Water, food and energy are at the core of human needs and there is a boundless complex cycle among these three basic human needs. Ecosystems are in the center of this nexus, since they contribute to the provision of each component, making it imperative to understand the role of ecosystems in securing food, water and energy for human well-being. In this study we aimed to map and assess water provisioning services and associated benefits to support the ecosystem–water–food–energy nexus by taking into account environmental flow requirements for riverine ecosystems using the hydrological model Soil and Water Assessment Tool (SWAT). We developed a framework that includes indicators of renewable water (capacity of ecosystem to provide water) and water use (service flow) and we applied it in the Danube river basin over the period 1995–2004. Water scarcity indicators were used to map the possible water scarcity in the subbasins, and analyze the spatial match of water availability and water use. The results show that modelling is instrumental to perform the integrated analysis of the ecosystem–water–food–energy nexus; and that spatial mapping is a powerful tool to display environmental availability of water provisioning and regulatory services delivered by ecosystems, and can support the nexus analysis.

This special issue aims to provide a knowledge base that is focused on geospatial mapping approaches for a better understanding of spatiotemporal dynamics of agricultural intensification from food/water security standpoints. This issue is of special importance to researchers engaged in applications of geospatial technologies in various agricultural science and engineering disciplines including agronomy, hydrology, geography, climatology, computer science, and engineering | Mahesh Rao, Chandrashekhar Biradar, Sudhanshu Panda. (1/1/2017). Agricultural Intensification: Combating Food/Water Security Challenges Using Remote Sensing and GIS

The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km2 (26 575 200 ha), comparing a water-surplus year (2000-2001) and a water-deficit year (2002-2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61-100% for various land-use classes and 61-81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R2-values between 0.82 and 0.86. The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002-2003) when compared with the water-surplus year (2000-2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.

The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km2 (26 575 200 ha), comparing a water-surplus year (2000-2001) and a water-deficit year (2002-2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61-100% for various land-use classes and 61-81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R2-values between 0.82 and 0.86. The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002-2003) when compared with the water-surplus year (2000-2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.