Temporal dynamics of hydrological threshold events

International audienceThe episodic nature of hydrological flows such as surface runoff and preferential flow is a result of the nonlinearity of their triggering and the intermittency of rainfall. In this paper we examine the temporal dynamics of threshold processes that are triggered by either an infiltration excess (IE) mechanism when rainfall intensity exceeds a specified threshold value, or a saturation excess (SE) mechanism governed by a storage threshold. We analytically derive probabilistic measures of the time between successive events in each case, and in the case of the SE triggering, we relate the statistics of the time between events to the statistics of storage and the underlying water balance. In the case of the IE mechanism, the temporal dynamics of flow events is shown to be simply scaled statistics of rainfall timing. In the case of the SE mechanism the time between events becomes structured. With increasing climate aridity the mean and the variance of the time between SE events increases but temporal clustering, as measured by the coefficient of variation (CV) of the inter-event time, reaches a maximum in deep stores when the climatic aridity index equals 1. In very humid and also very arid climates, the temporal clustering disappears, and the pattern of triggering is similar to that seen for the IE mechanism. In addition we show that the mean and variance of the magnitude of SE events decreases but the CV increases with increasing aridity. The CV of inter-event times is found to be approximately equal to the CV of the magnitude of SE events per storm only in very humid climates with the CV of event magnitude tending to be much larger than the CV of inter-event times in arid climates. In comparison to storage the maximum temporal clustering was found to be associated with a maximum in the variance of soil moisture. The CV of the time till the first saturation excess event was found to be greatest when the initial storage was at the threshold

Exploring the physical controls of regional patterns of flow duration curves – Part 2: Role of seasonality, the regime curve, and associated process controls

The goal of this paper is to explore the process controls underpinning regional patterns of variations of streamflow regime behavior, i.e., the mean seasonal variation of streamflow within the year, across the continental United States. The ultimate motivation is to use the resulting process understanding to generate insights into the physical controls of another signature of streamflow variability, namely the flow duration curve (FDC). The construction of the FDC removes the time dependence of flows. Thus in order to better understand the physical controls in regions that exhibit strong seasonal dependence, the regime curve (RC), which is closely connected to the FDC, is studied in this paper and later linked back to the FDC. To achieve these aims a top-down modeling approach is adopted; we start with a simple two-stage bucket model, which is systematically enhanced through addition of new processes on the basis of model performance assessment in relation to observations, using rainfall-runoff data from 197 United States catchments belonging to the MOPEX dataset. Exploration of dominant processes and the determination of required model complexity are carried out through model-based sensitivity analyses, guided by a performance metric. Results indicated systematic regional trends in dominant processes: snowmelt was a key process control in cold mountainous catchments in the north and north-west, whereas snowmelt and vegetation cover dynamics were key controls in the north-east; seasonal vegetation cover dynamics (phenology and interception) were important along the Appalachian mountain range in the east. A simple two-bucket model (with no other additions) was found to be adequate in warm humid catchments along the west coast and in the south-east, with both regions exhibiting strong seasonality, whereas much more complex models are needed in the dry south and south-west. Agricultural catchments in the mid-west were found to be difficult to predict with the use of simple lumped models, due to the strong influence of human activities. Overall, these process controls arose from general east-west (seasonality) and north-south (aridity, temperature) trends in climate (with some exceptions), compounded by complex dynamics of vegetation cover and to a less extent by landscape factors (soils, geology and topography)

Exploring the physical controls of regional patterns of flow duration curves – Part 1: Insights from statistical analyses

The flow duration curve (FDC) is a classical method used to graphically represent the relationship between the frequency and magnitude of streamflow. In this sense it represents a compact signature of temporal runoff variability that can also be used to diagnose catchment rainfall-runoff responses, including similarity and differences between catchments. This paper is aimed at extracting regional patterns of the FDCs from observed daily flow data and elucidating the physical controls underlying these patterns, as a way to aid towards their regionalization and predictions in ungauged basins. The FDCs of total runoff (TFDC) using multi-decadal streamflow records for 197 catchments across the continental United States are separated into the FDCs of two runoff components, i.e., fast flow (FFDC) and slow flow (SFDC). In order to compactly display these regional patterns, the 3-parameter mixed gamma distribution is employed to characterize the shapes of the normalized FDCs (i.e., TFDC, FFDC and SFDC) over the entire data record. This is repeated to also characterize the between-year variability of "annual" FDCs for 8 representative catchments chosen across a climate gradient. Results show that the mixed gamma distribution can adequately capture the shapes of the FDCs and their variation between catchments and also between years. Comparison between the between-catchment and between-year variability of the FDCs revealed significant space-time symmetry. Possible relationships between the parameters of the fitted mixed gamma distribution and catchment climatic and physiographic characteristics are explored in order to decipher and point to the underlying physical controls. The baseflow index (a surrogate for the collective impact of geology, soils, topography and vegetation, as well as climate) is found to be the dominant control on the shapes of the normalized TFDC and SFDC, whereas the product of maximum daily precipitation and the fraction of non-rainy days was found to control the shape of the FFDC. These relationships, arising from the separation of total runoff into its two components, provide a potential physical basis for regionalization of FDCs, as well as providing a conceptual framework for developing deeper process-based understanding of the FDCs

Socio-hydrologic drivers of the pendulum swing between agricultural development and environmental health: A case study from Murrumbidgee River basin, Australia

This paper presents a case study centred on the Murrumbidgee River basin in eastern Australia. It illustrates the dynamics of the balance between water extraction and use for food production, and efforts to mitigate and reverse consequent degradation of the riparian environment. In particular, the paper traces the history of a pendulum swing between an exclusive focus on agricultural development and food production in the initial stages and its attendant socio-economic benefits, followed by the gradual realization of the adverse environmental impacts, subsequent efforts to mitigate these with the use of remedial measures, and ultimately concerted efforts and externally imposed solutions to restore environmental health and ecosystem services. The 100-year history of development within the Murrumbidgee is divided into four eras, each underpinned by the dominance of different values and norms and turning points characterized by their changes. The various stages of development can be characterized by the dominance, in turn, of infrastructure systems, policy frameworks, economic instruments, and technological solutions. The paper argues that, to avoid these costly pendulum swings, management needs to be underpinned by long-term coupled socio-hydrologic system models that explicitly include the two-way coupling between human and hydrological systems, including the slow evolution of human values and norms relating to water and the environment. Such coupled human-water system models can provide insights into dominant controls of the trajectory of their co-evolution in a given system, and can also be used to interpret patterns of co-evolution of such coupled systems in different places across gradients of climatic, socio-economic and socio-cultural conditions, and in this way to help develop generalizable understanding. © 2014 Author(s)

An optimality-based model of the coupled soil moisture and root dynamics

The main processes determining soil moisture dynamics are infiltration, percolation, evaporation and root water uptake. Modelling soil moisture dynamics therefore requires an interdisciplinary approach that links hydrological, atmospheric and biological processes. Previous approaches treat either root water uptake rates or root distributions and transpiration rates as given, and calculate the soil moisture dynamics based on the theory of flow in unsaturated media. The present study introduces a different approach to linking soil water and vegetation dynamics, based on vegetation optimality. Assuming that plants have evolved mechanisms that minimise costs related to the maintenance of the root system while meeting their demand for water, we develop a model that dynamically adjusts the vertical root distribution in the soil profile to meet this objective. The model was used to compute the soil moisture dynamics, root water uptake and fine root respiration in a tropical savanna over 12 months, and the results were compared with observations at the site and with a model based on a fixed root distribution. The optimality-based model reproduced the main features of the observations such as a shift of roots from the shallow soil in the wet season to the deeper soil in the dry season and substantial root water uptake during the dry season. At the same time, simulated fine root respiration rates never exceeded the upper envelope determined by the observed soil respiration. The model based on a fixed root distribution, in contrast, failed to explain the magnitude of water use during parts of the dry season and largely over-estimated root respiration rates. The observed surface soil moisture dynamics were also better reproduced by the optimality-based model than the model based on a prescribed root distribution. The optimality-based approach has the potential to reduce the number of unknowns in a model (e.g. the vertical root distribution), which makes it a valuable alternative to more empirically-based approaches, especially for simulating possible responses to environmental change

An optimality-based model of the dynamic feedbacks between natural vegetation and the water balance

The hypothesis that vegetation adapts optimally to its environment gives rise to a novel framework for modeling the interactions between vegetation dynamics and the catchment water balance that does not rely on prior knowledge about the vegetation at a particular site. We present a new model based on this framework that includes a multilayered physically based catchment water balance model and an ecophysiological gas exchange and photosynthesis model. The model uses optimization algorithms to find those static and dynamic vegetation properties that would maximize the net carbon profit under given environmental conditions. The model was tested at a savanna site near Howard Springs (Northern Territory, Australia) by comparing the modeled fluxes and vegetation properties with long-term observations at the site. The results suggest that optimality may be a useful way of approaching the prediction and estimation of vegetation cover, rooting depth, and fluxes such as transpiration and CO2 assimilation in ungauged basins without model calibration

DYSMENORRHEA AMONG FEMALE MEDICAL SCIENCES STUDENTS IN MACHS: PREVALENCE, PREDICTORS AND OUTCOME

Objective: This study intended to determine the prevalence, predictors, and outcome of dysmenorrhea among female medical sciences students at Mohammed Al-Mana College for Medical Sciences (MACHS), Dammam, Saudi Arabia. Methods: A cross-sectional study was adopted, and 292 female medical sciences students of MACHS were selected using stratified random sampling. A semi-structured and self- administrated questionnaire was used to collect personal and socio-demographic information from the selected female medical sciences students. The information about the menstrual history, stress, and smoking were also gathered. The data analysis was carried out using the descriptive statistics and Chi-square test. Results: The prevalence of dysmenorrhea was 73.28% among female medical sciences students. Concerning the signs and symptoms of dysmenorrhea, the abdominal pain was predominant symptoms among 73.28% of the respondents, and it was found to be statistically significant (p≤0.05). Sleep disturbance was observed as the prominent outcome of dysmenorrhea, as reported by 64% of the respondents

Review of EEG and ERP studies of extraversion personality for baseline and cognitive tasks

According to psychological studies, the most fundamental personality is the extraversion personality. Most studies looking at differences between extroverts and introverts are pen and paper based studies. However, in a few studies, electrophysiological signals were involved. In this paper, we reviewed studies examining extraversion personality using electroencephalography (EEG) and event-related potentials (ERP). It was found that some of the EEG studies claimed that extroverts and introverts can be differentiated using baseline EEG, while some others claimed otherwise. Conflicting findings were also observed in the ERP studies; higher/lower P300 amplitude in extroverts compared to that of introverts in visual stimuli tasks. These various findings are probably due to differences in their experimental protocols, sample size, or age of subjects. Other possible reasons include no consideration given on the main feature of extraversion and the studies only focused on EEG power spectral analysis. We are thus suggesting for future investigations to involve the main feature such as sociability and/or to incorporate more EEG features in the analysis to produce more robust and reliable results. This review constitutes a guidance for research on brain-related conditions of extroverts and introverts and shall be useful in many areas