Hydrologic Concepts Research Articles

Impacts of agriculture and snow dynamics on catchment water balance in the U.S. and Great Britain

The Budyko water balance is a fundamental concept in hydrology that links aridity to how precipitation is divided between evapotranspiration and streamflow. While the model is powerful, its ability to explain temporal changes and the influence of human activities and climate change is limited. Here we introduce a causal discovery algorithm to explore deviations from the Budyko water balance, attributing them to human interventions such as agricultural activities and snow dynamics. Our analysis of 1342 catchments across the U.S. and Great Britain reveals distinct patterns: in the U.S., snow fraction and irrigation alter the Budyko water balance predominantly through changes in aridity-streamflow relationships, while in Great Britain, deviations are primarily driven by changes in precipitation-streamflow relationships, notable in catchments with high cropland percentage. By integrating causal analysis with the Budyko water balance, we enhance understanding of how human activities and climate dynamics affect water balance, offering insights for water management and sustainability in the Anthropocene.

Estimation of the time of concentration of small watersheds located in Northeastern North America

ABSTRACT The time of concentration is an important concept in hydrology. It provides a characteristic hydrological response time (CHRT) useful in many applications. Estimation of the time of concentration is challenging because small watersheds (<100 km2) with sub-daily flow and precipitation records are uncommon. Many practitioners therefore use empirical equations developed from watersheds exposed to different climates and with different attributes. The main objective of this study is to develop an approach to estimate the CHRT from physiographic characteristics for small watersheds located in Ontario, Québec and the northeastern USA. Regression trees are used to identify the physiographic characteristics associated with CHRT. The fraction of lakes and wetlands was identified as the most significant attribute related to CHRT, followed by the ratio between the main watercourse length and the square root of the main watercourse slope. Uncertainties on estimated CHRT values based on regression tree are also provided.

How you teach changes who you reach: understanding the effect of teaching modality on engagement, interest, and learning in hydrology

ABSTRACT There is a growing consensus that hydrology education should move towards student-led learning formats and simultaneously incorporate recent hydrologic technologies that reflect workforce expectations. Prior theory suggests improvements in learning outcomes from student-led learning; however, little empirical evidence has been collected to confirm this success. We measured the classroom impact of three teaching modalities: 1) instructor-led lectures, 2) student-led hydrologic modeling, and 3) student-led design evaluation studios. Educational outcomes were measured with student surveys, direct observation of class activity, and student grades. In aggregate, the student population did not express a significant preference for one modality over another, yet individual students showed dramatic preferences for each modality. This suggests best practice is to increase the variety of teaching modalities we employ as instructors to positively engage more students. The total frequency of interactions between students and the instructor was similar across all three modalities; however, the frequency of student-initiated engagements (both total and unique engagements) significantly increased in both student-led modalities. Variations in student enthusiasm did not correlate with written assessment scores. Alternating modalities improved interest in hydrologic science and perceptions of positive experiences, however, did not change the retention of hydrologic concepts. Multiple teaching modalities should be employed to engage the greatest number of students and generate enthusiasm, and multiple methods of assessing student learning should be employed.

Remotely controlled water channel system for laboratory education utilizing internet of things and SCADA technologies

This paper was discussed the hardware components of a remotely controlled water channel management system for laboratory education utilizing the internet of things(IoT) and supervisory control and data acquisition systems (SCADAs). The system consists of various sensors and devices included the air pressure sensor (mpx5010dp), water pressure sensor, ultrasonic distance sensor (JSNSR04T) and solenoid water valve plastic. The air pressure sensor (mpx5010dp) was used to detect the water level in the manometer of the pitot tube, a water pressure sensor for detecting the pressure of water, an ultrasonic distance sensor (JSN-SR04T) for detecting the level of water in the channel, a solenoid water valve plastic with relay for protecting the motor when the water level in the tank reduces to 5 cm. These components work together to monitor and control the water channel system remotely, providing users with a more scalable, flexible, and accessible solution for laboratory education. Also, a web page was developed with an IoT and SCADA system for remote control and management of a water channel system that was used for teaching hydraulic and hydrological concepts to students.

Exploring controls on rainfall–runoff events: spatial dynamics of event runoff coefficients in Iran

ABSTRACT This study investigates the controls that influence the spatial variability of event runoff coefficients (RCs) based on the comparative hydrology concept. We analysed 18 468 storm events in 963 Iranian catchments ranging in size from 101 to 8467 km2. The mean RCs vary spatially due to long-term hydro-climate conditions and other catchment descriptors (CDs). The controls on spatial variability of RCs are investigated using a correlation analysis of the statistical moments of the RCs and CDs. The results indicate (1) catchment elevation is the most important control on RCs at the country scale, and hydro-climatic attributes such as mean annual precipitation, ratio of actual evaporation to precipitation, and the ratio of potential evaporation to precipitation are other important controls on RCs; and (2) at the regional scale, catchment area is a major control on RCs, although it is not as important as hydro-climatic controls at the national scale.

Evaluating Model Effectiveness for Soil Infiltration Attribute: Comparison of Green-Ampt, Horton and Modified Green-Ampt Infiltration Models

Soil infiltration is a very important concept in hydrology as well as irrigation, which plays a vital role in estimating surface runoff and groundwater recharge. It is a complicated process that varies with numerous factors. Accurate estimation of soil infiltration is required for future irrigation, and many other purposes. To estimate the infiltration process, there are numerous models. The majority of them have some presumptions, a unique calculation method, and some limitations. The purpose of the paper was to assess the model’s performance for a similar hypothetical scenario involving soil infiltration. It compared the infiltration rate, runoff rate, and incremental infiltration versus time for three different infiltration models: the Green-Ampt model (GA), the Horton model and the Modified Green-Ampt (MGA) model. A spreadsheet was used to calculate the Horton model, and HYDROL-INF (V 5.03) was used to simulate the other two models. Among those three models, the MGA model outperformed those three models, while the GA model produced greater infiltration rate than rainfall, which was insensible. The study showed that the MGA model, which provides useful infiltration predictions, outperformed the other two infiltration models. Since the Horton model does not consider ponding conditions, it is only applicable when the effective rainfall intensity exceeds the final infiltration capacity. Moreover, the GA model’s initial infiltration rate is irrational because it disregards the intensity of the rainfall. The results of this study will assist in selecting the most accurate method for estimating soil infiltration for agricultural purposes.

Harnessing Project-Based Learning to Enhance STEM Students’ Critical Thinking Skills Using Water Treatment Activity

Water treatment processes are designed to ensure that any pollutant’s adverse effects on the environment are reduced to the minimum allowable discharge limit. Water-literate individuals ought to effectively and constantly think about novel hydrologic concepts to improve the quality and sufficiency of water. Socio-hydrological issues remain the main source of water pollution and insufficiency in society. Therefore, effective water management and treatment require societal understanding. The complexity of water issues requires equipping STEM education students with the necessary knowledge to acquire water solution reasoning skills. However, STEM students need meaningful challenges with everyday connections to capture their interest to apply intuitive understanding in project-based learning. Water-related issues such as high turbidity are ubiquitous problems facing communities. This study specifically explored how project-based learning can be harnessed to enhance STEM students’ critical thinking skills using water treatment activities. The water treatment activity involved the development of novel products using agricultural wastes for efficient water treatment. The social issues associated with agricultural wastes, especially orange and banana peels in the environment, are too obvious to be overlooked; hence, they were chosen as base materials to develop water treatment products. The study adopted an action research design and involved 12 purposively selected third-year Bachelor of Science students majoring in Chemistry at a South African university. The students were divided into two groups consisting of six participants. The researchers implemented team teaching and invoked students’ knowledge of Earth Science, Physics, Chemistry, and Technology to develop and implement laboratory experimental activities and class-based lesson plans. The empirical investigation was underpinned by the Five Steps of Project-Based Learning as the underlying theoretical framework. The chemistry of the processed peels such as particle size and functional groups provided insight into the mechanism responsible for water turbidity reduction. Laboratory experimental results revealed that the turbidity reduction obtained from the use of processed banana peels was higher than the processed orange peels coagulant. However, the performance of both coagulants in turbidity reduction complied with the South African National Standard (SANS241) for drinking water quality.

The ParFlow Sandtank: An interactive educational tool making invisible groundwater visible

Physical aquifer models are a highly effective teaching tool for hydrology education, however they come with inherent limitations that include the high cost to purchase, the static configuration of the model materials, the time required to visualize hydrogeological phenomena, and the effort to reset and clean them over time. To address these and other limitations, we have developed an interactive computer simulation of a physical aquifer model called the ParFlow Sandtank. In this gamified interface, users run the simulation using a familiar web-app like interface with sliders and buttons while learning real hydrologic concepts. Our user interface allows participants to dive into the world of hydrology, understanding assumptions about model parameters such as hydraulic conductivity, making decisions about inputs to groundwater aquifer systems such as pumping rates, visualizing outputs such as stream flow, transport, and saturation, and exploring various factors that impact real environmental systems such as climate change. The ParFlow Sandtank has already been used in a variety of educational settings with more than 9,000 users per year, and we feel this emerging educational tool can be used broadly in educational environments and can be scaled-up to provide greater accessibility for students and educators. Here we present the capabilities and workflow of the ParFlow Sandtank, two use cases, and additional tools and custom templates that have been developed to support and enhance the reach of the ParFlow Sandtank.

The Study on Water Balance in Mlech Reservoir Under Climate Change Effects, Kampot Province

The Mlech Water Treatment Plant (WTP) has produced 2,000 m3/day of drinking water using raw water from Mlech, Kampot province. Since water demand would be increased in the future, so that the extension water treatment capacity will be the main challenges in correspondence with the development of planning of PPWSA. The water balance estimation is also the critical point in order to make a good decision on extension WTP at existing area. Therefore, the objectives of this study aimed to analyse the water balance in Mlech reservoir by using data from 2002 to 2011, in 2030s and in 2050s. The Rational Method was applied for estimating the streamflow into the reservoir. Water balance was computed following hydrological concept. SWAT and HEC-HMS models were performed to predict the future streamflow. The future climatic data were projected from 2012 to 2050 under climate change scenario RCP 4.5 with three general circulation models (GCMs) including IPSL-CM5A-MR, GISS-E2-R-CC and GFDL-CM3. As a result, the water balance remains about 11.40 Mm3/year in reservoir in baseline. In 2030s, the water quantity will be approximately 58.70 Mm3/year, 62.09 Mm3/year and 59.58 Mm3/year under model IPSL-CM5A-MR, GISS-E2-R-CC and GFDL-CM3, respectively. In addition, the water quantity will be slightly changed in 2050s comparing to 2030s. According to the scenario of extension WTP capacity, this study found that the water flow into downstream will be decreased to 37.14 Mm3/year to 33.84 Mm3/year when WTP’s capacity increased from 2,000 m3/day to 14,000 m3/day,respectively. Furthermore, the volume of water overflow to downstream for irrigation uses is 30.32 Mm3/year when WTP’s capacity increased to 12,000 m3/day in 2050s. Irrigation water need is about 28.00 Mm3/year. In recommendation, the total WTP’s capacity should be extended from 2,000 m3/day to 10,000m3/day from Mlech reservoir based on the future water demand.

The Determination of Priority Areas for the Restoration of Degraded Tropical Peatland Using Hydrological, Topographical, and Remote Sensing Approaches

Degraded peatland is caused by forest clearing and the construction of artificial water networks. When water management is not implemented across land uses in the entire peatland landscape, then it will be a big issue that causes a water deficit and leads to increasing droughts and fires. Effective restoration must first identify the part of Peatland Hydrological system Units (PHUs) with insufficient water storage and resources. This study used intercorrelated factors of water balance, deficit months, NDMI-NDVI indices, dry periods, recurrent fires, peat depth, and water loss conditions, as the evaluation parameters, within individual sub-PHUs to determine the most degraded areas that require intervention and restoration. Sub-PHU was determined based on the peat hydrological unity concept by identifying streamline, outlet channels, peat-depth, slopes, and network connectivity. Global hydrological data using TerraClimate and CHIRPS, combined with field observations, were used to validate and calculate each sub-PHU’s water balance and dry periods. Soil moisture (NDMI), vegetation density (NDVI), and fire frequency were extracted from multispectral satellite images (e.g., Landsat 8, MODIS-Terra, and MODIS-Aqua). Each parameter was ranked by the score for each sub-PHU. The parameters that can be ranked are only the ordinal type of number. The lowest ranks indicated the most degraded sub-PHUs requiring peat rewetting interventions.

Hydrological concept formation inside long short-term memory (LSTM) networks

Abstract. Neural networks have been shown to be extremely effective rainfall-runoff models, where the river discharge is predicted from meteorological inputs. However, the question remains: what have these models learned? Is it possible to extract information about the learned relationships that map inputs to outputs, and do these mappings represent known hydrological concepts? Small-scale experiments have demonstrated that the internal states of long short-term memory networks (LSTMs), a particular neural network architecture predisposed to hydrological modelling, can be interpreted. By extracting the tensors which represent the learned translation from inputs (precipitation, temperature, and potential evapotranspiration) to outputs (discharge), this research seeks to understand what information the LSTM captures about the hydrological system. We assess the hypothesis that the LSTM replicates real-world processes and that we can extract information about these processes from the internal states of the LSTM. We examine the cell-state vector, which represents the memory of the LSTM, and explore the ways in which the LSTM learns to reproduce stores of water, such as soil moisture and snow cover. We use a simple regression approach to map the LSTM state vector to our target stores (soil moisture and snow). Good correlations (R2&gt;0.8) between the probe outputs and the target variables of interest provide evidence that the LSTM contains information that reflects known hydrological processes comparable with the concept of variable-capacity soil moisture stores. The implications of this study are threefold: (1) LSTMs reproduce known hydrological processes. (2) While conceptual models have theoretical assumptions embedded in the model a priori, the LSTM derives these from the data. These learned representations are interpretable by scientists. (3) LSTMs can be used to gain an estimate of intermediate stores of water such as soil moisture. While machine learning interpretability is still a nascent field and our approach reflects a simple technique for exploring what the model has learned, the results are robust to different initial conditions and to a variety of benchmarking experiments. We therefore argue that deep learning approaches can be used to advance our scientific goals as well as our predictive goals.

Review of Rain or Shine: An Introduction to Soil Physical Properties and Processes. Tyson Ochsner. Published by Oklahoma State University Libraries under the Creative Commons Attribution 4.0 International License. Version 6. Last updated 19 Jan. 2022. DOI: https://doi.org/10.17605/OSF.IO/Z4RBT

Review of <i>Rain or Shine: An Introduction to Soil Physical Properties and Processes</i>. Tyson Ochsner. Published by Oklahoma State University Libraries under the Creative Commons Attribution 4.0 International License. Version 6. Last updated 19 Jan. 2022. DOI: https://doi.org/10.17605/OSF.IO/Z4RBT

Geophysical imaging of the Yellowstone hydrothermal plumbing system.

The nature of Yellowstone National Park's plumbing system linking deep thermal fluids to its legendary thermal features is virtually unknown. The prevailing concepts of Yellowstone hydrology and chemistry are that fluids reside in reservoirs with unknown geometries, flow laterally from distal sources and emerge at the edges of lava flows1-4. Here we present a high-resolution synoptic view of pathways of the Yellowstone hydrothermal system derived from electrical resistivity and magnetic susceptibility models of airborne geophysical data5,6. Groundwater and thermal fluids containing appreciable total dissolved solids significantly reduce resistivities of porous volcanic rocks and are differentiated by their resistivity signatures7. Clay sequences mapped in thermal areas8,9 and boreholes10 typically form at depths of less than 1,000 metres over fault-controlled thermal fluid and/or gas conduits11-14. We show that most thermal features are located above high-flux conduits along buried faults capped with clay that has low resistivity and low susceptibility. Shallow subhorizontal pathways feed groundwater into basins that mixes with thermal fluids from vertical conduits. These mixed fluids emerge at the surface, controlled by surficial permeability, and flow outwards along deeper brecciated layers. These outflows, continuing between the geyser basins, mix with local groundwater and thermal fluids to produce the observed geochemical signatures. Our high-fidelity images inform geochemical and groundwater models for hydrothermal systems worldwide.

Supporting undergraduate students\u2019 developing water literacy during a global pandemic: a longitudinal study

To prepare students to address water-related challenges, undergraduate STEM education must provide them with opportunities to learn and reason about water issues. Water in Society is an introductory-level, innovative, and interdisciplinary undergraduate course offered annually at a large midwestern university. The course focuses on both disciplinary concepts and civic engagement, and is designed around a variety of interactive, research-based practices to support students’ learning, engagement with authentic data, scientific models and modeling, and collaboration and learning among peers. This study aims to evaluate, “how have student outcomes and perceptions changed over five years of the course?”. The results are based on data from students (n = 326) in five consecutive years of the course, during which time the course transitioned from a face-to-face model to fully asynchronous online model due, in part, to impacts of the COVID-19 pandemic. The particularly rapid and abrupt transition between 2020 and 2021 in response to COVID-19 led to many course changes, including modes of communication between instructors and students and opportunities for collaboration. Here, multiple measures are used to evaluate students’ learning about water concepts, model-based reasoning about socio-hydrologic systems, and perceptions of the course across all five years. By the end of each iteration of the course, students improved their knowledge of hydrologic concepts, independent of the course format or other student-level variables. However, results also show that students’ performance on complex socio-hydrologic systems modeling tasks, as well as their overall satisfaction with the course, decreased in Year 5 when the course was fully online. Results provide insight into efforts to move undergraduate STEM courses online and specific evidence of the COVID-19 pandemic’s impacts on undergraduate STEM teaching and learning about water.

Application of a novel artificial neural network model in flood forecasting.

In this paper, a novel ANN flood forecasting model is proposed. The ANN model is combined with traditional hydrological concepts and methods, taking the initial Antecedent Precipitation Index (API), rainfall, upstream inflow and initial flow at the forecast river section as input of model, and flood flow forecast of the next time steps as output of the model. The distributed rainfall is realized as the input of the model. The simulation is processed by dividing the watershed into several rainfall-runoff processing units. Two hidden layers are used in the ANN, and the topology of ANN is optimized by connecting the hidden layer neurons only with the input which has physical conceptual causes. The topological structure of the proposed ANN model and its information transmission process are more consistent with the physical conception of rainfall-runoff, and the weight parameters of the model are reduced. The arithmetic moving-average algorithm is added to the output of the model to simulate the pondage action of the watershed. Satisfactory results have been achieved in the Mozitan and Xianghongdian reservoirs in the upper reaches of Pi river in Huaihe Basin, and the Fengman reservoir in the upper reach of Second Songhua river in Songhua basin in China.

Hydrological Concept Formation inside Long Short-Term Memory (LSTM) networks

Hydrological Concept Formation inside Long Short-Term Memory (LSTM) networks

The politics of evaporation and the making of atmospheric territory in Australia’s Murray-Darling Basin

Scholarship on the hydrosocial cycle has tended to overlook the atmospheric phase of the cycle. This paper identifies and conceptualises a politics of evaporation in Australia’s Murray-Darling Basin. Evaporation is not a neutral hydrological concept to be understood, measured or acted on without an appreciation of the networks in which it originates, the geo-political circumstances that continue to shape its circulation, and its socio-spatial effects. The politics of evaporation is conceptualised here as a process of hydrosocial territorialisation in which atmospheric water came to be known as a force acting within a balanced hydrologic cycle, and ‘atmospheric territory’ was created. The scientific origins of evaporation show (i) how modernist hydrologic technologies and conventions that relied on containment and territorialisation to account for and control water led to the negative depiction of evaporation as a loss, and (ii) the historical depth of processes of abstraction and commensuration that are so influential in today’s regimes of water accounting and marketisation. The politics of evaporation is identified empirically in the controversy surrounding the management of the Menindee Lakes and the lower Darling River in New South Wales, where efforts to ‘save’ water according to the logic of efficiency have enrolled atmospheric water into a Basin-wide program to redistribute surface water. The lens of evaporation theorises a neglected aspect of the materiality of water that is particularly important to the dry, hot parts of the world. It challenges us to rethink the ‘cycle’ as well as the ‘hydro’, while providing further evidence of the value of thinking about territory in a material register as volumetric and not areal.

Impact of rainfall spatiotemporal variability and model structures on flood simulation in semi-arid regions

The spatiotemporal heterogeneity in precipitation and underlying surfaces and hybrid runoff generation mechanism make hydrological modelling and forecasting in semi-arid regions becoming a challenging work. Therefore, to provide a reference for the development of hydrological models in such regions, two nested hydrological experimental watersheds in semi-arid regions were selected for attribution analysis. Based on the concept of large-sample hydrology, large-scale numerical simulation experiments were performed by constructing different spatial and temporal scale rainfall schemes and combining three hydrological models with different runoff generation mechanisms. Finally, the influences of the time step, station density, and model structure on the flood simulations in semi-arid regions were evaluated. The spatial interpolation technique was used simultaneously to describe the high-dimensional complicated nonlinear relationships between the influencing factors and simulation results. The results show the following: (1) the flood simulation accuracy was more sensitive to the time step than the spatial station density of the rainfall schemes and was highly dependent on the time step of the original observation data, and (2) compared with the accuracy of the rainfall schemes, the model structure plays a dominant role in flood simulation accuracy. Thus, the hybrid model has significant potential for flood forecasting in semi-arid regions by combining different runoff generation mechanisms. (3) The spatial interpolation technique based on the k-nearest neighbour algorithm can construct a high-dimensional distribution between the influencing factors and model simulation accuracy, and describe the complicated relationships among the time step, station density, model structure, and flood simulations.

Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective

Abstract. Following the rise of R as a scientific programming language, the increasing requirement for more transferable research and the growth of data availability in hydrology, R packages containing hydrological models are becoming more and more available as an open-source resource to hydrologists. Corresponding to the core of the hydrological studies workflow, their value is increasingly meaningful regarding the reliability of methods and results. Despite package and model distinctiveness, no study has ever provided a comparison of R packages for conceptual rainfall–runoff modelling from a user perspective by contrasting their philosophy, model characteristics and ease of use. We have selected eight packages based on our ability to consistently run their models on simple hydrology modelling examples. We have uniformly analysed the exact structure of seven of the hydrological models integrated into these R packages in terms of conceptual storages and fluxes, spatial discretisation, data requirements and output provided. The analysis showed that very different modelling choices are associated with these packages, which emphasises various hydrological concepts. These specificities are not always sufficiently well explained by the package documentation. Therefore a synthesis of the package functionalities was performed from a user perspective. This synthesis helps to inform the selection of which packages could/should be used depending on the problem at hand. In this regard, the technical features, documentation, R implementations and computational times were investigated. Moreover, by providing a framework for package comparison, this study is a step forward towards supporting more transferable and reusable methods and results for hydrological modelling in R.

From mythology to science: the development of scientific hydrological concepts in Greek antiquity and its relevance to modern hydrology

Abstract. Whilst hydrology is a Greek term, it was not in use in the Classical literature, but much later, during the Renaissance, in its Latin form, hydrologia. On the other hand, Greek natural philosophers (or, in modern vocabulary, scientists) created robust knowledge in related scientific areas, to which they gave names such as meteorology, climate and hydraulics. These terms are now in common use internationally. Greek natural philosophers laid the foundation for hydrological concepts and the hydrological cycle in its entirety. Knowledge development was brought about by searches for technological solutions to practical problems as well as by scientific curiosity. While initial explanations belong to the sphere of mythology, the rise of philosophy was accompanied by the quest for scientific descriptions of the phenomena. It appears that the first geophysical problem formulated in scientific terms was the explanation of the flood regime of the Nile, then regarded as a paradox because of the spectacular difference from the river flow regime in Greece, i.e. the fact that the Nile flooding occurs in summer when in most of the Mediterranean the rainfall is very low. While the early attempts were unsuccessful, Aristotle was able to formulate a correct hypothesis, which he tested through what appears to be the first scientific expedition in history, in the transition from the Classical to Hellenistic periods. The Hellenistic period brought advances in all scientific fields including hydrology, an example of which is the definition and measurement of flow discharge by Heron of Alexandria. These confirm the fact that the hydrological cycle was well understood in Ancient Greece, yet it poses the question why correct explanations were not accepted and, instead, why ancient and modern mythical views were preferred up to the 18th century.