Search Results (13)

Understanding the relationship between the processes involved in hydrology and changesin land use becomes more urgent amid the accelerated development of urban areas. In this regard, this paper proposes the application of a spatio-temporal analysis of flood vulnerability through multi-criteria analysis (Analytical Hierarchy Process), integrated with GIS and modeling of multidimensional urban development processes within Cizre, Turkey. Important hydrological factors for the formation of flood risks, such as elevation, slope, land use/cover, rainfall, drainage density, and proximity to the river, were considered when preparing the flood susceptibility map. It was revealed that high- and very-high-risk zones are mainly located near the Tigris River and in urbanized areas, which occupy more than half of the territory under consideration. Multidimensional analysis showed that unplanned development increases flood risks in the area because of the increased area of impervious surfaces and the violation of natural water flows. As a way to overcome the limitations of traditional methods of static analysis of flood risks, the Flood Risk Transfer Index (FRTI) has been developed to describe the process of spatial redistribution of risks resulting from the impact of the increase in urbanization rates. The indicator of spatial redistribution of flood risk reached a value of 0.72, showing that flood pressures increased in existing cities instead of reducing them. Thus, this study provides a breakthrough in understanding flood risks through the introduction of a new methodology. Full article

This article presents a comprehensive assessment of mudflow risk in the Talgar River basin through the application of Multi-Criteria Decision Analysis (MCDA) methods and numerical modeling using the Rapid Mass Movement Simulation (RAMMS) environment. The first part of the study involves a spatial assessment of mudflow hazard and susceptibility using GIS technologies and MCDA. The key condition for evaluating mudflow hazard is the identification of factors influencing the formation of mudflows. The susceptibility assessment was based on viewing the area as an object of spatial and functional analysis, enabling determination of its susceptibility to mudflow impacts across geomorphological zones: initiation, transformation, and accumulation. Relevant criteria were selected for analysis, each assigned weights based on expert judgment and the Analytic Hierarchy Process (AHP). The results include maps of potential mudflow hazard and susceptibility, showing areas of hazard occurrence and risk impact zones within the Talgar River basin. According to the mudflow hazard map, more than 50% of the basin area is classified as having a moderate hazard level, while 28.4% is subject to high hazard, and only 1.8% falls under the very high hazard category. The remaining areas are categorized as very low (4.1%) and low (14.7%) hazard zones. In terms of susceptibility to mudflows, 40.1% of the territory is exposed to a high level of susceptibility, 35.6% to a moderate level, and 5.5% to a very high level. The remaining areas are classified as very low (1.8%) and low (15.6%) susceptibility zones. The predictive performance was evaluated through Receiver Operating Characteristic (ROC) curves, and the Area Under the Curve (AUC) value of the mudflow hazard assessment is 0.86, which indicates good adaptability and relatively high accuracy, while the AUC value for assessing the susceptibility of the territory is 0.71, which means that the accuracy of assessing the susceptibility of territories to mudflows is within the acceptable level of model accuracy. To refine the spatial risk assessment, mudflow modeling was conducted under three scenarios of glacial-moraine lake outburst using the RAMMS model. For each scenario, key flow parameters—height and velocity—were identified, forming the basis for classification of zones by impact intensity. The integration of MCDA and RAMMS results produced a final mudflow risk map reflecting both the likelihood of occurrence and the extent of potential damage. The presented approach demonstrates the effectiveness of combining GIS analysis, MCDA, and physically-based modeling for comprehensive natural hazard assessment and can be applied to other mountainous regions with high mudflow activity. Full article

This article focuses on forecasting morphological changes in small rivers, using the Ulken Almaty River, located on the northern slope of the Ile Alatau range in the Tien Shan mountain system, as a case study. One of the key components of river morphology is the dynamics of channel processes, including erosion, accretion, and the shifting of channel forms. Understanding these processes in rivers flowing through urbanized areas is essential for mitigating environmental and infrastructural risks. Despite their importance, studies of this nature in Kazakhstan remain at a formative stage and are largely fragmentary, underscoring the need for modern approaches to river morphology analysis. Three representative sections of the Ulken Almaty River (upstream, midstream, and downstream) were selected for analysis. Satellite imagery from 2012 to 2021 was used for manual digitisation of river channel outlines. Annual erosion and accretion areas were calculated based on these data. The DSAS 5.1 module, integrated into ArcGIS 10.8.1, was applied to determine the rates of erosion and accretion over the ten-year period. To forecast future channel changes, the Kalman filter model was employed, enabling projections for 10 and 20 years into the future. A comparative analysis of the intensity of the erosion and accretion processes was conducted for each river section. Spatial and temporal variations in bank dynamics were identified, with the most significant changes occurring in the middle and lower reaches. Forecasted scenarios indicate the possible deformation pathways of the river channel influenced by both natural and anthropogenic factors. The results provide valuable insights into the spatiotemporal dynamics of fluvial processes in small mountain rivers under the pressure of urban development and climatic variability. The methodology employed in this study offers practical applications for urban planning, river management, and the mitigation of geomorphological hazards. Full article

The study explores the impact of floods, phenomena amplified by climate change and human activities, on the natural and anthropogenic environment, focusing on the analysis of a section of the Cigher River in the Crișul Alb basin in western Romania. The research aims to identify areas vulnerable to flooding under different discharge scenarios, assess the impact on agricultural lands, and propose a reproducible methodology based on the integration of GIS technologies, hydraulic modeling in HEC-RAS, and the use of LiDAR data. The methodology includes hydrological analysis, processing of the Digital Elevation Model (DEM), delineation of geometries, hydraulic simulation for four discharge scenarios (S1–S4), and evaluation of the flood impact on agricultural and non-agricultural lands. Evaluated parameters, such as water velocity and flow section areas, highlighted an increased flood risk under maximum discharge conditions. The results show that scenario S4, with a discharge of 60 m³/s, causes extensive flooding, affecting 871 hectares of land with various uses. The conclusions emphasize the importance of using modern technologies for risk management, protecting vulnerable areas, and reducing economic and ecological losses. The proposed methodology is also applicable to other river basins, representing a useful model for developing sustainable strategies for flood prevention and management. Full article

Monitoring and protecting flowing watercourses is a complex and challenging task that requires the collaboration and coordination of various stakeholders such as governments, industries, farmers, consumers and environmental groups. The study of the dynamics of the concentration of polluting factors and especially the concentrations of heavy metals and highlighting a seasonal variation is a necessary element from this point of view. In this article, we present the results of our analyses carried out in two measurement campaigns executed in 10 monitoring points along the Danube River, between Braila city and Isaccea city in the pre-deltaic area, during the summer season and autumn season 2022. The importance of this area is given by the fact that the Danube Delta is part of the UNESCO heritage, and the monitoring of polluting factors is a necessity in the desire to protect this area. The data measured during the July and August 2022 campaign cover a wide range of chemical species: Phosphate, CCO, CBO₅, NH₄⁺, N-NO₂, N-NO₃⁻, N-Total, P-PO₄ ³⁻, SO₄²⁻, Cl⁻, phenols, as well as metals with a harmful effect: Al, As, Cd, Cr, Fe. The study includes an evaluation based on the statistical approach of the results to highlight the significant correlations and differences identified between the two data sets. Next, to highlight the obtained results, a numerical model was considered using HEC-RAS and ESRI ArcGIS applications in a two-dimensional unsteady flow model in order to obtain the non-homogenous concentrations’ distributions in the studied area. These two-dimensional models have been less studied in the specialized literature. In this way, interesting results could be obtained, and prediction methods regarding the dynamics of metal concentrations could be structured. The data obtained were used for the terrain model from the USGS service, and the flows of the Danube and its two tributaries were simulated using the data provided by the national services. In this work, we present the results obtained for the dynamics of the concentrations of the metals Al, As, Cd, Cr and Fe and the evaluation of the specific absorption coefficients for the explanation and correlation with the results of the measurements. Except for the numerical model presented, we would like to highlight the existence of some contributions of the main tributaries of the Danube in the study area. Such a systematic study has not been carried out due to conditions imposed by the border authorities. From this point of view, this study has an element of originality. The study is part of a more complex project in which the spatio-temporal distribution of the polluting factors in the water was evaluated, and the habitats in the study area were inventoried—especially those of community interest. In this way, we were able to expose the self-purification capacity of the Danube and highlight the existence of a concentration reduction gradient along the course of the river. The aspects related to the influence of the distribution of polluting factors on the state of health will be the subject of another article. Full article

Floods are among the most devastating disasters in terms of socio-economics and casualties. However, these natural disasters can be managed and their effects can be minimized by flood modeling performed before the occurrence of a flood. In this study, flood modeling was developed for the Göksu River Basin, Mersin, Türkiye. Flood hazard and risk maps were prepared by using GIS, HEC-RAS, and HEC-HMS. In hydraulic modeling, Manning’s n values were obtained from 2018 CORINE data, return period flow rates (Q25, Q50, Q100, Q500) were obtained from HEC-HMS, and the application was carried out on a 5 m resolution digital surface model. In the study area, the water depths could reach up to 10 m, and water speeds were approximately 0.7 m/s. Considering these values and the fact that the study area is an urban area, hazard maps were obtained according to the UK Department for Environment, Food and Rural Affairs (DEFRA) method. The results indicated that possible flood flow rates from Q25 to Q500, from 1191.7 m³/s to 1888.3 m³/s, were detected in the study area with HEC-HMS. Flooding also occurred under conditions of the Q25 flow rate (from 4288 km² to 5767 km²), and the impacted areas were classified as extremely risky by the DEFRA method. Full article

During the last decade, climate change has generated extreme rainfall events triggering flash floods in short periods worldwide. The delimitation of flood zones by detailed mapping generally makes it possible to avoid human and economic losses, especially in regions at high risk of flooding. The Taguenit basin, located in southern Morocco, is a particular case. The mapping of the flood zones of this basin by the method of the Flood Hazard Index (FHI) in a GIS geographic information systems environment was based on the multi-criteria analysis, taking into consideration the seven parameters influencing these extreme phenomena, namely rainfall, slope, flow accumulation, drainage network density, distance from rivers, permeability, and land use. Average annual rainfall data for 37 years (1980 to 2016) was used in this study for floodplain mapping. A weight was calculated for each parameter using the Analytical Hierarchy Process (AHP) method. The combination of the maps of the different parameters made it possible to draw up a final map classified into five risk intervals: very high, high, moderate, lower and very lower presenting, respectively, 8.04%, 20.63%, 31.47%, 15.36%, and 24.50% of the area of the basin. The reliability of this method was tested by a Flood susceptibility analysis. The results generated by the Flood Hazard Index (FHI) model are similar to those of previous historical events. Realistic and applicable solutions have been proposed to minimize the impact of these floods as much as possible. Full article

Floods are the most frequent and destructive natural disasters causing damages to human lives and their properties every year around the world. Pakistan in general and the Peshawar Vale, in particular, is vulnerable to recurrent floods due to its unique physiography. Peshawar Vale is drained by River Kabul and its major tributaries namely, River Swat, River Jindi, River Kalpani, River Budhni and River Bara. Kabul River has a length of approximately 700 km, out of which 560 km is in Afghanistan and the rest falls in Pakistan. Looking at the physiography and prevailing flood characteristics, the development of a flood hazard model is required to provide feedback to decision-makers for the sustainability of the livelihoods of the inhabitants. Peshawar Vale is a flood-prone area, where recurrent flood events have caused damages to standing crops, agricultural land, sources of livelihood earnings and infrastructure. The objective of this study was to determine the effectiveness of the ANN algorithm in the determination of flood inundated areas. The ANN algorithm was implemented in C# for the prediction of inundated areas using nine flood causative factors, that is, drainage network, river discharge, rainfall, slope, flow accumulation, soil, surface geology, flood depth and land use. For the preparation of spatial geodatabases, thematic layers of the drainage network, river discharge, rainfall, slope, flow accumulation, soil, surface geology, flood depth and land use were generated in the GIS environment. A Neural Network of nine, six and one neurons for the first, second and output layers, respectively, were designed and subsequently developed. The output and the resultant product of the Neural Network approach include flood hazard mapping and zonation of the study area. Parallel to this, the performance of the model was evaluated using Root Mean Square Error (RMSE) and Correlation coefficient (R2). This study has further highlighted the applicability and capability of the ANN in flood hazard mapping and zonation. The analysis revealed that the proposed model is an effective and viable approach for flood hazard analysis and zonation. Full article

Understanding the soil and hydrologic processes in agricultural watersheds are vital for reliable assessments of water quantity and quality to support integrated river basin management. However, deriving hydrology-relevant information is complicated in flat data-scarce agricultural watersheds due to constraints in watershed delineation, flat topography, poor natural drainage, and irregular irrigation schedules by human intervention. The study aimed to improve the applicability of the Soil and Water Assessment Tool (SWAT) model to simulate daily flow and NO₃ concentrations in a flat data-scarce agricultural watershed in the Lower Seyhan Plain (LSP) in Turkey. Refined digitized stream networks, discharge data derived from fully equipped gauging stations, and satellite data (Landsat 7 ETM+, Aster GDEM, etc.) had to be integrated into the modeling process to improve the simulation quality. The model was calibrated using a 2-year (2011–2012) dataset of streamflow and NO₃ using the Sequential Uncertainty Fitting (SUFI-2) approach and validated from 2013 to 2018. Daily water yields were predicted with a reasonable simulation accuracy (E values ranging from 0.53 to 0.82 and percent bias (PBIAS) from 0 to +4.1). The results proved that integrating redefined stream networks to SWAT within a Geographic Information System (GIS) environment increases the simulation capability of flow and nitrate dynamics efficiently. Automated delineation of these networks and sub-basins at low topographic transitions limits the SWAT accuracy. Full article

Assessing available water resources and their potential for irrigation water use is vital for sustainable agricultural development and planning. This is particularly of interest in developing countries like Ethiopia, where a small portion of largely accessible land for surface irrigation applications has been utilized, despite the majority of the population relying on agricultural productivity. This study utilized the Dhidhessa River Basin (Ethiopia) as a case study and analyzed the main challenges to balance the sustainable water resources utilization and enhance agricultural productivity of the basin. The study mainly focused on estimating the available water resources and their potential for surface irrigation water use in the basin. This was achieved by utilizing Geographic Information System (GIS)-based tools, a hydrological Soil and Water Assessment Tool (SWAT) model, and a Crop Water and Irrigation Requirements Program of FAO (CROPWAT) model. While the SWAT estimated the water availability in the basin, GIS-tools such as Model Builder were used to map the irrigation potential of the basin. For irrigation water potential assessment, we selected six crops (cabbage, maize, tomato, pepper, groundnut and sugarcane) and estimated their irrigation water requirements using the CROPWAT model. We developed the SWAT model for the period from 1986 to 2012 using the available hydro-meteorological and geo-spatial data. Due to many parameters used in the model, we first performed a parameter sensitivity analysis and identified the most essential/sensitivity parameters via Sequential Uncertainty Fitting-II (SUFI-2). The identified sensitive parameters were subsequently used for model calibration (1989–2000) and validation (2001–2012) procedures achieved via SUFI-2. SWAT was able to reproduce the observed monthly streamflow values with a coefficient of determination (R²) and Nash-Sutcliffe Coefficient (NSE) of 0.85 and 0.87 for the calibration period and 0.91 and 0.89 for the validation period, respectively. The findings generally indicated a “good” performance of the model in simulating the hydrology. The annual available water of the basin is 9.26 billion cubic meters (BCM) whereas the 70% and 80% dependable flow is 7.56 and 6.97 BCM, respectively. Based on the Model Builder of ArcGIS, the SWAT estimated available water can potentially irrigate an area of 259,028 ha for slope less than 8%, 643,162 ha for slopes less than 15% and 1,023,581 ha for slopes less than 30%. Moreover, the irrigation water requirements were calculated by the CROPWAT model for the six selected crops indicated that although the need for irrigation water varies depending on the season, the potential irrigation area of the Dhidhessa River Basin is greater than its irrigated land. Therefore, it is concluded that the basin’s surface irrigation systems need to be expanded to enhance the agricultural productivity and improve the livelihood of the basin’s communities and similar basins elsewhere. Full article

A variety of flood models and commercial flood simulation software are provided in the literature, with different accuracies and precisions changing from coarse to fine, depending on model structure and detailed descriptions of basin and hydrologic properties. These models generally focus on river processes, taking overland processes as inputs of 1D or 2D hydrodynamic or hydrologic river flow models. Due to the discrete structure of overland flow and unknown-dynamic boundary conditions, such classical approaches are not cable of fast and reliable spatio–temporal estimations for overland flows, and require detailed and well-organized spatial data that cannot be immediately obtained during an emergency. A spatially-distributed Geographical Information Systems (GIS) based flood model is developed in this study to simulate overland floods, using cellular automata principles. GIS raster cells are considered hydrologic homogeneous areas throughout which hydrologic properties remain constant. Hydrodynamic flow principles, conservations of mass, momentum and energy are applied at pixel level to simulate floodwaters. The proposed GIS model is capable of directly manipulating spatio–temporal pixel level data (e.g., topography, precipitation, infiltration, surface roughness etc.) for modeling of rainfall-induced overland floods; therefore, it can provide fast, temporal and spatial flood depth estimations as well as maximum flood depths and times of concentration for all pixels throughout a study area. The model is quite simple and easy to apply via easily creatable GIS input layers, and is thus very convenient for preliminary engineering applications that need quick and fast response. Its main advantage is that it does not need a predefined flood boundary and boundary conditions. This advantage is especially valuable for coastal plains where delineation of a basin is generally too difficult. Floodwaters of Cyclone Nargis/Myanmar were simulated to test the model. Sensitivity analyses were applied to evaluate the effects of the model parameters (i.e., surface roughness and infiltration rates) on simulation results. The study shows that the proposed GIS model can be readily applied for the fast and inexpensive modeling of rainfall caused floods in areas where flood boundaries and boundary conditions cannot be clearly identified. Full article

The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language Python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous. Full article

Like most land surface models (LSMs) coupled to regional climate models (RCMs), the original Common Land Model (CoLM) predicts runoff from net water at each computational grid without explicit lateral flow (LF) schemes. This study has therefore proposed a CoLM+LF model incorporating a set of lateral surface and subsurface runoff computations controlled by topography into the existing terrestrial hydrologic processes in the CoLM to improve runoff predictions in land surface parameterizations. This study has assessed the new CoLM+LF using Earth observations at the 30-km resolution targeted for mesoscale climate applications, especially for surface and subsurface runoff predictions in the Nakdong River Watershed of Korea under study. Both the baseline CoLM and the new CoLM+LF are implemented in a standalone mode using the realistic surface boundary conditions (SBCs) and meteorological forcings constructed from remote sensing products and in situ observations, mainly by geoprocessing tools in a Geographic Information System (GIS) for the study domain. The performance of the CoLM and the CoLM+LF simulations are evaluated by the comparison of daily runoff results from both models with observations during 2009 at the Jindong stream gauge station in the study watershed. The proposed CoLM+LF, which can simulate the effect of runoff travel time over a watershed by an explicit lateral flow scheme, more effectively captures seasonal variations in daily streamflow than the baseline CoLM. Full article