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1
The Land and Water Development Division of the Food and Agriculture Organization of the United Nations and the Johann Wolfgang Goethe University, Frankfurt am Main, Germany, are cooperating in the development of a global irrigation-mapping facility. This report describes an update of the Digital Global Map of Irrigated Areas for the continent of Asia. For this update, an inventory of subnational irrigation statistics for the continent was compiled. The reference year for the statistics is 2000. Adding up the irrigated areas per country as documented in the report gives a total of 188.5 million ha for the entire continent. The total number of subnational units used in the inventory is 4 428. In order to distribute the irrigation statistics per subnational unit, digital spatial data layers and printed maps were used. Irrigation maps were derived from project reports, irrigation subsector studies, and books related to irrigation and drainage. These maps were digitized and compared with satellite images of many regions. In areas without spatial information on irrigated areas, additional information was used to locate areas where irrigation is likely, such as land-cover and land-use maps that indicate agricultural areas or areas with crops that are usually grown under irrigation. Contents 1. Working Report I: Generation of a map of administrative units compatible with statistics used to update the Digital Global Map of Irrigated Areas in Asia 2. Working Report II: The inventory of subnational irrigation statistics for the Asian part of the Digital Global Map of Irrigated Areas 3. Working Report III: Geospatial information used to locate irrigated areas within the subnational units in the Asian part of the Digital Global Map of Irrigated Areas 4. Working Report IV: Update of the Digital Global Map of Irrigated Areas in Asia, Results Maps
2
This paper provides global terrestrial surface balances of nitrogen (N) at a resolution of 0.5 by 0.5 degree for the years 1961, 1995 and 2050 as simulated by the model WaterGAP-N. The terms livestock N excretion (Nanm), synthetic N fertilizer (Nfert), atmospheric N deposition (Ndep) and biological N fixation (Nfix) are considered as input while N export by plant uptake (Nexp) and ammonia volatilization (Nvol) are taken into account as output terms. The different terms in the balance are compared to results of other global models and uncertainties are described. Total global surface N surplus increased from 161 Tg N yr-1 in 1961 to 230 Tg N yr-1 in 1995. Using assumptions for the scenario A1B of the Special Report on Emission Scenarios (SRES) of the International Panel on Climate Change (IPCC) as quantified by the IMAGE model, total global surface N surplus is estimated to be 229 Tg N yr-1 in 2050. However, the implementation of these scenario assumptions leads to negative surface balances in many agricultural areas on the globe, which indicates that the assumptions about N fertilizer use and crop production changes are not consistent. Recommendations are made on how to change the assumptions about N fertilizer use to receive a more consistent scenario, which would lead to higher N surpluses in 2050 as compared to 1995.
3
Groundwater recharge is the major limiting factor for the sustainable use of groundwater. To support water management in a globalized world, it is necessary to estimate, in a spatially resolved way, global-scale groundwater recharge. In this report, improved model estimates of diffuse groundwater recharge at the global-scale, with a spatial resolution of 0.5° by 0.5°, are presented. They are based on calculations of the global hydrological model WGHM (WaterGAP Global Hydrology Model) which, for semi-arid and arid areas of the globe, was tuned against independent point estimates of diffuse groundwater recharge. This has led to a decrease of estimated groundwater recharge under semi-arid and arid conditions as compared to the model results before tuning, and the new estimates are more similar to country level data on groundwater recharge. Using the improved model, the impact of climate change on groundwater recharge was simulated, applying two greenhouse gas emissions scenarios as interpreted by two different climate models.
4
Artificial drainage of agricultural land, for example with ditches or drainage tubes, is used to avoid water logging and to manage high groundwater tables. Among other impacts it influences the nutrient balances by increasing leaching losses and by decreasing denitrification. To simulate terrestrial transport of nitrogen on the global scale, a digital global map of artificially drained agricultural areas was developed. The map depicts the percentage of each 5’ by 5’ grid cell that is equipped for artificial drainage. Information on artificial drainage in countries or sub-national units was mainly derived from international inventories. Distribution to grid cells was based, for most countries, on the "Global Croplands Dataset" of Ramankutty et al. (1998) and the "Digital Global Map of Irrigation Areas" of Siebert et al. (2005). For some European countries the CORINE land cover dataset was used instead of the both datasets mentioned above. Maps with outlines of artificially drained areas were available for 6 countries. The global drainage area on the map is 167 Mio hectares. For only 11 out of the 116 countries with information on artificial drainage areas, sub-national information could be taken into account. Due to this coarse spatial resolution of the data sources, we recommended to use the map of artificially drained areas only for continental to global scale assessments. This documentation describes the dataset, the data sources and the map generation, and it discusses the data uncertainty.
5
The Land and Water Development Division of the Food and Agriculture Organization of the United Nations and the Johann Wolfgang Goethe University, Frankfurt am Main, Germany, are cooperating in the development of a global irrigation-mapping facility. This report describes an update of the Digital Global Map of Irrigation Areas for the continents of Africa and Europe as well as for the countries Argentina, Brazil, Mexico, Peru and Uruguay in Latin America. For this update, an new inventory of subnational irrigation statistics was compiled. The reference year for the statistics is 2000. Adding up the irrigated areas per country as documented in the report gives a total of 48.8 million ha while the total area equipped for irrigation at the global scale is 278.8 million ha. The total number of subnational units in the inventory used for this update is 16 822 while the number of subnational units in the global inventory increased to 26 909. In order to distribute the irrigation statistics per subnational unit, digital spatial data layers and printed maps were used. Irrigation maps were derived from project reports, irrigation subsector studies, and books related to irrigation and drainage. These maps were digitized and compared with satellite images of many regions. In areas without spatial information on irrigated areas, additional information was used to locate areas where irrigation is likely, such as land-cover and land-use maps that indicate agricultural areas or areas with crops that are usually grown under irrigation.
6
A data set of monthly growing areas of 26 irrigated crops (MGAG-I) and related crop calendars (CC-I) was compiled for 402 spatial entities. The selection of the crops consisted of all major food crops including regionally important ones (wheat, rice, maize, barley, rye, millet, sorghum, soybeans, sunflower, potatoes, cassava, sugar cane, sugar beets, oil palm, rapeseed/canola, groundnuts/peanuts, pulses, citrus, date palm, grapes/vine, cocoa, coffee), major water-consuming crops (cotton), and unspecified other crops (other perennial crops, other annual crops, managed grassland). The data set refers to the time period 1998-2002 and has a spatial resolution of 5 arc minutes by 5 arc minutes which is 8 km by 8 km at the equator. This is the first time that a data set of cell-specific irrigated growing areas of irrigated crops with this spatial resolution was created. The data set is consistent to the irrigated area and water use statistics of the AQUASTAT programme of the Food and Agriculture Organization of the United Nations (FAO) (http://www.fao.org/ag/agl/aglw/aquastat/main/index.stm) and the Global Map of Irrigation Areas (GMIA) (http://www.fao.org/ag/agl/aglw/aquastat/irrigationmap/index.stm). At the cell-level it was tried to maximise consistency to the cropland extent and cropland harvested area from the Department of Geography and Earth System Science Program of the McGill University at Montreal, Quebec, Canada and the Center for Sustainability and the Global Environment (SAGE) of the University of Wisconsin at Madison, USA (http://www.geog.mcgill.ca/~nramankutty/ Datasets/Datasets.html and http://geomatics.geog.mcgill.ca/~navin/pub/Data/175crops2000/). The consistency between the grid product and the input data was quantified. MGAG-I and CC-I are fully consistent to each other on entity level. For input data other than CC-I, the consistency of MGAG-I on cell level was calculated. The consistency of MGAG-I with respect to the area equipped for irrigation (AEI) of GMIA and to the cropland extent of SAGE was characterised by the sum of the cell-specific maximum difference between the MGAG-I monthly total irrigated area and the reference area when the latter was exceeded in the grid cell. The consistency of the harvested area contained in MGAG-I with respect to SAGE harvested area was characterised by the crop-specific sum of the cell-specific difference between MGAG-I harvested area and the SAGE harvested area when the latter was exceeded in the grid cell. In all three cases, the sums are the excess areas that should not have been distributed under the assumption that the input data were correct. Globally, this cell-level excess of MGAG-I as compared to AEI is 331,304 ha or only about 0.12 % of the global AEI of 278.9 Mha found in the original grid. The respective cell-level excess of MGAG-I as compared to the SAGE cropland extent is 32.2 Mha, corresponding to about 2.2 % of the total cropland area. The respective cell-level excess of MGAG-I as compared to the SAGE harvested area is 27 % of the irrigated harvested area, or 11.5 % of the AEI. In a further step that will be published later also rainfed areas were compiled in order to form the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000). The data set can be used for global and continental-scale studies on food security and water use. In the future, it will be improved, e.g. with a better spatial resolution of crop calendars and an improved crop distribution algorithm. The MIRCA2000 data set, its full documentation together with future updates will be freely available through the following long-term internet site: http://www.geo.uni-frankfurt.de/ipg/ag/dl/forschung/MIRCA/index.html. The research presented here was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) within the framework of the research project entitled "Consistent assessment of global green, blue and virtual water fluxes in the context of food production: regional stresses and worldwide teleconnections". The authors thank Navin Ramankutty and Chad Monfreda for making available the current SAGE datasets on cropland extent (Ramankutty et al., 2008) and harvested area (Monfreda et al., 2008) prior to their publication.
7
A new global crop water model was developed to compute blue (irrigation) water requirements and crop evapotranspiration from green (precipitation) water at a spatial resolution of 5 arc minutes by 5 arc minutes for 26 different crop classes. The model is based on soil water balances performed for each crop and each grid cell. For the first time a new global data set was applied consisting of monthly growing areas of irrigated crops and related cropping calendars. Crop water use was computed for irrigated land and the period 1998 – 2002. In this documentation report the data sets used as model input and methods used in the model calculations are described, followed by a presentation of the first results for blue and green water use at the global scale, for countries and specific crops. Additionally the simulated seasonal distribution of water use on irrigated land is presented. The computed model results are compared to census based statistical information on irrigation water use and to results of another crop water model developed at FAO.
8
A data set of annual values of area equipped for irrigation for all 236 countries in the world during the time period 1900 - 2003 was generated. The basis for this data product was information available through various online data bases and from other published materials. The complete time series were then constructed around the reported data applying six statistical methods. The methods are discussed in terms of reliability and data uncertainties. The total area equipped for irrigation in the world in 1900 was 53.2 million hectares. Irrigation was mainly practiced in all the arid regions of the globe and in paddy rice areas of South and East Asia. In some temperate countries in Western Europe irrigation was practiced widely on pastures and meadows. The time series suggest a modest rate of increase of irrigated areas in the first half of the 20th century followed by a more dynamic development in the second half. The turn of the century is characterized by an overall consolidating trend resulting at a total of 285.8 million hectares in 2003. The major contributing countries have changed little throughout the century. This data product is regarded as a preliminary result toward an ongoing effort to develop a detailed data set and map of areas equipped for irrigation in the world over the 20th century using sub-national statistics and historical irrigation maps.
09
Agriculture of crops provides more than 85% of the energy in human diet, while also securing income of more than 2.6 billion people. To investigate past, present and future changes in the domain of food security, water resources and water use, nutrient cycles, and land management it is required to know the agricultural land use, in particular which crop grows where and when. The current global land use or land cover data sets are based on remote sensing and agricultural census statistics. In general, these only contain one or very few classes of agricultural land use. When crop-specific areas are given, no distinction of irrigated and rainfed areas is made, whereas it is necessary to distinguish rainfed and irrigated crops, because crop productivity and water use differ significantly between them.
To support global-scale assessments that are sensitive to agricultural land use, the global data set of Monthly Irrigated and Rainfed Crop Areas around the year 2000 (MIRCA2000) was developed by the author. With a spatial resolution of 5 arc-minutes (approximately 9.2 km at the equator), MIRCA2000 provides for the first time, spatially explicit irrigated and rainfed crop areas separately for each of the 26 crop classes for each month of the year, and includes multi-cropping. The data set covers all major food crops as well as cotton, while the remaining crops are grouped into three categories (perennial, annual and fodder grasses). Also for the first time, crop calendars on national or sub-national level were consistently linked to annual values of harvested area at the 5 arc-minutes grid cell level, such that monthly growing areas could be computed that are representative for the time period 1998 to 2002.
The downscaling algorithm maximizes the consistency to the grid-based input data of cropland extent [Ramankutty et al., 2008], crop-specific total annual harvested area [Monfreda et al., 2008], and area equipped for irrigation [Siebert et al., 2007]. In addition to the methodology, this dissertation describes differences to other datasets and standard scaling methods, as well as some applications. For quality assessment independent datasets and newly developed quality parameters are used, and scale effects are discussed.
Supplementary Appendices document crop calendars for irrigated and rainfed crops for each of the 402 spatial units (Appendix I), data sources of harvested area and of cropping periods for irrigated crops, country by country (Appendix K), as well as data quality parameters (Appendix L, including spreadsheet files).
10
Die vorliegende Arbeit wurde im Rahmen des Forschungsprojekts „Integrierte Analyse von mobilen, organischen Fremdstoffen in Fließgewässern“ (INTAFERE) am Institut für Physische Geographie an der Goethe-Universität Frankfurt erstellt. In INTAFERE wurde das Gefährdungspotenzial von mobilen, organischen Fremdstoffen (MOF) für aquatische Ökosysteme und die natürlichen Wasserressourcen in integrierter und partizipativer Art und Weise untersucht. MOF sind chemische Substanzen, die in Alltagsprodukten enthalten sind und durch unterschiedliche Eintragsfade in unbekannten Mengen in Oberflächengewässer eingetragen werden. Problematisch sind aus Umweltgesichtspunkten ihre Eigenschaften: sie besitzen im Wasser eine hohe Mobilität und sind schwer abbaubar. Dies führt zu einer Persistenz über lange Zeiträume. Für einige dieser Substanzen wurde zudem gezeigt, dass sie in sehr geringen Konzentrationen biologisch aktiv sind und für aquatische Ökosysteme eine Gefahr darstellen. In INTAFERE wurden drei zentrale Ziele verfolgt: Charakterisierung des Problemfeldes MOF, Erzeugung von praxisrelevantem Wissen für das Management von MOF und Entwicklung einer Softwareanwendung, die gesellschaftliche Aushandlungsprozesse durch eine transparente Darstellung der Wirkungszusammenhänge im Problemfeld unterstützt. Um einen Beitrag für die Erfüllung der Ziele zu leisten, war es die Aufgabe der Verfasserin, eine Akteursanalyse und -modellierung durchzuführen sowie Zukunftsszenarien im Bereich der MOF zu entwickeln. Dafür existierte keine adäquate Methodik, daher verfolgt die Dissertation zum einen die Entwicklung einer Methodik und zum anderen deren Anwendung im Kontext des Projektes INTAFERE. Da im Forschungsprozess die Durchführung von Analysen, die wissenschaftliche und gesellschaftliche Sichtweise der Problematik sowie die Erarbeitung von praktischen Lösungen im Mittelpunkt standen, wurde eine transdisziplinäre Herangehensweise gewählt. Ziel war es, eine Methodik zu entwerfen, die sowohl eine Entwicklung von Szenarien als auch eine Modellierung von Handlungsentscheidungen umfasst. Eine Modellierung und Visualisierung von Handlungsentscheidungen ist notwendig, um Strategien für ein Umweltproblem für verschiedene Szenarien zu ermitteln, und damit einen Lernprozess der Stakeholder zu initiieren. Dies wurde mit der transdisziplinären Methode „Akteursbasierte Modellierung“ umgesetzt. Hierbei wurden insbesondere Aspekte der Problemwahrnehmung von Akteuren und deren Darstellung, der partizipativen Szenarienentwicklung sowie der semi-quantitativen Modellierung von Handlungsentscheidungen berücksichtigt. Die Verfasserin hat mit der semi-quantitativen akteursbasierten Modellierung eine Methode erarbeitet und getestet, die bisher unverbundene Komponenten (wie die Software Dynamic Actor Network Analysis (DANA) und die Szenarienentwicklung) zusammenführt. Um Handlungsentscheidungen unter verschiedenen Szenarien zu modellieren hat die Autorin eine sequentielle Modellierung entwickelt, die mit der Software DANA durchgeführt werden kann. Die dafür notwendige Weiterentwicklung von DANA wurde von Dr. Pieter Bots (TU Delft) umgesetzt. Die akteursbasierte Modellierung läuft in drei methodischen Schritten ab: 1. Modellierung von Akteurs-Sichtweisen in Form von Wahrnehmungsgraphen und deren Analyse, aufbauend auf Ergebnissen von qualitativen, leitfaden-gestützten Expertengesprächen (= Akteursmodellierung), 2. partizipative Szenarienentwicklung mit den Akteuren und 3. Zusammenführung der Ergebnisse der Akteursmodellierung und der Szenarienentwicklung und darauf aufbauend eine sequentielle Modellierung von Handlungsentscheidungen und deren Auswirkungen auf Schlüsselfaktoren. Im Zuge der Anwendung auf das Problemfeld der MOF wurde für folgende Akteure jeweils ein Wahrnehmungsgraph modelliert: Obere Wasserbehörde, Umweltbundesamt, Umwelt- und Verbraucherschutzorganisationen, Wasserversorger sowie für die Hersteller von verschiedenen MOF, weiterhin für die European Flame Retardants Association und die Weiterverarbeitende Industrie. Das Ergebnis der Szenarienentwicklung waren vier Szenarien: ein Gesundheitsszenario, unter der Annahme von hohen lokalen Umweltstandards durch nachhaltigkeitsorientierte KonsumentInnen, ein Umweltszenario, in dem eine starke Regulierung und nachhaltigkeitsorientierter Konsum Hand in Hand gehen, ein Globalisierungsszenario, in dem Wirtschaftsmacht und preisbewusste KonsumentInnen statt staatliche Regulierung vorherrschen und ein Technikszenario, unter der Annahme, dass Kläranlagen, bedingt durch eine starke Regulierung, aufgerüstet werden. Bei der Modellierung von Handlungsentscheidungen wurden die Wahrnehmungsgraphen und die vier Szenarien miteinander verknüpft. Pro Substanz wurde ein Modell entwickelt, welches die wichtigsten Systemkomponenten in einer angemessenen Komplexität umfasst und die von den Akteuren gemeinsam getragene Einschätzung der Wirkungsbeziehungen darstellt. Insgesamt wurden 16 Modelle entwickelt. Basierend auf den simulierten Akteurshandlungen wurden relativen Veränderungen der Schlüsselfaktoren Produktion, Import und Leistungsfähigkeit der Kläranlagen für die vier genannten Szenarien berechnet. In Zusammenarbeit mit Pieter Bots konnten algorithmische Beiträge zur Analyse- und Modellierungssoftware DANA getestet und verbessert werden. Da keine vollständige und zugleich leicht verständliche Einführung zu DANA vorlag, wurde für Nutzer im Rahmen dieser Dissertation eine Anleitung verfasst, die die Modellierung von Wahrnehmungsgraphen und deren Analyse sowie alle Schritte der akteursbasierten Modellierung mit DANA erläutert.