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Regionalization methods dependent on hydrological models comprise techniques for transferring calibrated parameters in instrumented watersheds (donor basins) to non-instrumented watersheds (target basins). There is a lack of flow regionalization studies in regions with humid subtropical and hot temperate climates, and one of the main novelties of this research is to assess the regionalization of low flows in Paraná in the south of Brazil. In addition to filling this gap, this research presents innovative artificial-intelligence techniques for transferring parameters from hydrological models. This study aims to evaluate regionalization methods for transferring GR4J parameters and predicting river flow in catchments from the south of Brazil. We created a dataset for the state of Paraná with daily hydrological time series (precipitation, evapotranspiration, and river flow) and watershed physiographic and climatological indices for 126 catchments. Rigorous quality-controlling techniques were applied to recover data from 1979 to 2020. The regionalization methods compared in this study are based on simple spatial proximity, physiographic–climatic similarity, and regression by random forest techniques. Direct regression of Q95 was calculated using random forest techniques and compared with indirect methods, i.e. using regionalization of GR4J parameters. A set of 100 basins was used to train the regionalization models, and another 26 catchments (pseudo-non-instrumented) were used to evaluate and compare the performance of regionalizations. The GR4J model showed acceptable performances for the sample of 126 catchments, with 65 % of watersheds presenting a log-transformed Nash–Sutcliffe coefficient greater than 0.70 during the validation period. According to the evaluation carried out for the sample of 26 basins, regionalization based on physiographic–climatic similarity was shown to be the most robust method for the prediction of daily and Q95 reference flow in basins from the state of Paraná. When increasing the number of donor basins, the method based on spatial proximity has comparable performance to the method based on physiographic–climatic similarity. Based on the physiographic–climatic characteristics of the basins, it was possible to classify six distinct groups of watersheds in Paraná. Each group shows similarities in forest cover, urban area, number of days with more than 150 mm of precipitation, and average duration of consecutive dry days. Although the physiographic–climatic similarity method obtained the best performance, the use of machine learning algorithms to regionalize the model parameters had good performance using climatic and physiographic indices as inputs. This research represents a proof of concept that basins without flow monitoring can have a good approximation of streamflow if physiographic–climatic information is provided. [ABSTRACT FROM AUTHOR]

We assess the ability of two modelling chains to reproduce, over the last century (1902–2009) and from large-scale atmospheric information only, the temporal variations in river discharges, low-flow sequences and flood events observed at different locations of the upper Rhône River catchment, an alpine river straddling France and Switzerland (10 900 km 2). The two modelling chains are made up of a downscaling model, either statistical (Sequential Constructive Atmospheric Analogues for Multivariate weather Predictions – SCAMP) or dynamical (Modèle Atmosphérique Régional – MAR), and the Glacier and SnowMelt SOil CONTribution (GSM-SOCONT) model. Both downscaling models, forced by atmospheric information from the global atmospheric reanalysis ERA-20C, provide time series of daily scenarios of precipitation and temperature used as inputs to the hydrological model. With hydrological regimes ranging from highly glaciated ones in its upper part to mixed ones dominated by snow and rain downstream, the upper Rhône River catchment is ideal for evaluating the different downscaling models in contrasting and demanding hydro-meteorological configurations where the interplay between weather variables in both space and time is determinant. Whatever the river sub-basin considered, the simulated discharges are in good agreement with the reference ones, provided that the weather scenarios are bias-corrected. The observed multi-scale variations in discharges (daily, seasonal, and interannual) are reproduced well. The low-frequency hydrological situations, such as annual monthly discharge minima (used as low-flow proxy indicators) and annual daily discharge maxima (used as flood proxy indicators), are reproduced reasonably well. The observed increase in flood activity over the last century is also reproduced rather well. The observed low-flow activity is conversely overestimated, and its variations from one sub-period to another are only partially reproduced. Bias correction is crucial for both precipitation and temperature and for both downscaling models. For the dynamical one, a bias correction is also essential for getting realistic daily temperature lapse rates. Uncorrected scenarios lead to irrelevant hydrological simulations, especially for the sub-basins at high elevation, due mainly to irrelevant snowpack dynamic simulations. The simulations also highlight the difficulty in simulating precipitation dependency on elevation over mountainous areas. [ABSTRACT FROM AUTHOR]

Cultivation of the 'Apple of the Sahel' (also known as Indian Jujube) is central to the food security, nutrition, and income of rural communities in developing countries like Niger. However, rainfall variability significantly impacts the development of this plant. This study aims to determine the effects of seasonal water regimes on the growth and productivity of the Apple of the Sahel. The trials were conducted in 2020 and 2021 during the rainy and dry seasons at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) experimental site in Sadore, Niamey, Niger. The experiment was arranged in a factorial design with three irrigation doses (D) and three irrigation systems (G) as main and subplot factors, respectively. The sub-subplot factors were irrigation frequencies (F) and growth boosters (B), each with two levels. In the dry season, irrigation dose application significantly (p = 0.001) increased soil volumetric water content (vwc). A similar increase in soil vwc was achieved under small-scale drip irrigation with an application of the same dose of organic material (p = 0.001). The diameter of the Apple of the Sahel trees significantly increased (p = 0.03) under the small-scale drip irrigation systems with 6.72 mm recorded under the two-drip irrigation system (G2) as compared with the manual system (G0). In the dry season, the total fruit harvest of Apple of the Sahel recorded had increased (p = 0.04) under the irrigated system, varying from 112 to 246% depending on the number of drippers, and compared to the manual system. These results highlight that small-scale drip irrigation should be used in combination with appropriate water and fertilizer management to improve water availability and tree yield in agroforestry systems in arid regions such as Niger. [ABSTRACT FROM AUTHOR]

This research paper deals with the study of the morphological characteristics of the oued Loussif sub-catchment, located in the Wilaya of Sétif, Algeria. This study is part of a more general study on the hydrogeological study of the Kherzet Youcef deposit. In all fields interested in the study of spatial phenomena, a need for automation is emerging, especially for 'network' type geographic structures, given their systemic organization of space which is not explained in geographic data bases. In order to meet this need for automation, the use of Geographic Information Systems has proven to be profitable. Morphological features such as flow accumulation, flow direction and stream network were extracted based on the digital elevation model (DEM), and the results were interpreted and analyzed. The Geographic Information System (GIS) based approach with the use of DEM facilitates the understanding of different morphological features represented in the thematic raster data maps, and the correlation between flow accumulations, flow direction, stream order and stream network was well explored. The study represents the morphological features extracted from the DEM. The software used to perform the overall analysis was ESRI ArcGIS version 10.8 with ESRI Spatial Analysis Analyst extension and ArcHydro. The morphological features are effective in understanding the spatial distribution of the stream network and identifying potential groundwater locations. [ABSTRACT FROM AUTHOR]

Stochastic modeling to forecast hydrological variables under changing climatic conditions is essential for water resource management and adaptation planning. This study explores the applicability of stochastic models, specifically SARIMA and SARIMAX, to forecast monthly average river discharge in a sub-basin of the Paranaíba River near Patos de Minas, MG, Brazil. The Paranaíba River is a vital water source for the Alto Paranaíba region, serving industrial supply, drinking water effluent dilution for urban communities, agriculture, fishing, and tourism. The study evaluates the performance of SARIMA and SARIMAX models in long-term discharge modeling and forecasting, demonstrating the SARIMAX model's superior performance in various metrics, including the Nash–Sutcliffe coefficient (NSE), the root mean square error (RMSE), and the mean absolute percentage error (MAPE). The inclusion of precipitation as a regressor variable considerably improves the forecasting accuracy, and can be attributed to the multivariate structure of the SARIMAX model. While stochastic models like SARIMAX offer valuable decision-making tools for water resource management, the study underscores the significance of employing long-term time series encompassing flood and drought periods and including model uncertainty analysis to enhance the robustness of forecasts. In this study, the SARIMAX model provides a better fit for extreme values, overestimating peaks by around 11.6% and troughs by about 5.0%, compared with the SARIMA model, which tends to underestimate peaks by an average of 6.5% and overestimate troughs by approximately 76.0%. The findings contribute to the literature on water management strategies and mitigating risks associated with extreme hydrological events. [ABSTRACT FROM AUTHOR]

The Niger River drains a large part of the West African Craton, where rocks ranging in age from Paleoarchean to recent offer an unexcelled opportunity to map the diverse time structures of sediment sources and provide essential information for provenance diagnoses. In this study, U‐Pb zircon dating is complemented with bulk‐sand geochemical (Zr, Hf, REE) and Nd‐Hf isotope data to pin‐point parent rocks of zircon grains and draw inferences on sediment generation across sub‐Saharan western Africa. In Upper Niger sand, zircon ages pass from exclusively Archean in Guinea headwaters to dominantly Paleoproterozoic in the Inner Delta in Mali, testifying to the progressive dilution by tributary sediment derived from the Birimian domain. Zircon ages abruptly change to dominantly Neoproterozoic downstream of the Inner Delta, becoming indistinguishable from those in Saharan eolian dunes across the Sahel. Most of the sediment generated in the headwaters is thus dumped in the marshlands and bedload is reconstituted downstream by recycling eolian sand. Zircon grains in the Lower Niger yielded virtually the same U‐Pb ages as in Benue sediment, indicating an overwhelming supply from the Benue tributary. In the Niger Delta, however, Archean zircons reappear, and both εNd and εHf values become notably more negative, indicating extensive reworking of sand deposited along the coastal plain at earlier times of wetter climate, when artificial barriers to the sediment flux did not exist in the upper to middle Niger River catchment. Plain Language Summary: Across sub‐Saharan western Africa, the Niger River drains rocks with ages spanning more than 3 billion years. In such a vast region, diverse techniques can be combined to identify processes of erosion and transport, starting from the analysis of sediments and the zircon grains they contain. The very old ages of zircons derived from Guinean headwaters (all older than 2650 million years) are gradually diluted by younger zircons generated in SW Mali (from 1900 to 2200 million years), whereas a sharp change to more recent zircon ages (from 500 to 700 million years) is documented downstream of the Inner Delta. Most sediment generated in the headwaters is thus dumped in these marshlands and subsequently replaced with sand eroded from eolian dunes along the southern edge of the Sahara Desert. Rigid segmentation of fluvial sediment transport has become the rule after the extensive construction of dams worldwide, but can also be caused by natural processes. Marshlands formed at the subequatorial edge of tropical deserts can represent very efficient natural barriers to sediment transport, preventing a large part of the detritus generated in the highlands from reaching the ocean, with consequent impact on both sediment budgets and sediment composition. Key Points: The Niger River offers an unexcelled opportunity to use detrital geochronology to map the diverse time structures of sediment sourcesSand generated in the headwaters is dumped in the Inner Delta as indicated by a significant change in the U‐Pb signature and εNd‐εHf valuesReworking of sand along the coastal plain testifies the absence of artificial or major natural barriers to the sediment flux in earlier times [ABSTRACT FROM AUTHOR]

Analytical multiplicative random cascades (MRCs) are widely used for the temporal disaggregation of coarse-resolution precipitation time series. This class of models applies scaling models to represent the dependence of the cascade generator on the temporal scale and the precipitation intensity. Although determinant, the dependence on the external precipitation pattern is usually disregarded in the analytical scaling models. Our work presents a unified MRC modelling framework that allows the cascade generator to depend in a continuous way on the temporal scale, precipitation intensity and a so-called precipitation asymmetry index. Different MRC configurations are compared for 81 locations in Switzerland with contrasted climates. The added value of the dependence of the MRC on the temporal scale appears to be unclear, unlike what was suggested in previous works. Introducing the precipitation asymmetry dependence into the model leads to a drastic improvement in model performance for all statistics related to precipitation temporal persistence (wet–dry transition probabilities, lag-n autocorrelation coefficients, lengths of dry–wet spells). Accounting for precipitation asymmetry seems to solve this important limitation of previous MRCs. The model configuration that only accounts for the dependence on precipitation intensity and asymmetry is highly parsimonious, with only five parameters, and provides adequate performances for all locations, seasons and temporal resolutions. The spatial coherency of the parameter estimates indicates a real potential for regionalisation and for further application to any location in Switzerland. [ABSTRACT FROM AUTHOR]

This paper presents a comparison between the black box Nonlinear Auto-Regressive with eXogenous inputs-Neural Network (NARX-NN) and the conceptual Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) Rainfall-Runoff models. The two models were applied on a small urban watershed to assess its response to fourteen hourly real storm events. The differences between the steps engaged in each model to reach the hydrograph were presented in detail. The estimation of the best parameters is carried out using a weighted average function during the calibration phase. A statistical evaluation was conducted to assess the model's performance thereafter; a critical comparison was made to illustrate the differences and discuss the steps involved. The results indicate that both models successfully reflect the urban basin runoff. However, the NARX-NN outperforms in the testing phase owing to their strength generalization feature. The NARX-NN model has more strength to produce the shape bending of the hydrograph. Consequently, this model is better to highlight the curvatures resulting from the local peaks of rainfall. [ABSTRACT FROM AUTHOR]

This article is based on the freely available data of the web-based hydropower map HYPOSO, which the authors compiled. Only the Ugandan river network and associated hydropower potential are highlighted here, using freely available geospatial datasets. The main objective was to assess Ugandan river and stream hydropower potential, compare it with previous assessments, and identify potential sites for small hydropower plant installation. GIS techniques were extensively used to analyse hydrological and other related geospatial data. The stream-reach power potential was determined based on channel slope, the length between tributaries, and the average flow derived from a specific runoff distribution map. Stream profiles extracted from the river network's digital elevation model were validated against previous assessments. Uganda's hydropower potential was determined in various patterns, and its values were compared with prior estimates. Around 500 potential high-energy intensity stream reaches and new potential areas for small hydropower plant development were identified in this country, considering a range of characteristics. Statistical datasets were analysed, and their straightforward summaries were presented. These summary characteristics of hydropower potential are necessary for decision-makers to foster hydropower development in this country. [ABSTRACT FROM AUTHOR]

Particle aggregation modifies sediment dynamics, which is a determining factor for morphodynamic and ecological processes in deltaic plains. Here, we investigated the link between intra-annual hydrodynamics variability and flocculation in the Grijalva-Usumacinta system. Monthly (2016–2017) and seasonal (2021–2022) river data was processed using analytical methods and the simplified sonar equation. Flocs were reformed and characterized in the laboratory, validating the in situ settling velocities (0.5–3.8 mm/s) and the existence of large low-density macro-flocs (>300 μm). We verified that flocculation prevailed, exhibiting seasonal patterns; (1) the highest aggregation rates matched the increase in total suspended solids at rising-flow (>100 mg/L), (2) periods of high-flow showed stable aggregation rates, and (3) an influence of marine conditions occurred at low-flow. Particulate phosphorous and organic fraction showed seasonal patterns linked to flocculation. Due to damming, the shear rates varied slightly (7–11 L/s) in the Grijalva, leading to high flocculation intensities affecting the diffusivity ratio. In the Usumacinta, aggregation was limited by shear rates that normally exceed 15 1/s. We found seasonal Rouse parameters representative of sediment dynamics. [ABSTRACT FROM AUTHOR]

Droughts are natural disasters with a significant impact on the economy and social life. Prolonged droughts can cause even more damage than floods. The novelty of this work lies in the definition of a synthetic drought hydrograph (SDH) which can be derived at each gaging station of a river network. Based on drought hydrographs (DHs) recorded for a selected gaging station, the SDH is statistically characterized and provides valuable information to water managers regarding available water resources during the drought period. The following parameters of the registered drought hydrograph (DH) are proposed: minimum drought discharge Q D m i n , drought duration D D   and deficit volume V D . All these parameters depend on the drought threshold Q T , which is chosen based on either pure hydrological considerations or on socio-economic consequences. For the same statistical parameters of the drought, different shapes of the synthetic drought hydrograph (SDH) can be considered. In addition, the SDH varies according to the probabilities of exceedance of the minimum drought discharge and deficit volume. [ABSTRACT FROM AUTHOR]

As a result of urbanization, combined with the anthropogenic effects of climate change, natural events such as floods are showing increasingly adverse impacts on human existence. This study proposes a new model, based on shallow water equations, that is able to predict these floods and minimize their impacts. The first-order finite volume method (FVM), the Harten Lax and van Leer (HLL) scheme, and the monotone upwind scheme for conservation laws (MUSCL) are applied in the model. In addition, a virtual boundary cell approach is adopted to achieve a monotonic solution for both interior and boundary cells and flux computations at the boundary cells. The model integrates the infiltration parameters recorded in the area, as well as the Manning coefficient specific to each land-cover type of the catchment region. The results provided were mapped to highlight the potential flood zones and the distribution of water heights throughout the catchment region at any given time, as well as that at the outlet. It has been observed that when standard infiltration and the Manning parameters were selected, the floodable surface increased, as expected, with the increasing rainfall intensity and duration of the simulation. With sufficient infiltration, only a portion of the water tends to stagnate and flow off on the surface toward the outlet. A sensitivity analysis of certain parameters, such as rainfall data and the final infiltration coefficient in the lower watershed of the littoral region, was conducted; the results show that the model simulates well the general character of water flow in the watershed. Finally, the model's validation using field-collected parameters during the flood of 25 July 2017 and 18 to 22 July 2016 in the Grand Ouaga basin in Burkina reveals Nash–Sutcliffe values of 0.7 and 0.73, respectively. [ABSTRACT FROM AUTHOR]

A user‐friendly high‐resolution intermediate complexity dynamic and spatially distributed flow model is crucial in urban flood modeling. Planners and consultants need to improve the accuracy of floods and estimation of risks. A new flow model will serve as a rapid tool to improve identification of these. This article provides a detailed explanation of a model based on a multiple flow algorithm. Model testing was performed on selected urban and rural areas. Additionally, a sensitivity analysis is conducted to analyze functionality. The model includes basic hydrological processes and is therefore less complex than fully physical models. The data needed to set up and run the new model include spatially and temporally distributed basic geometric and hydrologic variables (i.e., digital elevation model, precipitation, infiltration, and surface roughness). The model is implemented using open‐source coding and can easily be applied to any selected area. Outputs are water volumes, depths, and velocities at different modeling times. Using GIS, results can be visualized and utilized for further analyses. The test, applied in urban as well as rural areas, demonstrates its user‐friendliness, and that the estimated distributed water depths and water velocity at any time step can be saved and visualized. [ABSTRACT FROM AUTHOR]

Backwater effects in surface water streams and on adjacent lowland areas caused by mostly complex drainage and flow control structures are not directly computed with hydrological approaches yet. A solution to this weakness in hydrological modelling is presented in this article. The developed method enables transfer of discharges into water levels and calculation of backwater volume routing along streams and adjacent lowland areas by balancing water level slopes. The implemented and evaluated method extends the application of hydrological models for rainfall–runoff simulations of backwater-affected catchments with the advantages of (1) modelling complex flow control systems in tidal backwater-affected lowlands, (2) less effort to parameterise river streams, (3) directly defined input factors of driving forces (climate change and urbanisation) and (4) runtime reduction of 1 to 2 orders of magnitude in comparison to coupled hydrodynamic models. The developed method is implemented in the open-source rainfall–runoff model Kalypso-NA (4.0). Evaluation results show the applicability of the model for simulating rainfall–runoff regimes and backwater effects in an exemplary lowland catchment (Hamburg, Germany) with a complex flow control system and where the drainage is influenced by a tidal range of about 4 m. The proposed method is applicable to answer a wide scope of hydrological and water management questions, e.g. water balances, flood forecasts and effectiveness of flood mitigation measures. It is re-usable to other hydrological numerical models, which apply conceptual hydrological flood-routing approaches (e.g. Muskingum–Cunge or Kalinin–Miljukov). [ABSTRACT FROM AUTHOR]

In the present study, the hydrochemical dynamic and the water quality of La Purísima reservoir, Central Mexico, have been determined. The reservoir presents total dissolved solids (TDSs) between 146 and 328 mg L−1 and water quality neutral to slightly alkaline (pH 7.0 to 8.7) during the dry season, whereas it becomes clearly alkaline (pH 8.1–9.9) in the rainy-warm season. Through its main tributaries, La Purísima reservoir has been receiving water affected by anthropic activities, such as mining, urbanization, and agriculture. La Purísima reservoir indicates water quality suitable for irrigation and aquatic lives, but unsuitable for drinking purposes. A geochemical evolution from the riverine to the lacustrine zone is evidenced by the complexation of several free ions: the higher saturation indexes; the lower toxic metal concentrations; and the lower trophic status, which ameliorate the water quality in the lacustrine zone. Trace elements co-precipitate and are adsorbed onto bottom sediments. During summer, high evaporation rates and atmospheric precipitation are found to decline the water quality. Cluster analyses reflect the geo-setting and different pollution levels: urban impact from the north coast, and agricultural activities from the east coast. The sensitivity of the lake to geochemical behavior can be used to understand the complex dissolved geochemical dynamics in a lake and the potential effects from long-term anthropic impact variability. The information about water quality of La Purísima reservoir may be useful to preserve the ecosystem and its biodiversity. [ABSTRACT FROM AUTHOR]

Purpose: Suspended sediment transport, which represents the majority of the sediment load, has been studied across very different scales and in a wide variety of regions and climates. Despite numerous studies, data for European watersheds are generally limited and correspond to large rivers systems. Especially, in Belgium, little data is available outside the Belgian loess belt. Moreover, the high heterogeneity of soil erosion and sediment transport makes it difficult to measure or model at watershed scale. The purpose of this research is to estimate the median sediment yields in different geographical regions and to detect their explanatory variables. Materials and methods: Gathering data from 1994 to 2016, more than 2000 measurements of suspended sediment concentration at 72 river stations mainly located in South-Belgium were sampled according to a flood-event-based manual methodology. This allowed fast acquisition of data in watersheds ranging from 7 to 3600 km2 in different geographical regions. Median area-specific sediment yields (SSY) were calculated at watershed scale while looking for regional differences. Results and discussion: Median area-specific sediment yields computed for the period 1996–2018 show regional differences: 19.2 t km−2 year−1 on sandy substrate (Lorraine), 24.9 t km−2 year−1 on schisto-sandstone substratum (Ardenne), and up to 119 t km−2 year−1 in the loamy Brabant plateau, with a link to the agricultural land cover and, to a lesser extent, to the watershed slope. The high temporal and spatial variability of rainfall has great effects on the SSY, necessitating the gathering of more than 20 years of data to smooth the high variability of SSY. A multiple correlation of land cover variables and the average slope of the watershed with SSY managed to explain 48% of the variance within the SSY observations. Conclusions: The agricultural land cover has an important effect on median SSY values. While the regionalization of Belgium is largely based on lithology, soils, and altitude, the land use resulting from these physical and climatic characteristics explains the differences in SSY. Field values of clogged dams and waterways confirm the matching of the SSY computation from discrete samples, despite the high temporal variability of sediment transport. [ABSTRACT FROM AUTHOR]

Numerical simulation of sediment transport in alluvial rivers often becomes untenable due to the absence of requisite data. Over the years, artificial neural network (ANN) models have been successfully employed for tackling such scenarios. However, the effect of input and target datasets on the simulation of sediment transport using ANN has not yet been adequately addressed in the literature so far. To study the effect of input-target dataset on the performance of ANN models, the present study employs seven input-target datasets for the development of several ANN models and assessment of their performance. The limited study carried out reveals that there are multiple ANN models – having different combinations of training algorithms, transfer functions and input/target datasets – that can reliably be employed to estimate bed elevation changes in alluvial rivers. [ABSTRACT FROM AUTHOR]

The surface water is a significant feature in the hydrological system and is a vital compound for life growth. Assessment of trace elements in the water bodies is essential since it poses huge threats to aquatic organisms and humans if present in high concentrations. This study was carried out to assess the seasonal changes in the dissolved trace elements concentration in Bhavani river, which is one of the major rivers of Tamil Nadu, southern India and also to assess the human health risk due to its consumption. A total of 46 surface water samples were collected along the river during pre-monsoon and post-monsoon of 2018 and were analyzed for various trace elements such as Zn, Cu, Fe, Ni, and Pb. The variation in trace element concentration is observed spatially, where higher concentration is found in samples from agricultural and urban areas than the samples from the undisturbed natural-mountain terrains. The results highlighted that the concentrations of trace elements differ temporally where the concentration is greater during the monsoon due to increased discharge of sewage and agricultural run off to the river. Multivariate statistical analysis indicates stronger relationship between trace elements and other physio-chemical parameters hinting that natural and anthropogenic sources alters the riverine chemistry. Thus, the rainfall–runoff characteristics along with lithology, topography, and landuse of the basin plays a dominant role in the seasonal variation of dissolved trace elements. The water quality index value shows "good/excellent" during pre-monsoon and "marginal/fair" during monsoon season and the Heavy Metal Pollution Index values were also low during both the seasons. The river water samples which defy these indices were found to be either from urban or agricultural lands. The oral and dermal ingestion health risk to adults was assessed, which indicates that the risks posed to humans by consumption of water were minimal. The trace metal concentration of the river was then compared with the other rivers of world and India, where it shows that Zn, Cu, and Ni concentration was higher in Bhavani than in most of the rivers. Thus, the study highlighted that the urban settlements and agricultural lands have a considerable influence on river quality thereby triggering the increase in trace element concentrations. Therefore, the study necessitates on the continuous monitoring of river along with adoption of stringent discharge protocols. [ABSTRACT FROM AUTHOR]

Population growth, the intensification of human activities, the impact of natural hazards related to water and climate change, directly and indirectly, affect the availability of water resources. This requires rational and sustainable management of water resources. Thus, it is essential to conduct a comprehensive assessment of available water resources based on current and future needs. This assessment involves collecting and processing hydrological data to provide reliable information on water resources' status and evolution. However, the non-availability and lack of hydrological data constrain the process of this assessment. Therefore, we propose in this work to adopt a clustering analysis based-regionalization approach combining multivariate data analysis (PCA) and clustering algorithms (HAC and KM) to delineate watersheds' homogeneous clusters. Clustering analysis produces groups of watersheds based on their similarity which will allow the transfer of data from gauged sites to ungauged sites. At the end of the present study, 6 clusters of watersheds were identified. These identified clusters have their characteristics in terms of surface, perimeter, length of the equivalent rectangle, time of concentration, and land use. Based on result validation indicators (cross-validation approach), the studied catchment areas have been assigned to the clusters that represent them the best. [ABSTRACT FROM AUTHOR]