Case Study Of Catchment Research Articles

Key changes across valley floors in mountain areas affected by different levels of human impact: a case study of the Ochotnica river catchment in the Polish Carpathians

AbstractThe goal of this paper was to present knowledge on changes in the morphodynamic structure of the Ochotnica River (Polish Carpathians) and transformations within its active river zone since the end of the 19th century. The study used a set of archival and contemporary cartographic materials and the results of three-fold field mapping of the morphodynamic structure of the riverbed. Direct and indirect human interference with the natural environment of the catchment and the fluvial system was taken into account in the analysis. Analysis of changes in the morphodynamic structure of the Ochotnica and its active river zone since the end of the 19th century indicated significant changes in the development trend of the riverbed. The contemporary structure of the Ochotnica is more complex than in the 1980s. There has been a fragmentation of the riverbed into sections with different morphodynamic sections. The proportion of erosive sections has increased, which explains the reduced in the width of the active river zone of the Ochotnica. The average width of the active river zone of the river between 1861 and 2022 has changed from 80 m to 18 m. Human impact has been identified as the main reason for the changes in the morphodynamic structure of the riverbed and its active river zone. Currently, only the unregulated sect ion is characterised by free lateral migration of the riverbed and the widest active river zone (∼ 28 m).

Soil Erosion Analysis with GIS: A Case Study of Oued Sly Catchment, Northern Algeria

Soil erosion is a process that involves the detachment and transportation of soil particles by water, presenting notable challenges of the depletion of soil fertility, diminished agricultural productivity, and consequences for water reservoirs. The integration of Geographic Information System (GIS) and modeling techniques provides a valuable platform for assessing and addressing soil water erosion. This study specifically examines the risk of soil water erosion in the Oued Sly catchment within the Middle Cheliff watershed in northern Algeria. Employing the Universal Soil Loss Equation (USLE) and thematic maps, the research evaluates the key factors influencing erosion. Results reveal that the catchment generally experiences low to moderate erosion levels, averaging 23.4 to 40 t ha-1 yr-1 across 90.7% of the total area. However, around 9.3% of the catchment exhibits higher erosion rates exceeding 40 t ha-1 yr-1. These findings offer valuable insights for informed watershed management and strategies to mitigate soil water erosion in comparable regions

Variability in land surface temperature concerning escalating urban development using thermal data of Landsat sensor: A case study of Lower Kharun Catchment, Chhattisgarh, India

Over the past few years, there has been a revitalized emphasis on comprehending the shifts in land cover and their implications for a range of environmental factors. This investigation seeks to analyze how changes in land surface temperatures (LST), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and alterations in land cover intersect within the lower Kharun catchment area. The primary dataset utilized in this study is for 2001 and 2021 Landsat 7 and 8, part of the Landsat program managed by the United States Geological Survey (USGS), offer essential Earth observation data using their multispectral and thermal sensors which are designed to detect thermal radiation emitted from the Earth's surface. When these bands are properly processed, they enable accurate temperature measurements. Visual interpretation was conducted on these images, categorizing them into five specific classes of land cover these were vegetation, open land, settlement, waterbodies, and cultivation. Following this, spectral indices like NDVI and NDBI were calculated, and LST was derived using a single-channel algorithm. Subsequently, correlation analysis was utilized to explore the interconnectedness or mutual relationship among the spatial distribution of these parameters. Over the period from 2001 to 2021, the most significant changes in land use were observed in the settlement area and cultivation, which increased by 6.92 and 6.23 sq. km, respectively. Conversely, open land, vegetation, and waterbodies experienced decreases of 7.13, 5.56, and 0.46 sq. km, respectively. The patterns in which LST, NDBI, and NDVI are distributed, exhibited corresponding variations following changes in land cover. The observed alterations in LST, NDBI, and NDVI are believed to be primarily influenced by the expansion of built-up areas. A noticeable association suggests that as built-up areas increase, both NDBI and LST values typically rise.Furthermore, a correlation observed between LST with NDVI was negative, suggesting an inverse relationship between these parameters. On the other hand, the correlation of LST with NDBI observed was positive, indicating that these parameters exhibit a direct relationship. Overall, these findings seem to be complex and highlight the interactions between changing land cover and environmental parameters, underscoring the importance of understanding these relationships for effective land management and environmental monitoring.

Agent-Based Modeling for Household Decision-Making in Adoption of Private Flood Mitigation Measures: The Upper Kan Catchment Case Study

Residential areas in developing arid and semi-arid countries are highly vulnerable to flooding, and water shortages have forced their inhabitants to live close to rivers. While climate change is expected to cause more extreme weather conditions in the future, adopting private loss-reduction measures can diminish flood risk. Although the number of flood models has grown significantly for developing arid and semi-arid lands, these models suffer from being incapable of performing micro-scale flood risk analysis and including household behaviors. This research work presents a novel socio-economic simulation model in the framework of flood risk management (FRM) to couple household adaptive responses with flood risk analysis. Agent-based modeling (ABM) embeds human behaviors in a flood-simulating environment. The focus of this research is the upper Kan catchment in Iran with a long history of severe flash flooding. Our results show the ability of the developed framework to address household participation in FRM activities through private precautionary measures. Moreover, the results indicate the importance of presenting such micro-level behaviors in flood modeling for a more realistic flood risk assessment. It is also demonstrated that household adaptation in a continuous way can lead to less flood risks in the region, even under climate change and the future economy. Finally, the results reveal that the remaining and diminished regional flood risks are influenced by the behavioral framework through which the individuals make decisions in adopting flood-loss-reduction measures. A similar pattern is, however, observed in household contributions over time among the discussed behavioral approaches.

Applicability of CHIRPS-based Pitman model for simulation of climate change flows

Hydrological modelling and continuous monitoring are important for the management of water resources, especially with intensified climate variability. Effective water management is reliant on the availability of climate data and simulations of future projections of the available water resources. The increased likelihood of climatic extremes has made effective water management challenging, especially for vulnerable data-scarce catchments that are highly reliant on natural water resources and have low adaptive capacities. However, advancements in remote sensing have availed alternative sources of climate data for hydrological studies of such catchments. This research evaluated the applicability of Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) in simulating climate change flows. Climate change data of 11 Global Circulatory Models (GCMs), enforced by Representative Concentration Pathways (RCP) 4.5 & 8.5 were downloaded and downscaled to represent near (2021–2060) and far (2061–2099) future scenarios. Climate change signals were derived by comparing future scenarios with the present-day period (1981–2019). Climate change signals were then used to adjust input climate data for the Pitman model. The Pitman model was calibrated and projected future flows were simulated for study catchments in drainage regions B, V and G of South Africa. Climate change simulation results demonstrated projected decreases of between 1.49% and 29.96% for the near future scenarios & between 0.45% and 40.31% for the far future scenarios in all the study catchments. Simulated flows for drainage region B recorded contrasting increasing projections of between 17.18% and 24.88% (RCP 4.5) for the near future scenarios while drainage region G also illustrated contrasting increasing projections of between 6.23% and 7.67% (RCP 4.5) for the far future scenarios. Generally, the results of simulated climate change flows based on observed rainfall and CHIRPS data demonstrated decreasing future flows for the South African case study catchments, corroborating with previous studies in projecting a drier future. This research hence recommends the application of CHIRPS estimates as a suitable substitute to dwindling observed rainfall data in the simulation of climate change flows for data-scarce catchments using the Pitman model.

Application of electrical and electromagnetic data to delineate shallow aquifer zones: a case study of Vea catchment, Ghana

Application of electrical and electromagnetic data to delineate shallow aquifer zones: a case study of Vea catchment, Ghana

Surface water catchment deformation—toward a conceptual model: the case study of Zarqa river catchment, Jordan

Surface water catchment deformation—toward a conceptual model: the case study of Zarqa river catchment, Jordan

A framework for modelling the probability of flooding under levee breaching

AbstractLevees aim to provide protection during floods, however, these structures can breach, causing significant damage. Flood maps that include levee breaching are often limited to deterministic methods. Where probabilistic breaching is done, it often requires computationally expensive Monte Carlo simulations and an understanding of the geotechnical levee properties that are often limited. In this paper, we combine existing fragility curves and empirical breaching equations with a framework for automating levee breaching in catchments with limited geotechnical information. This method can be adapted and applied to existing 2D flood models to determine the probability of inundation, given that a breach occurs. This ultimately allows for greater emergency responses and land use planning to reduce the flood risk faced by our communities. The method was applied to four case study catchments. The results showed that including levee breaching in one catchment led to an average increase in the inundated area by 48.2% and a tripling in the potentially exposed area. However, breaching in some locations reduced the inundation extent by 12%, illustrating the potential for fuse plug levees and floodways as a flood mitigation strategy. This strategy has seen successful usage internationally. Further investigation is recommended to consider whether these mitigation strategies should be enacted.

Water Colour Changes in High-Elevation Alpine Lakes during 2017–2022: A Case Study of the Upper Orco Valley Catchment

The water resource is severely compromised by climate change, and its availability and quality can no longer be taken for granted, even in places considered pristine, such as mountains. In this study, we evaluated the water colour variability of three artificial mountain lakes located in a relatively small basin (Western Italian Alps) at high elevations, and related this variability to the local climate conditions of the hydrological basin to which they belong. We estimated the dominant wavelength (DW) of lake water from Sentinel-2 acquisitions for the period 2017–2022, performing a chromaticity analysis. We correlated DW with climatic parameters recorded by two automated weather stations. Average DW varies from 497 nm of Serrù Lake and Agnel Lake to 512 nm of Lake Ceresole, where DW varies seasonally (variation of 75–100 nm in one year). During April–July, the DW of Lake Ceresole is significative correlated with air temperatures and snow cover (−0.8 and +0.8, respectively). During August–October, the relationship with temperature decreases to −0.5, and a correlation of 0.5 with the amount of rainfall appears. This work shows that mountain lake waters can exhibit variable quality (expressed here by water colour) in response to meteorological and hydrological conditions and events.

Channel morphological change monitoring using high-resolution LiDAR-derived DEM and multi-temporal imageries

Natural processes and human activities both cause morphological changes in channels. Remote sensing products are often used to assess planform changes, but they tend to overlook vertical changes. However, considering both planform and vertical changes is crucial for a comprehensive evaluation of morphological changes. Using spatiotemporal aerial imagery and topographic data, remote sensing plays a vital role in evaluating channel morphological changes and flood-carrying capacity. This study aimed to investigate the morphological changes of a creek in an urban catchment using very high-resolution remote sensing products. In this study, we developed a new framework for investigating overall channel morphology change by employing very high-resolution aerial imagery and a LiDAR-derived digital elevation model (DEM). By digitizing channel boundaries using ArcGIS Pro 3.0, and analyzing various morphological parameters, erosion, and deposition patterns, we examined the impact of urban expansion and infrastructure development on channel adjustments. Channel adjustments have been performed in the case study catchment (Dry Creek, South Australia, Australia) due to urban expansion and development of infrastructure in the downstream reaches. Our findings revealed a significant southwest shift in the planform of the channel, with a maximum shift of 478 m and an average shift of 217 m since 1998. This alteration resulted in an increase in the sinuosity index reaching 1.2. Over the period from 2018 to 2022, the channel experienced a net deposition depth of 3.4 cm to 3.6 cm in downstream reaches. The annual deposition volume in the downstream reaches was 1963 m3, necessitating regular desilting to prevent channel capacity loss and flooding in the surrounding environment. This study also highlights the incremental growth of riparian vegetation within the channel, which affects surface roughness, channel slope, and carrying capacity. These findings provide a valuable baseline for future investigations into stream channel morphology changes and emphasize the importance of implementing appropriate measures such as desilting and vegetation management to mitigate deposition levels, reduce flood risks, and enhance the overall health and functionality of Dry Creek. The framework used in this study can be applied to other case studies employing reliable and high-resolution remote sensing data products.

Neglecting hydrological errors can severely impact predictions of water resource system performance

Risk-based decision making for water resource systems often relies on streamflow predictions from hydrological models. These predictions are integral for estimating the frequency of high consequence extreme events, such as floods and droughts. However, streamflow predictions are known to have errors due to various factors such as incomplete hydrological understanding, parameter misspecification, and uncertain data. Despite these errors being well known, they are frequently neglected when undertaking risk-based decision-making. This paper demonstrates that neglecting hydrological errors can impact on drought risk estimation for high stakes decisions with potentially severe consequences for water resource system performance. A generic framework is introduced to evaluate the impact of hydrological errors for a wide range of water resource system properties. This framework is applied in two Australian case study catchments, where we use a stochastic rainfall model, the GR4J hydrological model, a residual error model, and a simplified reservoir storage model to estimate water resource performance metrics (risk and yield). The results underscore the impact of neglecting hydrological errors on decision-making. In one case study catchment, the yield was over-estimated by ∼15%–55%, resulting in the (actual) risk of running out of water being ∼2–30 times larger than reservoir design. The magnitude of these errors in water resource performance metrics is striking, especially considering that the streamflow predictions appear reasonable based on typical performance metrics (e.g., NSE of ∼0.7). The errors in performance metrics stem from the complex propagation of hydrological errors through the water resource system modelling chain. By accounting for critically important hydrological errors we can mitigate highly erroneous risk estimates and improve decision-making related to water resource management.

Evaluation of a weather forecasting model and HEC-HMS for flood forecasting: case study of Talesh catchment

Reports demonstrate that floods are among the most prevalent and deadliest natural disasters affecting 520 million people annually. The present study seeks to evaluate flood forecasting using the weather research and forecasting (WRF) model and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model. To this end, WRF and HEC-HMS were calibrated by comparing their results with the data observed at measuring stations. Then, the output rainfall data of the WRF model were implemented by the calibrated HEC-HMS model and were examined using the statistical indices, which were revealed to be 4.13, 3.42, and 2.67 for the flow volume and 6.2, 2.46, and 5.11 for the peak flow, suggesting the accurate performance of WRF model alongside HEC-HMS in the Talesh catchment.

Geospatial and AHP technique in assessment of groundwater potential zones—a case study of Boranakanive reservoir catchment in India

Geospatial and AHP technique in assessment of groundwater potential zones—a case study of Boranakanive reservoir catchment in India

Changes in concentrations of potentially toxic elements during storage of hard river water samples at low temperatures using different sample preservation procedures

PurposeAccording to standard procedure recommended by the Water Framework Directive (WFD), dissolved concentrations of potentially toxic elements (PTEs) in river water are determined by inductively coupled plasma mass spectrometry (ICP-MS) in filtered (0.45 µm) and acidified (pH 2) samples. Properly prepared and stored composite samples can enhance the temporal representativity of monitoring without increasing analytical costs. For this purpose, the WFD recommends freezing, which can preserve the species integrity and prevent adsorption processes of PTEs.MethodsLow storage temperature in hard water samples can trigger precipitation of calcium carbonate (CaCO3) and subsequent co-precipitation of PTEs. To test and determine to what extent co-precipitation with CaCO3 can influence the determination of PTE concentrations, composite river water samples from two case study catchments in Hungary (Zagyva and Koppány) were prepared following two different sample preservation procedures. To study the behavior of PTEs in river water during storage, in the first procedure, samples were frozen, and they were thawed, filtered, and acidified directly prior to the analysis. In the second procedure, samples were filtered on-site and acidified prior to freezing to prevent precipitation of CaCO3 and then only thawed to carry out the chemical analyses. Concentrations of PTEs were determined by ICP-MS.ResultsA statistical evaluation of the results using Student’s t-test revealed significant differences between the two sample preservation procedures, suggesting that PTEs were largely co-precipitated with CaCO3 if the samples were not acidified prior to freezing.ConclusionWhen establishing protocols for sample preservation procedures, the phenomenon of co-precipitation of PTEs with CaCO3 should be considered if the samples were not acidified before freezing. Therefore, to prevent co-precipitation of PTEs with CaCO3, samples should be filtered and acidified before freezing.

Application of bivariate statistical techniques for landslide susceptibility mapping: A case study in Kaghan Valley, NW Pakistan

Landslides are dangerous events that threaten both human life and property. This research presents a case study of Kaghan valley catchment, which is an area of frequent landslide activity. We aim to present a comparison between the bivariate Landslide Numerical Risk Factor (LNRF), Statistical Index (SI) and Information Value (InfV) statistical models to evaluate landslide susceptibility. A total of 1556 landslides were identified using earlier reports, field surveys, and GOOGLE Earth imagery. The abundance of landslides is primarily controlled by acute deformation caused by a major thrust fault system and proximity to Hazara Kashmir Syntaxis (HKS). A landslide inventory was randomly partitioned into two datasets. 70% (1106) of landslides were used as a training phase of the models, whereas 30% (450) as validation of the three models. A spatial database of 11 conditioning factors was produced consisting of slope, aspect, elevation, lithology, land use, Topographic Wetness Index (TWI), rainfall, Stream Power Index (SPI), distance to faults, rivers and streams. All the landslide susceptibility assessment parameters were obtained from different sources and different landslide susceptibility maps were prepared on the GIS software. Performance of the three models was validated through the Receiver operator Characteristics (ROC) through success and prediction rate curves. Results show that the area under the ROC curve (AUC) for InfV, LNRF and SI models are 70.95, 83.99 and 67.56 for success rate curves and 70.75, 83.99 and 67.85 for prediction rate curves, respectively. LNRF having the highest AUC value proved to be superior for generating regional scale landslide susceptibility maps.

Benchmarking Three Event-Based Rainfall-Runoff Routing Models on Australian Catchments

In the field of hydrology, event-based models are commonly used for flood-flow prediction in catchments, for use in flood forecasting, flood risk assessment, and infrastructure design. The models are simplistic, as they do not consider longer-term catchment processes such as evaporation and transpiration. This paper examines the relative performance of two widely used models, the American HEC-HMS model, the Australian RORB model, and a newer model, the RRR model. The evaluation is conducted on four case study catchments in Australia. The first two models, HEC-HMS and RORB, do not include baseflow, necessitating the estimation of baseflow through alternate means. By contrast, the RRR model includes baseflow, by extracting a separate loss from the rainfall, and then routing the resultant flow through the catchment, much like quickflow, but with a longer delay time. The models are calibrated and then verified with weighted mean parameter values on an independent set of events in each case study catchment. This gives an indication of the ability of the models to correctly predict flow, which is important when the models are used with design rainfalls to predict design flows. The results demonstrate that all models perform adequately on the four examined catchments, but the RRR model exhibits superior calibration, and, to a lesser extent, better validation compared to the other two models.

Prioritization of soil erosion prone sub-watersheds through morphometric analysis using geospatial and weighted sum approach: a case study of Boranakanive reservoir catchment in Tumkur district, Karnataka, India

Prioritization of soil erosion prone sub-watersheds through morphometric analysis using geospatial and weighted sum approach: a case study of Boranakanive reservoir catchment in Tumkur district, Karnataka, India

Dynamically coupling system dynamics and SWAT+ models using Tinamït: application of modular tools for coupled human–water system models

Abstract. Participatory water resource management requires modeling techniques that are accurate and flexible yet stakeholder-friendly. While different modeling frameworks offer advantages and disadvantages, system dynamics (SDs) models have seen sustained use as a stakeholder-friendly approach for participatory water resource modeling. Physically based models (e.g., SWAT+) have seen sustained use to model the hydrological components of water systems. Proposed as a way to combine the relative strengths of both modeling paradigms, model coupling allows researchers to, for example, build participatory SD models with stakeholders, while delegating the hydrological components of the overall model to an external hydrological model. Recently developed to facilitate model coupling, the Tinamït Python package presents an extensible, outward-facing application programming interface (API). It allows for the development of extensions (wrappers) that expand compatibility with different physically based models. However, no watershed hydrological model has yet been connected to this API. In the present study, a socket and JavaScript Object Notation (JSON)-based communication protocol was developed with the goal of facilitating the coupling of models written in languages such as Fortran. This novel protocol served to develop a Tinamït-compatible wrapper for the hydrological model SWAT+, allowing it to be coupled to human–water SD models. The novel coupling protocol was then applied to a case study of Tanzania's Usa river catchment. This approach provides the modeler with the benefits of both physically based and SD models, thereby allowing the detection of potentially far-reaching effects of policy-makers' decisions.

Temporal Transferability of Calibrated Hydrological Model Parameters: A Case Study of Gin Catchment, Sri Lanka

Lack of observed data for model calibration hinders the application of hydrological models in many poorly-gauged catchments, particularly in the humid tropical region. Despite much less attention given, it is vital to assess transferability of calibrated parameters in order to apply hydrological models in such catchments to assist their water resources planning and management activities. Thus, this study investigated temporal transferability of a lumped conceptual hydrological model’s (MIKE 11 NAM) calibrated model parameters for rainfall-runoff simulations in two different time periods beyond its calibration period. Study area was selected as Gin catchment located in the humid tropical region. MIKE 11 NAM model was calibrated for the period 1995-1998 [Nash Sutcliffe coefficient (NSE) = 0.73, percent bias (PBIAS) = 3.9%, ratio of the root mean square error to the standard deviation of measured data (RSR) = 0.52] and validated for the period 1999-2002 (NSE=0.66, PBIAS = 8.7%, RSR = 0.59) for the Gin catchment. The temporal transferability of the calibrated model parameters was tested using two scenarios which formulated based on the temporal lag between the calibration period and the transfer period: scenario A having a 4-year time lag and scenario B having a 8-year time lag. Scenario A which evaluated the model performance using 2003-2006 streamflow data indicated only a marginal loss in the model performance in comparison to the calibration. It showed an overall ‘good’ performance (NSE=0.64, PBIAS = 8.6%, RSR = 0.59) including promising capability to reproduce the peak flows (<10th percentile) with Pearson’s correlation coefficient of 0.6. However, scenario B which evaluated the model performance using 2007-2010 streamflow data indicated ‘unsatisfactory’ model performance (NSE=0.42, PBIAS = 13.6%, RSR = 0.76). Therefore, this study suggests that the calibrated parameters of MIKE 11 NAM model can be temporally transferred within a catchment with a 4-year time lag from the calibration period implying the applicability of this modelling framework for rainfall-runoff simulations especially in the catchments where streamflow data is sparse.

Assessing climate change impacts on surface water availability using the WEAP model: A case study of the Buffalo river catchment, South Africa

Study regionThe Buffalo River (BR) catchment, KwaZulu-Natal, South Africa. Study focusDue to the vast majority of the BR catchment’s water demands not being fully satisfied in recent years, studies investigating potential climate change impacts on the catchment's water supply availability are needed. The study’s objective was to therefore assess climate change-induced surface water availability (SWA) variations in the BR catchment from 2020 to 2100. To achieve this, the hydrologic Water Evaluation and Planning model was forced with the catchment's physical and hydrological data, and projected climate data from an ensemble of GCMs under RCP4.5 and RCP8.5 scenarios from CMIP5. New hydrological insights for the regionThe study findings projected increased precipitation, especially in the far future (2070–2100) whereby mean annual precipitation increased by 5 % to 8286 Mm3/annum under the worst-case climate change scenario (RCP8.5). With evapotranspiration and water abstractions averaging 4500 Mm3/annum and 115 Mm3/annum, respectively, surface runoff and SWA increased by 8 % and 10 %, yielding averages of 3265 Mm3/annum and 287 Mm3/annum, respectively. Even with the increased SWA, unmet demands also increased by 113 % towards the end of the 21st century. As the study established that climate change might exacerbate the BR catchment's water supply system's insufficiency to meet growing demands, such findings present an opportunity for the integrated Water-Energy-Food nexus approach to be further utilised for formulating sustainable water management strategies.