Frankfurt Hydrology Paper
https://www.uni-frankfurt.de/53949648/FHG
Refine
Year of publication
Document Type
- Working Paper (12)
- Doctoral Thesis (7)
Has Fulltext
- yes (19)
Is part of the Bibliography
- no (19)
Keywords
- Bewässerung (4)
- Modellierung (3)
- hydrology (3)
- Grundwasser (2)
- Landwirtschaft (2)
- MIRCA2000 (2)
- climate change (2)
- global modeling (2)
- Ackerbau (1)
- Anbauflächen (1)
Institute
- Geowissenschaften (12)
- Geographie (5)
- Geowissenschaften / Geographie (2)
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.
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.
17
Floodplains and other wetlands depend on seasonal river flooding and play an important role in the terrestrial water cycle. They influence evapotranspiration, water storage and river discharge dynamics, and they are the habitat of a large number of animals and plants. Thus, to assess the Earth’s system and its changes, a robust understanding of the dynamics of floodplain wetlands including inundated areas, water storages, and water flows is required.
This PhD thesis aims at improving the modeling of large floodplains and wetlands within the global-scale hydrological model WaterGAP, in order to better estimate water flows and water storage variations in different storage compartments. Within the scope of this thesis, I have developed a new approach to simulate dynamic floodplain inundation on a global-scale. This approach introduces an algorithm into WaterGAP, which has a spatial resolution of 0.5 degree (longitude and latitude) globally. The new approach uses subgrid-scale topography, based on high-resolution digital elevation models, to describe the floodplain elevation profile within each grid cell by applying a hypsographic curve. The approach comprises the modeling of a two-way river-floodplain interaction, the separate downstream water transport within the river and the floodplain – both with temporally and spatially different variable flow velocities – and the floodplain-groundwater interactions. The WaterGAP version that includes the floodplain algorithm, WaterGAP 2.2b_fpl, estimates floodplain and river water storage, inundated area and water table elevation, and also simulates backwater effects.
WaterGAP 2.2b_fpl was applied to model river discharge, river flow velocity, water storages, water heights and surface water extent on a global-scale. Model results were comprehensively validated against ground observations and remote sensing data. Overall, the modeled and observed data are in agreement. In comparison to the former version WaterGAP 2.2b, the model performance has improved significantly. The improvements are most remarkable in the Amazon River basin. However, the seasonal variation of surface water extent and total water storage anomalies are still too low in many regions on the globe when compared to observations. A detailed analysis of the simulated results suggests that in the Amazon River basin the introduction of backwater effects is important for realistically simulating water storages and surface water extent. Future efforts should focus on the simulation of water levels in order to better model the flow routing according to water slope. To further improve the model performance in specific regions, I recommend that the globally constant model parameters that affect inundation initiation, river-floodplain interaction, DEM correction for vegetation, and backwater amount at basin or subbasin-scale be adjusted.
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.
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.
14
Within the framework of the Transboundary Waters Assessment Programme (TWAP), initiated by the Global Environment Facility (GEF), we contributed to a comprehensive baseline assessment of transboundary aquifers (TBAs) by quantifying different groundwater indicators using the global water resources and water use model WaterGAP 2.2. All indicators were computed under current (2010) and projected conditions in 2030 and 2050 for 91 selected TBAs larger than 20,000 km2 and for each nation’s share of the TBAs (TBA-CU: country unit). TBA outlines were provided by the International Groundwater Resources Assessment Centre (IGRAC). The set of indicators comprises groundwater recharge, groundwater depletion, per-capita groundwater recharge, dependency on groundwater, population density, and groundwater development stress (groundwater withdrawals to groundwater recharge). Only the latter four indicators were projected to 2030 and 2050. Current-state indicators were quantified using the Watch Forcing Data climate dataset, while projections were based on five climate scenarios that were computed by five global climate models for the high-emissions scenario RCP 8.5. Water use projections were based on the Shared Socio-economic Pathway SSP2 developed within ISI-MIP. Furthermore, two scenarios of future irrigated areas were explored. For individual water use sectors, the fraction of groundwater abstraction was assumed to remain at the current level.
According to our assessment, aquifers with the highest current groundwater depletion rates worldwide are not transboundary. Exceptions are the Neogene Aquifer System (Syria) with 53 mm/yr between 2000 and 2009 and the Indus River Plain aquifer (India) with 28 mm/yr. For current conditions, we identified 20 out of 258 TBA-CUs suffering from medium to very high groundwater development stress, which are located in the Middle East and North Africa region, in South Asia, China, and the USA. Considering projections, ensemble means of per-cent changes or percent point changes to current conditions were determined. Per-capita groundwater recharge is projected to decrease in 80-90% of all TBA-CUs until 2030/2050. Due to the strongly varying projections of the global climate models, we applied a worst-case scenario approach to define future hotspots of groundwater development stress, taking into account the strongest computed increase until either 2030 or 2050 among all scenarios and individual GCMs. Based on this approach, the number of TBA-CUs under at least medium groundwater development stress increases from 20 to 58, comprising all hotspots under current conditions. New hotspots are projected to develop mainly in Sub-Saharan Africa, China, and Mexico.
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.
18
The Global Irrigation Model (GIM) is used within the framework of the global hydrological model WaterGAP to calculate monthly irrigation crop water use. Results on a 0.5 degrees grid include, consumption (ICU) and, via division by irrigation efficiencies, water withdrawal (IWU). The model distinguishes up to two cropping periods of rice and non-rice crops, each grown for 150 days, using a grid of area equipped for irrigation (AEI). Historical development of AEI and fraction of area actually irrigated (AAI) was previously considered via scaling of cell-specific results with country-specific factors for each year. In this study, GIM was adapted to use the new Historical Irrigation Data set (HID) with cell-specific AEI for 14 time slices between 1900 and 2005. AEI grids were temporally interpolated, and using the optional grid of AAI/AEI, results for years 1901-2014 were generated (runs "HID-ACT"). Thus, new installation or abandonment of irrigation infrastructure in new grid cells can be represented in a spatially explicit manner. For evaluated years 1910, 1960, 1995, and 2005, ICU from HID-ACT was superior to country-specific scaled results (run "HID-ACTHIST") in representing historical development of the spatial pattern. Compared to US state-level reference data, spatial patterns were better, while country totals were not always better. For calculating the cropping periods, 30-years climate means are needed, the choice of which is relevant. Four chosen periods before 1981-2010 all resulted in considerable, pertaining changes of ICU spatial pattern, and various percent changes in country totals. This might be because of already present climate change.
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).
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.