In many parts of South Africa, soil erosion rates are high, and likely to be exacerbated by the longer droughts and more intense rainfall that are predicted in long-term regional climate change scenarios. Suspended sediment loads (SSL) and yields (SSY) are accepted means of expressing and comparing sediment transport and soil erosion rates. Land care and water security initiatives in South Africa require these data to provide benchmarking, and trajectories of change. International researchers began in the 1970s to investigate SSL estimation approaches. These investigations typically used near-continuous turbidity data from installed probes as a surrogate for sampled SS, and auto-samplers to monitor SS concentration and develop sediment rating curves. Biophysical and socio-economic conditions in South Africa differ markedly from the northern hemisphere environments where foundational studies were conducted. SSL estimations in South Africa are associated with extreme hydrological regimes, remote study areas and lack the resources required to collect and analyse representative SS data. There is a dearth of measured SS data, and of observed SSL and SSY for South African catchments. Using measured SS data from the Tsitsa River catchment (Eastern Cape, South Africa) we found that a discharge-weighted interpolation estimator was more appropriate than regression estimators, and that SSY responses to biophysical factors were in some ways more similar to northern hemisphere norms than expected. Lack of technical, infrastructural, human and financial resources were our main constraints to monitoring and estimating SSY. Our findings highlight the challenges of, and provide some guidance for, estimating directly measured SSL in the southern Africa region and inform future research in resource scarce areas.

Glacial and proglacial erosion are important sediment sources in a river basin. The retreat of many glaciers on the Tibetan Plateau has important implications on the supply of fresh water and sediment dynamics for downstream river basins. Despite the importance of water and sediment dynamics at these catchments, existing quantification of suspended sediment fluxes from glacial catchments on the Tibetan Plateau is limited due to poor accessibility and challenging environments. This study presents the results of in-situ investigations of water discharge and suspended sediment fluxes from the Ming Yong glacial catchment in Yunnan, Southwest China, between August 2013 and July 2017. The results show that the variation in water discharge and suspended sediment was highly seasonal. The variation of average suspended sediment concentration was large – 69±45 mg/L; 119±104 mg/L; 94±97 mg/L in 2013, 2015, 2016, respectively. We estimate that the sediment yield from Ming Yong catchment was highly variable ranging from 1104 t/km 2/year in 2013to 2281 t/ km 2/year in 2016, with 65-78% of the total annual sediment load occurring during summer (June to August). These annual variations in the sediment yield can be attributed largely to precipitation patterns, or otherwise, extreme melting events. This study has provided a benchmark dataset that can be used for further works that investigate the impact of climate change on sediment dynamics in glacierized catchments in the Tibetan Plateau. Subsequently, the study let us better understand the increasing sediment supply to the Upper Mekong River from glacierized catchments.

Chesnaux (2018) distinguished between the pressure front displacement pulse and the groundwater displacement during a pumping test in a confined aquifer. The physical interpretation of the expression that Chesnaux (2018) adopted for the radial distance traveled by the pressure front is explored. It is shown that the expression adopted by Chesnaux (2018) is an implicit statement regarding the magnitude of the head change caused by pumping. The statement is consistent with the integrated effect of a continuous sequence of pulses. Alternative expressions for the migration of the pressure front and celerity are derived that are consistent with the conception of the migration of a pulse.

Channel banks can contribute a significant proportion of fine-grained (<63 µm) sediment to rivers, thereby also contributing to riverine total particulate phosphorus loads. Improving water quality through better agricultural practices alone can be difficult since the contributions from non-agricultural sources, including channel banks, can generate a ‘spatial mismatch’ between the efficacy of best management applied on farms and the likelihood of meeting environmental objectives. Our study undertook a reconnaissance survey (n=76 sites each with 3 profiles sampled) to determine the total phosphorus (TP) concentrations of channel banks across England and to determine if TP content can be predicted using readily accessible secondary data. TP concentrations adjacent field topsoils and local soil soil type/texture and geological parent material were examined as potential predictors of bank TP. Carbon and nitrogen content were also analysed to explore the impacts of organic matter content on measured TP concentrations. The results suggest that channel bank TP concentrations are primarily controlled by parent material rather than adjacent topsoils, but significant local variability in concentrations prevents the prediction of bank TP content using mapped soil type or geology. A median TP concentration of 873 mg kg -1 was calculated for the middle section of the sampled channel bank profiles, with a 25 th percentile of 675 mg kg -1, and 75 th percentile of 1159 mg kg -1. Using these concentrations and, in comparison with previously published estimates, the estimated number of inland WFD waterbodies in England for which channel bank erosion contributes >20% of the riverine total PP load increased from 15 to 25 (corresponding range of 17 to 35 using the 25 th and 75 th percentiles of measured TP concentrations). Collectively, these 25 waterbodies account for 0.2% of the total inland WFD waterbody area comprising England.

River estuaries are characterized by mixing processes between marine water masses and freshwater inflows depleted in heavier stable isotopes. Therefore, they often show a linear correlation between salinity and water isotopes (δ 18O and δ 2H values). In this study we evaluated spatial and seasonal isotope dynamics along three estuarine lagoon transects, located at the northern German Baltic Sea coast. The data show strong seasonality of isotope values, even at locations located furthest from the river mouths. They further reveal a positive and linear salinity-isotope correlation in spring, but hyperbolic and partially reverse correlations in summers. We conclude, that additional physical processes such as evaporation from the shallow lagoons, partially overprint the two-phase mixing correlation during summers. Understanding those water isotope and salinity dynamics are crucial in context of ecological studies. For example, when interpreting oxygen and hydrogen isotope data in aquatic organisms, that depend on ambient estuarine waters.

Smart drainage management to limit summer drought damage in Nordic agriculture under the circular economy conceptSyed Md Touhidul Mustafa 1, *, Kedar Ghag1, Anandharuban Panchanathan2, Bishal Dahal 1, Amirhossein Ahrari1, Toni Liedes 3, Hannu Marttila1, Tamara Avellán1, Mourad Oussalah2, Björn Klöve 1, & Ali Torabi Haghighi11Water, Energy and Environmental Engineering Research Unit, University of Oulu, P.O. Box 4300, FIN90014, Oulu, Finland2Center for Machine Vision and Signal Analysis, University of Oulu, Finland3Intelligent Machines and Systems, University of Oulu, PO Box 4200, 90014 Oulu, Finland

Headwater basins are central for meeting water management and, in humid tropical areas, essential to understand the baseflow, the discharge component that maintains water availability during the dry season, and the stormflow generated from recurrent convective clouds that can lead to flash floods. We measured field data in a typical headwater basin and four sub-basins, in subtropical climate region of Serra da Mantiqueira/South-East Brazil, with a multi-instrument hydrometeorological set (precipitation, streamflow, baseflow, stormflow, soil moisture SM, water table depth WTD), towards providing regional data, to our knowledge, hitherto non-existent, on hydrological response patterns, and variation of stormflow generation with boundary conditions and scale. Precipitation recovered in September and peaked in January concurrently with streamflow. Baseflow responded for most of the streamflow during the dry season and about half in the wettest months, and peaked ahead in March, highly covariated with WTD. In contrast, SM described a longer yearly memory, that recovered 3 months earlier than streamflow, and depleted 2 months latter in March. The monthly scale stormflow responded significantly to rainfall although with low predictability. At the event scale, revealling patterns for all basins showed thresholds of precipitation (≃ 10 mm), SM (≃45% to 57%) and WTD ≃135 cm, below which stormflow was modest. The event stormflow coeficient (eSC) reached up a maximum of 25%, albeit with large variance and little seasonality of the median. Estimates of eSC with double mass and SM thresholds showed pronounced spatial and temporal differences (3.2 to 9.6% in drier conditions and 7.7 to 15.4% wetter conditions). Mean streamflow and runoff coefficient were quite lower at the main basin (21% compared to about ≃32% between sub-basins), where there possibly exists groundwater flux exportation, that discharge on a larger spatial scale, by water exiting the basin without passing through the surface outlet.

Beavers influence hydrology by constructing woody dams. Using a before after control impact experimental design, we quantified the effects of a beaver dam sequence on the flow regime of a stream in SW England. Building upon our previous research (Puttock et al., 2021), we consider the mechanisms that underpin flow attenuation in beaver wetlands. Rainfall-driven hydrological events were extracted between 2009 and 2020, for the impacted (n=612) and control (n=634) catchments, capturing events seven years before and three years after beaver occupancy, at the impacted site. General additive models were used to describe average hydrograph geometry across all events. After beaver occupancy, Lag times increased by 55.9% and declined by 17.5% in impacted and control catchments, respectively. Flow duration curve analysis showed a larger reduction in frequency of high flows, following beaver dam construction, with declines of Q5 exceedance levels of 33% and 15% for impact and control catchments, respectively. Using event total rainfall to predict peak flow, five generalised linear models were fitted to test the hypothesis that beaver dams attenuate flow, to a greater degree, with larger storm magnitude. The best performing model showed we can have high confidence that beaver dams attenuated peak flows, with increasing magnitude, up to between 0.5-2.5 m 3 s -1 for the 94 th percentile of event total rainfall; but we cannot confidently detect attenuation beyond the 97 th percentile. Increasing flow attenuation, with event magnitude, is attributed to transient floodplain storage in low gradient/profile floodplain valleys. These findings support the assertion that beaver dams restore attenuated flows. However, with long-term datasets of extreme hydrological events lacking, it is challenging to predict the effect of beaver dams during extreme events with high precision. Beaver dams will have spatially variable impacts on hydrological processes, requiring further investigation to quantify responses to dams across differing landscapes and scales.

A document by Hanshe Lim. Click on the document to view its contents.

Modelling the response of hydrological processes to the changing climate requires the use of a chain of numerical models, each of which contributes some degree of uncertainty to the final outputs. As a result, hydrological projections, despite the progressive increase in the accuracy of the models along the chain, can still display high levels of uncertainty, especially at small temporal and spatial scales. The randomness intrinsic to climate phenomena, known as internal climate variability, is also a component contributing to the uncertainty of the hydrological projections. Unlike the uncertainties emerging from the climate and hydrological models, the internal climate variability is irreducible. In this work, we quantify and partition the uncertainty of hydrological processes in two mountainous catchments in Switzerland, emerging from climate models and internal variability, across a broad range of scales. To that end, we used high-resolution ensembles of climate and hydrological data, produced by a two-dimensional weather generator (AWE-GEN-2d) and a distributed hydrological model (Topkapi-ETH). We quantified the uncertainty in hydrological projections towards the end of the century through the estimation of the values of signal-to-noise ratios (STNR). We found small STNR values (<-1) in the projection of annual streamflow for most sub-catchments in both study sites that are dominated by the large natural variability of precipitation (explains ~70% of total uncertainty). Furthermore, we investigated in detail specific hydrological components that are critical in the model chain. For example, snowmelt or liquid precipitation exhibits robust change signals, which translates into high STNR values for streamflow during warm seasons and at higher elevations, together with a larger contribution of climate model uncertainty, suggesting that an improvement of the involved models has the potential of significantly narrowing the uncertainty. In contrast, extreme flows show low STNR values due to large internal climate variability across all elevations, which limits the possibility of narrowing their estimation uncertainty in a warming climate.

Process understanding of the interaction between streamflow, groundwater and water usages under drought are hampered by a limited number of gauging stations, especially in tributaries. Recent technological advances facilitate the application of non-commercial measurement devices for monitoring environmental systems. The Dreisam River in the South-West of Germany was affected by several hydrological drought events from 2015 to 2020, when parts of the main stream and tributaries fell dry. A flexible longitudinal water quality and quantity monitoring network was set up in 2018. Among other measurements it employs an image based method with QR codes as fiducial marker. In order to assess under which conditions the QR-code based water level loggers (WLL) deliver data according to scientific standards, we present a comparison to conventional capacitive based WLL. The results from 20 monitoring stations reveal that the riverbed was dry for > 50 \% at several locations and even for > 70 \% at most severely affected locations during July and August 2020, with the north western parts of the catchment being especially concerned. Thus, the highly variable longitudinal drying patterns of the stream reaches could be monitored. The image-based method was found to be a valuable asset for identification of confounding factors and validation of zero level occurrences. Nevertheless, a simple image processing approach (based on an automatic thresholding algorithm) did not compensate for errors due to natural conditions and technical setup. Our findings highlight that the complexity of measurement environments is a major challenge when working with image-based methods.

We examined changes in catchment-scale annual and seasonal evapotranspiration after 50% strip thinning, using runoff data from headwater catchments. The short-term water balance (STWB) method between periods from 8 to 100 days was applied to the treated (KT) and control (KC) catchments. The estimated evapotranspiration during the pre- and post-thinning periods were 840 and 910 and 780 and 860 mm/year in the catchments KT and KC, respectively. According to a paired catchment analysis of estimated evapotranspiration, monthly evapotranspiration increased from 3 to 20 mm from June to December, while it decreased from 7 to 31 mm from January to May. The estimated annual and monthly evapotranspiration was compatible with the values monitored in the plot-scale interception, canopy transpiration, and ground surface evapotranspiration. Our findings showed that the decreases in evapotranspiration due to 50% thinning were similar or different in different methods of measurement when compared with thinning in the other catchments around the world. The STWB model can evaluate the effects of timber harvesting on changes in evapotranspiration (ET), including the reproduction of seasonal patterns of ET.

Concentration-discharge (C-Q) relationships can provide insight into how catchments store and transport solutes, but analysis is often limited to long-term behavior assessed from infrequent grab samples. Increasing availability of high-frequency sensor data has shown that C-Q relationships can vary substantially across temporal scales, and in response to different hydrologic drivers. Here, we present four years of dissolved organic carbon (DOC) and nitrate-nitrogen (NO3-N) sensor data from a snowmelt- dominated catchment in the Rocky Mountains of Colorado. We assessed both the direction (enrichment vs. dilution) and hysteresis in C-Q relationships across a range of time scales, from interannual to sub-daily. Both solutes exhibited a seasonal flushing response, with concentrations initially increasing as solute stores are mobilized by the melt pulse, but then declining as these stores are depleted. The high-frequency data revealed that the seasonal melt pulse was composed of numerous individual daily melt pulses. The solute response to daily melt pulses was relatively chemostatic, suggesting mobilization and depletion to be progressive rather than episodic processes. In contrast, rainfall-induced pulses produced short-lived but substantial enrichment responses, suggesting they may activate alternative solute sources or transport pathways. The results clearly demonstrate that solute responses to individual events may differ significantly from the longer-term behavior these events combine to generate, something which only becomes apparent when high-frequency data are used.  

Accurate simulation of plant water use across agricultural ecosystems is essential for various applications, including precision agriculture, quantifying groundwater recharge, and optimizing irrigation rates. Previous approaches to integrating plant water use data into hydrologic models have relied on evapotranspiration (ET) observations. Recently, the flux variance similarity approach has been developed to partition ET to transpiration (T) and evaporation, providing an opportunity to use T data to parameterize models. To explore the value of T/ET data in improving hydrologic model performance, we examined multiple approaches to incorporate these observations for vegetation parameterization. We used ET observations from 5 eddy covariance towers located in the San Joaquin Valley, California, to parameterize orchard crops in an integrated land surface – groundwater model. We find that a simple approach of selecting the best parameter sets based on ET and T performance metrics works best at these study sites. Selecting parameters based on performance relative to observed ET creates an uncertainty of 27% relative to the observed value. When parameters are selected using both T and ET data, this uncertainty drops to 24%. Similarly, the uncertainty in potential groundwater recharge drops from 63% to 58% when parameters are selected with ET or T and ET data, respectively. Additionally, using crop type parameters results in similar levels of simulated ET as using site-specific parameters. Different irrigation schemes create high amounts of uncertainty and highlight the need for accurate estimates of irrigation when performing water budget studies.

Soil water repellency (SWR) increases surface runoff and preferential flows. Thus, quantitative evaluation of SWR distribution is necessary to understand water movements. Because the variability of SWR distribution makes it difficult to measure directly, we developed a method for estimating an SWR distribution index, defined as the areal fraction of surface soil showing SWR (SWRarea). The theoretical basis of the method is as follows: (1) SWRarea is equivalent to the probability that a position on the soil surface is drier than the critical water content (CWC); SWR is present (droplets absorbed in >10 s) when the soil surface is drier than the CWC and absent when it is wetter. (2) CWC and soil moisture content (θ) are normally distributed independent variables. (3) Thus, based on probability theory, the cumulative normal distribution of θ – CWC (f(x)) can be obtained from the distributions of CWC and θ, and f(0), the cumulative probability that θ – CWC < 0, gives the SWRarea. To investigate whether the method gives reasonable results, we repeatedly measured θ at 0–5 cm depth and determined the water repellency of the soil surface at multiple points in fixed plots with different soils and topography in a humid-temperate forest. We then calculated the CWC from the observed θ–SWR relationship at each point. We tested the normality of the CWC and θ distributions and the correlation between CWC and θ. Then, we determined f(x) from the CWC and θ distributions and estimated the SWRarea on each measurement day. Although CWC and θ were both normally distributed, in many cases they were correlated. Nevertheless, the CWC–θ dependency had little effect on the estimation error, and f(x) explained 69% of the SWRarea variability. Our findings show that a stochastic approach is useful for estimating SWRarea.

Lateral saturated soil hydraulic conductivity, Ks,l, is the soil property governing subsurface water transfer in hillslopes, and the key parameter in many numerical models simulating hydrological processes both at the hillslope and catchment scales. Likewise, the hydrological connectivity of lateral flow paths plays a significant role in determining the intensity of the subsurface flow at various spatial scales. The objective of the study is to investigate the relationship between Ks,l and hydraulic connectivity at the hillslope spatial scale. Ks,l was determined by the subsurface flow rates intercepted by drains, and by water table depths observed in a well network. Hydraulic connectivity of the lateral flow paths was evaluated by the synchronicity among piezometric peaks, and between the latter and the peaks of drained flow. Soil moisture and precipitation data were used to investigate the influence of the transient hydrological soil condition on connectivity and Ks,l. It was found that the higher was the synchronicity of the water table response between wells, the lower was the time lag between the peaks of water levels and those of the drained subsurface flow. Moreover, the most synchronic water table rises determined the highest drainage rates. The relationships between Ks,l and water table depths were highly non-linear, with a sharp increase of the values for water table levels close to the soil surface. Estimated Ks,l values for the full saturated soil were in the order of thousands of mm h-1, suggesting the activation of macropores in the root zone. The Ks,l values determined at the peak of the drainage events were correlated with the indicators of synchronicity. The sum of the antecedent soil moisture and of the precipitation was correlated with the indicators of connectivity and with Ks,l. We suggest that, for simulating realistic processes at the hillslope scale, the hydraulic connectivity could be implicitly considered in hydrological modelling through an evaluation of Ks,l at the same spatial scale.

Salt marshes are hotspots of nutrient processing en route to sensitive coastal environments. While our understanding of these systems has improved over the years, we still have limited knowledge of the spatiotemporal variability of critical biogeochemical processes within salt marshes. Sea-level rise will continue to force change on salt marsh functioning, highlighting the urgency of filling this knowledge gap. Our study was conducted in a central California estuary experiencing extensive marsh drowning and relative sea-level rise, making it a model system for such an investigation. Here we instrumented three marsh positions with different degrees of inundation (6.7%, 8.9%, and 11.2% of the time for the upper, middle, and lower marsh positions, respectively), providing locations with varied geochemical characteristics and hydrological interaction at the site. We continuously monitored redox potential (Eh) at depths of 0.1, 0.3, and 0.5 m, subsurface water levels (WL), and temperature at each marsh position to understand how drivers of subsurface biogeochemical processes fluctuate across tidal cycles, using wavelet analyses to explain the interactions between Eh and WL. We found that tidal forcing significantly affects biogeochemical processes by imparting controls on Eh variability, likely driving subsurface hydro-biogeochemistry of the salt marsh. Wavelet coherence showed that the Eh-WL relationship is non-linear, and their lead-lag relationship is variable. We found that precipitation events perturb Eh at depth over timescales of hours, even though WL show relatively minimal change during events. This work highlights the importance of high-frequency measurements, such as Eh, to help explain factors that govern subsurface geochemistry and hydrological processes in salt marshes.

Increased surface temperatures (0.7℃ per decade) in the Arctic affects polar ecosystems by reducing the extent and duration of annual snow cover. Monitoring of these important ecosystems needs detailed information on snow cover properties (depth and density) at resolutions (< 100 m) that influence ecological habitats and permafrost thaw. As arctic snow is strongly influenced by vegetation, an ecotype map at 10 m resolution was added to a method with the Random Forest (RF) algorithm previously developed for alpine environments and applied here over an arctic landscape for the first time. The topographic parameters used in the RF algorithm were Topographic Position Index (TPI) and up-wind slope index (Sx), which were estimated from the freely available Arctic DEM at 2 m resolution. Ecotypes with taller vegetation with moister soils were found to have deeper snow because of the trapping effect. Using feature importance with RF, snow depth distributions were predicted from topographic and ecosystem parameters with a root mean square error = 8 cm (23%) (R² = 0.79) at 10 m resolution for an arctic watershed (1 500 km²) in western Nunavut, Canada.