Case Study Of Catchment Research Articles

Application of hydrological modelling for temporal prediction of rainfall-induced shallow landslides

In some rainfall-triggered landslides, intensity-duration thresholds can have limited prediction ability; therefore, investigation of alternative approaches that can be used for temporal prediction of rainfall-induced landslides is needed. This paper presents a methodology for predicting rainfall-induced shallow landslides based on a lumped conceptual hydrological model. The production storage level during the rainfall event and the rainfall sum during the event are used for landslide prediction. Based on these two hydro-meteorological variables a threshold is defined that could be used for rainfall-induced landslides prediction as part of an early warning system. The presented methodology is tested using the meso-scale Selška Sora River catchment case study in western Slovenia where 20 active landslides from the Slovenian National Landslide Database are used to calibrate and evaluate the methodology performance. The results are compared to three different (i.e. local, regional, and global) intensity-duration thresholds. The results of the presented approach are superior in terms of several goodness-of-fit criteria compared to tested local and global ID thresholds. Because only daily rainfall, evapotranspiration, and discharge data are needed to calibrate the selected hydrological model and only daily rainfall and evapotranspiration to run the model, the presented approach could also be useful for data-scarce areas where detailed physically based landslide prediction models that require many data cannot be constructed. Moreover, we have also derived the probabilistic version of the proposed threshold for triggering of shallow landslides using copula functions.

A Comparison of Continuous and Event-Based Rainfall–Runoff (RR) Modelling Using EPA-SWMM

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).

Enabling policy innovations promoting multiple ecosystem benefits: lessons learnt from case studies in the Baltic Sea Region

Abstract This paper analyses how specific institutional barriers and drivers affect the success of agri-environmental governance and policy innovations in four case study catchments in Germany, Latvia, Poland and Sweden. Possible adaptations of institutional settings are explored, aiming at increased effectiveness of policies and governance in delivering multiple ecosystem benefits along with reduced nutrient emissions and flood management. Factors of success synthesized from existing examples of innovative policy instruments in the EU and further afield are used to identify barriers and opportunities for the implementation of policy innovations in different institutional settings across the Baltic Sea Region (BSR). Key factors of success include close and trusting cooperation in scheme development, utilization of intermediaries in trust building, an active role of civil society and private sector, spatial targeting and coordination of measures, and result-based and long-term approaches. It is concluded that the effectiveness of measures can be increased by (i) adopting a less prescriptive approach to implementation, (ii) strengthening bottom-up participatory stakeholder learning processes, (iii) fostering cross-sectoral planning and funding initiatives, (iv) creating incentives for local collaborative actions, (v) developing cooperative nutrient management initiatives in the BSR and (vi) developing a systematic and coordinated approach to pilot-testing of new concepts and measures.

Predicting water erosion in arid lands using the GIS-based RUSLE model: A case study of Bedour catchment, central Tunisia

Abstract This study was conducted with a view to quantifying soil erosion in arid lands of Tunisia. To do this, we have opted to use the RUSLE model based on geographic information systems. By collecting data on rainfall, soils, vegetation, slopes and conservation practices separately as a layer and determining the pixel values for each of these factors, a quantified assessment of erosion in the basin is obtained. The data superposition and computing, following the model equations and protocol, allowed us to know the spatialized water erosion values at the pixel level. For the whole catchment, the study showed values oscillating between 0 and 163 Mgꞏha−1ꞏyear−1 with an average annual rate of 3 Mgꞏha−1ꞏyear−1. With such a low R (rainfall erosivity) factor (between 21.43 and 21.88 MJꞏmmꞏha–1ꞏh–1ꞏyear–1) itself related to low monthly and annual rainfall amounts, the region experiences locally very high annual erosion rates. Soil protection through conservation practices has saved the basin from even higher erosion. While plains cultivated and equipped with contour benches often suffer from low rates of erosion (less than 2 Mg·ha–1·year–1), unused slopes are neglected without protection, resulting in significantly high rates of erosion.

Mechanisms influencing non-stationarity in rainfall-runoff relationships in southeast Australia

Arid and semi-arid regions experience large hydroclimatic variability and decadal-scale droughts. During droughts, the reduced water availability alters the biophysical properties of the catchments which leads to non-stationarity in rainfall-runoff (r-r) relationships. Uncertainty exists regarding the mechanisms causing r-r non-stationarity, especially at seasonal scales. This study analyses endogenous and exogenous catchment mechanisms which could possibly influence r-r relationships in two case study catchments in southeast Australia (SEA). The case study catchments are chosen such that they are representative of arid to semi-arid catchments that experience large climatic variability and decadal-scale droughts. The results demonstrate that endogenous catchment mechanisms (i.e. groundwater table, baseflow and vegetation) have stronger influences on non-stationarity in r-r relationships than exogenous catchment mechanisms like temperature and potential evapotranspiration. These findings highlight the importance of understanding changes in r-r relationships in order to develop more realistic and reliable hydrological models that are needed to quantify and adapt to the impacts of changing catchment or hydroclimatic conditions. While this study is focussed on SEA the findings are relevant to all catchments that experience large climatic variability and decadal-scale droughts.

A combined approach for a modern hydrogeological mapping: the case study of Tennacola stream catchment (central Apennine, Italy)

ABSTRACT The current European water legislation, specifically the one addressed to groundwater for human consumption (EU Water Framework Directive, WFD-2000/60/EC), provides clear indications on the objectives and actions to be taken for the proper management and protection of water resources. In Italy, as well as in other countries of the EU, the implementation of this Directive, in the face of an adjustment of the legislation at national level, is still far behind, as regards the obligations on the part of local administrations. Among the reasons there is a lack of cognitive tools, adequate and, above all, univocally accepted by the scientific point of view. The hydrogeological mapping here presented, which covers an area of around 44 km2 and is edited at 1:10,000 scale, goes in this direction, combining different approaches and methodologies (field surveys, spring hydrograph analysis, surface flow measurements, numerical models …) to arrive at a complete and functional study of an aquifer exploited for drinking purposes.

Theoretical and practical research into excavation slope protection for agricultural geographical engineering in the Loess Plateau: A case study of China's Yangjuangou catchment

The Loess Plateau is one of the most vulnerable areas in the world as it is extremely susceptible to soil erosion and ecological destruction. Recently, the local government carried out the “Gully Land Consolidation Project” (GLCP) in the Loess Plateau region to increase farmland area, improve rural production and living conditions. Among all the GLCP engineering constructions, slope protection engineering plays an important role in ensuring the safety of the main project, residential lives and properties, although more theoretical and technical research on comprehensive protection of engineering slopes is required. In this study, a field experiment using 12 standard runoff plots (length 4m×width 2m) was performed in Yangjuangou catchment of Yan'an City, to compare and analyze the comprehensive benefit to vegetative growth, soil erosion and engineering benefit from four vegetation styles and three levels of slope gradient (45°, 53°,63°). Results show that under different slope gradient and vegetation styles, significant differences existed in the comprehensive benefit to slopes, as well as the levels of vegetative growth, soil erosion and engineering benefit. The comprehensive benefit of the 53° slope was significantly better than that of 45° and 63° slopes. In addition, the comprehensive benefit of slopes with one or more vegetation styles was better than that of non-vegetation covered slopes. With the increase in slope gradient, the vegetative growth and slope erosion indices of vegetation average height, species richness, vegetation coverage slope, runoff production and sediment yield, showed a remarkable declining trend. Conversely, the engineering benefit index including newly-increased farmland area and excavating earthwork volume, showed an increasing trend. Recently, agricultural geographical engineering (AGE) has become an indispensable method for ecological construction and agricultural development, resulting in an increase in research in the field of geography. These findings not only have theoretical significance and enrich our understanding of the influence of gradient and vegetation styles on excavation slope protection, but also have practical significance and provide a baseline for engineering parameters and suggestions for slope protection engineering strategies.

Change detection and attribution of flow regime: A case study of Allegheny river catchment, PA (US)

The present study focuses on change detection and attribution analysis for a case study of Allegheny river catchment (at two unregulated sites namely Eldred and Salamanca) in USA. The proposed methodology involves, multiple change-point detection (MCPD) techniques i.e., Binary Segmentation based cumulative sum algorithms with Monte Carlo based threshold (BSCSth) and Bayesian Information Criteria (BIC) based penalty (BSCSBIC) and validating the two techniques using standard performance measures for different hypothetical riverflow time-series. The proposed BSCSth technique was applied to the Allegheny river at two sites for the series of different hydrological alteration indicators to identify the location of change-point in mean, and the hydrological regime shifts. To perform attribution analysis, hydrologic simulations were carried out using Sacramento model for the identified segments. The overall hydrologic alterations of selected annual flow metrics extracted from daily simulated flows and observed flow values were also estimated. The results of MCPD analysis showed that overall three hydrological regimes comprising of three segments i.e., near natural period (NNP, 1940–1955), low impact period (LIP, 1956–1966) and high impact period (HIP, 1967–2014) were identified for both the sites. The results of attribution analysis for the three cases (case-1: NNP & LIP; case-2: LIP & HIP; case-3: NNP & HIP) showed that for the case-1, the changes of flow regimes in Eldred and Salamanca were predominantly affected by climate-induced processes. But, for case-2 and case-3, it was seen that there were magnification of human-induced changes probably due to the landuse change (forest and rangeland increased by 18.31% (19.79%) for Eldred (Salamanca) from 1940 to 1992), construction of Kinzua dam (in the year 1966) and other anthropogenic pressures. Thus, the results of the study can be helpful for quantifying the main drivers of hydrological changes in river basin, and planning suitable water resource management strategies in the basin.

Flash flood risk assessment in urban arid environment: case study of Taibah and Islamic universities’ campuses, Medina, Kingdom of Saudi Arabia

Flooding impacts can be reduced through application of suitable hydrological and hydraulic tools to define flood zones in a specific area. This article proposes a risk matrix technique which is applied on a case study of Taibah and Islamic universities catchment in Medina, Kingdom of Saudi Arabia (KSA). The analysis is based on integration of the hydrologic model hydraulic models to delineate the flood inundation zones. A flood risk matrix is developed based on the flood occurrence probability and the associated inundation depth. The risk matrix criterion is classified according to the degree of risks as high, moderate and low. The case study has indicted low to moderate risk for flood frequencies of 5 years return periods and moderate to high risk may exist for flood with rerun period of 50 and 100 years. The results are projected on a two-dimensional satellite images that shows the geographical locations exposed to flooding. A quantitative summary of the results have been presented graphically to estimate the magnitude of the inundation areas that can assess the degree of damage and its economic aspects. The developed flood risk matrix tool is a quantitative tool to assess the damage which is crucial for decision makers.

Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement

AbstractRainfall‐runoff models are often deficient under changing climatic conditions, yet almost no recent studies propose new or improved model structures, instead focusing on model intercomparison, input sensitivity, and/or quantification of uncertainty. This paucity of progress in model development is (in part) due to the difficulty of distinguishing which cases of model failure are truly caused by structural inadequacy. Here we propose a new framework to diagnose the salient cause of poor model performance in changing climate conditions, be it structural inadequacy, poor parameterization, or data errors. The framework can be applied to a single catchment, although larger samples of catchments are helpful to generalize and/or cross‐check results. To generate a diagnosis, multiple historic periods with contrasting climate are defined, and the limits of model robustness and flexibility are explored over each period separately and for all periods together. Numerous data‐based checks also supplement the results. Using a case study catchment from Australia, improved inference of structural failure and clearer evaluation of model structural improvements are demonstrated. This framework enables future studies to (i) identify cases where poor simulations are due to poor calibration methods or data errors, remediating these cases without recourse to structural changes; and (ii) use the remaining cases to gain greater clarity into what structural changes are needed to improve model performance in changing climate.

Simulating future climate projection under HadCM3 GCM scenarios on a tropical karst island using SDSM: A case study of tropical karst catchment in Rote Island, Indonesia

A robust assessment on the impact of climate change at regional atmospheric condition is crucial to ensure the sustainability of groundwater resource for tropical karst island, where water is considered relatively scarce and thus important for the community. In this study, future long-term climate projection under HadCM3 global model climate (GCM) scenarios for a period of 2020-2090 is validated and simulated, using input data of weather variables downscaled by Statistical Downscaling Model (SDSM). The simulation indicated that the climate variables, i.e. temperature and rainfall, are expected to be affected by climate change and generally vary over the period under the scenarios. The rainfall is estimated to slightly raise by 0.14% and 0.09% under H3A2a and H3B2a scenarios, respectively. Steady temperature increases by 1.89-2.16% (Tmax) and 1.05-1.59 % (Tavg) and a decrease of 0.73-0.76% were predictable for all scenarios.

Anthropogenic sources of potassium in surface water: The case study of the Bystrzyca river catchment, Poland

A three-year river monitoring was carried out in the Bystrzyca River catchment (Poland) dominated by arable areas and wastewater treatment plants. The concentrations of potassium (K) – “a neglected nutrient” – in fresh waters were determined. Analysis of variance (ANOVA) and principal component analysis (PCA) showed spatial and seasonal variability in potassium concentrations. The highest potassium levels were observed in sites located directly below the outlet of the sewage treatment plant of Lublin. The impact of smaller sewage treatment plants on the water quality of the Bystrzyca River was low. Contents of K+ in waters situated in areas experiencing crop and animal production were significantly lower in comparison to ‘sewage’ points. There was a differentiation of correlations between concentrations of K and NH4-N, NO3-N and PO4-P depending on the source of pollution. The potassium levels in river waters usually decreased in early spring.

Modelling of metaldehyde concentrations in surface waters: A travel time based approach

Diffuse agricultural pollution is widely recognized as a significant threat to the quality of water resources. Metaldehyde is a soluble synthetic aldehyde pesticide used globally in agriculture which has caused recent concern due to high observed levels (exceeding the European and UK standards for pesticides in drinking water value of 0.1 µg/l) in surface waters utilized for potable water supply. This paper describes the development of a new travel time based physically distributed metaldehyde prediction model which aims to describe the short term fluctuations of metaldehyde concentrations in surface waters caused by rainfall runoff events. This will enable water infrastructure operators to consider informed control decisions in order to improve the quality of abstracted surface water. The methodology is developed and trailed within a case study catchment in the UK. The new approach integrates spatially and temporally disaggregated surface runoff generation, routing and build-up/wash-off concepts using a simple structure in a GIS environment to build a metaldehyde concentration prediction model. The use of 1 km2 resolution radar rainfall data and identification of high risk areas in the catchment provide an approach which considers the spatio-temporal variations of pollutant generation and transport in the catchment. The model is calibrated and validated using available catchment flow and a new metaldehyde concentration dataset acquired using automatic samplers over four rainfall events. An average coefficient of determination and model efficiency of 0.75 and 0.46 respectively have been obtained for the rainfall events used to validate the model. This shows the capability of the model for the intended purpose of predicting the arrival of peak metaldehyde concentrations at surface water abstraction sites and informing abstraction decisions.

Applications of the PyTOPKAPI model to ungauged catchments

Many catchments in developing countries are poorly gauged/totally ungauged which hinders water resource management and flood prediction in these countries. This study explored the application of the PyTOPKAPI model to South African (Mhlanga) and Ethiopian (Gilgel Ghibe) case study catchments to test its suitability for simulating stream flows from ungauged catchments. The aim is to extend the model application to poorly gauged/totally ungauged catchments in developing countries. The model uses digital elevation data and other spatial data sources to set up the model parameters and the forcing files. To generate reliable stream flows, models generally need to be calibrated, which typically relies on the availability of reliable stream flow data. We show how application of simple lumped models for average runoff ratios, such as that proposed by Schreiber in 1904, can be used as an alternative to detailed calibration with gauged flows. This approach seems to be new; and we show how the proposed method, together with the PyTOPKAPI model, can be used to predict runoff responses in ungauged catchments for water resource applications and flood forecasting in developing countries.

Quantifying nonpoint source emissions and their water quality responses in a complex catchment: A case study of a typical urban-rural mixed catchment

As two key threats to receiving water bodies, the generation mechanisms and processes of urban and agricultural nonpoint sources (NPSs) show clear differences, which lead to distinct characteristics of water quality responses with mixed land-uses catchments compared to single land-use ones. However, few studies have provided such insights in these characteristic or quantified different water environment responses to NPS pollution. In this study, an integrated modelling approach was developed for those complex catchments by combining three commonly used models: SWMM (Storm Water Management Model), SWAT (Soil and Water Assessment Tool) and MIKE 11. A case study was performed in a typical urban–rural catchment of Chao Lake, China. The simulated results indicated that urban NPS pollution responded sensitively to rainfall events and was greatly affected by the antecedent dry days. Compare to urban NPS, agricultural NPS pollution was characterized with the time-lag to rainfall depended on soil moisture and the post-rain-season emissions carried by lateral flows, and were also affected by the local farm-practice schedule. With comprehensive impacts from urban-rural land-uses, the time-interleaved urban and agricultural NPS pollution emissions and more abundant pollution accumulation both led to a decrease in the responsive time and an increase in the frequency of peak pollution concentration values even during the dry season. These obtained characteristics can provide guidance for drafting watershed management plans in similar mixed land use catchments.

Hydropedology of a High Tableland with Cerrado, Brazilian Central Plateau: the Frutal Catchment Case Study

ABSTRACT: Currently, the Brazilian savanna (Cerrado) represents the main agricultural area of the country, comprising a great variety of landscapes and soils, geological formations and vegetation patterns, as well as the major watershed. We studied the hydropedology and morphometry of a representative catchment (Frutal river), on a high tableland (Chapada) in the Triângulo Mineiro region, Brazil, describing the soil-water-landscape relationships to understand land use and water resources. To this end, we applied physical, chemical, micromorphological, and morphometric methods. When dry, [...]

Attributing uncertainty in streamflow simulations due to variable inputs via the Quantile Flow Deviation metric

Abstract Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.

The role of glacier changes and threshold definition in the characterisation of future streamflow droughts in glacierised catchments

Abstract. Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light) model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5). Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975–2004) and future (2071–2100) period. Two existing threshold approaches to define future droughts are employed: (1) the threshold from the historical period; (2) a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical threshold combined with a constant glacier area results in a drastic decrease of the number of droughts. The drought characteristics between future and historical periods are more similar when the transient threshold is used, for both glacier area conceptualisations. With the transient threshold, factors causing future droughts can be analysed. This study revealed the different effects of methodological choices on future streamflow drought projections and it highlights how the options can be used to analyse different aspects of future droughts: the transient threshold for analysing future drought processes, the historical threshold to assess changes between periods, the constant glacier area to analyse the effect of short-term climate variability on droughts and the dynamic glacier area to model more realistic future discharges under climate change.

Effect of GIS parameters on modelling runoff from river basin. The case study of catchment in the Puck District

The study was preceded to check the impact of the adopted digital elevation model resolution on the determination of catchment parameters and the further influence of the received information on calculations related to the hydrograph at the closing point of the basin after a synthetic 100-year precipitation episode. The study area are river basins located in the Puck commune convoying water directly to the Puck Bay. These studies allowed the formulation of the basic assumptions for the research project (in short called WaterPuck) supported by the National Centre for Research and Development.

Generation of multi-site stochastic daily rainfall with four weather generators: a case study of Gloucester catchment in Australia

Four weather generators, namely, R-package version of the Generalised Linear Model for daily Climate time series (RGLIMCLIM), Stochastic Climate Library (SCL), R-package multi-site precipitation generator (RGENERATRPREC) and R-package Multi-site Auto-regressive Weather GENerator (RMAWGEN), were used to generate multi-sites stochastic daily rainfall for a small catchment in Australia. The results show the following: (1) All four models produced reasonable results in terms of annual, monthly and daily rainfall occurrence and amount, as well as daily extreme, multi-day extremes and dry/wet spell length. However, they also simulated a large range of variability, which not only demonstrates the advantages of multiple weather generators rather than a single model but also is more suitable for climate change and variability impact studies. (2) Every model has its own advantages and disadvantages due to their different theories and principles. This enhances the benefits of using multiple models. (3) The models can be further calibrated/improved to have a “better” performance in comparison with observations. However, it was chosen not to do so in this case study for two reasons: to obtain a full range of climate variability and to acknowledge the uncertainties associated with observation data. The latter are interpolated from limited stations and therefore have high pairwise correlations—ranging from 0.69 to 0.99 with a median and mean value of 0.87 and 0.88, respectively, for daily rainfall. These conclusions were drawn from a case study in Australia, but could be extended to general guidelines of using weather generators for climate change and variability studies.