A framework of integrated hydrological and hydrodynamic models using synthetic rainfall for flash flood hazard mapping of ungauged catchments in tropical zones

Flash flood hazard maps provide a scientific support to mitigate flash flood risk. The present study develops a practical framework with the help of integrated hydrological and hydrodynamic modelling in order to estimate the potential flash floods. We selected a small pilot catchment which has already suffered from flash floods in the past. This catchment is located in the Nan River basin, northern Thailand. Reliable meteorological and hydrometric data are missing in the catchment. Consequently, the entire upper basin of the main river was modelled with the help of the hydrological modelling system PANTA RHEI. In this basin, three monitoring stations are located along the main river. PANTA RHEI was calibrated and validated with the extreme flood events in June 2011 and July 2008, respectively. The results show a good agreement with the observed discharge data. In order to create potential flash flood scenarios, synthetic rainfall series were derived from temporal rainfall patterns based on the radar-rainfall observation and different rainfall depths from regional rainfall frequency analysis. The temporal rainfall patterns were characterized by catchment-averaged rainfall series selected from 13 rainstorms in 2008 and 2011 within the region. For regional rainfall frequency analysis, the well-known L-moments approach and related criteria were used to examine extremely climatic homogeneity of the region. According to the L-moments approach, Generalized Pareto distribution was recognized as the regional frequency distribution. The synthetic rainfall series were fed into the PANTA RHEI model. The simulated results from PANTA RHEI were provided to a 2-D hydrodynamic model (MEADFLOW), and various simulations were performed. Results from the integrated modelling framework are used in the ongoing study to regionalize and map the spatial distribution of flash flood hazards with four levels of flood severities. As an overall outcome, the presented framework can be applied in areas with inadequate runoff records

Classification of Hydrological Relevant Parameters by Soil Hydraulic Behaviour

Soil water simulations on hydrological meso- or macroscale require parameters that describe the physical characteristics of the soil. At these scales, information regarding soil properties is mostly only available on very coarse spatial resolutions with texture based soil characterisations, where it is dicult to select representative soil hydraulic parameters. We improved the parameter estimation by introducing a new soil classification system, which is based on soil hydraulic behaviour in order to realistically reproduce the soil water interaction within meso-scaled hydrological models. The time series of soil water flux were simulated based on one million dierent parameterisations, which were then utilised for similarity analyses while applying the k-means clustering. The resulting classes show a dierent pattern when compared to the United States Department of Agriculture (USDA) texture based classes. Representative time series of water flux representative of the new classes were compared to time series of the USDA texture classification. The new classes show remarkably lower uncertainties. The bandwidth of the time series within a class is orders of magnitudes higher for the USDA system when compared to the new system. The evaluation of similarity of the simulated water flux time series within one and the same class were also clearly better for the new system

Multivariate statistical assessment of a polluted river under nitrification inhibition in the tropics.

A large complex water quality data set of a polluted river, the Tay Ninh River, was evaluated to identify its water quality problems, to assess spatial variation, to determine the main pollution sources, and to detect relationships between parameters. This river is highly polluted with organic substances, nutrients, and total iron. An important problem of the river is the inhibition of the nitrification. For the evaluation, different statistical techniques including cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) were applied. CA clustered 10 water quality stations into three groups corresponding to extreme, high, and moderate pollution. DA used only seven parameters to differentiate the defined clusters. The PCA resulted in four principal components. The first PC is related to conductivity, NH4-N, PO4-P, and TP and determines nutrient pollution. The second PC represents the organic pollution. The iron pollution is illustrated in the third PC having strong positive loadings for TSS and total Fe. The fourth PC explains the dependence of DO on the nitrate production. The nitrification inhibition was further investigated by PCA. The results showed a clear negative correlation between DO and NH4-N and a positive correlation between DO and NO3-N. The influence of pH on the NH4-N oxidation could not be detected by PCA because of the very low nitrification rate due to the constantly low pH of the river and because of the effect of wastewater discharge with very high NH4-N concentrations. The results are deepening the understanding of the governing water quality processes and hence to manage the river basins sustainably

Discovering Water Quality Changes and Patterns of the Endangered Thi Vai Estuary in Southern Vietnam through Trend and Multivariate Analysis

Temporal and spatial water quality data are essential to evaluate human health risks. Understanding the interlinking variations between water quality and socio-economic development is the key for integrated pollution management. In this study, we applied several multivariate approaches, including trend analysis, cluster analysis, and principal component analysis, to a 15-year dataset of water quality monitoring (1999 to 2013) in the Thi Vai estuary, Southern Vietnam. We discovered a rapid improvement for most of the considered water quality parameters (e.g., DO, NH4, and BOD) by step trend analysis, after the pollution abatement in 2008. Nevertheless, the nitrate concentration increased significantly at the upper and middle parts and decreased at the lower part of the estuary. Principal component (PC) analysis indicates that nowadays the water quality of the Thi Vai is influenced by point and diffuse pollution. The first PC represents soil erosion and stormwater loads in the catchment (TSS, PO4, and Fetotal); the second PC (DO, NO2, and NO3) determines the influence of DO on nitrification and denitrification; and the third PC (pH and NH4) determines point source pollution and dilution by seawater. Therefore, this study demonstrated the need for stricter pollution abatement strategies to restore and to manage the water quality of the Thi Vai Estuary

Hochwasser und Sturzfluten an Flüssen in Deutschland

Flusshochwasser werden in lokale und plotzliche Sturzfluten und in Hochwasser an groseren Flussen unterschieden. Fur verschiedene Hochwasserindikatoren und Flusseinzugsgebiete ergeben sich erhebliche Unterschiede, wobei sowohl uberwiegend aus Regen als auch uberwiegend aus Schmelzwasser gespeiste Hochwasserereignisse betrachtet werden. Besondere Aufmerksamkeit finden Hochwasserereignisse an Rhein, Elbe, Weser und Ems sowie die Entwicklung von Sturzfluten infolge von Extremniederschlagen kurzer Dauer, wobei die Beobachtungen und Trends zu Modellierungsergebnissen in Beziehung gesetzt werden. Auch die Notwendigkeit von Anpassungsmasnahmen aufgrund uberwiegend positiver Trends wird diskutiert