Darstellung und Analyse hydrologischer Topologien auf der Basis künstlicher neuronaler Netze

Die Sicherung und nachhaltige Nutzung der Ressource Wasser stellt eine globale Problematik dar, die nur durch eine Vielzahl von Einzelanstrengungen auf lokaler bis regionaler Ebene gelöst werden kann. Hierbei gilt es, ein ausgewogenes Verhältnis zwischen der Berücksichtigung von Anforderungen an die Wasserqualität auf der einen und der Bewirtschaftung der zugehörigen Einzugsgebiete auf der anderen Seite zu finden. Gerade die Bewirtschaftung landwirtschaftlich genutzter Flächen ist hierbei von vielen, häufig unbekannten Parametern abhängig wie etwa den spezifischen, physiografischen Eigenschaften der Einzelfläche oder auch individuellen Präferenzen der Bewirtschafter. Der anthropogen verursachte Stickstoffeintrag ist hierbei aufgrund der engen Verknüpfung mit der Bewirtschaftung geeignet, als Leitparameter zu fungieren. Eine Konfiguration optimierter Stickstoffeinträge kann dann in Verknüpfung mit den übrigen Parametern der realweltlichen Problemstellung zur Formulierung optimierter Bewirtschaftungskonfigurationen herangezogen werden. Sollen dabei jedoch topologische Beziehungen, die in reliefierten Einzugsgebieten z.B. in Form lateraler Stoffflüsse zwischen Einzelflächen auftreten, berücksichtigt werden, so stellt die Ermittlung solcher Konfigurationen ein bislang ungelöstes Problem dar. Zur Bearbeitung dieser Problemstellung wurde im Rahmen der vorliegenden Arbeit ein neuartiges Verfahren auf der Basis künstlicher neuronaler Netze entwickelt, welches gezielt nach optimalen Stickstoffeinträgen suchen und dabei topologische Beziehungen, große Datenmengen sowie detaillierte Prozessbeschreibungen verarbeiten kann

How Climate Extremes Influence Conceptual Rainfall-Runoff Model Performance and Uncertainty

Rainfall-runoff models are frequently used for assessing climate risks by predicting changes in streamflow and other hydrological processes due to anticipated anthropogenic climate change, climate variability, and land management. Historical observations are commonly used to calibrate empirically the performance of conceptual hydrological mechanisms. As a result, calibration procedures are limited when extrapolated to novel climate conditions under future scenarios. In this paper, rainfall-runoff model performance and the simulated catchment hydrological processes were explored using the JAMS/J2000 model for the Berg River catchment in South Africa to evaluate the model in the tails of the current distribution of climatic conditions. An evolutionary multi-objective search algorithm was used to develop sets of parameters which best simulate “wet” and “dry” periods, providing the upper and lower bounds for a temporal uncertainty analysis approach to identify variables which are affected by these climate extremes. Variables most affected included soil-water storage and timing of interflow and groundwater flow, emerging as the overall dampening of the simulated hydrograph. Previous modeling showed that the JAMS/J2000 model provided a “good” simulation for periods where the yearly long-term mean precipitation shortfall was 0.7) during “wet” periods using parameters from a long-term calibration, “wet” parameters were not recommended for the Berg River catchment, but could play a large role in tropical climates. The results of this study are likely transferrable to other conceptual rainfall/runoff models, but may differ for various climates. As greater climate variability drives hydrological changes around the world, future empirically-based hydrological projections need to evaluate assumptions regarding storage and the simulated hydrological processes, to enhanced climate risk management

Modelling of Hydrological Responses in the Upper Citarum Basin based on the Spatial Plan of West Java Province 2029 and Climate Change

In 2010, a spatial plan for West Java Province up to 2029 was published (Perda 22/2010). The purpose of the plan is to guide settlement area development. This study aims to assess the hydrological implications of the Spatial Plan 2029 within the Upper Citarum Basin (UCB) and with regard to climate change. A hydrological simulation based on land-use at the time of the plan (2010) and planned land use was performed using the JAMS/J2000 hydrological model. The settlement area from the spatial plan for 2029 was extracted and then superimposed onto the 2010 land use. Two different land-use scenarios (2010 and 2029) and a climate change scenario (1990-2030) were used for the hydrological simulation, with IPSL-CM4 and UKMO-HadCM3 being the products used for the latter. The simulation results were presented as river discharge and surface runoff. From the simulation results, the annual average of the simulated river discharge is expected to increase by 1.8% up to 2029 compared to the 2010 level. More substantial changes were noticed in the surface runoff, which is projected to increase on average by 8.9% annually due to the expansion of urban areas and agricultural land use. The seasonal analysis showed that river discharge and surface runoff both increased more markedly in the wet season. The study shows the potential of the JAMS/J2000 model to assess the impacts of land-use and climate change on hydrological dynamics

River Basin Information System: Open Environmental Data Management for Research and Decision Making

An open, standardized data management and related service infrastructure is a crucial requirement for a seamless storage and exchange of data and information within research projects, for the dissemination of project results and for their application in decision making processes. However, typical project databases often refer to only one research project and are limited to specific purposes. Once implemented, those systems are often not further maintained and updated, rendering the stored information useless once the system stops operating. The River Basin Information System (RBIS) presented here is designed to fit not only the requirements of one research project, but focuses on generic functions, extensibility and standards compliance typically found in interdisciplinary environmental research. Developed throughout more than 10 years of research cooperation worldwide, RBIS is designed to manage different types of environmental data with and without spatial context together with a rich set of metadata. Beside data management and storage, RBIS provides functions for the visualization, linking, analysis and processing of different types of data to support research, decision making, result dissemination and information discovery for all kinds of users. The focus of this paper is on the description of the technical implementation and the presentation of functions. This will be complemented by an overview of example applications and experiences during RBIS development and operation

Geospatial Virtual Appliances Using Open Source Software

Part 2: eEnvironment and Cross-Border Services in Digital Agenda for EuropeInternational audienceThe hype on the Cloud is based on promising cost savings if, considering the new service platform concepts (IaaS, PaaS, SaaS) the term comes with, IT resources will be used effectively. Therefore, the trend is moving away from physical systems to more instant and short-term environments and virtualization is increasingly taking on a key role in various system architectures. This is already well accepted by a few business units such as customer relationship management or marketing, operated from Salesforce.com for instance [1]. However, earth scientific offers featuring specialized functions and services on demand are still rare but of great benefit in order to overcome the global changes in environmental conditions. Only one task from the field of model preprocessing at the DGHM was picked out for virtualization purposes and the results will be introduced in the following

Prediction of flow intermittence in Drying River Networks using a process-based hydrological model

International audienceIntermittent rivers and ephemeral streams (IRES) account for about half of the world’s river networks and are considered to increase under climate change and growing anthropogenic water use. However, the hydrological mechanisms that control the spatio-temporal flow patterns in IRES and their effects on the expansion and contraction of stream segments are not fully understood. Discharge measurements mainly exist for gauging stations, which are often located downstream and in the rivers’ main stems. They are often less impacted by flow intermittence than headwaters and smaller river channels. In consequence, impacts of climate change and anthropogenic alterations on hydrological process dynamics in IRES cannot easily be analysed, neither the influences of climate change and human water use on IRES be quantified.Within the framework of the Horizon 2020 project DRYvER on Drying River Networks and Climate Change, we try to tackle this challenge by developing methods and tools using the JAMS modelling framework and J2K model family to assess hydrological process interactions at high spatial and temporal resolutions, which include the scale of small reaches (about 50 ha catchment size). For that purpose, we developed process-based hydrological models for six mesoscaled river basins between 200 km2 and 350 km2 in different European countries (Croatia, Czech Republic,Finland, France, Hungary, Spain). At the same time, we used data from field measurements and a citizens science application to validate our models at the reach scale. In this study we analyse the ability of our hydrological model to represent observed temporal and spatial dynamics of flow intermittence at high resolution, and develop adaptations that allows using these models in an upscaling step to estimate the impacts of future climatic changes and anthropogenic water consumption on flow intermittence all over Europe

Virtual Appliances for geospatial data management and processing in the Integrated Land Management System (ILMS)

Virtualization is increasingly taking on a key role in various system architectures which follow new platform concepts like Software as a Service (SaaS). This trend addresses more instant and short-term environments and comes with new methods and strategies for the distribution of mainly complex application stacks not only in large IT infrastructures. The paper presents how a so called Virtual Appliance can be set up in order to operate in virtual server environments using hypervisor software like Oracle Virtual-Box. Using the example of two server-side components within the Integrated Land Management System (ILMS), it will be shown that the use of state-of-the-art methods, standardized tools and interfaces on servers enables different aspects of environmental system management, analysis and planning

RBIS - An Environmental Information System for Integrated Landscape Management

Part 3: Environmental Information Systems and Services – Infrastructures and PlatformsInternational audienceIn this paper we present the web-based River Basin Information System (RBIS) for data management, analysis and exchange as an integral standalone part of the Integrated Landscape Management System (ILMS). Its architectural layout will be outlined together with the underlying software platform. Selected RBIS modules will be characterized in more detail to emphasize the benefits of integrated data management as a basis of the holistic environmental planning workflow covered by ILMS

Determining Hydrological Variability Using a Multi-Catchment Model Approach for the Western Cape, South Africa

Understanding the impacts of climate change requires the development of hydrological modelling tools. However, data scarcity hinders model application, performance, process simulation and uncertainty, especially for Sub-Saharan Africa. In this study, a multi-catchment approach was used to assess hydrological process variability in the Western Cape (WC) of South Africa using the JAMS/J2000 rainfall–runoff model and a Monte Carlo analysis (MCA). Due to much steeper slopes and lower evapotranspiration, the models suggest that WC is dominated by surface runoff from mountainous regions and regional groundwater flow. The results highlight the impact of the catchment size, availability and position of hydroclimatic and anthropogenic factors and the frequency of the signal-to-noise ratio (water balance). For large catchments (>5000 km2), the calibration was able to achieve a Nash–Sutcliffe efficiency (NSE) of 0.61 to 0.88. For small catchments (<2000 km2), NSE was between 0.23 to 0.39. The large catchments had an overall surface runoff, interflow and baseflow contribution of 44, 19 and 37%, respectively, and lower overall uncertainty. The simulated flow components for the small catchments were variable and these results are less certain. The use of a multi-catchment approach allows for identifying the specific factors impacting parameter sensitivities and in turn provides a means to improve hydrological process simulation