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Monday, November 9, 2020 | History

3 edition of Spatial modelling of mountainous basins found in the catalog.

Spatial modelling of mountainous basins

Walter Immerzeel

Spatial modelling of mountainous basins

an integrated analysis of the hydrological cycle, climate change and agriculture

by Walter Immerzeel

  • 14 Want to read
  • 33 Currently reading

Published by Koninklijk Nederlands Aardrijkskundig Genootschap, Faculteit Geowetenschappen Universiteit Utrecht in Utrecht .
Written in English

    Subjects:
  • Water supply,
  • Hydrologic cycle,
  • Mountain climate,
  • Agriculture -- Environmental aspects

  • Edition Notes

    StatementWalter Immerzeel.
    SeriesNederlandse geografische studies / Netherlands geographical studies -- 369, Nederlandse geografische studies -- 369.
    Classifications
    LC ClassificationsTD345 .I47 2008
    The Physical Object
    Pagination145 p. :
    Number of Pages145
    ID Numbers
    Open LibraryOL16849588M
    ISBN 109068094114
    ISBN 109789068094114
    LC Control Number2008400396

    International meetings - (book of abstracts) Célleri, R., P. Willems, W. Buytaert and Feyen (). Analysis of the spatial rainfall variability in a mountain basin of the Andes of South Ecuador. ERB conference: Uncertainties in the 'monitoring-conceptualisation-modelling' sequence of catchment research. Luxemburg. September.


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Spatial modelling of mountainous basins by Walter Immerzeel Download PDF EPUB FB2

Spatial modelling of mountainous basins An integrated analysis of the hydrological cycle, climate change and agriculture Walter Immerzeel Utrecht Koninklijk Nederlands Aardrijkskundig Genootschap Faculteit Geowetenschappen Universiteit Utrecht Netherlands Geographical Studies Spatial modelling of mountainous basins.

Utrecht: Koninklijk Nederlands Aardrijkskundig Genootschap, Faculteit Geowetenschappen Universiteit Utrecht, (OCoLC) Material Type: Thesis/dissertation, Internet resource: Document Type: Book, Internet Resource: All Authors / Contributors: Walter Immerzeel.

basins remains acute. In this paper we address this problem with a 'model to recover, later in the season, the spatial distri- bution of SWE in mountain basins at the onset of snowmelt. The duration (D) of snow cover at any given location may be viewed as a function of the original quantity of SWE at thatCited by: C.

Andrew Day, Modelling impacts of climate change on snowmelt runoff generation and streamflow across western US mountain basins: a review of techniques and applications for water resource management, Progress in Physical Geography, /, 33, 5, (), ().Cited by: Accurate representation of the spatial distribution of snow water equivalent (SWE) in mountainous basins is critical for furthering the understanding of snow as a water resource, especially in the Western United States.

To estimate the spatial distribution and total volume of SWE over mountainous basins, previous work has either assumed uniform snow density or used simple approaches to Cited by: Our modelling results show a spatial distribution of sediment yield between all 50 subbasins (0 to 7 t/ha/a) with highest amounts predicted for cabbage cultivation ( t/ha/a) and only low.

In mountainous areas where snow is a significant part of the hydrologic cycle, snowmelt is a primary water input to the soil and stream system. It is, therefore, essential to simulate snow accumulation and melt accurately.

Spatially distributed hydrologic modelling in mountainous areas first requires spatially distributed snowmelt modelling. The spatial distribution of critical rainfall values is compared with landslide locations mapped from aerial photographs and in the field for three study basins where high-resolution digital.

Braun, L. and Aellen, M. Modelling discharge of glacierized basins assisted by direct measurements of glacier mass balance.

In Lang, H. and Musy, A. editors, Hydrology of mountainous regions I, Proceedings of two Lausanne Symposia,Wallingford: IAHS PublicationGoogle Scholar. Spatial modelling of mountainous basins book edited volume assesses capabilities of data mining algorithms for spatial modeling of natural hazards in different countries based on a collection of essays written by experts in the field.

The book is organized on different hazards including landslides, flood. The major role of basin models is to reconstruct the history Spatial modelling of mountainous basins book sedimentary basins in an effort to predict how the processes of generation, expulsion, migration, trapping, and preservation control the volumetrics, quality, and distribution of oil and gas in a basin.

There are two aspects to basin modeling: thermal and fluid flow modeling. It is with great satisfaction and personal delight that I can write the foreword for this book Fundamentals of Basin and Petroleum Systems Modeling by Thomas Hantschel and Armin Ingo Kauerauf.

It is a privilege for us geosci- tists that two outstanding physicists, with scienti?c backgrounds in numerical methods of continuum-mechanics and in Reviews: 1. Aristizabal E, Velez J, Martinez H, Jaboyedoff M () SHIA_Landslide: a distributed conceptual and physically based model to forecast the temporal and spatial occurrence of shallow landslides triggered by rainfall in tropical and mountainous basins.

The assessment and prevention of floods require appropriate forecasting and knowledge of the related hydrological processes. Due to the similar form of the governing equations, flood hydrograph shows a clear analytical and mathematical analogy with electrical circuits.

In this paper, a spatially distributed hydrological model is developed which is analogue to a network of electrical resistance. Hydrogen gas is seeping from the sedimentary basin of São Franciso, Brazil. The seepages of H 2 are accompanied by helium, whose isotopes reveal a strong crustal signature.

Geophysical data indicates that this intra-cratonic basin is characterized by (i) a relatively high geothermal gradient, (ii) deep faults delineating a horst and graben structure and affecting the entire sedimentary.

Impact of climate change on the seasonal distribution of runoff in mountainous. Using a Monte Carlo technique for modelling the natural variability of streamflow.

Spatial variation in evapotranspiration in Swiss Alpine regions Lucas Menzel. Spatial Modelling of the Terrestrial Environment deals with the use of remote sensing, numerical models and GIS in addressing important natural and human environmental sciences issues, focusing on the theory and application of modelling remotely sensed data within the context of environmental processes.

Abstract. Adequate estimation of the spatial distribution of snowfall is critical in hydrologic modelling. How-ever, this is a well-known problem in estimating basin-scale snowfall, especially in mountainous basins with data scarcity.

This study focuses on correction and estimation of this spatial distribution, which considers topographic ef. The decrease of density contrast with depth in sedimentary basins could be approximated by a quadratic function.

The sedimentary basin is viewed as a number of outcropping vertical prisms put in juxtaposition at each observation point. Equations are derived for the gravity anomaly of a. BASINS provides a framework that brings together modeling tools and environmental spatial and tabular data into a geographic information system (GIS) interface.

BASINS can be used for investigations and analysis on a variety of geospatial scales from small watersheds within a single municipality, to a large watershed across several states. One sees that, in the mountainous and valley subbasins [Figs.

7(e and f)], the corresponding values of ETP change significantly when excluding orographic influences, whereas when the whole Flumendosa basin is considered the differences are smeared out due to spatial averaging effects.

In addition, at the mountainous subbasin, the ETP values are. UHLENBROOK S., TETZLAFF D. Significance of spatial and temporal variability of precipitation for flood modelling in mountainous basins In: Hydrological and meteorological coupling in mountain areas: Experiments and modelling (Hrsg.

We present a modeling approach that couples information about snow cover duration from remote sensing with a distributed energy balance model to calculate the spatial distribution of snow water equivalence (SWE) in a km 2 mountain basin at the peak of the accumulation season.

In situ measurements of incident solar radiation, incident longwave radiation, air temperature, relative. Geologic interpretations are the basis of most exploration workflows, whether building a 3-D framework, a geocellular model, or modeling HC basins and estimating HC reserves.

All these workflows rely on the most realistic and accurate interpretation in order to produce high-confidence results. Submitted to: Book Chapter Publication Type: Book / Chapter Publication Acceptance Date: 7/20/ Publication Date: N/A Citation: N/A Interpretive Summary: A new method to estimate the spatial distribution of snow water equivalent (SWE) in mountainous areas is using a combination of modeling and remote sensing is presented.

Written for graduates, researchers and professionals, Spatial Analysis: A Guide For Ecologists will be a valuable source of reference for years to come. Contents. Preface 1. Spatial concepts and notions 2. Ecological and spatial processes 3. Points, lines and graphs 4.

Spatial analysis of complete point location data 5. Contiguous units analysis 6. thermal histories of basins. The models lead to an estimation of the timing of hydrocarbon generation and expulsion. In recent years, however, basin modeling has expanded to include evaluation of secondary migration and trapping of hydrocarbons within basins.

1D modelling: model building, burial history, heat flow history, temperature calibration. Analysis and Modelling of Spatial Environmental Data presents traditional geostatistics methods for variography and spatial predictions, approaches to conditional stochastic simulation and local probability distribution function estimation, and select aspects of Geographical Information Systems.

It includes real case studies using Geostat. Spatial analysis is a type of geographical analysis which seeks to explain patterns of human behavior and its spatial expression in terms of mathematics and geometry, that is, locational analysis.

Examples include nearest neighbor analysis and Thiessen of the models are grounded in micro-economics and predict the spatial patterns which should occur, in, for example, the growth of. This selective list contains the main references: PCRaster and dynamic modelling: Van Deursen, W.P.A.

Geographical Information Systems and Dynamic Models: development and application of a prototype spatial modelling language. Doctor's dissertation, Utrecht University, NGS Karssenberg, D. Building dynamic spatial environmental models.

basins remains acute. In this paper we address this problem with a model to recover, later in the season, the spatial distri-bution of SWE in mountain basins at the onset of snowmelt. The duration (D) of snow cover at any given location may be viewed as a function of the original quantity of SWE at that location at the onset of snowmelt (SWE.

Hydrological modelling and integrated water resources management in ungauged mountainous watersheds. --Analysis of the dominant climatic factors of evaporation change over the main basins in mainland China based on Budyko and Bouchet hypotheses / Hanbo Yang [and others] --A unit hydrograph model with spatial variations of rainfall.

The imprint of geologic events left on the materials of sedimentary basins is the most detailed record of the history of Earth's outer shell, the lithosphere. Basins come in many shapes and sizes and form in response to a variety of processes that influence the elevation of Earth's surface.

A first wave of exploration of the Cenozoic half graben basins of the East African Rift System in the early 's resulted in the acquisition of 2D seismic in the Turkana area (northern Kenya) and the drilling of well Loperot-1 in the eastern part of the unconformities and the orientation of spatial trends in the isopach maps suggest three.

Magnus Wangen has worked in the field of sedimentary basin-modelling since the late s - conducting research on a wide range of topics. He obtained a Dr Scient. degree in applied mathematics from Universitetet i Oslo in with a thesis on the modelling of heat- and fluid-flow in sedimentary : $ Understanding source rock provides a key to evaluating the hydrocarbon potential of super basins and an important tool for basin exploration.

Geologists get the basics right, in general, but sometimes they might be thinking about source rock the wrong way.

Minimum temperature for reproduction is oC. Native range The native range of P. parva is the East Asian subregion including the basins of the rivers Amur, Yang-tze, Huang-ho, Japanese islands (Kiusiu, Sikoku and the southern and central parts of Honsiu), western and southern parts of the Korean Peninsula and Taiwan (Minkiang river system).

Chapter 8. Spatial data modelling, collection and management. objectives of the application. basins, agro-ecological units, measurements of actual evapotranspiration, meteorological data. Month HTML views PDF downloads XML downloads; Feb 1: Mar 4: Apr 4: May 5: Jun 9: Jul Basin modelling is the term broadly applied to a group of geological disciplines that can be used to analyse the formation and evolution of sedimentary basins, often but not exclusively to aid evaluation of potential hydrocarbon reserves.

At its most basic, a basin modelling exercise must assess: The burial history of the basin (see back-stripping).; The thermal history of the basin (see. Spatial Planning (MESP) and River Basin Authorities iii Institutional support to the Ministry of Environment and An EU funded project managed by the European Commission Liaison Office (ECLO) List of Tables Table 1: Morphological parameters of the main sub-basins 3 Table 2: Land covered by forest (source: Master Plan) 4.Cambridge Core - Environmental Science - Runoff Prediction in Ungauged Basins - edited by Günter Blöschl.Author(s): Cline, DW; Bales, RC; Dozier, J | Abstract: We present a modeling approach that couples information about snow cover duration from remote sensing with a distributed energy balance model to calculate the spatial distribution of snow water equivalence (SWE) in a km2 mountain basin at the peak of the accumulation season.

In situ measurements of incident solar radiation, incident.