Abstract. Hydrological observatories bear a lot of resemblance to the more traditional research catchment concept, but tend to differ in providing more long-term facilities that transcend the lifetime of individual projects, are more strongly geared towards performing interdisciplinary research, and are often designed as networks to assist in performing collaborative science. This paper illustrates how the experimental and monitoring set-up of an observatory, the 66 ha Hydrological Open Air Laboratory (HOAL) in Petzenkirchen, Lower Austria, has been established in a way that allows meaningful hypothesis testing. The overarching science questions guided site selection, identification of dissertation topics and the base monitoring. The specific hypotheses guided the dedicated monitoring and sampling, individual experiments, and repeated experiments with controlled boundary conditions. The purpose of the HOAL is to advance the understanding of water-related flow and transport processes involving sediments, nutrients and microbes in small catchments. The HOAL catchment is ideally suited for this purpose, because it features a range of different runoff generation processes (surface runoff, springs, tile drains, wetlands), the nutrient inputs are known, and it is convenient from a logistic point of view as all instruments can be connected to the power grid and a high-speed glassfibre local area network (LAN). The multitude of runoff generation mechanisms in the catchment provides a genuine laboratory where hypotheses of flow and transport can be tested, either by controlled experiments or by contrasting sub-regions of different characteristics. This diversity also ensures that the HOAL is representative of a range of catchments around the world, and the specific process findings from the HOAL are applicable to a variety of agricultural catchment settings.

Mapping saturation areas during rainfall events is important for understanding the dynamics of overland flow. In this study, we evaluate the potential of high temporal resolution time‐lapse photography for mapping the dynamics of saturation areas (i.e., areas where water is visually ponding on the surface) on the hillslope scale during natural rainfall. We take 1 image per minute over a 100 × 15 m2 depression area on an agricultural field in the Hydrological Open Air Laboratory, Austria. The images are georectified and classified by an automated procedure, using grey intensity as a threshold to identify saturation area. The optimum threshold T is obtained by comparing saturation areas from the automated analysis with the manual analysis of 149 images. T is found to be highly correlated with an image brightness characteristic defined as the greyscale image histogram mode M (Pearson correlation r = 0.91). We estimate T as T = M + C where C is a calibration parameter assumed to be constant during each event. The automated procedure estimates the total saturation area close to the manual analysis with mean normalized root mean square error of 9% and 21% if C is calibrated for each event and taken constant for all events, respectively. The spatial patterns of saturation are estimated with a geometric mean accuracy index of 94% as compared to the manual analysis of the same photos. The patterns are tested against field observations for one date as a preliminary demonstration, which yields a root mean square error of the shortest distance between the measured boundary points and the automatically classified boundary as 23 cm. The usefulness of the patterns is illustrated by exploring run‐off generation processes of an example event. Overall, the proposed classification method based on grey intensity is found to process images with highly varying brightnesses well. It is more efficient than the manual tracing for a large number of images, which allows the exploration of surface flow processes at high temporal resolution.

This study investigated the added value of different data for calibrating a runoff model for small basins. The analysis was performed in the 66 ha Hydrological Open Air Laboratory, in Austria. An Hydrologiska Byråns Vattenbalansavdelning (HBV) type, spatially lumped hydrologic model was parameterized following two approaches. First, the model was calibrated using only runoff data. Second, a step-by-step approach was followed, where the modules of the model (snow, soil moisture, and runoff generation) were calibrated using measurements of runoff and model state variables and output fluxes. These measurements comprised laser-based measurements of precipitation, satellite and camera observations of snow, ultrasonic measurements of snow depth, eddy covariance measurements of evapotranspiration, time domain transmissometry-based soil moisture measurements, time-lapse photography of overland flow, and groundwater level measurements by piezometers. The two model parameterizations were evaluated on annual, seasonal, and daily time scales, in terms of how well they simulated snow, soil moisture, evapotranspiration, overland flow, storage change in the saturated zone, and runoff. Using the proposed step-by-step approach, the relative runoff volume errors in the calibration and validation periods were 0.00 and −0.01, the monthly Pearson correlation coefficients were 0.92 and 0.82, and the daily logarithmic Nash Sutcliffe efficiencies were 0.59 and 0.18, respectively. By using different sources of data besides runoff, the overall process consistency improved, compared to the case when only runoff was used for calibration. Soil moisture and evapotranspiration observations had the largest influence on simulated runoff, while the parameterization of the snow and runoff generation modules had a smaller influence.

Abstract. The objective of this study was to present a sophisticated method of developing supporting material for flood control implementation in DKI Jakarta. High flow rates in the Ciliwung River flowing through Jakarta regularly causes extensive flooding in the rainy season. The affected area comprises highly densely populated villages. For developing an efficient early warning system in view of decreasing the vulnerability of the locations a flood index map has to be available. This study analyses the development of a flood risk map of the inundation area based on a two-dimensional modeling using FESWMS. The reference event used for the model was the most recent significant flood in 2007. The resulting solution represents flood characteristics such as inundation area, inundation depth and flow velocity. Model verification was performed by confrontation of the results with survey data. The model solution was overlaid with a street map of Jakarta. Finally, alternatives for flood mitigation measures are discussed.

Banjir merupakan bencana yang sering terjadi di ibukota DKI Jakarta dengan kejadian terbesar pada tahun 2007. Penentuan langkah yang tepat dalam menyelesaikan masalah banjir dapat dibantu dengan pemetaan resiko banjir. Daerah studi kasus dalam penelitian ini adalah Kelurahan Bukit Duri, Kecamatan Tebet, Jakarta yang terletak di hulu pintu air Manggarai. Penelitian difokuskan pada estimasi bahaya banjir, kerentanan, kapasitas, dan resiko di daerah studi. Peta genangan banjir dikembangkan dengan model matematis aliran 1-D tak tunak DUFLOW dengan hidrograf banjir tahun 2007. Limpasan hidrograf banjir akan membebani daerah retensi dan menyebabkan variasi genangan. Indeks bahaya banjir dianalisis berdasarkan peta genangan dengan diverifikasi data lapangan. Analisis indeks kerentanan menggunakan parameter jaringan pipa dan kabel, jenis bangunan, sebaran populasi, dan potensi bahaya kolateral. Analisis indeks kapasitas memakai parameter kondisi pompa, tanggul, dan intervensi (peningkatan kewaspadaan banjir). Peta resiko dievaluasi menggunakan GIS dalam skenario optimis dan pesimis dengan persamaan: resiko = bahaya x kerentanan / kapasitas. Intervensi pada skenario optimis menunjukkan penurunan resiko signifikan di beberapa daerah, sedangkan pada skenario pesimis tidak berbeda dibandingkan kondisi eksisting. Peta resiko kondisi eksisting dianalisis serupa dengan keadaan aktual, dimana daerah studi merupakan daerah beresiko banjir tinggi karena perumahan penduduk yang padat dan kapasitas penanggulangan banjir yang tidak memadai.