Proportional Variation of Potential Groundwater Recharge as a Result of Climate Change and Land-Use: A Study Case in Mexico

Artículo en revista indexadaThis work proposes a methodology whereby the selection of hydrologic and land-use cover change (LUCC) models allows an assessment of the proportional variation in potential groundwater recharge (PGR) due to both land-use cover change (LUCC) and some climate change scenarios for 2050. The simulation of PGR was made through a distributed model, based on empirical methods and the forecasting of LUCC stemming from a supervised classification with remote sensing techniques, both inside a Geographic Information System. Once the supervised classification was made, a Markov-based model was developed to predict LUCC to 2050. The method was applied in Acapulco, an important tourism center for Mexico. From 1986 to 2017, the urban area increased 5%, and by 2050 was predicted to cover 16%. In this period, a loss of 7 million m3 of PGR was assumed to be caused by the estimated LUCC. From 2017 to 2050, this loss is expected to increase between 73 and 273 million m3 depending on the considered climate change scenario, which is the equivalent amount necessary for satisfying the water needs of 6 million inhabitants. Therefore, modeling the variation in groundwater recharge can be an important tool for identifying water vulnerability, through both climate and land-use change.CONACyT Centro de Ciencias de Desarrollo Regional (CCDR

Estimating the uncertainty of land-cover extrapolations while constructing a raster map from tabular data

This paper presents novel techniques to estimate the uncertainty in extrapolations of spatially-explicit land-change simulation models. We illustrate the concept by mapping a historic landscape based on: 1) tabular data concerning the quantity in each land cover category at a distant point in time at the stratum level, 2) empirical maps from more recent points in time at the grid cell level, and 3) a simulation model that extrapolates land-cover change at the grid cell level. This paper focuses on the method to show uncertainty explicitly in the map of the simulated landscape at the distant point in time. The method requires that validation of the land-cover change model be quantified at the grid-cell level by Kappa for location (Klocation). The validation statistic is used to estimate the certainty in the extrapolation to a point in time where an empirical map does not exist. As an example, we reconstruct the 1951 landscape of the Ipswich River Watershed in Massachusetts, USA. The technique creates a map of 1951 simulated forest with an overall estimated accuracy of 0.91, with an estimated user\u27s accuracy ranging from 0.95 to 0.84. We anticipate that this method will become popular, because tabular information concerning land cover at coarse stratum-level scales is abundant, while digital maps of the specific location of land cover are needed at a finer spatial resolution. The method is a key to link non-spatial models with spatially-explicit models

An HGIS Approach to Land-Use/Land-Cover Change in the Blanice Watershed, Czech Republic

In the South Bohemian region of the Czech Republic, the landscape is distinguished by a network of long narrow fields bordered by hedgerows clustered in small groups. These unique clusters of hedgerows have been interacting with their environment, effectively mitigating erosion, since they were first established in the High Middle Ages. In this research project I used historical maps to characterize land-use and land-cover (LULC) change relating to hedgerow features in one cadastral territory in the Blanice Watershed. Using georeferenced historical maps from 1837 and 1952, and unreferenced historical maps from 1837 to 1953, I compared the historical LULC to the current LULC within the cadastral territory of Křišťanovice. From 1837 to present-day Křišťanovice, the percentage of farmed land has decreased from 59.9% to 25.8%, while the percentage of forested area has increased from 26.6% to 61.9%. These changes reflect historical trends in land management as well as the impact of social and political changes on the environment. This project is also a methodological and epistemological exploration of a Historical GIS approach to research, and the methods developed to conduct LULC change analysis reflect these theoretical components. The results of this research provide a spatiotemporal HGIS analysis of LULC change, a workflow for applying the HGIS methods developed for this research, and a geodatabase for the storage, classification, and visualization of historical LULC data