<p>Regional analysis is often used for flood quantile estimation in ungauged catchments. The regionalization procedure has two phases: the formation of homogeneous regions and flood quantile estimation. The presented research results consider the first phase of the regional analysis for 41 catchments in Serbia. The catchment similarity attributes are catchment area and catchment mean elevation. The number of formed regions and the number of stations within the regions are determined by maximising the mean silhouette width of the region. Regions were first obtained by cluster analysis and then adjusted to comprise catchments with a positive silhouette width. For the three formed regions, homogeneity was checked by the Gini index - GI.</p>

Flood quantile estimation in ungauged basins is often performed using regional analysis. A regionalization procedure consists of two phases: the definition of homogeneous regions among gauged basins, i.e., clusters of stations, and information transfer to the ungauged sites. Due to its simplicity and widespread use, a combination of hierarchical clustering by Ward’s algorithm and the index-flood method is applied in this research. While hierarchical clustering is very efficient, its shortcomings are the lack of flexibility in the definition of clusters/regions and the inability to transfer objects/stations from one cluster center to another. To overcome this, using silhouette width for induced clustering of stations in flood studies is proposed in this paper. A regionalization procedure is conducted on 53 gauging stations under a continental climate in the West Balkans. In the induced clustering, a negative silhouette width is used as an indicator for the relocation of station(s) to another cluster. The estimates of mean annual flood and 100-year flood quantiles assessed by the original and induced clustering are compared. A jackknife procedure is applied for mean annual flood estimation and 100-year flood quantiles. Both the Hosking–Wallis and Anderson–Darling bootstrap tests provide better results regarding the homogeneity of the defined regions for the induced clustering compared to the original one. The goodness-of-fit measures indicate improved clustering results by the proposed intervention, reflecting flood quantile estimation at the stations with significant overestimation by the original clustering.

In this paper will be given actual state of the main groundwater supply source of  Sarajevo, from which  provides about 90 % of the total water needs for  the City. Given that, from the period of the source formation (50 - ies of the last century) until today,  there has been an spreading of the city in the direction of the source zone, as well as changes in land use in the narrow and wide source zones, and it can be said that the source  is potentially threatened. In this regard, special emphasis will be given to recent research results of qualitative and quantitative characteristics of the groundwater. Also, will be shown the current and potential, point source and nonpoint source of water pollutions in the entire catchment area of Sarajevsko polje. Based on the current situation, the paper will point out the problems that undoubtedly threaten to preserve qualitative but also quantitative characteristics of the groundwater source, and will also be given recommendations to mitigate and prevent negative consequences.

. A truly important challenge in flood frequency assessment (FFA) in Bosnia and Herzegovina is lack of continuous gaged flow data, because the reliability of FFA results depends on the length and quality of flow records. At the case study location - hydrologic station (HS) Maglaj on the river Bosna the reference period for flow record is 1961-1990. The research goal in this paper is to exploit the water stage gauge data and information (1933-1960) for the extension of flow dataset from 30 to 58 years. We apply the original rating curve from the period 1960-1970 to the water table record to generate daily flow datasets. Anticipating three rating curve change developments, we generate six longer flow datasets -with and without instantaneous maxima, for the period 1933-1990 at HS Maglaj - Poljice. Together with two reference period flow datasets we arrive at the total of eight datasets/scenarios and subject these datasets to FFA on the annual maxima series and partial duration series. For the former, we use conventional statistical analysis (CSA) and for the latter, the peak over threshold (POT) method. The FFA results show no significant difference in the values of the selected quantiles for scenarios involving time extrapolation. The quantiles for the reference period 1961-1990 are generally higher, among both CSA and POT results. We find the absence of instantaneous maxima a major influence on FFA.

In the flood frequency assessment, engineers often face the problem of mixed peak data in the data record: some peaks are instantaneous daily flows (IDF), while the others are mean daily flows (MDF). If the problem is recognized, correction factor to the MDFs in the dataset is usually applied. In our research, we use flood flow datasets from 8 hydrologic stations with catchment area up to 1000 km 2 in the Sava River basin. Four hydrologic stations are located in Bosnia and Herzegovina (BiH) and four in Serbia. We apply Sangal’s procedure to establish a correction factor for a single station analysis to produce the IDFs from MDFs. We use three annual maxima datasets at each hydrologic station, comprising: 1) IDF only, 2) MDF only, and 3) mixed IDF and MDF (officially available). We subject each dataset to flood frequency assessment using USACE HEC-SSP Bulletin 17b and 17c analysis. The results show the diversity of flood quantile estimates at each station, with the most significant differences obtained according to expected probability curve in Bulletin 17b analysis. The highest uncertainty shown as mean square error of skewness coefficient is observed at stations with large data gaps, and large number of detected low outliers. The case study revealed a potential for significant underestimation or overestimation of flood