Understanding the spatial variability of groundwater recharge in response to distributed Land-use, soil texture, topography, groundwater level, and hydrometeorological parameters is significant when considering the security of groundwater resource development. Thus, this study was aimed at estimating the spatial groundwater recharge of Raya valley, northern Ethiopia using spatially distributed water balance model (WetSpass). Input data for the model were prepared in the form of grid maps using 90 m grid size and the parameter attribute tables were adjusted to represent the Raya valley condition using expert knowledge and scientific literatures. The results of the model indicated that the long-term temporal and spatial average annual rainfall of 710 mm was partitioned as 57 mm (8%) of surface runoff, 598 mm (84%) of evapotranspiration, and 55 mm (8%) of recharge. The recharge corresponds to 137 million cubic meters (Mm3) for the Raya basin (with area of about 2500 km2) from which 84% of the recharge takes place during summer season, while the remaining 16% takes place during the winter (dry) season. The analysis of the simulated result showed that WetSpass works well to simulate water balance components of Raya valley and is especially suitable for studying the effects of Land-use changes on the water regime in the basin.
Tag: geographical information systems
Batch-produced, GIS-informed range maps for birds based on provenanced, crowdsourced data inform conservation assessments
Accurate maps of species ranges are essential to inform conservation, but time-consuming to produce and update. Given the pace of change of knowledge about species distributions and shifts in ranges under climate change and land use, a need exists for timely mapping approaches that enable batch processing employing widely available data. We develop a systematic approach of batch-processing range maps and derived Area of Habitat maps for terrestrial bird species with published ranges below 125,000 km2 in Central and South America. (Area of Habitat is the habitat available to a species within its range.) We combine existing range maps with the rapidly expanding crowd-sourced eBird data of presences and absences from frequently surveyed locations, plus readily accessible, high resolution satellite data on forest cover and elevation to map the Area of Habitat available to each species. Users can interrogate the maps produced to see details of the observations that contributed to the ranges. Previous estimates of Areas of Habitat were constrained within the published ranges and thus were, by definition, smaller-typically about 30%. This reflects how little habitat within suitable elevation ranges exists within the published ranges. Our results show that on average, Areas of Habitat are 12% larger than published ranges, reflecting the oftenconsiderable extent that eBird records expand the known distributions of species. Interestingly, there are substantial differences between threatened and non-threatened species. Some 40% of Critically Endangered, 43% of Endangered, and 55% of Vulnerable species have Areas of Habitat larger than their published ranges, compared with 31% for Near Threatened and Least Concern species. The important finding for conservation is that threatened species are generally more widespread than previously estimated. © 2021 Huang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The FTA Geoportal Manual
As a collaborative research project, involving numerous researchers from member organisations, data sharing is important for FTA to optimise the use of their data inventory as well as for exchanging their knowledge, thus improving the quality and exposure of FTA research. This geoportal has been designed and developed as a system that can facilitate effective and efficient (geospatial) data access to, and data sharing among, FTA members’ internal data inventory as well as that of other organisations. Moreover, this geoportal is also expected to fulfil the need for showcasing or disseminating FTA’s research to a wider community/audience.
The Geospatial data quality and metadata: Handbook
This handbook is intended to provide guidance on geospatial data quality and metadata management. While it can provide the reader with answers to basic questions on the latter, it does not have all the answers. The reader should also find the information and guidance helpful when dealing with important questions on geospatial data quality and metadata.
Forest fire estimation and risk prediction using multispectral satellite images: Case study
Forest fires are increasing in terms of number, size, and extent which have a growing influence on the achievement of the Sustainable Development Goals (SDGs). The economy and ecology of Northeast India have been seriously impacted by forest fires in many places, it is important to comprehend the region’s spatiotemporal distribution, severity, and future projections for forest fires in light of climate change. Geographical information systems (GIS) integrating with remote sensing (RS) were used to understand the role of different parameters in all four bioclimatic zones of the region. and discussion: Most of the fires were restricted to pre-monsoon season (93 %), alone 62 % in March. The forest fire in the present scenario was highest in the Lawngtlai district, followed by Dhalai and Ri-Bhoi. The Lawngtlai and Dhalai districts are at the highest risk (greater than 70 %) for future forest fires. Categorically, among the protected areas, Lengteng WLS has the highest (86.6 %) future forest fire risk followed by Tawi WLS (86.5 %), Ngengpui WLS (84.9 %), and Pualreng WLS (84.6 %). The results suggest that underground biomass in the lower elevated forest needs to be managed effectively at the onset of the fire season to reduce the occurrence of forest fires. There is a need for a well-defined framework supported by geospatial technology to predict, identify, and prioritize the fire potential zone with synergic strategies supported by the local community to mitigate the fire impact on the forests.