technique. In order to provide a timely summary of the available results and to inform further research and applications, this paper reviews and synthesizes the literature on the general implementation routes of the video-based river discharge measurement technique and the principles and advances of today's popular image-recognition algorithms for velocity detection. Then, it discusses the challenges of image-recognition algorithms in terms of image acquisition conditions, parameter uncertainties, and complex meteorological and water environments. It is concluded that the performance of this technique can be improved by enhancing the robustness and accuracy of video-based discharge measurement algorithms, minimizing weather effects, and improving computational efficiency. Finally, future development directions for further perfecting this technique are outlined.

Evaluating flood hazards in data-sparse coastal lowlands: highlighting the Ayeyarwady Delta (Myanmar)

Coastal lowlands and river deltas worldwide are increasingly exposed to coastal, pluvial and fluvial flooding as well as relative sea-level rise (RSLR). However, information about both single and multiple flood-type hazards, their potential impact and the characteristics of areas, population and assets at risk is often still limited as high-quality data either does not exist or is not accessible. This often constitutes a main barrier for generating sound assessments, especially for scientific and public communities in the so-called Global South. We provide a standardised, integrative approach for the first-order assessment of these single and multiple flood-type hazards and show how this can be conducted for data-sparse, hardly accessible and inaccessible coastal lowlands such as the Ayeyarwady Delta in Myanmar by using only open accessible and freely available datasets of satellite imagery, global precipitation estimates, satellite-based river discharge measurements, elevation, land use, and population data. More than 70% of the delta, mainly used for agriculture, and about 40% of its present population are prone to flooding due to either monsoon precipitation and runoff, storm surge, and RSLR, or their combination, jeopardising food security and economic development in the region. The approach allows for the integration and combination of various datasets, combined in a highly flexible workflow that performs at low computational capacities, supporting the evaluation of flood-prone areas on regional and local scale for data-sparse coastal lowlands worldwide. It thereby allows to attribute different types of flood hazards, complements concepts of vulnerability and risk, and supports risk-informed decision making and development of effective multi-flooding adaptation strategies.

Congo Basin Water Balance and Terrestrial Fluxes Inferred From Satellite Observations of the Isotopic Composition of Water Vapor

AbstractLarge spatio‐temporal gradients in the Congo basin vegetation and rainfall are observed. However, its water‐balance (evapotranspiration minus precipitation, or ET − P) is typically measured at basin‐scales, limited primarily by river‐discharge data, spatial resolution of terrestrial water storage measurements, and poorly constrained ET. We use observations of the isotopic composition of water vapor to quantify the spatio‐temporal variability of net surface water fluxes across the Congo Basin between 2003 and 2018. These data are calibrated at basin scale using satellite gravity and total Congo river discharge measurements and then used to estimate time‐varying ET − P over four quadrants representing the Congo Basin, providing first estimates of this kind for the region. We find that the multi‐year record, seasonality, and interannual variability of ET − P from both the isotopes and the gravity/river discharge based estimates are consistent. Additionally, we use precipitation and gravity‐based estimates with our water vapor isotope‐based ET − P to calculate time and space averaged ET and net river discharge within the Congo Basin. These quadrant‐scale moisture flux estimates indicate (a) substantial recycling of moisture in the Congo Basin (temporally and spatially averaged ET/P > 70%), consistent with models and visible light‐based ET estimates, and (b) net river outflow is largest in the Western Congo where there are more rivers and higher flow rates. Our results confirm the importance of ET in modulating the Congo water cycle relative to other water sources.

Observational Constraints on Basin‐Scale Runoff: A Request for Both Improved ESMs and Streamflow Reconstructions

AbstractEfforts to predict long‐term changes in continental runoff at both global and basin scales generally remain ambiguous. Here we use a global runoff reconstruction and a Bayesian statistical method to narrow uncertainties in runoff projections from the latest generation of global climate models. Three representative tropical river basins are used to illustrate the application and showcase the potential for substantial reduction in modeling uncertainty. Yet, results are fairly sensitive to the selected reconstruction thus highlighting the need for reliable and homogeneized gridded runoff data sets or river discharge measurements. Moreover, climate models do not account for water withdrawals, whose effect on observed runoff should also be removed in order to detect and attribute the hydrological effect of climate change. Finally, and more importantly, most models fail at capturing the observed recent decrease in runoff ratio, which may highlight either model deficiencies or increasing water derivation over the selected river basins.

Siting Considerations for Satellite Observation of River Discharge

AbstractWith growing global capability for satellite measurement of river discharge (flow) comes a need to understand and reduce error in satellite‐based discharge measurements. Satellite‐based discharge estimates are based on measurements of water surface width, elevation, slope, and potentially velocity. Site selection is important for reducing error and uncertainty in both conventional and satellite‐based discharge measurements because geomorphic river characteristics have strong control over the relationships between discharge and width, water surface elevation (or depth), slope, and velocity. A large ground‐truth data set of 8,445 conventional hydraulic measurements, collected by acoustic Doppler current profilers at 503 stations in the United States, was developed and quality assured to examine correlation between river discharge and water surface width, depth, velocity, and cross‐sectional area. A separate database of river surface slope and discharge time‐series was developed from paired continuous monitoring stations to examine slope‐discharge correlations. Results show that discharge correlates most strongly with velocity, cross‐sectional area, depth, width, and slope, in that order. Uncertainty of satellite discharge estimates is affected by observed hydraulic variable and reach‐specific variability in observed variable(s) characteristics including range of variability, georegistration accuracy, and stability over time of relationships between discharge and observed hydraulic variable.

Adaptive river flow measurement method based on spatiotemporal image velocimetry and optical flow.

This paper proposes an adaptive river discharge measurement method based on spatiotemporal image velocimetry (STIV) and optical flow to solve the problem of blurred texture features and limited measurement accuracy under complex natural environmental conditions. Optical flow tracking generates spatiotemporal images by following the flow mainstream direction of rivers with both regular and irregular natural banks. A texture similarity function filtering method effectively enhances spatiotemporal texture features. The proposed method is applied to a natural river, with measurement results from a propeller-type current meter used as truth values. It is evaluated and compared with three other methods regarding measurement accuracy, error, and other evaluation indices. The results demonstrate that the method significantly improves spatiotemporal image quality. Its estimation outcomes perform better across all evaluation metrics, enhancing the adaptability and accuracy of the flow measurement method.

Quantifying and Reducing the Operator Effect in LSPIV Discharge Measurements

AbstractOperator choices, both in acquiring the video and data and in processing them, can be a prominent source of error in image‐based velocimetry methods applied to river discharge measurements. The Large Scale Particle Image Velocimetry (LSPIV) is known to be sensitive to the parameters and computation choices set by the user, but no systematic comparisons with discharge references or intercomparisons have been conducted yet to evaluate this operator effect in LSPIV. In this paper, an analysis of a video gauging intercomparison, the Video Globe Challenge 2020, is proposed to evaluate such operator effect. The analysis is based on the gauging reports of the 15 to 23 participants using the Fudaa‐LSPIV software and intents to identify the most sensitive parameters for the eight videos. The analysis highlighted the significant impact of the time interval, the grid points and the filters on the LSPIV discharge measurements. These parameters are often inter‐dependent and should be correctly set together to strongly reduce the discharge errors. Based on the results, several automated tools were proposed to reduce the operator effect. These tools consist of several parameter assistants to automatically set the orthorectification resolution, the grid and the time interval, and of a sequence of systematic and automatic filters to ensure reliable velocity measurements used for discharge estimation. The application of the assisted LSPIV workflow using the proposed tools leads to significant improvements of the discharge measurements with strong reductions of the inter‐participant variability. On the eight videos, the mean interquartile range of the discharge errors is reduced from 17% to 5% and the mean discharge bias is reduced from −9% to 1% with the assisted LSPIV workflow. The remaining inter‐participant variability is mainly due to the user‐defined surface velocity coefficient α.

Water table level dynamics in the drained part of the great Vasyugan mire

Relevance. The need to assess mire-river interaction in Western Siberia under the influence of drainage and the pyrogenic factor. Aim. To study water table level dynamics in the Great Vasyugan Mire and the patterns of its change under the influence of drainage and the pyrogenic factor. Objects. Nоrtheastern part оf the Great Vasyugan Mire clоse tо Pоlynyanka village, Bakchar district, Tоmsk regiоn. Methods. Hydrological monitoring of drained and pristine part of the Great Vasyugan Mire is organized within the small model catchments of the Gavrilovka River and Klyuch River in the Vasyugan station of the Siberian Research Institute of Agriculture and the Peat branch of the Siberian Research Institute оf Agriculture and Peat RAS. Water table level monitoring was carried out in 2022 using Solinst Levelloger (Canada) with a frequency of 1 hour. River discharge measurements were made in different water periods using an acoustic current meter OTT Hydromet. The research methodology included an assessment of the spatial and temporal variation in water levels over the drained territory of the Great Vasyugan Mire in the Gavrilovka River basin in comparison with pristine part and depending on the main meteorological factors, correlation curves construction of mire water level and river discharges, the specific yield calculation. Statistical analysis of the data was carried out using the nonparametric Wilcoxon test, correlation and cluster analysis. Results. The studies shown that the drained area of the Great Vasyugan Mire within the Gavrilovka River basin is characterized by a significant transformation of the hydrological regime; there is a significant decrease in the water levels and an increase in the amplitude of their fluctuations. The influence of the pyrogenic factor is expressed in a certain increase in water levels as a result of the surface burnout and the leveling of microtopography. An analysis of the spatial variation of the water levels showed that it depends on the vegetation type of key sites, the slope of the surface, and the degree of surface burnout. It also depends on the location of the site relative to the lagg area, zones of backwater flow formed near overgrown drainage ditches, dirt roads and main ditch drainage zones. As a result of the forest reclamation and fire event in the study area of the Great Vasyugan Mire, active decomposition of plant residues was noted. This led to a decrease in the storage capacity (specific yield) of the upper peat layer. A decrease of the specific yield will increase the runoff from the mire area, which means the increase of possibility of extreme hydrological events in the conditions of growth in the amount of precipitation.

Implementasi Alat Pemantau Debit dan Ketinggian Air Sungai Berbasis Internet of Things Untuk Penanggulangan Banjir

The increasing frequency and intensity of floods in Cirebon City demands innovative solutions to reduce the impact of damage and risks to society and infrastructure. requires the latest approaches to risk management and prevention. This research focuses on the implementation of an Internet of Things (IoT)-based river discharge and water level monitoring tool designed to improve flood detection and prevention capabilities in Cirebon City. The main problems faced include accurate measurements, real-time monitoring, and rapid response to river water fluctuations. By combining the latest sensors and IoT technology, this tool is able to provide accurate data about water discharge and river levels continuously. The first stage in developing the Internet of Things (IoT) is identification and study of flooding problems in Cirebon City and analysis of the need for a monitoring system for flood prevention. Second, design a monitoring tool concept that meets the needs and specifications and determine the type of sensors, hardware and IoT technology that will be used. Third, choose a sensor to measure river discharge and water level. Fourth, build a monitoring tool prototype based on conceptual design. Fifth, Testing and Validation. The results of this research are based on river tests in the city of Cirebon, there are 4 rivers that frequently flood and the results of the test are that the Kalijaga River has a height of 20cm in the Safe level category, the Kedung Pane River has a height of 15cm in the Safe Level Category, the Kesunean River has a height of 10cm in the Safe Level Category and the Sukalila River has a height of 17cm in the Safe level category this is influenced by dry weather. Then the data collected from monitoring tools can be used to analyze flood patterns, trigger factors and impacts. Then, from this data, a flood classification analysis can be carried out based on the level of river water discharge, so that it can be classified as light, medium or heavy floods based on the amount of water flowing.

Hydrological characteristics of Mahakam cascade lake as a reference for the sustainability management

Mahakam cascade lakes consist of Lake Semayang, Melintang, and Jempang is a floodplain lake. Mahakam cascade lakes include the 15 national priority lakes which are the most urgent situation. This lake is characterized by dynamic water level fluctuation, resulting in high fishery productivity. The lake’s hydrological characteristic is the main component in controlling the lake ecosystem, therefore it is crucial to evaluate the influenced factors. The objective of this research is to describe the lake’s hydrological characteristics, including inlet-outlet discharge, sedimentation, water level pattern, and land cover change in the catchment area. Further, provide a reference for the conservation of lake ecosystems. We performed a field campaign to measure river discharge and collect water samples for sediment-load laboratory analysis. We analyzed daily water level data recorded from 1989 to 2010. We obtained the time series land cover from Landsat data and performed GIS spatial analysis. Our results revealed that first, the Rebak Rinding River has the biggest contribution to lake sedimentation (3,859 tons/day, 77% of the total sediments entering the lake). Second, the water level tended to increase during the medium and extreme flood seasons. Contrary, a relatively small decrease in the water level during the medium-receding season. Third, the catchment area is 51,573 km2 (66 times larger than the lake water bodies). From 2000 to 2019, the forest decreased by 2,063 km2. As a consequence, increased erosion-sensitive area by 2,695 km2. We emphasized preserving the catchment area is vital to reduce the sedimentation rate and water fluctuation. We recommend the Rebak Rinding sub-catchment as the priority area for controlling deforestation, and erosion on the plantation, mining, and agricultural area.

Seasonal Variations of Recharge–Storage–Runoff Process over the Tibetan Plateau

Abstract The Tibetan Plateau (TP) is a vital and vulnerable water tower that supports the livelihoods of billions of people. The use of a data-driven recharge–storage–runoff perspective enables a more comprehensive estimation of multiple aspects of the water cycle. Through an analysis of the diagnostic net water flux from ERA5, water storage changes (dS/dt) from GRACE, runoff estimations (R) from the land–atmosphere water balance, and river discharge measurements (Rd), the annual cycle of recharge–storage–runoff has been studied over the TP and its basins. The net water flux determines a recharge of 326 mm yr−1 over the TP. Recharge in coupled storages, leading to an increase in water mass (dS/dt > 0) and runoff (R > 0) during the wet season, is considered the fast response and is measured using the ratio of runoff to net water flux (r1). Conversely, the slow response determined by the water storage release (dS/dt < 0) during the dry season is quantified by the ratio of storage release to runoff (r2). The ratios of r1 and r2 are influenced by climatic and terrain drivers, indicating specific characteristics of recharge–storage–runoff at the basin scale. Small r1 values and large r2 values suggest high buffer capacity, while the basin of Amu Darya (Salween) is characterized by the highest (lowest) buffer capacity over the TP. However, measurements of river discharge at Amu Darya suggest an uncoupled recharge–storage–runoff. The imbalance between river discharge and runoff estimation was most severe in the first decade of the twenty-first century but has been mitigated since 2012. River discharge at Amu Darya is likely constrained by energy during summer.

River Discharge Inversion Algorithm Based on the Surface Velocity of Microwave Doppler Radar

Non-contact methods, which are of great significance to the measurement of river discharge, can not only improve the efficiency of measurement but can also ensure the safety of equipment and personnel. However, owing to their inherent drawbacks such as the requirement of riverbed topography measurements and the difficulty in determining hydrological parameters such as equivalent roughness height, velocity index, etc., there are still challenges for measuring river discharge with high levels of efficiency and accuracy using non-contact methods. To overcome the aforementioned challenges, a new river discharge inversion method is proposed in this paper. In this method, vertical velocities are divided into inner and outer region velocities which can be described by the logarithmic law and the parabolic law, respectively. Applying the river surface velocities collected by microwave Doppler radar and the vertical velocity distributions, the water depths are estimated according to the continuity of the vertical velocities and the shear stresses, and then, the river discharges are obtained by the velocity–area method. The proposed method not only has a simple formula but also comprehensively considers the influence of different hydrological conditions, making it suitable for different river widths and water depths. In this paper, surface velocities collected by microwave Doppler radar on the Yangtze River and the San Joaquin River are used to invert the river discharge, and the results show that for wide–shallow, wide–deep, and narrow–shallow river conditions, the mean percent error (MPE) values of the discharges invertedby the proposed method are 3.91%, 3.82%, and 3.6%, respectively; the root mean square error (RMSE) values are 4.53%, 5.19%, and 4.81%, respectively; and the maximum percent error (MaPE) is less than 15%. The results prove that the proposed method can invert the river discharge with high efficiency and high accuracy under different river widths and water depths without measuring water depth in advance, making it is possible to automatically measure the river discharge in real time.

Determining discharge rating curve at Karai sub watershed

The availability of discharge rating curve equation in a watershed is very important to predict river discharge in a watershed, while discharge shown the water availability in a watershed. This research aims to determine discharge rating curve equation at Karai Sub Watershed in rainy season. This research was conducted by recording water level using water level logger and measuring river discharge using current meter and then analyze the relation of the water level and river discharge data to make the equation of discharge rating curve. The equation of discharge rating curve determined by using several methods that are polynomial, linear, power function, logaritmic and exponential. The equation which obtained by that methods will be examined by the value of coefficient determination (R2) and root mean square error (RMSE). The result shown the best methods in obtaining the equation was polynomial method which performs the R2 = 0.849 and RMSE= 0.01 with the equation Q = -1.327h2 + 3.807h - 0.215.

Reconstructing runoff components and glacier mass balance with climate change: Niyang river basin, southeastern Tibetan plateau

The southeastern part of the Tibetan Plateau (TP), one of the regions with the largest glacier distribution on the plateau, has been experiencing a significant loss in glacier mass balance (GMB) in recent decades due to climate warming. In this study, we used the Spatial Processes in Hydrology (SPHY) model and satellite data from LANDSAT to reconstruct the runoff components and glacier mass balance in the Niyang River basin (NRB). The measured river discharge data in the basin during 2000–2008 were used for model calibration and validation. Then, the validated model was applied to reconstruct the runoff components and GMB in the Niyang River basin for the period 1969–2013. Results showed that rainfall runoff (67%) was the dominant contributor to total runoff, followed by snowmelt runoff (14%), glacier melt runoff (10%), and baseflow (9%). The NRB experienced a severe loss in GMB, with a mean value of −1.26 m w. e./a (corresponding to a cumulative glacier mass loss of −56.72 m w. e.) during 1969–2013. During periods Ⅰ (1969–1983), Ⅱ (1984–1998), and Ⅲ (1999–2013) glacier mass loss was simulated at rates of −1.27 m w. e./a, −1.18 m w. e./a, and −1.33 m w. e./a, respectively. The annual loss of glacier mass in the northern region of the NRB (−1.43 m w. e./a) was significantly greater than that of the southern region (−0.53 m w. e./a) from 1969 to 2013, largely due to temperature variations, especially in summer months. These findings enhance our understanding of how different hydrological processes respond to climate change and provide a potential method to study runoff components and GMB in other glacierized catchments worldwide.

The Assessment of Sedimentation Problems in Kenyir Hydropower Reservoir, Malaysia

Lakes may take a while to respond to management interventions because of the management implications of incremental development and degradation issues. This includes the requirement for the ongoing participation of key lake basin management institutions and their operations. This study’s objective is to assess the impacts of land use activities along the Kenyir Lake Basin based on the sedimentation problem level. There are a few hydrological methods that are necessary indicators to measure the level of sediment production, such as Total Suspended Solid (TSS), area of sub-catchment, river discharge measurement, and annual sediment load production. The results showed that the sub-catchment of Besar River released the lowest annual average estimation at 3833.70 kg/km2/year, and the sub-catchment of Kenyir River produced the highest annual average estimation at 128,070.86 kg/km2/year for annual sediment load flow produced from tributary rivers into Kenyir Lake. Kenyir Lake Basin’s downstream and midstream regions had higher sediment load values than its upstream regions. This study highlighted the significance of the effects of anthropogenic factors, hydrological, geomorphological, growth, and developmental factors, and climate changes as the key variables attributing to the sedimentation phenomenon along the Kenyir Lake Basin. The construction of a long-term lake or reservoir catchment development and management plan, combined with the formation of a vision and comprehensive strategic plan, are vital components of sound management practice. The efficient implementation of the suggested watershed management programmes depends on the active involvement of all significant catchment stakeholders.

Integrated modeling of global change impacts on land and water resources

There is a common scientific understanding that global change impact analysis, mitigation, and adaptation require interdisciplinary work. Integrated modeling could help to address the challenges associated with the impacts of global change. Particularly, integrated modeling that takes feedback effects into account will allow for the derivation of climate resilient land use and land management. Here, we call for more of such integrated modeling work focusing on the interdisciplinary subject of water resources and land management. As a proof-of-concept, we tightly couple a hydrologic (SWAT) and a land use model (CLUE-s) and illustrate the benefits of this coupled land and water modeling framework (LaWaCoMo) with a scenario on cropland abandonment induced by water stress. As compared to standalone model runs of SWAT and CLUE-s for the past, LaWaCoMo performs slightly better regarding measured river discharge (PBIAS: +0.8% and +1.5% compared at two gauges) and land use change (figure of merit: +6.4% and +2.3% compared to land use maps at two points in time). We show that LaWaCoMo is suitable for global change impact analysis as it is sensitive to climate and land use inputs as well as to management decisions. Our results shed light on the importance of feedback effects between land use and hydrology to assess impacts of global change on land and water resources accurately and consistently. To facilitate that the developed methodology can serve as a blueprint for integrated modeling of global change impacts, we used two freely available models that belong to the most widely used models in their respective disciplines.

Estimating river discharge from rainfall satellite data through simple statistical models

Quantitative knowledge of river discharge measurements is essential for understanding coastal and estuarine dynamics and salinity variations. However, direct measurements are scarce for a large portion of rivers in Brazil. In this study, five simple models based on remote sensing and local rainfall datasets (MERGE) for the Ribeira de Iguape catchment are used to estimate the Valo Grande Channel (VGC) discharge on the southeastern coast of Brazil. These models use linear, quadratic, exponential, and two different multiple linear regression methods. The predicted VGC discharge time series resulting from each model is compared with the estimated time series based on in situ data from the Water and Electric Energy Department (DAEE in Portuguese). The estimated time series presented reasonable results, with skills varying from 0.84 to 0.92 and Nash–Sutcliffe efficiency (NSE) indices varying from 0.54 to 0.75, with the highest values corresponding to the multiple linear regression models. This methodology allowed us to reproduce longer time series at a daily frequency, as well as monthly averages between 2000 and 2020.

How do silicate weathering rates in shales respond to climate and erosion?

Mineral weathering, a major control on long term atmospheric CO2, can be limited by processes such as reaction kinetics, supply of fresh mineral, or water throughput in the weathering zone. In these cases, weathering fluxes increase with temperature, erosion, and runoff, respectively, and we refer to the regimes as kinetically limited (KL), erosive transport limited (ETL), and runoff limited (RL). Larger watersheds can exhibit mixtures of these behaviors in a transition regime (TR). To understand these weathering regimes, we focused on the lithology (shale) that is one of the most widespread lithologies exposed on continents globally. We identified and analyzed 142 shale watersheds across the United States, spanning a diverse range of climatic (mean annual temperature (MAT): 3–17 °C; mean annual precipitation (MAP): 220–1975 mm yr−1; potential evapotranspiration (PET): 908–2059 mm yr−1), topographic (mean catchment elevation: 78–2346 m; mean catchment slope: 0.4–28°), and hydrologic (annual runoff (q): 0.002–1.3 m yr−1) conditions. For these sites, we calculated silica fluxes (i.e., FSiO2) using SiO2 concentrations and river discharge measurements. We observed that when the humidity index (HI; MAP/PET) is <0.55, FSiO2 increases with MAP and q; however, when HI > 0.55 FSiO2, does not increase with MAP nor q. We posit that sites with HI < 0.55 are RL. The river chemistry for the RL sites is consistent with equilibrium between smectite and kaolinite. Fitting the data for sites with HI > 0.55 to an exponential temperature dependence, we find that the sensitivity of weathering to temperature is consistent with an apparent activation energy, Ea, of 56 ± 8 kJ mol−1. If sites with HI > 0.55 but average slopes <10°are removed, the value increases to 92 ± 10 kJ mol−1. This value is consistent with the Ea measured experimentally for the dissolution of the common shale clay, chlorite. To extrapolate from our measurements, we use geospatial-based definitions to classify HUC12 watersheds across the United States. This reveals that 48%, 37%, 9%, and 7% of US shale watersheds are RL, ETL, TR, and KL, respectively. Globally, we estimate that silicates weathering in shales consume 2.6 × 1012 mol CO2 yr−1, which is 22% of the total CO2 sequestered by silicate weathering.