Novel modelling approaches and data sources in socio-hydrology
File(s)
Author(s)
Blair, Peter
Type
Thesis
Abstract
Increasing interactions between anthropogenic and hydrological systems have prompted the development of a new way of thinking in water resource management: socio-hydrology. Socio-hydrology explicitly considers the two-way interactions and feedbacks between humans and water and includes these in models to explore trajectories of development. Expanding system boundaries to include human behaviour and interactions with natural systems brings significant challenges.
This study was largely divided into two parts, modelling in socio-hydrology and data in socio-hydrology. The modelling section focuses on investigating the utility of diff erent modelling techniques in socio-hydrology, and then covers the development and use of models in socio-hydrology, while the data section investigates the use of freely available data sets to investigate an aspect of socio-hydrological systems and in a context of determining land-use.
In the modelling section, a detailed review of modelling in socio-hydrology was initially carried out which found that work should focus on further conceptual modelling, as well as developing calibration/validation methodologies. A conceptual model was then developed, focusing on drought in a socio-hydrological context; this model was able to produce some
archetypal system behaviours.
In the section focusing on data in socio-hydrology, a learning approach was used to try to determine the impact of
ooding on house prices. Unfortunately, the data available was not detailed enough to allow for a model with predictive power, and so this learning approach was not able to give more insight than other investigations that have been carried out in this area. In the chapter exploring the use of satellite data in determining land-cover, the model which was learnt had success in determining land-cover at the time and place it was trained on, but had limited success in determining land-cover in other times and places, and so does not represent an improvement on what techniques already exist.
This study was largely divided into two parts, modelling in socio-hydrology and data in socio-hydrology. The modelling section focuses on investigating the utility of diff erent modelling techniques in socio-hydrology, and then covers the development and use of models in socio-hydrology, while the data section investigates the use of freely available data sets to investigate an aspect of socio-hydrological systems and in a context of determining land-use.
In the modelling section, a detailed review of modelling in socio-hydrology was initially carried out which found that work should focus on further conceptual modelling, as well as developing calibration/validation methodologies. A conceptual model was then developed, focusing on drought in a socio-hydrological context; this model was able to produce some
archetypal system behaviours.
In the section focusing on data in socio-hydrology, a learning approach was used to try to determine the impact of
ooding on house prices. Unfortunately, the data available was not detailed enough to allow for a model with predictive power, and so this learning approach was not able to give more insight than other investigations that have been carried out in this area. In the chapter exploring the use of satellite data in determining land-cover, the model which was learnt had success in determining land-cover at the time and place it was trained on, but had limited success in determining land-cover in other times and places, and so does not represent an improvement on what techniques already exist.
Version
Open Access
Date Issued
2017-11
Date Awarded
2018-08
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Buytaert, Wouter
Ewers, Robert
Sponsor
Natural Environment Research Council (Great Britain)
Grant Number
NE/L002515/1
Publisher Department
Civil and Environmental Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Master of Philosophy (MPhil)