Stream Stage Research Articles

Detecting biological motion signals in human and monkey superior colliculus: a subcortical-cortical pathway for biological motion perception.

Most vertebrates, including humans, are highly adept at detecting and encoding biological motion, even when it is portrayed by just a few point lights attached to the head and major joints. However, the function of subcortical regions in biological motion perception has been scarcely explored. Here, we investigate the role of the superior colliculus in local biological motion processing. Using high-field (3 T) and ultra-high-field (7 T) functional magnetic resonance imaging, we record the neural responses of the superior colliculus to scrambled point-light walkers (with local kinematics retained) in both humans and male macaque monkeys. Results show that the superior colliculus, especially the superficial layers, selectively responds to local biological motion. Furthermore, dynamic causal modeling analysis reveals a subcortical-cortical functional pathway that transmits local biological motion signals from the superior colliculus via the middle temporal visual complex to the posterior superior temporal sulcus in the human brain. These findings suggest the existence of a cross-species mechanism in the superior colliculus that facilitates the detection of local biological motion at the early stage of the visual processing stream.

Long-term efficacy and safety of two short standardised regimens for the treatment of rifampicin-resistant tuberculosis (STREAM stage 2): extended follow-up of an open-label, multicentre, randomised, non-inferiority trial

STREAM stage 2 showed that two bedaquiline-containing regimens (a 9-month all-oral regimen and a 6-month regimen with 8 weeks of aminoglycoside) had superior efficacy to a 9-month injectable-containing regimen for rifampicin-resistant tuberculosis up to 76 weeks after randomisation. Our objective in this follow-up analysis was to assess the durability of efficacy and safety, including mortality, at 132 weeks. We report the long-term outcomes from STREAM stage 2, a randomised, phase 3 non-inferiority (10% margin) trial in participants (aged ≥15 years) with rifampicin-resistant tuberculosis without fluoroquinolone or aminoglycoside resistance at 13 clinical sites in seven countries (Ethiopia, Georgia, India, Moldova, Mongolia, South Africa, and Uganda). Participants were randomly assigned 1:2:2:2 (via permuted blocks and stratified by site and HIV status plus CD4 cell count) to the 2011 WHO long regimen (terminated early), a 9-month control regimen, a 9-month oral regimen with bedaquiline (primary comparison), or a 6-month regimen with bedaquiline and 8 weeks of an injectable antituberculous drug. Participants and clinicians were aware of treatment-group assignments, but laboratory staff were masked. The primary outcome, reported previously, was favourable status (negative cultures for Mycobacterium tuberculosis without a preceding unfavourable outcome; any death, bacteriological failure or recurrence, and major treatment change were considered unfavourable) at week 76. Here we report efficacy outcomes at week 132, analysed in the modified intention-to-treat (mITT) population. Safety assessments continued to 132 weeks and were in all participants who received at least one dose of the study regimen. All comparisons used concurrently randomised participants. This trial is registered on ISRCTN (ISRCTN18148631) and is now completed. Between March 28, 2016, and Jan 28, 2020, 588 participants were randomly assigned to the long (n=32), control (n=202), oral (n=211), or 6-month (n=143) treatment regimens; 352 (60%) were male and 236 (40%) were female. Of the 556 participants on the three shorter regimens, 517 were included in the mITT population (187 in control group, 196 in oral group, and 134 in 6-month group) and 465 in the per-protocol analyses. Six additional participants had an unfavourable outcome that occurred between week 76 and the end of efficacy follow-up (one in control group, four in oral group, one in 6-month group). In the mITT population, the proportion of patients with an unfavourable outcome at the end of follow-up was 19·6% (95% CI 14·3 to 24·9) in the oral group and 29·3% (23·3 to 36·5) in the control group (-9·7 percentage points difference [95% CI -18·7 to -1·8]; psuperiority=0·024). An estimated 9·8% (95% CI 4·6 to 14·9) of participants on the 6-month regimen had an unfavourable outcome, which was significantly lower than for those concurrently on the control regimen (32·5% [23·7 to 40·2]; psuperiority<0·0001) or the oral regimen (23·8% [16·9 to 31·1]; psuperiority=0·013). Few serious or severe adverse events were reported after week 76, with no indication of a difference between the regimens. At week 132, treatment-emergent hearing loss was recorded in significantly fewer participants on the oral regimen (7/205; 3%) than the control regimen (16/198; 8%; p=0.041); there was no significant difference in severe hearing loss between the oral regimen (6/139; 4%) and the 6-month regimen (5/143; 4%; p=0·72). Death rates were low: 1·01 (95% CI 0·48 to 2·12) per 100 person-years in participants allocated to bedaquiline (ie, oral and 6-month regimen, n=287) compared with 1·52 (0·63 to 3·66) in participants on the control regimen (n=140; p=0·49). Both of the bedaquiline-containing regimens maintained superiority to the control regimen, without evidence of increased mortality, providing two additional evidence-based treatment options for patients; previous mortality concerns for bedaquiline were not substantiated. US Agency for International Development and Janssen Research & Development.

Semi-Analytical Modeling of Transient Stream Drawdown and Depletion in Response to Aquifer Pumping.

Analytical and semi-analytical models for stream depletion with transient stream stage drawdown induced by groundwater pumping are developed to address a deficiency in existing models, namely, the use of a fixed stream stage condition at the stream-aquifer interface. Field data are presented to demonstrate that stream stage drawdown does indeed occur in response to groundwater pumping near aquifer-connected streams. A model that predicts stream depletion with transient stream drawdown is developed based on stream channel mass conservation and finite stream channel storage. The resulting models are shown to reduce to existing fixed-stage models in the limit as stream channel storage becomes infinitely large, and to the confined aquifer flow with a no-flow boundary at the streambed in the limit as stream storage becomes vanishingly small. The model is applied to field measurements of aquifer and stream drawdown, giving estimates of aquifer hydraulic parameters, streambed conductance, and a measure of stream channel storage. The results of the modeling and data analysis presented herein have implications for sustainable groundwater management.

Renewable risk assessment of heterogeneous streaming time-to-event cohorts.

The analysis of streaming time-to-event cohorts has garnered significant research attention. Most existing methods require observed cohorts from a study sequence to be independent and identically sampled from a common model. This assumption may be easily violated in practice. Our methodology operates within the framework of online data updating, where risk estimates for each cohort of interest are continuously refreshed using the latest observations and historical summary statistics. At each streaming stage, we introduce parameters to quantify the potential discrepancy between batch-specific effects from adjacent cohorts. We then employ penalized estimation techniques to identify nonzero discrepancy parameters, allowing us to adaptively adjust risk estimates based on current data and historical trends. We illustrate our proposed method through extensive empirical simulations and a lung cancer data analysis.

T-wave morphology abnormalities in the STREAM stage 1 trial

ABSTRACT Background Shorter regimens for drug-resistant tuberculosis (DR-TB) have non-inferior efficacy compared with longer regimens, but QT prolongation is a concern. T-wave morphology abnormalities may be a predictor of QT prolongation. Research design and methods STREAM Stage 1 was a randomized controlled trial in rifampicin-resistant TB, comparing short and long regimens. All participants had regular ECGs. QT/QTcF prolongation (≥500 ms or increase in ≥60 ms from baseline) was more common on the short regimen which contained high-dose moxifloxacin and clofazimine. Blinded ECGs were selected from the baseline, early (weeks 1–4), and late (weeks 12–36) time points. T-wave morphology was categorized as normal or abnormal (notched, asymmetric, flat-wave, flat peak, or broad). Differences between groups were assessed using Chi-Square tests (paired/unpaired, as appropriate). Results Two-hundred participants with available ECGs at relevant times were analyzed (QT prolongation group n = 82; non-prolongation group n = 118). At baseline, 23% (45/200) of participants displayed abnormal T-waves, increasing to 45% (90/200, p < 0.001) at the late time point. Abnormalities were more common in participants allocated the Short regimen (75/117, 64%) than the Long (14/38, 36.8%, p = 0.003); these occurred prior to QT/QTcF ≥500 ms in 53% of the participants (Long 2/5; Short 14/25). Conclusions T-wave abnormalities may help identify patients at risk of QT prolongation on DR-TB treatment. Trial Registration The trial is registered at ClinicalTrials.gov (CT.gov identifier: NCT02409290). Current Controlled Trial number, ISRCTN78372190

Deep Convolutional LSTM for improved flash flood prediction

Flooding remains one of the most devastating and costly natural disasters. As flooding events grow in frequency and intensity, it has become increasingly important to improve flood monitoring, prediction, and early warning systems. Recent efforts to improve flash flood forecasts using deep learning have shown promise, yet commonly-used techniques such as long short term memory (LSTM) models are unable to extract potentially significant spatial relationships among input datasets. Here we propose a hybrid approach using a Convolutional LSTM (ConvLSTM) network to predict stream stage heights using multi-modal hydrometeorological remote sensing and in-situ inputs. Results suggest the hybrid network can more effectively capture the specific spatiotemporal landscape dynamics of a flash flood-prone catchment relative to the current state-of-the-art, leading to a roughly 26% improvement in model error when predicting elevated stream conditions. Furthermore, the methodology shows promise for improving prediction accuracy and warning times for supporting local decision making.

Quantifying hydrological responses to monsoon‐controlled precipitation across the soil‐groundwater‐stream continuum with long‐term high‐frequency hydrometric monitoring

AbstractStream water, groundwater and soil water in the riparian zone are closely linked. Their responses to rainfall events controlled by monsoon climate are variable and intertwined, which are still not well known. To address this knowledge gap, we established a monitoring transect adjacent to a headwater stream in Huashan Catchment, eastern China, with typical monsoon climate. We monitored precipitation, stream stage, groundwater level and soil moisture content at intervals of maximum 30 min. We then conducted an event‐based analysis of rainfall event characteristics and diverse response metrics, and assessed their correlations and interrelationships through correlation and regression analysis. Our 2‐year monitoring results show that water level responses occurred in most rainfall events. They had smaller threshold of rainfall amount and timing but longer time to peak response. Stream responses exhibited smaller response magnitude and intensities than groundwater responses. Rainfall amount and event duration were the most critical driving factors for groundwater responses. Soil moisture responses varied with depth. Only large storms could propagate into topsoil and generate rapid responses. Middle soil moisture responses had more frequent response occurrence and more variable response magnitude, while deep soil moisture responses had smaller response magnitude, longer time to peak response and larger wetting front movement velocity. Attenuated initial response timing with depth identified preferential flow, reflecting heterogeneity in the soil profile. Monsoon‐controlled heavy rainfall improved hydrologic connectivity in the soil‐groundwater‐stream continuum (SGSC), mediating the influence of heterogeneity on soil moisture responses and potentially contributing more subsurface flow to catchment runoff. Overall, this study aimed to reveal the mechanism of hydrological responses to monsoon‐controlled precipitation across the SGSC.

Radiographic characteristics of rifampicin-resistant tuberculosis in the STREAM stage 1 trial and their influence on time to culture conversion in the short regimen

BackgroundStage 1 of the STREAM trial demonstrated that the 9 month (Short) regimen developed in Bangladesh was non-inferior to the 20 month (Long) 2011 World Health Organization recommended regimen. We assess the association between HIV infection and radiographic manifestations of tuberculosis and factors associated with time to culture conversion in Stage 1 of the STREAM trial.MethodsReading of chest radiographs was undertaken independently by two clinicians, and films with discordant reading were read by a third reader. Recording of abnormal opacity of the lung parenchyma included location (right upper, right lower, left upper, and left lower) and extent of disease (minimal, moderately-advanced, and far advanced). Time to culture conversion was defined as the number of days from initiation of treatment to the first of two consecutive negative culture results, and compared using the log-rank test, stratified by country. Cox proportional hazards models, stratified by country and adjusted for HIV status, were used to identify factors associated with culture conversion.ResultsOf the 364 participants, all but one had an abnormal chest X-ray: 347 (95%) had opacities over upper lung fields, 318 (87%) had opacities over lower lung fields, 124 (34%) had far advanced pulmonary involvement, and 281 (77%) had cavitation. There was no significant association between HIV and locations of lung parenchymal opacities, extent of opacities, the presence of cavitation, and location of cavitation. Participants infected with HIV were significantly less likely to have the highest positivity grade (3+) of sputum culture (p = 0.035) as compared to participants not infected with HIV. Cavitation was significantly associated with high smear positivity grades (p < 0.001) and high culture positivity grades (p = 0.004) among all participants. Co-infection with HIV was associated with a shorter time to culture conversion (hazard ratio 1.59, 95% CI 1.05–2.40).ConclusionsRadiographic manifestations of tuberculosis among the HIV-infected in the era of anti-retroviral therapy may not differ from that among those who were not infected with HIV. Radiographic manifestations were not consistently associated with time to culture conversion, perhaps indicating that the Short regimen is sufficiently powerful in achieving sputum conversion across the spectrum of radiographic pulmonary involvements.Trial registrationISRCTN ISRCTN78372190. Registered 14/10/2010. The date of first registration 10/02/2016.

Rating curve development and uncertainty analysis in mountainous watersheds for informed hydrology and resource management

Accurate measurement of continuous stream discharge poses both excitement and challenges for hydrologists and water resource planners, particularly in mountainous watersheds. This study centers on the development of rating curves utilizing the power law at three headwaters of the lesser Himalayas—Aglar, Paligaad, and Balganga—through the installation of water level recorders for stage measurement and salt dilution for discharge measurement from 2014 to 2016. The stream stage–discharge relationship, crucially known as the rating curve, is susceptible to numerous factors in mountainous watersheds that are often challenging to comprehend or quantify. Despite significant errors introduced during the rating curve development, such as stemming from observations, modeling, and parameterization, they are frequently overlooked. In this study, acknowledging the inherent uncertainty, we employ the maximum-likelihood method to assess uncertainty in the developed rating curve. Our findings reveal substantial inconsistency in the stage–discharge relationship, particularly during high flows. A novel contribution of this study is introducing a weighing factor concept that correlates uncertainty with the morphological parameters of the watershed. The higher value of the weighting factor in Paligaad (0.37) as compared to Balganga (0.35) and less in the case of Aglar (0.27) will have more uncertainty. The authors contend that precise rating curves and comprehensive uncertainty analyses can mitigate construction costs, foster robust decision-making, and enhance the perceived credibility of decisions in hydrology and water resource management.

Predicting Streamflow Duration From Crowd‐Sourced Flow Observations

AbstractStreamflow duration is important for aquatic ecosystems and assigning stream protection status. This study predicts streamflow duration, represented as the fraction of time with flow each year, using a combination of sensor data and crowd‐sourced visual observations for a study area in northern Colorado, USA. We used 11 stream stage sensors and 177 visual monitoring points to examine how frequently streams should be sampled to compute flow fractions accurately. This showed that the number of visual observations needed to compute accurate flow fractions increases with decreasing flow duration. We then developed random forest models to predict mean annual flow fractions using climate, topographic, and land cover predictors and found that snow persistence, summer precipitation, and drainage area were important predictors. Model performance was best when using sites with ≥10 visual observations. Our model predicts that almost all (98%) of streams in the study region are non‐perennial, about 10% more than the amount of non‐perennial streams in the National Hydrography Dataset. Stream type maps are sensitive to the time period of data collection and to thresholds used to represent perennial versus non‐perennial flow. To improve maps of non‐perennial streams, we recommend moving beyond categorical classification of streams to a continuous variable like flow fraction. These efforts can be best supported with frequent observations in time that span streams with a wide range of flow fractions and drainage area attributes.

Stream temperature responses to forest harvesting with different riparian buffer prescriptions in northern California, USA

Forested riparian zones adjacent to headwater streams provide unique habitat attributes and influence water quantity and quality. Forest harvesting adjacent to and within these zones has led to changes in stream temperature (Ts) and impacts on aquatic ecosystems. As such, policies and regulations have sought to limit forest management activities in riparian zones; however, water temperature responses have been variable, necessitating additional research to improve our understanding of the effectiveness of contemporary riparian harvesting prescriptions in limiting water temperature increases after harvest. We sought to quantify the effects of three different riparian buffer prescriptions with increasing intensity of basal area removal (2–43% area harvested) on Ts in forested headwaters in northern California, USA. We measured Ts in 18 headwater catchments (12 harvested, 6 six unharvested references) during a pre-harvest year and two post-harvest years using 12 thermistors distributed longitudinally down each stream (i.e., 216 total sensors). We analyzed the Ts data to assess (1) the seasonal variability of seven-day moving average of daily maximum stream temperature (T7-day-max) and (2) the relative importance of the different harvesting prescriptions and catchment physiographic characteristics in influencing the T7-day-max. Our analysis indicated substantial changes in basal area and shade in the riparian areas with the most intensive harvesting treatment (i.e., 50% reduction in canopy cover). However, these changes in riparian canopy were poorly related to stream temperature. Results indicated a median T7-day-max increase of ∼ 2 °C in the sites with the most intensive harvesting treatment. The greatest changes in seasonal T7-day-max occurred during the summer and fall but only during the first year after harvesting. There was no evidence of increases in T7-day-max during the second post-harvest year. While air temperatures in the riparian areas increased by 1–5 °C after harvesting, this warming did not directly transfer to strong warming in stream temperatures. Rather, random forest models revealed that T7-day-max was more strongly related to topography (i.e., elevation) and climatic variability (i.e., changes in precipitation and stream stage) than to the riparian harvesting prescription or the harvesting period. Our study further highlights the challenges in understanding the thermal regimes of headwater streams and their responses to forest disturbances. Predictions of stream temperature responses to forest disturbances are complicated by the heterogeneity of the factors that influence this important physical water quality parameter. However, with global climate change and increasing pressures on water resources and aquatic ecosystems it is increasingly important to continue to provide insights into the relationships between forest management activities and the thermal regimes of headwater streams.

Cost of digital technologies and family-observed DOT for a shorter MDR-TB regimen: a modelling study in Ethiopia, India and Uganda

BackgroundIn 2017, the WHO recommended the use of digital technologies, such as medication monitors and video observed treatment (VOT), for directly observed treatment (DOT) of drug-susceptible TB. The WHO’s 2020 guidelines extended these recommendations to multidrug-resistant tuberculosis (MDR-TB), based on low evidence. The impact of COVID on health systems and patients underscored the need to use digital technologies in the management of MDR-TB.MethodsA decision-tree model was developed to explore the costs of several potential DOT alternatives: VOT, 99DOTS (Directly-observed Treatment, Short-course) and family-observed DOT. Assuming a 9-month, all-oral regimen (as evaluated within the STREAM trial), we constructed base-case cost models for the standard-of-care DOTs in Ethiopia, India, and Uganda, as well as for the three alternative DOT approaches. The models were populated with STREAM Stage 2 clinical trial outcome and cost data, supplemented with market prices data for the digital DOT strategies. Sensitivity analyses were conducted on key parameters.ResultsModelling suggested that the standard-of-care DOT approach is the most expensive DOT strategy from a societal perspective in all three countries evaluated (Ethiopia, India, Uganda), with considerable direct- and indirect-costs incurred by patients. The second most expensive DOT approach is VOT, with high health-system costs, largely caused by up-front technology expenditure.Each of VOT, 99DOTS and family-observed DOT would reduce by more than 90% patients’ direct and indirect costs compared to standard of care DOT.Results were robust to the sensitivity analyses.ConclusionsWhile data on the costs and efficacy of alternative DOT approaches in the context of shorter MDR-TB treatment is limited, our modelling suggests alternative DOT approaches can significantly reduce patient costs in all three countries. Health system costs are higher for VOT and lower for 99DOTS and family-observed therapy when compared to standard of care DOT, as low smartphone penetration and internet availability requires the VOT health system to fund the cost of making them available to patients.

Geostatistical inverse modeling to characterize the transience of streambed hydraulic conductivity

Quantitative investigation of the interaction between surface water and groundwater relies on the determination of transience of streambed hydraulic conductivity (Ksb). The commonly used successive inversion approach (i.e., the inversion is repeated over successive time steps) of interpreting aquifer hydraulic response data belongs to different optimization windows consists of a sizable number of inversion sub-processes and tends to lose sharp changes in Ksb. This study treats the transience of a parameter in the time domain as the heterogeneity in 1D space domain and uses geostatistical inverse modeling to characterize such transience. The methodology is first tested through a group of ten synthetic cases with independently generated random transient patterns of Ksb. Results of these synthetic cases reveal the capability of geostatistical inverse modeling to effectively characterize the general varying pattern as well as sharp changes in Ksb. Subsequently, the methodology is applied to interpret the aquifer hydraulic response data measured at the Rhône River site, Town of Fully, Switzerland. A significant improvement in model calibration is observed when the methodology is compared to the successive inversion approach. The field investigation reveals that the transience of in-situ Ksb is closely related to stream stage variations. Particularly, multiple occurrences of sharp increases and decreases in Ksb appear when the stream stage lowers below and rises above the aquifer head. The driving mechanism for these sharp variation events is that fine-grained sediments within the streambed can be partly washed away when the aquifer water flows toward the river, and vice versa. The geostatistical approach has the potential to help investigate other physical or chemical processes in groundwater hydrology associated with transient changes in Ksb.

A comparison of spatial and temporal drivers of stream metabolism

Abstract Stream metabolism provides insight into the functional processes that regulate trophic status, biomass, and nutrient cycling in streams. Comparative (spatial) analyses of streams generally do not account for shifting at‐site controls on stream metabolism over time and, thus, may not identify the primary controls on cross‐site differences in trophic status, biomass, and nutrient cycling over longer time scales. The spatial component included assessing environmental factors controlling stream metabolism (daily values) during a summer low‐flow period (August) at 17 wadable stream sites in four regions of the United States. Explanatory variables for the spatial analysis included discrete nutrients and physical parameters. The temporal component included assessing 12 of the 17 sites with more than 90 days of stream metabolism values, and continuous nitrate, photosynthetically active radiation (PAR), turbidity, maximum water temperature (°C) and stream stage (water surface elevation). Spatial analysis at the 17 sites during August (31 days) found that average gross primary production (GPP) ranged from 0.1 to 4 g O2 m−2 day−1 and ecosystem respiration (ER) from 0.37 to 6.4 g O2 m−2 day−1. Sites were primarily heterotrophic; however, some sites varied from autotrophic to heterotrophic daily. Multiple regression indicated that GPP was a function of orthophosphate, percent canopy cover, and the number of days since a high flow (R2 = 0.51), whereas ER was primarily a function of GPP (R2 = 0.40). Temporal patterns in daily stream metabolism were evaluated using at‐site autoregressive models at 12 streams with relatively complete, continuous records. PAR, nitrate and maximum water temperature were the dominant variables influencing GPP, and water depth and nitrate were the most common explanatory variables for ER models. The autoregressive components (i.e., GPP or ER for the previous day) had a strong influence on both GPP and ER except after spates, indicating that biomass may be the dominant control on metabolism rather than variability in environmental factors during stable‐flow periods. We found two dominant temporal metabolism regimes: a seasonal pattern with elevated spring metabolism followed by low stable summer metabolism and a temporally disturbed pattern which tended to occur in streams with frequent spates. These patterns were not indicated by differences in metabolism among streams during stable low‐flow conditions. Because streams are generally heterotrophic with only limited periods when production may be high, comparative analyses must estimate stream metabolism over a time scale representing at‐site spatial variability and account for controls on periods of high production to adequately characterise differences between streams.

Characterizing basin-scale subsurface hydraulic heterogeneity with multiscale geological and hydrological measurements

Mapping aquifer heterogeneity is a pressing need for managing regional groundwater resources. Many studies have shown that combining hydraulic tomographic surveys with point-scale geological information is viable for detailing meter-scale to kilometer-scale hydraulic heterogeneity of aquifers. However, due to the complexity of aquifer systems, few field investigations have been conducted on basin-scale systems. In this study, we collected datasets of stream stages, groundwater levels, and borehole logs from 35 wells in a river plain during the wet season, when flood events altered the groundwater flow fields. We then analyzed these datasets using correlation analysis and a geostatistical inverse model. The hydraulic transmissivity and storage coefficient distributions were inverted based on different numbers of geological zones. By validating the estimated parameter fields with independent datasets, we demonstrated that appropriate selection of the number of geological zones, using point-scale geological information and clustering, improved the estimated fields. Further increasing the number of zones beyond an appropriate number deteriorated the estimates at the basin-scale site. The proposed method offers a cost-effective approach for basin-scale characterization. The better knowledge of subsurface hydraulic heterogeneity can support water resource management decisions.

Influence of Critical Zone Architecture and Snowpack on Streamflow Generation Processes: A Mountain‐Meadow Headwater System in a Mediterranean Climate

AbstractObservations from a granitic watershed within a Mediterranean climate reveal the hydrologic and critical zone functioning of a perennial stream headwater and its upslope contributing area within a meadow system in the Sierra Nevada, California. Chemical analysis (diagnostic tools of mixing models, end member mixing analysis, tritium, etc.) and physical data (stream stage, piezometers, soil water, snowpack, etc.) indicate there are two primary pathways of water input into a headwater stream sourced from a mountain meadow. One input is a shallower and younger subsurface pathway with water that resembles snowpack chemistry, and the other a deeper and older subsurface pathway with water that reflects the chemistry of the groundwater derived from the contributing hillslopes. Multi‐year observations reveal that regardless of snowpack amount, during the period of peak hillslope infiltration, shallow and deep pathways in the hillslope behave similarly to initiate headwater streams. However, during summer dry periods, similarities in active pathways within the meadow center are not maintained between high and low snowpack years. With less snow, perennial groundwater discharge within the meadow center is eliminated, becoming only a seasonal source at the meadow's outlet. At the meadow's edge, geophysically observed downslope thinning in saprolite thickness creates reduced lateral transmissivity and initiation points for headwater streams via enhanced groundwater discharge of upslope water. Combined, these findings suggest how loss of snowpack and critical zone structure can together mediate hydrologic function in a wet meadow system in a Mediterranean climate. Creating new understanding about the stability of hydraulic functioning in headwater wet‐meadow systems under a changing climate.

Counting piglet suckling events using deep learning-based action density estimation

Analysis of piglet suckling behaviour is important for the evaluation of piglet nutrient ingestion, health, welfare, and affinity with the sow. In this study, an action density estimation network (ADEN) was proposed for counting the events of piglet suckling followed by automated analysis of suckling behaviour. ADEN is a two-stream network primarily composed of 1) a network stream that processes video images with a higher frame rate (faster stream) and 2) a network stream that processes video images with a lower frame rate (slower stream). Each stream consists of a ResNet-50 with five convolutional stages. A multi-stage attention connection (MSAC), composed of four Spatial-Temporal-Channel (STC) multi-attention structures, is proposed to bridge Faster Stream and Slower Stream and capture discriminative features. The output attention features from each faster stream stage are laterally fused into the corresponding slower stream stage in a concatenating manner. Following this, the features from the last convolutional stages in the Slow stream and Fast stream are fused using concatenation and are then decoded by using three convolutional layers. The last convolutional layer outputs a heatmap on the action density of piglet suckling behaviour. Finally, the number of suckling events is predicted by integrating all the pixel values in the heatmap. Experimental and comparative tests were conducted to validate the effectiveness of the proposed ADEN with a training dataset and a test dataset from 14 pig pens. The 507 video clips (126,750 images for 7 h) from the 1-9th pens were selected as training datasets. The 143 video clips (35,750 images for 2 h) from the 10-13th pens were selected as short-term test datasets. One untrimmed video (162,000 images for 9 h) from the 14th pen was used to ultimately evaluate the action density estimation performance of the ADEN. ADEN was compared with seven approaches and its superiority was demonstrated with an r = 0.938, an RMSE = 1.080, and a MAE = 0.967 in short video clips and r = 0.982, MAE = 0.161, and RMSE = 0.563 in the untrimmed long video. The ADEN proved it feasible to predict the number of suckling events by using action density estimation.

A proposal of hazard analysis method using structured system theoretical process analysis

System Theoretic Process Analysis (STPA) is a method for analyzing hazards caused by interactions between components of an industrial product. STPA is applied in the upper stream stages of industrial product development, STPA detects hazards while referring to the whole configuration of the industrial product. Therefore, STPA generally does not deal with detailed information about the industrial product. Since the information on the industrial product is insufficient, it is difficult to clarify the factors of hazards, the occurrence order of factors, and the conditions that occur the hazard by STPA. Therefore, the following methods were added to the conventional STPA; the method of describing the components of industrial products in hierarchical detail, the method of clearly defining the behaviour of each component, and the method of tracking the structured CSD to clarify the causes of the hazard. By adding those methods, it became possible to conduct a hazard analysis of the industrial product in detail. As a result of applying the proposed method to the existing railroad crossing control system, it was confirmed that the proposed method could detect more factors of hazards and create adequate scenarios from the occurrence of hazard causes to the occurrence of the hazard.

Multiple timescales of streambed flux variability in two perennial mountain‐front streams

AbstractStreambed fluxes are highly variable through time and space, having a range implications for stream‐aquifer processes. This study investigated streambed fluxes over a 3‐year study period to characterize short‐ and long‐term variations and related implications for seepage recharge and hyporheic exchange. Time series of streambed fluxes were estimated through Darcy‐based methods using water level and temperature inputs from shallow (&lt;1.5 m) nested streambed piezometers installed in two mountain‐front streams in Colorado, USA. Three predominant temporal scales of variability were characterized: sub‐daily (&lt;1 day), daily (&gt;1 day; &lt;1 year), and interannual (&gt;1 year). Temporal variability was quantified using the median absolute deviation (MAD), a statistical measure that is resistant to extreme values associated with short‐duration events. Sub‐daily variability (MADS‐D) was related to ET, temperature‐induced changes in hydraulic conductivity, and variable stream stage, and was quantified using the MAD of detrended fluxes (daily mean subtracted). Daily variability (MADD), calculated as the MAD of daily median fluxes for a given year, exceeded sub‐daily variability, and was influenced by strong seasonality at some sites. For individual sites and water years, the ratio of MADS‐D to MADD ranged from 0.03 to 0.70, with an average of 0.25. Annual median fluxes at each site varied across years, but typically remained consistent in order of magnitude and direction. Results reveal a strong linear correlation between the daily variability and the median annual flux at individual sites. Within a year, summer months characterized by stronger losing conditions showed greater overall variability. 1D numerical heat and flow modelling was performed to calibrate hydraulic parameters and to investigate temperature‐related controls for sub‐daily variations. We discuss implications of documented temporal variability for analyses of hyporheic exchange and groundwater recharge. Results provide a basis for quantifying temporal variations in streambed fluxes and highlight the extent to which fluxes vary over multiple timescales.

Camera-based intelligent stream stage sensing for decentralized environmental monitoring

AbstractAccurate, vast, and real-time coverage of water level monitoring is crucial for the advancement of environmental research, specifically in the areas of climate change, water distribution, and natural disaster preparedness and management. The current state of the monitoring network requires an immediate solution to produce low-cost and accurate water level measurement sensors. This research presents a novel methodology for intelligent stream stage measurement, creating a distinct opportunity for a low-cost, camera-based embedded system that will measure water levels and share surveys to support environmental monitoring and decision-making. It is implemented as a stand-alone device that utilizes a registry of structures and points of interest (POI) along with the core modules of the application logic: (1) deep-learning powered water segmentation; (2) visual servoing; and (3) POI geolocation computation. The implementation relies on a Raspberry-Pi with a motorized camera for automated measurements and is supported by a Proportional–Integral–Derivative controller and multiprocessing. For future work, the involvement of the camera supports further use cases such as recognizing objects (e.g., debris, trees, humans, and boats) on the water surface. Additionally, the method shown can be made into a Progressive Web Application (PWA) that can be used on smartphones to allow crowdsourced citizen science applications for environmental monitoring.