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CoastalDEM v2.1 is a near-global digital elevation model (DEM) developed by Climate Central to provide more accurate land elevation data for coastal flood risk assessments. By utilizing a sophisticated convolutional neural network trained on NASA's ICESat-2 satellite lidar data, the model corrects the positive vertical bias common in satellite radar-derived DEMs, which often mistake building rooftops for ground level. Testing shows that CoastalDEM v2.1 virtually eliminates global median bias in the critical 0 to 5 m elevation band, significantly outperforming other publicly available global DEMs such as NASADEM, TanDEM-X, MERIT, and AW3D30, particularly in densely populated urban areas.

The document details the stakeholder engagement process and technical data used to develop a regional tool for integrated water and economic planning in the Berg WMA. It includes records of workshops and meetings with provincial government, local municipalities, and academic institutions. Technical appendices provide marginal values of water by crop, estimated irrigated agriculture water requirements, and forecasts for urban water demand for 2025 and 2040. The text also validates these bottom-up estimations against the WARMS database and Aurecon's Water Resources Simulation Model, while assessing the economic opportunity cost of potential supply deficits in terms of GVA and employment.