Flow Regime Classification and Hydrological Characterization: A Case Study of Ethiopian Rivers
TL;DR: In this paper, the Hierarchical Ward Clustering method was implemented to group the streams into three flow regimes (1) ephemeral, (2) intermittent, and (3) perennial).
Abstract: The spatiotemporal variability of a stream flow due to the complex interaction of catchment attributes and rainfall induce complexity in hydrology. Researchers have been trying to address this complexity with a number of approaches; river flow regime is one of them. The flow regime can be quantified by means of hydrological indices characterizing five components: magnitude, frequency, duration, timing, and rate of change of flow. Similarly, this study aimed to understand the flow variability of Ethiopian Rivers using the observed daily flow data from 208 gauging stations in the country. With this process, the Hierarchical Ward Clustering method was implemented to group the streams into three flow regimes (1) ephemeral, (2) intermittent, and (3) perennial. Principal component analysis (PCA) is also applied as the second multivariate analysis tool to identify dominant hydrological indices that cause the variability in the streams. The mean flow per unit catchment area (QmAR) and Base flow index (BFI) show an incremental trend with ephemeral, intermittent and perennial streams. Whereas the number of mean zero flow days ratio (ZFI) and coefficient of variation (CV) show a decreasing trend with ephemeral to perennial flow regimes. Finally, the streams in the three flow regimes were characterized with the mean and standard deviation of the hydrological variables and the shape, slope, and scale of the flow duration curve. Results of this study are the basis for further understanding of the ecohydrological processes of the river basins in Ethiopia.
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TL;DR: In this article, the authors compared the performance of event-based and continuous simulation modelling of a stormwater management model (EPA-SWMM) in calculating total runoff hydrographs and direct runoff hydragraphs.
Abstract: This study investigates the comparative performance of event-based and continuous simulation modelling of a stormwater management model (EPA-SWMM) in calculating total runoff hydrographs and direct runoff hydrographs. Myponga upstream and Scott Creek catchments in South Australia were selected as the case study catchments and model performance was assessed using a total of 36 streamflow events from the period of 2001 to 2004. Goodness-of-fit of the EPA-SWMM models developed using automatic calibration were assessed using eight goodness-of-fit measures including Nash–Sutcliff efficiency (NSE), NSE of daily high flows (ANSE), Kling–Gupta efficiency (KGE), etc. The results of this study suggest that event-based modelling of EPA-SWMM outperforms the continuous simulation approach in producing both total runoff hydrograph (TRH) and direct runoff hydrograph (DRH).
41 citations
TL;DR: Five thermal indicators based on the stream-air temperature relationship that together can identify the altered thermal signatures of dams and ponds allow for identifying and quantifying downstream thermal and ecological influences of different types of anthropogenic infrastructures without prior information on the source of modification and upstream water temperature conditions.
24 citations
TL;DR: In this paper, the authors developed a large-scale ephemerality classification and prediction methodology based on monthly discharge data, water and energy availability, and remote sensing measures of vegetation, that is relevant to epidemiology, and maintains a mechanistic link to catchment hydrologic processes.
21 citations
TL;DR: In this article, the impacts of different land uses, SWC and water harvesting interventions on water and suspended sediment yield (SSY) at plot and watershed scales in the central highlands of Ethiopia were assessed.
Abstract:
To tackle the problem of soil erosion and moisture stress, the government of Ethiopia introduced a yearly mass campaign where communities get together and implement various soil and water conservation (SWC) and water harvesting (WH) practices. Although the interventions are believed to have reduced soil erosion/sediment yield and enhanced surface and ground water, quantitative information on the impacts of various options at different scales is scarce. The objective of this study was to assess the impacts different land uses, SWC and WH interventions on water and suspended sediment yield (SSY) at plot and watershed scales in the central highlands of Ethiopia. Standard erosion plot experiments and hydrological stations were used to monitor the daily water and SSY during 2014 to 2017. The results show differences between treatments both at plot and watershed scales. Runoff and soil loss were reduced by an average 27 and 37%, respectively due to SWC practices at the plot level. Overall, SWC practices implemented at the watershed level reduced sediment yield by about 74% (in the year 2014), although the magnitude of sediment reduction due to the SWC interventions reduced over time. At both scales it was observed that as the number of years since SWC measures have been in place increased, their effectiveness declined due to the lack of maintenance. This study also revealed that extrapolating of plot data to watershed scale causes over or under estimation of net erosion.
20 citations
Cites background from "Flow Regime Classification and Hydr..."
...The BFI (the ratio of base flow to total flow) indicates the dynamics of stream water in relation to the ground water aquifer (Moliere et al., 2009; Berhanu et al., 2015)....
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TL;DR: In this article, the authors determined water temperature trends of rivers in Poland in the period 1971-2015, and also their spatial and temporal patterns using the Mann-Kendall (M-K) test.
Abstract: The study determined water temperature trends of rivers in Poland in the period 1971–2015, and also their spatial and temporal patterns. The analysis covered daily water temperature of 53 rivers recorded at 94 water gauge stations and air temperature at 43 meteorological stations. Average monthly, annual, seasonal and maximum annual tendencies of temperature change were calculated using the Mann–Kendall (M–K) test. Regional patterns of water temperature change were determined on the basis of Ward’s hierarchical grouping for 16 correlation coefficients of average annual water temperature in successive 30-year sub-periods of the multi-annual period of 1971–2015. Moreover, regularities in monthly temperature trends in the annual cycle were identified using 12 monthly values obtained from the M–K Z test. The majority of average annual air and water temperature series demonstrate statistically significant positive trends. In three seasons: spring, summer and autumn, upward tendencies of temperature were detected at 70%–90% of the investigated water gauges. In 82% of the analysed rivers, similarity to the tendencies of change of monthly air temperature was concluded, with the climatic factor being recognised as of decisive importance for the changes in water thermal characteristics of the majority of rivers in Poland. In the winter months, positive trends of temperature were considerably weaker and in general statistically insignificant. On a regional scale, rivers with a quasi-natural thermal regime experienced temperature increases from April to November. In the other cases, different directions of change in river water temperature (RWT) were attributed to various forms of human impact. It was also found that for the majority of rivers the average annual water temperature in the analysed 30-year sub-periods displayed upward trends, statistically significant or close to the significance threshold. Stronger trends were observed in the periods after 1980, while a different nature of water temperature change was detected only in a couple of mountainous rivers or rivers transformed by human impact. In the beginning of the analysed period (1971–2015), the average annual water temperature of these rivers displayed positive and statistically significant trends, while after 1980 the trends were negative. The detected regularities and spatial patterns of water temperature change in rivers with a quasi-natural regime revealed a strong influence of climate on the modification of their thermal regime features. Rivers characterised by a clearly different nature of temperature change, both in terms of the direction of the tendencies observed and their statistical significance, were distinguished by alterations of water thermal characteristics caused by human activity. The results obtained may be useful in optimising the management of aquatic ecosystems, for which water temperature is a significant indicator of the ongoing environmental changes.
19 citations
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Book•
01 Jan 2006TL;DR: In this article, the authors present a detailed, worked-through example drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology.
Abstract: "With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variable modeling. *Chapter on Bayesian CFA and multilevel measurement models. *Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. *Utilizes the latest versions of major latent variable software packages"--
7,620 citations
TL;DR: Data Mining Methods and Models is the second volume of a three-book series on data mining authored by Larose and is a fairly readable book for adoption in a graduate-level introductory course on datamining.
Abstract: Data Mining Methods and Models is the second volume of a three-book series on data mining authored by Larose. The following review was performed independently of LaRose’s other two books. Paraphrasing from the Preface, the goal of this book is to “explore the process of data mining from the point of view of model building.” Nevertheless, the reader will soon be aware that this book is not intended to provide a systematic or comprehensive coverage of various data mining algorithms. Instead, it considers supervised learning or predictive modeling only, and it walks the reader through the data mining process merely with a few selected modeling methods such as (generalized) linear modeling and the Bayesian approach. The book has seven chapters. Chapter 1 introduces dimension reduction, with a focus on principal components analysis (PCA) types of techniques. Chapters 2, 3, and 4 provide a detailed coverage of simple linear regression, multiple linear regression, and logistic regression, respectively. Chapter 5 introduces naive Bayes estimation and Bayesian networks. In Chapter 6, the basic idea of genetic algorithms is discussed. Finally, Chapter 7 presents a case study example of modeling response to direct mail marketing within the CRISP (crossindustry standard process) framework. This book is very easy to read, and this is absolutely the strength which many readers, especially those nonstatistically oriented ones, will greatly appreciate. Predictive modeling is perhaps the most technical part in a data mining process. The author has done an excellent job in making this difficult topic accessible to a broad audience. For example, I like the way in which Bayesian networks are introduced in Chapter 5. After the reader goes through a churn example on naive Bayes estimation in a step-by-step manner, Bayesian belief networks become easily understood as natural extensions. The overall style of the book is clear and patient. The main limitation of the book is its limited coverage. An inspired reader would expect to see a much more extended list of topics. Hastie, Tibishirani, and Friedman (2001) gave a full and more technical account of various data mining algorithms. The inclusion of genetic algorithms in Chapter 6 seems novel when compared to Hastie, Tibishirani, and Friedman (2001), but at the same time, a little unexpected as a separate chapter, since a genetic algorithm involves a stochastics search scheme, which is somewhat involved given the elementary nature of this text. Another noteworthy issue is that the author does not make an attempt to distinguish between conventional statistical analysis and data mining. I found a few errors. On Page 25, for example, it should be ai = 1, instead of ai = 1/4. Also, in the frame on the top of Page 211, it might have been “Posterior Odds,” instead of “Posterior Odds Ratio.” The book uses three different software packages to implement the ideas including SPSS with Clementine, Minitab, and WEKA, which might not be appealing. On the other hand, it is justifiable as it allows one to perform data mining with affordable costs. In summary, I recommend this fairly readable book for adoption in a graduate-level introductory course on data mining, especially when the students come from varied backgrounds.
6,409 citations
"Flow Regime Classification and Hydr..." refers methods in this paper
...PCA was selected in this analysis since it puts a unit on the diagonal and all of the variances (variance unique to each variable, variance common among variables and error variance) in the matrix are considered [43]....
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TL;DR: In this article, Naiman et al. pointed out that harnessing of streams and rivers comes at great cost: Many rivers no longer support socially valued native species or sustain healthy ecosystems that provide important goods and services.
Abstract: H umans have long been fascinated by the dynamism of free-flowing waters. Yet we have expended great effort to tame rivers for transportation, water supply, flood control, agriculture, and power generation. It is now recognized that harnessing of streams and rivers comes at great cost: Many rivers no longer support socially valued native species or sustain healthy ecosystems that provide important goods and services (Naiman et al. 1995, NRC 1992).
5,799 citations
"Flow Regime Classification and Hydr..." refers background in this paper
...Likens [32], Richter [33], and Poff [25] suggested five stream flow categories; magnitude, frequency, duration, predictability, and rate of...
[...]
...Flow regime classification is achieved commonly on the basis of stream flow characteristics using hydrologic indices with five stream flow components; magnitude, frequency, duration, timing, and rate of changes of flows [25,26]....
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...Poff and Ward [3] employed a conceptual stream classification model, which was based on a hierarchical ranking of four components of flow regime (intermittency, flood frequency, flood predictability, and overall flow predictability)....
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...Likens [32], Richter [33], and Poff [25] suggested five stream flow categories; magnitude, frequency, duration, predictability, and rate of Water 2015, 7 3152 change that include a number of flow characteristics and represent the flow regimes as ephemeral, intermittent, and perennial....
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TL;DR: In this article, the authors proposed a method for assessing the degree of hydrologic alteration attributable to human influence within an ecosystem, referred to as the "Indicators of Hydrologic Alteration".
Abstract: Hydrologic regimes play a major role in determining the biotic composition, structure, and function of aquatic, wetland, and riparian ecosystems. But human land and water uses are substantially altering hydrologic regimes around the world. Improved quantitative evaluations of human-induced hydrologic changes are needed to advance research on the biotic implications of hydrologic alteration and to support ecosystem management and restoration plans. We propose a method for assessing the degree of hydrologic alteration attributable to human influence within an ecosystem. This method, referred to as the “Indicators of Hydrologic Alteration,” is based upon an analysis of hydrologic data available either from existing measurement points within an ecosystem (such as at stream gauges or wells) or model-generated data. We use 32 parameters, organized into five groups, to statistically characterize hydrologic variation within each year. These 32 parameters provide information on ecologically significant features of surface and ground water regimes influencing aquatic, wetland, and riparian ecosystems. We then assess the hydrologic perturbations associated with activities such as dam operations, flow diversion, groundwater pumping, or intensive land-use conversion by comparing measures of central tendency and dispersion for each parameter between user-defined “pre-impact” and “post-impact” time frames, generating 64 Indicators of Hydrologic Alteration. This method is intended for use with other ecosystem metrics in inventories of ecosystem integrity, in planning ecosystem management activities, and in setting and measuring progress toward conservation or restoration goals.
2,204 citations
"Flow Regime Classification and Hydr..." refers background in this paper
...Likens [32], Richter [33], and Poff [25] suggested five stream flow categories; magnitude, frequency, duration, predictability, and rate of...
[...]
...Likens [32], Richter [33], and Poff [25] suggested five stream flow categories; magnitude, frequency, duration, predictability, and rate of Water 2015, 7 3152 change that include a number of flow characteristics and represent the flow regimes as ephemeral, intermittent, and perennial....
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Book•
01 Jan 1977
TL;DR: In this article, Biogeochemistry of a forested ecosystem, Biogeochemical properties of forested ecosystems, and biogeochemistry in forested environments, the authors present a biogeochemical model of forest ecosystems.
Abstract: Biogeochemistry of a forested ecosystem , Biogeochemistry of a forested ecosystem , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی
1,613 citations