ArcGIS Assignment 1
Geospatial Data Analysis for Hydrological Modelling

Var Catchment Analysis using GIS

Pages: Assignment - StepByStep - Results

This Web page describes the 1st assignment dealing with the DEM, rainfall station, landuse and soil data analysis of the river Var catchment nearby Nice/F. Please have also a look in the lecture notes and in the Step-By-Step tutorial for ArcGIS.

Case Study

River flood modelling and management is based on different types of information. Important, basic information sources are digital elevation models (DEM) of the relevant region. Raw data for a DEM could originate from remote sensing data (e.g. SRTM, Aster) or local surveying. In this case study two prepared DEM sources are available:

• 75 m resolution raster data
• 300 m resolution raster data

Both sources have been already pre-processed and reduced to the relevant Var catchment region. They can be used directly for the hydrological analysis of the Var catchment. The 300 m resolution raster data has been used for the Step-by-Step tutorials.

Assignment 1 has to be done using the 75 m resolution DEM raster data set or the 300 m resolution DEM raster data. An alternative to the 75 m / 300 m resolution DEM raster data are free available remote sensing data, such as SRTM or Aster data. Please feel free to use the related tiles for the region in case of interest.

Hydrological analysis of a catchment requires additional information such as land use and soil type or rainfall information. In this 1st assignment three additional information are used:

• a land use raster data (300m resolution)
• a soil type raster data (2000m resolution)
• a rainfall gauge location ASCII file

The land use, soil type and rainfall gauge data can be used for spatial analysis of the different sub-catchments.

General Objective

The objective of the 1st assignment is the understanding of the typical GIS analysis steps as input for hydrological modelling of a river catchment.

Analysis Targets

First analysis results should be (see result tables):

• delineation of the catchment towards sub-catchments and river network
• identification of sub-catchments (see figure below)
  - Upper Var
  - Esteron
  - Tinee
  - Vesubie
  - Lower Var
• spatial analysis of the sub catchments with key numbers e.g.
  - area
  - minimum/average/maximum elevation and slope
  - length of longest flow path

• land use distribution in the sub-catchments

• soil type distribution in the sub-catchments

• Thiessen polygons overlay to sub-catchments

The results of the different GIS analysis steps should be summarized in result tables:

Result Tables

Catchment geometry

Land Use

area contribution land use <-> sub-catchment in [km**2]

value / sub catchment	Tinee	Upper Var	Esteron	Vesubie	Lower Var
forest
semi-natural
agricultural
artificial surfaces
water bodies
wetlands

Soil Type Data

area contribution soil type <-> sub-catchment in [km**2]

value / sub catchment	Tinee	Upper Var	Esteron	Vesubie	Lower Var
clay loam
loam
sandy clay loam
sandy loam
silt loam
silty clay loam

Rainfall Gauges

area contribution Thiessen polygons <-> sub-catchment in [km**2]

gauge / sub catchment	Tinee	Upper Var	Esteron	Vesubie	Lower Var
Carros
Levens
Roquesteron
Puget
Guillaumes
St Martin

Figure: River Var sub catchments

Figure: River Var rain gauge stations