The map accompanies the SOLAW report 8 “Agriculture and water quality interactions”. Arsenic contamination in groundwater has been reported in more than 20 countries around the world and, in many, shallow groundwater is used for both drinking and irrigation purposes. Natural arsenic in groundwater at concentrations above the drinking water standard of 10 µg/liter is not uncommon, and the realization that water resources can contain insidious toxic concentrations of naturally-occurring chemical constituents, such as arsenic, is fairly recent and increasingly urgent. First estimates of arsenic toxicity (arsenosis) from drinking water, causing skin lesions and various types of cancers, indicate about 130 million people are impacted. Although the main geochemical mechanisms of arsenic mobilization are well understood, and there are important cases reported around the world, the real worldwide scale of affected regions is still unknown. . Amini. et al 2008 conducted un study using a large database of measured arsenic concentration in groundwater (around 20,000 data points) from around the world as well as digital maps of physical characteristics such as soil, geology, climate, and elevation to model probability maps of global arsenic contamination. This map therefore shows, at global scale, probability of geogenic arsenic contamination in groundwater for reducing groundwater conditions, based on modelling the above information.

The map shows the results of a simulation of land suitability assessment under climate change impacts on land resources. The map was compiled from climate projections and calculations produced by the UK Hadley Centre (GCM results from the UK HadCM3 model for the 2050s for an emission pathway of the IPCC SRES A2 scenario (Nakicenovic et al., 2000)). The impacts of climate change on the production potential of rain-fed cereals in current cultivated land are represented in the map for all the types of cereals represented in GAEZ 2009 (some 118 cereal LUTs covering wheat, rice, maize, barley, sorghum, millet, rye, oats and buckwheat). The computations determine separately for current climate and for future climate conditions the most productive cereal type in each grid-cell of the spatial resource inventory in order to define overall cereal productivity, i.e. assuming a high level of crop adaptation. Results indicate a somewhat increasing global rain-fed production potential by 2050, provided CO2 fertilization is effective and full adaptation of crop types is achieved; but climate change could as well result in a reduction of the global production of about 5 percent if these two aspects were not achieved. In the latter case most regions would experience a reduction. At the regional level, results for Southern Africa, North Africa and Central America show the largest negative climate change impacts on rain-fed cereal production potential. The suitability combines and classifies within grid cell the obtained suitability distribution by means of an index. This index is calculated as follows; SI= VS*0.9+ S*0.7+MS*0.5+mS*0.3+ VmS*0.1 Where: VS represents the share of very suitable land (80-100% of maximum attainable yield) S represents the share of suitable land (60-80% of attainable yield) MS represents the share of moderately suitable land (40-60% of maximum attainable yield) mS represents the share of marginally suitable land (20-40% of maximum attainable yield) VmS represents the share of very marginally suitable land (5-20% of maximum attainable yield)

The map shows the dominant soil and terrain constraints of land for low input farming conditions. The map was developed within the IIASA/FAO GAEZ 2009 modelling framework. It illustrates that soil nutrient availability is by far the most prevalent soil limitation in most regions, in particular in the tropics, especially in large parts of Middle Africa and Central South America.

The map shows the ratio of total withdrawals to the available renewable water resource. Renewable water resources are downscaled to a five arc-minute grid. Water is considered scarce when the withdrawals exceed 40% of the renewable resource. According to statistics compiled by FAO (FAOSTAT),several countries in North Africa, the Middle East and Central Asia withdraw more water than their total renewable resources. Domestic water withdrawals are downscaled by applying the per capita domestic water use to population of each pixel. Industrial water withdrawals were downscaled by using the industrial water use per unit GDP and applying downscaled information on GDP. Water consumption is assumed to be 30% of domestic use and 10% of industrial use. Finally, agricultural water consumption is assumed to be the crop water deficit in irrigated areas generated in the AEZ analysis and water used for livestock consumption, applied to a global spatial data set of livestock distribution prepared by FAO.Source of the map: GAEZ 2009 and AQUASTAT; downscaling simulations by authors.

The map presents soil quality ratings computed in GAEZ 2009 (IIASA/FAO GAEZ 2009 modelling framework) for low input farming conditions. Natural fertility status of soils as presented above may have further deteriorated over time through “nutrient mining”. Given proper soil management with appropriate fallowing, the natural status may be restored in the long run.

This map, compiled to support the analysis of SOLAW report concerning land tenure and water rights (FAO -NRL, SOLAW 2010 Report 5A - Hotspots of land tenure and water rights) shows the population growth rate, in percentage, according to CIA Factbook 2006. The need to feed 9 billion people by 2050 implies that the pressure on land and water will generally increase. Countries with the highest population growths rate are also those for which the number of calories available per person per day is lower. They are also, in part, countries in which the volume of water available per capita and year is the lowest.

The map presents soil quality ratings computed in GAEZ 2009 for low input farming conditions. Natural fertility status of soils as presented above may have further deteriorated over time through "nutrient mining". Given proper soil management with appropriate fallowing, the natural status may be restored in the long run. The map was developed within the IIASA/FAO GAEZ 2009 modelling framework

The map accompanies the SOLAW report 14 “Where are the poor and where are the land and water resources”. The analysis addressed in this report is aimed at identifying areas where land, water resources and farming systems pose potential threats to livelihoods. In particular this map, accompanying the report, shows the per capita share of easily available water by region. The data for the analysis comes from the FAO GeoNetwork data archive. The methodology draws from the main hypotheses set in the analysis that are to: • test if per capita share of land and water resources have a significant association with poverty • if land suitability and farming systems modify that relationship. Principal Component Analysis (PCA) is used to derive a single resource management index based on land and water resources, land suitability and farming systems. PCA involves a mathematical procedure that transforms a number of correlated variables into a smaller number of uncorrelated variables called Principal Components (PC). The new sets of variables (PCs) are a linear combination of the original variables which are derived in decreasing order of importance, with the first principal component accounting for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability. The first PC, which is a measure of variability in access to land and water resources and in farming systems, is chosen as the resource management index. The results from the analysis are presented in the form of graphs and maps that answer the following questions: • Where are the rural poor concentrated? • Where are the poor in relation to land and water resources and farming systems? • To what extent do access to land and water resources and current farming systems constrain livelihoods for the poor? • Can changes in resource management modify poverty outcomes in resource-constrained areas? The map shows per capita share of easily available water by region and rural-urban localities. Per capita share of easily available water is lowest in Asia – 5.8 mm/month per 1000 people. In Europe, America and Africa it is 6.2, 14.8 an 15.2 mm/month per 1000 people, respectively compared to 37.7 mm/month per 1000 in Oceania. Substantial rural-urban differentials exist in per capita share of easily available water. In rural areas of Asia, per capita share of easily available water is only 0.46 mm/month per 1000 people compared to 10.2 in urban areas of Asia.

The map, computed in GAEZ 2009 (IIASA/FAO GAEZ 2009 modelling framework), shows soil workability constraints to crop cultivation. Soil workability constraints are seen as major obstacle to crop cultivation, which are, for example, prevalent in large parts of Ethiopia, Sudan and central India. Soil workability constraints may be reduced with the use of high input and appropriate soil management.

The map accompanies the SOLAW report 8 “Agriculture and water quality interactions”. Agriculture intensification and improper management of nutrients and pesticides is increasing pollution of water resources. Intensified use of fertilizers has often come together with the improper management and/or excessive application of nutrients. Nowadays it is clear the linkage between expanding and intensification of cultivated areas, increasing unit fertiliser use and rising groundwater nitrate concentrations in developed countries. There is now growing concern in many developing countries where agriculture expansion and intensification is taking place. The map, developed within the Land and Water Degradation System (GLADIS) project, (Nachtergaele et al. 2010 ), shows a good world overview of areas with potential land and water pollution problems from agriculture.