Members’ Publication

Densely populated floodplains downstream of Asia’s mountain ranges depend heavily on mountain water resources, in particular for irrigation. An intensive and complex multi-cropping irrigated agricultural system has developed here to optimize the use of these mountain water resources in conjunction with monsoonal rainfall. Snow and glacier melt thereby modulate the seasonal pattern of river flows and, together with groundwater, provide water when rainfall is scarce. Climate change is expected to weaken this modulating effect, with potentially strong effects on food production in one of the world’s breadbaskets. Here we quantify the space-, time- and crop-specific dependence of agriculture in the Indo-Gangetic Plains on mountain water resources, using a coupled state-of-the-art, high-resolution, cryosphere–hydrology–crop model. We show that dependence varies strongly in space and time and is highest in the Indus basin, where in the pre-monsoon season up to 60% of the total irrigation withdrawals originate from mountain snow and glacier melt, and that it contributes an additional 11% to total crop production. Although dependence in the floodplains of the Ganges is comparatively lower, meltwater is still essential during the dry season, in particular for crops such as sugar cane. The dependency on meltwater in the Brahmaputra is negligible. In total, 129 million farmers in the Indus and Ganges substantially depend on snow and glacier melt for their livelihoods. Snow and glacier melt provides enough water to grow food crops to sustain a balanced diet for 38 million people. These findings provide important information for agricultural and climate change adaptation policies in a climate change hot spot where shifts in water availability and demand are projected as a result of climate change and socio-economic growth.

In this article, we build our theoretical arguments on an empirical account of a state-implemented housing project in the periphery of Dhaka. Thus, we elaborate on a set of bureaucratic acts, the existing power relations, and group interests that influence planning practices and condition people’s access to public resources. Analyzing the process of project implementation, we explain the various resources and strategies that those in relatively powerful positions activate in order to considerably influence planning practice and public resource distribution. We specifically analyze how the strategies and discourses employed to bring the project forward influence the emerging spatialities and issues of socio-spatial justice and inequality at Dhaka’s urban fringe. This article thus provides empirical evidence explaining the impossibility of rigid statutory planning. Finally, we reflect on what urban planning needs to acknowledge in order for positive change.

The global spatial accuracy of ortho-mosaics based on images from consumer-grade unmanned aerial vehicles (UAVs) is relatively low. The use of ground control points (GCPs) improves the accuracy but it requires RTK-GNSS (global navigation satellite system) measurements in the field. The objective of this study was to evaluate manual geo-rectification after ortho-mosaicking as a cost-effective alternative to GCPs or UAVs equipped with RTK-GNSS. Google Earth images and A-B lines used for tractor auto-steering were used for manual geo-rectification with a free geographic information system (GIS) and remote-sensing (RS) software (QGIS). Two different photogrammetry software (Agisoft Photoscan and Pix4DMapper) were used for ortho-mosaicking. Images were captured in three fields at two altitudes (40 and 80 m) with a multi-rotor camera drone equipped with a GNSS without ground reference (Phantom 4). The results showed that flight altitude and photogrammetry software had no impact on the spatial accuracy and that manual geo-rectification significantly improved the spatial accuracy. Root mean squares (RMSEs) for ortho-mosaics without geo-rectification was in the range of 4 to 28 m and the range was 0.6 to 2.5 m and 0.5 to 1.1 m for geo-rectification based on Google Earth images and A-B-lines, respectively. RTK-GNSS tagged UAV images and the use of GCPs gave average RMSEs of less than 0.1 m. It was concluded that manual geo-rectification offers a feasible alternative to GCPs and UAVs with RTK-GNSS when spatial accuracy of about 1 m is acceptable.