The Logistics of Feeding the Roman Army on the Lower Danube. / Matthews, Stephen.

2018. 463 p.

Research output: ThesisDoctoral Thesis

Unpublished

Documents

Abstract

This thesis sets out to quantify the logistical burden that a Roman garrison brought with it, in terms of land and transport requirements. The focus will be on arable land, both to feed the soldiers but also to provide feed-barley for the transport animals. First the needs are quantified, having considered likely ranges of key variables that impact upon agricultural productivity. Then an appraisal of the arable available in the study areas is carried out on the basis of the settlement activity seen in the archaeological record. This is used to build a model of what land was plausibly available to supply the army.
The study areas were selected according to where there had been previous landscape survey on the Lower Danube, around Novae and Nicopolis ad Istrum and also in Dobrogea, where it has long been assumed that settlement was encouraged to supply to the military. In this last case, my assessment of land available is carried out using the Romanian national database of sites – cIMeC – which aims to record all archaeological sites in the country. Although this is fraught with problems of interpretation, it is augmented both by works of traditional scholarship and by a dataset of tumuli for part of the region to arrive at a quantified, suggested solution to the needs of the garrison.
For this suggested solution and the deficit – that part not available locally –the modelling of transport solutions is carried out. This is done within ArcGIS using the Service Area function, which allocates the most effective routes to move cargoes from producer to consumer. As a result models of what land was available and how the produce of that land was moved to the garrison are arrived at.
Original languageEnglish
QualificationPh.D.
Awarding Institution
Supervisors/Advisors
Award date1 May 2018
Publication statusUnpublished - Mar 2018
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 29676230