Water management strategies and climate change in the Indus Civilisation

Projektinformationen

WaMStrIn

ID Finanzhilfevereinbarung: 746446

DOI

10.3030/746446

Projekt abgeschlossen

EK-Unterschriftsdatum 3 März 2017

Startdatum 2 Januar 2018

Enddatum 1 Januar 2020

Finanziert unter

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Gesamtkosten

€ 183 454,80

EU-Beitrag

€ 183 454,80

Koordiniert durch

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
United Kingdom

Periodic Reporting for period 1 - WaMStrIn (Water management strategies and climate change in the Indus Civilisation)

Berichtszeitraum: 2018-01-02 bis 2020-01-01

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

The WaMStrIn project has explored the relationship between human settlement and the changing hydrological network of the Indus River Basin in Pakistan during the time of the emergence of first urban centres in ancient South Asia (2500-1900 BC) and in later historical periods. The ancient Indus was the most extensive of the three so-called cradles of Old World civilizations and a number of attempts have been made to trace the network of palaeorivers that watered this region and sustained its ancient population and later historical cultures.
Water management and availability are relevant to a range of current archaeological debates, particularly those related to food security, sustainability and resilience. These issues are also directly relevant to current investigation into the impact of climate change on modern populations in regions that are becoming increasingly arid. The case of the Indus civilization is particularly significant in that aspect, being the earliest large-scale, urban, and interconnected society in South Asia. The shrinking of Indus urban centers have been a long puzzle for archaeologists and it is discussed how the weakening of the Indian Summer Monsoon around 4200 years ago could have impacted this process.
The objectives of the action were directed to exploiting the capacities of historical cartography, series of satellite imagery and archaeological databases to reconstruct aspects of the historical river network and long-term settlement patterns of the alluvial plains of Pakistani Punjab. Studying the relation of those two elements with the help of geostatistics, network analysis and landscape analysis has provided clues to understanding the complex relationship of human societies with the changes on water availability, the management of risks such inundations or droughts and the resilience to long-term climate change processes.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

The project has created two main datasets for the exploration of the interactions between human societies and river changes:
1) A map of river paleochannels integrating information from historical maps, specifically treated satellite imagery and micro-relief analysis.
2) A map of potential ancient settlements, based on previous archaeological knowledge and the analysis of historical cartography, topography and satellite imagery.
Analysing together the materials, conclusions about the geomorphological and settlement dynamics can be extracted. A proof of concept (Garcia, A., et al. 2019: https://doi.org/10.3390/geosciences9010021) was published at the middle of the action, focusing in how inundations and river movements can impact settlement and our archaeological knowledge about it.
The actions has implemented different techniques for taking advantages of the accumulation of temporal series of multispectral satellite images since the 1980s, the increasing resolution of satellite-obtained models of the earth surface and the existence of platforms that offer access to this data and computational power for large-scale intense analysis.
WaMStrIn has also developed new techniques for the automatic extraction of archaeological information from large series of historical maps and aerial imagery at specific resolution using Machine Learning techniques.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

The datasets generated for the project represents a major step forward with respect the archaeological materials known until now in the study area and they will be available for researchers interested in the study of the historical dynamics of the Indus Valley:
- Long-term series of satellite imagery have been used in the area to map paleochannels and identify archaeological sites.
- A large series of the historical cartography generated by the survey of India have been georeferenced and analysed for the extraction of potential archaeological sites. That have generated a map of potential sites invisible in present-day due to changes in the area.
The implementation of ML automatic extraction of archaeological features can potentially impact the capacities of archaeologists working in a wide range of contexts to develop intense surveys at a larger scale.
The action has also a potential impact in the management of Cultural Heritage, in that sense it can contribute to future researches of archaeologists in Punjab that can complement their knowledge of the regional archaeology with the datasets and techniques developed by WaMStrIn. The methodes developed here can be applied as well in other geographic areas and can be considered by both research groups and Heritage Agencies to increase its knowledge of the archaeological record and assess risks of lose. This research has also contributed to successful funding for ongoing research based in Cambridge.
The conclusions of the project regarding the long-term relationships between human societies and environmental changes can be of interest beyond archaeology, providing awareness about landscape management and socio-political implications of environmental transformations.

An archaeological mound-type site detected during the action.