Exploring between site differences in water quality trends: a functional data analysis approach

BackgroundA key problem in systems biology is estimating dynamical models of gene regulatory networks. Traditionally, this has been done using regression or other ad-hoc methods when the model is linear. More detailed, realistic modeling studies usually employ nonlinear dynamical models, which lead to computationally difficult parameter estimation problems. Functional data analysis methods, however, offer a means to simplify fitting by transforming the problem from one of matching modeled and observed dynamics to one of matching modeled and observed time derivatives–a regression problem, albeit a nonlinear one.ResultsWe formulate a functional data analysis approach for estimating the parameters of nonlinear dynamical models and evaluate this approach on data from two real systems, the gap gene system of Drosophila melanogaster and the synthetic IRMA network, which was created expressly as a test case for genetic network inference. We also evaluate the approach on simulated data sets generated by the GeneNetWeaver program, the basis for the annual DREAM reverse engineering challenge. We assess the accuracy with which the correct regulatory relationships within the networks are extracted, and consider alternative methods of regularization for the purpose of overfitting avoidance. We also show that the computational efficiency of the functional data analysis approach, and the decomposability of the resulting regression problem, allow us to explicitly enumerate and evaluate all possible regulator combinations for every gene. This gives deeper insight into the the relevance of different regulators or regulator combinations, and lets one check for alternative regulatory explanations.ConclusionsFunctional data analysis is a powerful approach for estimating detailed nonlinear models of gene expression dynamics, allowing efficient and accurate estimation of regulatory architecture.

Generally computational costs of reservoir and geomechanical models can be particularly high, making uncertainty evaluation and risk assessment difficult to perform. To overcome this problem, several approximation methodologies based on surrogate modelling have been developed and are commonly adopted. On the other side, Functional Data Analysis is a well-established technique in statistics but its application in reservoir uncertainty evaluation is less common. We present here a functional data analysis technique for reservoir and geomechanical models. The proposed approach, combines surrogate modelling and Functional Data Analysis to build, for a definite set of input values in the uncertainty space, a functional interpolation whose objects are functions representing the output variables in a full range of times or in a given time-space domain of interest. The methodology is particularly suited for geomechanical uncertainty assessment where the output variables are characterized by a relatively smooth behaviour and the computational cost for a direct Monte Carlo approach is very high. The methodology is first illustrated with a geomechanical uncertainty characterization problem and then through a real reservoir application. In low-dimensional uncertainty characterization studies, the proposed method makes possible to perform reliable time-space dependent risk assessment with a very limited computational cost.

This research implements two important main fields of the study which is functional data analysis and extreme value theory. The aims of this study are to convert the extreme rainfall data into functions and to propose method development for functional data analysis in extreme value theory. Functional data analysis is one of the techniques to convert or transform discrete observations into functions or curves. The daily rainfall data in Petaling Jaya from 1974 to 2003 will be tested on extreme value theory approach which is block maxima in order to practice the functional data analysis technique. The least squares and akaike criteria information method are used to smooth the fourier basis of the functional data analysis. A descriptive statistics which represents the behavior of a rainfall data for Petaling Jaya is analyzed and illustrated by a smooth curve from functional data analysis. This study indicates that there is an increase in rates of the rainfall in Petaling Jaya for the recent period compared to the last 30 years data both in the mean and standard deviation values.

Diatoms are powerful bioindicators, as each species has a specific tolerance for environmental variables, they are abundant in aquatic ecosystems and they respond rapidly to change. The use of diatoms as bioindicators is widespread especially in streams, rivers and natural lakes and is increasing in reservoirs. Typically, diatoms utilised in streams and rivers for biomonitoring consist of living benthic communities attached to rocks, while in lakes and reservoirs diatoms collected from the sediments consist of senescent planktonic diatom that have settled out of the water column. The development of diatoms as indicators in reservoirs can be problematic due to the complex hydrology and higher rates of sedimentation associated with these systems. Despite these challenges the use of diatoms in reservoir environments to develop transfer functions to infer historical changes in water quality is increasing. The development of regional datasets is important, as using indicators or transfer functions that have been developed in other areas to quantify changes in water quality does not provide accurate results. The aim of this thesis was to develop diatoms as bioindicators of water quality in freshwater reservoirs of subtropical south east Queensland (SEQ), to complement the traditional water quality monitoring across different sites. This will provide understanding of environmental drivers of diatom assemblages in this region. The diatom assemblages of reservoirs in this region have not been investigated to date and this study will provide the first investigation into their biological diversity and the water quality histories of the reservoirs. This study was undertaken in drinking water reservoirs of subtropical south east Queensland, Australia. Spatial variability of the sediment surface diatom assemblage was investigated in the Lake Wivenhoe, the largest reservoir of the region which supplies over two million people with drinking water. The diatom assemblage of surface sediments was found to vary spatially within a reservoir and aligned with zonation that is typical of reservoir environment, lacustrine, transition and riverine. Three groups of diatoms characterised the reservoir, taxa reported as cosmopolitan were found throughout, higher abundances of planktonic taxa were observed in the lacustrine zone and benthic taxa were reported in the riverine zone. Sediment samples were collected from 15 reservoirs in south east Queensland. The diatom assemblage and corresponding water quality parameters from each site were used to develop transfer functions specific for the region. Robust models were developed using weighted averaging partial least squares for conductivity and total phosphorus. The optimum and tolerances of these parameters are reported for 116 diatom taxa. Early in 2011, the largest rainfall on record took place in the Wivenhoe dam catchment which resulted in an extreme inflow into the reservoir. One core had been taken in October 2010 to determine historic changes in the diatom assemblage. Following the 2011 event another core was collected to assess the effect an extreme inflow had on the sediment record of the reservoir. Analysis of the cores revealed the impact that a high magnitude event has on the sediment record of a reservoir, with both the diatom assemblage and 210Pb profiles impacted. The diatom assemblage and 210Pb profile prior to the extreme inflow would have been insightful for reconstructing past water quality conditions and estimating sedimentation rates. However, following the inflow, diatom and 210Pb analysis should be undertaken carefully to account for the disruption to the upper sections of the sediment record caused by the extreme inflow. The construction of a new dam, Wyaralong, in SEQ provided the unique opportunity to assess the diatom assemblage as the environment changed from a stream to reservoir. Construction was completed in December 2010 and the reservoir filled within a month. A clear shift in the diatom assemblage from benthic to planktonic following infilling is seen. Additionally the collection and assessment of the sediment core provides an estimation of the sedimentation rate in this reservoir. Sediment diatom communities of freshwater reservoirs in south east Queensland are suitable for use as bioindicators of water quality parameters, in particular conductivity and total phosphorus. This work also provides a low cost estimation for rates of sedimentation. The transfer functions developed in this study provide a powerful and cost effective tool or inferring historic water quality, to be used cautiously in reservoirs known to have been impacted by large inflow events, and provide a baseline for future work using sediment surface diatom assemblages.

Addressing the intertwined challenges of food security and climate vulnerability requires robust and regionally tailored strategies for staple crops such as common beans. Although adjusting sowing dates is a key adaptive practice, spatio-temporal climate variability complicates the identification of optimal planting windows. This study integrates crop modeling with Functional Data Analysis (FDA) to quantify sowing-date-dependent yield losses for rainfed common beans across Central-Southern Brazil. The CSM-CROPGRO-Dry Bean model, driven by long-term climate data (1980–2016), soil properties, and management practices, was used to simulate yields for the BRS Estilo cultivar. FDA was subsequently applied to cluster yield-loss curves across municipalities and growing seasons, generating representative regional risk profiles. The results reveal clear spatial patterns. During the wet season, earlier sowing minimizes losses in Goiás, Minas Gerais, and western Paraná, whereas later sowing is beneficial in São Paulo, Santa Catarina, and eastern Paraná. In the dry season, earlier sowing consistently reduces losses across most regions. These patterns are primarily driven by water deficits and suboptimal temperatures during critical phenological phases. The resulting spatio-temporal sowing calendar provides an evidence-based decision-support tool to help farmers mitigate climatic risks. Moreover, it offers a scientific foundation for policymakers to refine sustainable management practices, improve crop insurance design, and enhance agricultural resilience and productivity under increasing climate uncertainty.

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Bailey et al. (2014) suggested that children's mathematical development is related more to trait characteristics than to prior mathematical development. However, their study analysis was designed to examine trait and state effects that did not vary flexibly across grades. This may lead to statistical bias in estimating the magnitude of effects, as well as educational interventions that are not targeted appropriately in time. We utilize both functional data analysis (FDA) and mixed FDA approaches to describe in detail grade-on-grade changes in the magnitude of trait and state effects. Mixed FDA methodology confirms the scientific hypotheses from Bailey et al. (2014) in a very general model setting. It acommodates both flexibly varying regression effects and testing of statistical hypotheses about them. In particular, trait terms account for 81.6% of variability in mathematical development vs. 68.2% for prior mathematical development. Additionally, of the four 'mathematical cognition' terms, the effects of simple addition and number line were not significant and these two terms were dropped out of the model. The effect of prior reading was not significant either. The effects of intelligence and prior fluency of processing the magnitudes associated with Arabic numerals were about constant over time. Skill at solving more complex addition problems became increasingly important over time, revealing an overall U-shaped pattern; central executive effect revealed an overall inverted-U pattern. With the possible exception of the central executive and complex addition, the pattern suggests that despite grade-to-grade differences in the significance of individual state and trait terms, the magnitude of the estimates of the effects of these terms is consistent across grades. Notably, in terms of relative magnitude, the regression term effects in first grade were in the same order as in 8th grade. We are thus able to answer research questions related to potential educational interventions in each grade that may improve children's mathematical development.

Daily changes in household water access and quality in urban slums undermine global safe water monitoring programmes.

The Himalayan rivers are vulnerable to devastating flooding caused by landslides and outbreak of glacial lakes. On 7 February 2021, a deadly disaster occurred near the Rishi Ganga Hydropower Plant in the Rishi Ganga River, killing more than 100 people. During the event, a large volume of debris and broken glacial fragments flooded the Rishi Ganga River and washed away the Rishi Ganga Hydropower plant ongoing project. This study presents the impact of the Chamoli disaster on the water quality of Rishi Ganga River in upstream near Tapovan and Ganga River in downstream near Haridwar through remote sensing data. Five points have been used at different locations across the two study areas and three different indices were used such as Normalized difference water index (NDWI), Normalized difference turbidity Index (NDTI), and Normalized difference chlorophyll index (NDCI), to analyze changes in water quality. Spectral signatures and backscattering coefficients derived from Sentinel-2 Optical and Sentinel-1 Synthetic-aperture radar (SAR) data were also compared to study the changes in water quality. It was evident from the water quality indices and spectral signatures that the flood plains changed significantly. Using spectral signatures and different indices, the water level in the Chilla dam canal near Haridwar was found to decreased after the Chamoli disaster event as the flood gates were closed to stop the deposit of sediments in the canal. Results suggest changes in water quality parameters (turbidity, chlorophyll concentration, NDWI) at the five locations near the deadly site and far away at Haridwar along the Ganga River. This study is a preliminary qualitative analysis showing changes in river flood plain and water quality after the Chamoli disaster.

Trends in Water Quality in Laborec River, Slovakia

The National Park Service collects water-quality samples on a rotating basis at three fixed water-quality stations in Bryce Canyon National Park (NP): Sheep Creek, Yellow Creek, and Mossy Cave Spring. Data collection began at Sheep Creek and Yellow Creek in November 2005 and at Mossy Cave in July 2008. Data on in-situ parameters, fecal-coliform samples, major ions, and nutrients are collected monthly, while trace elements are sampled quarterly. This report analyzes data from the beginning of the period of record for each station through water year 2021 to test for trends over time. Concentrations are also compared to relevant water-quality standards for the State of Utah. Overall, water quality at the park’s monitoring stations continues to be excellent, and park managers have been successful in their goal of maintaining these systems in unimpaired condition. Infrequent but continued Escherichia coli exceedances from trespass livestock at Sheep and Yellow creeks support the need for regular fence maintenance along the park boundary. High-quality conditions may qualify all three sites as Category 1 waters, the highest level of anti-degradation protection provided by the State of Utah. Minimum and maximum air temperatures at the park have increased, while precipitation remains highly variable. Increasing air temperatures have led to increasing water temperatures in Sheep and Yellow creeks. Sheep Creek also had a decrease in flow across several quantiles from 2006 to 2021, while higher flows decreased at Yellow Creek in the same period. Surface flows in these two creeks are likely to be increasingly affected by higher evapotranspiration due to warming air temperatures and possibly decreasing snowmelt runoff as the climate changes. The influx of ancient groundwater in both creek drainages helps sustain base flows at the sites. Mossy Cave Spring, which is sampled close to the spring emergence point, showed less of a climate signal than Sheep and Yellow creeks. In our record, the spring shows a modest increase in discharge, including higher flows at higher air temperatures. An uptick in visitation to Water Canyon and the Mossy Cave Trail has so far not been reflected by changes in water quality. There are additional statistical trends in water-quality parameters at all three sites. However, most of these trends are quite small and are likely ecologically negligible. Some statistical trends may be the result of instrument changes and improvements in quality assurance and quality control over time in both the field sampling effort and the laboratory analyses. Long-term monitoring of water-quality stations at Bryce Canyon NP suggests relatively stable aquatic systems that benefit from protection within the park. To maintain these unimpaired conditions into the future, park managers could consider: Regular fence checks and maintenance along active grazing allotments at the park boundary to protect riparian areas and aquatic systems from trespass livestock. Developing a springs-monitoring program to track changes in springflow at spring emergences to better understand bedrock-aquifer water supplies. These data would also help quantify springflow for use in water-rights hearings. Supporting hydrogeologic investigations to map the extent and flow paths of groundwater aquifers. Working with the State of Utah to develop groundwater-protection zones to protect groundwater aquifers from developments that would affect springs in the park. Prioritizing watershed management with proactive fire risk-reduction practices. Explicitly including watershed protection as a goal in plans for fire management and suppression. Using additional data and analyses to better understand the drivers of trends in water quality and their ecological significance. These could include higher-frequency data to better understand relationships between groundwater, precipitation, and surface flows at the sites. These could also include watershed metrics...

Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of readers, and especially those who would like apply these techniques to their research problems. It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlab languages for a set of data analyses that showcase functional data analysis techniques. The authors make it easy to get up and running in new applications by adapting the code for the examples, and by being able to access the details of key functions within these pages. This book is accompanied by additional web-based support at http://www.functionaldata.org for applying existing functions and developing new ones in either language. The companion 'fda' package for R includes script files to reproduce nearly all the examples in the book including all but one of the 76 figures.

We present a load carriage analysis for Malaysian soldier using functional data analysis (FDA) technique. The objectives of the study are to test the significance of curve registration in the analysis process flow and to investigate the effect of 10% load increment from 0% BW up to 40% BW on ground reaction force (GRF) for normal walking. Preliminary experiment on GRF was done using Vicon 1.4 motion analysis system, Kirstle and AMTI force plates and markers. Functional data analysis method was applied to analyze the data. B-spline smoothing, time normalization, landmark registration and permutation tests were performed. The result confirms that FDA is one of the best techniques in analyzing gait data. Curves registration can well distinguish the load increment and should be included in analysis sequences. The results show that 10 % BW load increment has significant effect on GRF for a Malaysian military.

A large, multiagency effort is underway in the interior Columbia River basin (ICRB) to restore salmon, trout, and char listed as threatened or endangered under the 1973 federal Endangered Species Act. Water quantity and quality are widely recognized as important components of habitat for these depleted salmonid populations. There is also broad concern about maintaining a high-quality water supply for other societal and ecosystem uses. A particularly active salmonid habitat restoration program is being conducted in the Entiat River, which drains a portion of the eastern slope of the Cascade Mountains in central Washington state. There, routine monitoring by the Washington Department of Ecology identifies pH and water temperature as water quality parameters of concern. In response, the U.S. Forest Service, Pacific Northwest Research Station is testing a more intensive approach to water quality monitoring that uses multiparameter data-logging instruments at four locations to measure fundamental water quality parameters (pH, water temperature, dissolved oxygen, and specific conductivity). This report presents results from the first 4 years of the study and discusses variation in water quality parameters with season, river discharge, and location. We demonstrate that unattended data-logging instruments effectively provide high-resolution data, which facilitate identification of forcing mechanisms such as direct solar radiation, air temperature, and river discharge. Results complement ongoing, broad-scale salmon recovery monitoring by quantifying concurrent changes in water quality. Although exploratory in nature, this study can inform future, more intensive monitoring programs.

Background:In patients who have undergone anterior cruciate ligament (ACL) reconstruction, there is a weak correlation between subjective evaluation of knee function on questionnaires and clinical or biomechanical test results.Hypothesis:Patients with lower subjective knee function will demonstrate lower ground-reaction forces (GRFs) in the operated leg and greater GRF asymmetries in both phase-specific and functional data analysis (FDA) approaches compared with patients with higher subjective knee function.Study Design:Descriptive laboratory study.Methods:The GRFs of the operated and nonoperated legs of 40 patients who previously underwent ACL reconstruction (patellar tendon) were analyzed during unilateral and bilateral countermovement jumps at a mean 2.5 years after surgery. The patients were separated into 2 groups depending on their International Knee Documentation Committee (IKDC) Subjective Form score: low IKDC and high IKDC.Results:Both phase-specific and FDA approaches showed lower GRF values in the operated compared with the nonoperated leg within the low-IKDC group during bilateral jumps. Moreover, lower GRF values were also present in the operated and nonoperated legs in the low-IKDC group compared with those of the high-IKDC group. Differences in GRFs were predominantly observed during the eccentric deceleration phase of jumping.Conclusion:Patients with previous ACL reconstruction who have limited subjective knee function have lower GRF values and greater GRF asymmetries, suggesting the use of interlimb compensation strategies.Clinical Relevance:The study results lead to a better understanding of the motor control needed during the eccentric and concentric movement phases of unilateral and bilateral jumps in patients who have undergone ACL reconstruction.

Application of functional data analysis to explore movements: walking, running and jumping - A systematic review