Applied Hydrological Modeling
Preface
Foreword
Study Guide & Materials
Study Guide
Prerequisites
Day 1: Introduction and installation of software
Day 2: Hydrological processes & characterization
Day 3: Hydrological models & Introduction to RS Minerve
Day 4: Data for hydrological modeling
Day 5: The HBV model
Day 6: Model calibration and validation
Day 7: Case studies
Day 8: Real-world applications
Day 9: Student presentations and wrap-up of workshop
Study Materials
I Part I Hydrological Systems
1
Short History of Water in Central Asia
1.1
The Taming of the Central Asian Rivers
1.2
Post-Transition Development and Challenges
2
Hydrological Systems in Central Asia
2.1
Regional Hydro-Climatological Features
2.2
Regional Water Balance
2.3
Runoff Formation
2.4
Average Multi-Year Runoff
2.5
Annual Runoff Fluctuations
3
Case Studies
3.1
Gunt River Basin
3.1.1
Basin Characterization
3.1.2
Hydrology
3.1.3
Climate
3.2
Chirchik River Basin
3.2.1
Basin Characterization
3.2.2
Hydrology
3.2.3
Climate
3.2.4
Discharge Estimation from the Ungauged Kosku Tributary
II Part II Applied Modeling
4
Budyko-Type Long-term Water Balance Modeling
4.1
Derivation of the Budyko Relationship
4.2
Effects of Snow Ratio on Annual Runoff within the Budyko Framework
4.3
Hydrological Response to a Changing Climate
4.4
Application to Central Asian River Basins
4.4.1
Data
4.4.2
Model
4.4.3
Conclusions
5
Data Retrieval, Preparation & Analysis
5.1
Station Data
5.1.1
Available Data
5.1.2
Gap Filling Discharge Data
5.1.3
Gap Filling Meteorological Data
5.1.4
Anomalies and Outliers
5.1.5
Putting it all together
5.2
Geospatial Data
5.2.1
Prerequisites
5.2.2
Setting up QGIS
5.2.3
Load DEM
5.2.4
Catchment delineation
5.2.5
Run through the process model
5.2.6
Manually edit the GIS layers for import in RS MINERVE
5.3
Climate Reanalysis Data
5.3.1
CHELSA V1.2.1 Data and Bias Correction
5.3.2
ERA5 Download and Data Resampling with PBCORR CHELSA
5.4
Data on Climate Projections
5.4.1
High Res. Monthly Climate Time Series for 2006 - 2100
5.4.2
Using a Weather Generator to Simulate Daily Future Climate
5.5
Snow Cover Data
5.6
Glacier Data
6
Hydrological-Hydraulic Modeling
6.1
Prerequisites
6.2
Recap: Hydrological response
6.3
Recap: The general modeling process
6.4
Data Preparation and Setup
6.4.1
Examining and Understanding the GIS Data
6.4.2
Loading GIS Data and Model Creation
6.4.3
Climate Data
6.5
The HBV model
6.5.1
HBV example: Simple model of the Nauvalisoy river catchment
6.6
Model Calibration and Validation
6.6.1
Basic Principles
6.6.2
Practical Steps
6.7
Application: Investigating Climate Change Impacts
6.8
Discussion
7
Discharge Forecasting with Predictive Inference
Prerequisites
7.1
Forecasting Using Predictive Inference
7.2
Forecasting in the Central Asian Hydromets
7.2.1
Background
7.2.2
Forecasting for What and Whom?
7.3
Data and Preparation
7.3.1
Available Data
7.3.2
Gap Filling Discharge Data
7.3.3
Gap Filling Meteorological Data
7.3.4
Anomalies and Outliers
7.3.5
Putting it all together
7.4
Data Analysis
7.4.1
Data Transformation
7.4.2
Detecting Trends
7.4.3
Auto- and Crosscorrelations
7.4.4
Time Series Seasonality
7.5
Investigating and Engineering Predictors
7.5.1
Benchmark: Current Operational Forecasting Models in the Hydrometeorological Agencies
7.5.2
Time Series Regression Models
7.5.3
Assessing the Quality of Forecasts
7.5.4
Generating and Assessing Out-of-Sample Forecasts
7.5.5
Machine Learning Models
7.6
Save Data for Hot Start
8
Operationalization of Models - Opportunities and Challenges
8.1
Co-design Phase
8.2
Modeling Phase
8.3
Testing Phase
8.4
Operational Deployment
9
(APPENDIX) Appendix
9.1
Appendix A: Open-source resources
9.1.1
Literature
9.1.2
QGIS
9.1.3
R and RStudio
9.1.4
RS Minerve
9.2
Appendix B: Quick Guides
EE: Register for an account
EE: Download SRTM data for a selected region
QGIS installation guide
The QGIS window - overview
QGIS: Saving a new QGIS project
QGIS: Change the projection of the QGIS project
QGIS: Install and activate plugins in QGIS3
GQIS: Managing panels visibility in QGIS
QGIS: Loading public background maps
QGIS: Zoom to layer
QGIS: Import SRTM layers using the SRTM plugin
QGIS: Merge SRTM tiles to a single layer
QGIS: Add raster layer
QGIS: Change color of raster layer
QGIS: Add map decorations
9.2.1
QGIS: Verify projection of layer and re-project layer
QGIS: Save a temporary layer
QGIS: Add vector layer
QGIS: Change color of a vector layer
QGIS: Fill sinks
QGIS: Calculate the area upslope of a point
QGIS:
QGIS: Edit Junctions layer
RSM: Create HBV model and edit parameters
RSM: Add and link climate station
RSM: Import climate data
RSM: Adapt model settings
RSM: Export simulation results to data base
RSM: Add comparator and load discharge measurements
RSM: Copy-paste data to database
9.3
Appendix C: Processing Climate Data
9.3.1
Cutting CHELSA v.1.2.1 to CA Domain
9.3.2
Bias Correcting CHELSA v1.2.1 Precipitation Data for Snow Undercatch
9.3.3
Computing Mean Monthly Temperature Climatology from CHELSA v1.2.1 data
9.3.4
ERA5
9.4
Appendix D: Solutions to exercises
Exercise on Linear Reservoir modelling
Exercise on creating GIS layers for import to RS Minerve
Exercises on the HBV model
10
References
Published with bookdown
Applied Modeling of Hydrological Systems in Central Asia
4.3
Hydrological Response to a Changing Climate
Source articles:
Ning et al.
(
2018
)
,
(
Zhou et al. 2016
)
.
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