Frankfurt Hydrology Paper
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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.
19
Groundwater is the largest source of accessible freshwater with its dynamics having significantly changed due to human withdrawals, and being projected to continue to as a result of climate change. The pumping of groundwater has led to lowered water tables, decreased base flow, and depletion.
Global hydrological models (GHMs) are used to simulate the global freshwater cycle, assessing impacts of changes in climate and human freshwater use. Currently, groundwater is commonly represented by a bucket-like linear storage component in these models. Bucket models, however, cannot provide information on the location of the groundwater table. Due to this limitation, they can only simulate groundwater discharge to surface water bodies but not recharge from surface water to groundwater and calculate no lateral and vertical groundwater flow whatsoever among grid cells. For instance this may lead to an underestimation of groundwater resources in semiarid areas, where groundwater is often replenished by surface water. In order to overcome these limitations it is necessary to replace the linear groundwater model in GHMs with a hydraulic head gradient-based groundwater flow model
This thesis presents the newly developed global groundwater model G3M and its coupling to the GHM WaterGAP spanning over 70,000 lines of newly developed code. Development and validation of the modeling software are discussed along with numerical challenges. Based on the newly developed software, a global natural equilibrium groundwater model is presented showing better agreements with observations than previous models. Groundwater discharge to rivers is found to be the most dominant flow component globally, compared to flows to other surface water bodies and lateral flows. Furthermore, first global maps of the distribution of gaining and losing surface water bodies are displayed.
For the purpose of determining the uncertainty in model outcomes a sensitivity study is conducted with an innovative approach through applying a global sensitivity analysis for a computationally complex model. First global maps of spatially distributed parameter sensitivities are presented. The results at hand indicate that globally simulated hydraulic heads are equally sensitive to hydraulic conductivity, groundwater recharge and surface water body elevation, even though parameter sensitivities do vary regionally.
A high resolution model of New Zealand is developed to further understand the involved uncertainties connected to the spatial resolution of the global model. This thesis finds that a new understanding is necessary how these models can be evaluated and that a simple increase in spatial resolution is not improving the model performance when compared to observations.
Alongside the assessment of the natural equilibrium, the concept of a fully coupled transient model as integrated storage component replacing the former model in the hydrological model WaterGAP is discussed. First results reveal that the model shows reasonable response to seasonal variability although it contains persistent head trends leading to global overestimates of water table depth due to an incomplete coupling. Nonetheless, WaterGAP-G3M is already able to show plausible long term storage trends for areas that are known to be affected by groundwater depletion. In comparison with two established regional models in the Central Valley the coupled model shows a highly promising simulation of storage declines.
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.
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).
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.
16
The estimation of water balance components as well as water-related indicators on the land surface by means of global hydrological models have evolved in recent decades. Results of such models are frequently used in global- and continental-scale assessments of the current and future state of the terrestrial water cycle and provide a valuable data basis, e.g., for the Intergovernmental Panel on Climate Change. The Water – Global Assessment and Prognosis (WaterGAP) model is one of the state-of-the-art models in that field and has been in development and application for around 20 years. The evaluation, modification and application of WaterGAP is the subject of this thesis. In particular, the sensitivity of climate input data on radiation calculation and simulated water fluxes and storages is evaluated in the first part. Effects of model modification such as updated spatial input datasets, improved process representation or an alternative calibration scheme are the focus of the second part. Finally, three applications of WaterGAP give insight into the capabilities of that model, namely an estimate of global and continental water balance components, an assessment of groundwater depletion and the impact of climate change on river flow regimes. Model experiments, which are described in six journal papers as well as the appendices, were used as the basis for answering the total of 13 research questions. One of the major foci was to quantify the sensitivity of simulated water fluxes and storages to alternative climate input data. It was found that the handling of precipitation undercatch leads to the greatest difference in water balance components, especially in those areas where WaterGAP is not calibrated due to a lack of river discharge observations. The modifications of WaterGAP in the last few decades has led in general to an improved simulation of monthly river discharge, but process representation in semi-arid and arid regions still requires improvements. With the most current model version, WaterGAP 2.2b, and for the time period 1971–2000, river discharge to the oceans and inland sinks is estimated to be 40 000 km3 yr-1, whereas actual evapotranspiration is simulated as 70 500 km3 yr-1. Future research needs for WaterGAP in particular but also for the global hydrological model community in general are defined, promoting a community-driven effort for a robust assessment of the continental water cycle.
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.
11
Bayesian Networks are computer-based environmental models that are frequently used to support decision-making under uncertainty. Under data scarce conditions, Bayesian Networks can be developed, parameterized, and run based on expert knowledge only. However, the efficiency of expert-based Bayesian Network modeling is limited by the difficulty in deriving model inputs in the time available during expert workshops. This thesis therefore aimed at developing a simple and robust method for deriving conditional probability tables from expert estimates in a time-efficient way. The design and application of this new elicitation and conversion method is demonstrated using a case study in Xinjiang, Northwest China. The key characteristics of this method are its time-efficiency and the approach to use different conversion tables based on varying levels of confidence. Although the method has its limitations, e.g. it can only be applied for variables with one conditioning variable; it provides the opportunity to support the parameterization of Bayesian Networks which would otherwise remain half-finished due to time constraints. In addition, a case study in the Murray-Darling Basin, Australia, is used to compare Bayesian Network types and software to improve the presentation clarity of large Bayesian Networks. Both case studies aimed at gaining insights on how to improve the applicability of Bayesian Networks to support environmental management.
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.
13
Transforming the current rather centralized electricity generating system into a climate neutral system based on renewable energy is an important approach to reduce greenhouse gas emissions and thus mitigate climate change. Stakeholders have each of them their own perception of the best strategies to achieve such a transformation. All perspectives are equally legitimate and needed for developing a specific transformation strategy suited for the region in focus....