Value of river discharge data for global-scale hydrological modeling

his paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are required for assessing water resources, flood risk and habitat alteration of aqueous ecosystems. An improved version of WGHM (WaterGAP Global Hydrology Model) was tuned in a way that simulated and observed long-term average river discharges at each station become equal, using either the 724-station dataset (V1) against which former model versions were tuned or a new dataset (V2) of 1235 stations and often longer time series. WGHM is tuned by adjusting one model parameter (γ) that affects runoff generation from land areas, and, where necessary, by applying one or two correction factors, which correct the total runoff in a sub-basin (areal correction factor) or the discharge at the station (station correction factor). The study results are as follows. (1) Comparing V2 to V1, the global land area covered by tuning basins increases by 5%, while the area where the model can be tuned by only adjusting γ increases by 8% (546 vs. 384 stations). However, the area where a station correction factor (and not only an areal correction factor) has to be applied more than doubles (389 vs. 93 basins), which is a strong drawback as use of a station correction factor makes discharge discontinuous at the gauge and inconsistent with runoff in the basin. (2) The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus renewable water resources) with WGHM is high, particularly for river basins outside of the V1 tuning area and for basins where the average sub-basin area has decreased by at least 50% in V2 as compared to V1. For these basins, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 and 1.3, respectively, if the additional discharge information were not used for tuning. The value tends to be higher in semi-arid and snow-dominated regions where hydrological models are less reliable than in humid areas. The deviation of the other simulated flow characteristics (e.g. low flow, inter-annual variability and seasonality) from the observed values also decreases significantly, but this is mainly due to the better representation of average discharge but not of variability. (3) The optimal sub-basin size for tuning depends on the modeling purpose. On the one hand, small basins between 9000 and 20 000 km2 show a much stronger improvement in model performance due to tuning than the larger basins, which is related to the lower model performance (with and without tuning), with basins over 60 000 km2 performing best. On the other hand, tuning of small basins decreases model consistency, as almost half of them require a station correction factor

Assessment of ecologically relevant hydrological change in China due to water use and reservoirs

As China’s economy booms, increasing water use has significantly affected hydro-geomorphic processes and thus the ecology of surface waters. A large variety of hydrological changes arising from human activities such as reservoir construction and management, water abstraction, water diversion and agricultural land expansion have been sustained throughout China. Using the global scale hydrological and water use model WaterGAP, natural and anthropogenically altered flow conditions are calculated, taking into account flow alterations due to human water consumption and 580 large reservoirs. The impacts resulting from water consumption and reservoirs have been analyzed separately. A modified “Indicators of Hydrologic Alteration” approach is used to describe the human pressures on aquatic ecosystems due to anthropogenic alterations in river flow regimes. The changes in long-term average river discharge, average monthly mean discharge and coefficients of variation of monthly river discharges under natural and impacted conditions are compared and analyzed. The indicators show very significant alterations of natural river flow regimes in a large part of northern China and only minor alterations in most of southern China. The detected large alterations in long-term average river discharge, the seasonality of flows and the inter-annual variability in the northern half of China are very likely to have caused significant ecological impacts

The Global Crop Water Model (GCWM) : documentation and first results for irrigated crops

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

Impact of climate change on freshwater ecosystems: a global-scale analysis of ecologically relevant river flow alterations

River flow regimes, including long-term average flows, seasonality, low flows, high flows and other types of flow variability, play an important role for freshwater ecosystems. Thus, climate change affects freshwater ecosystems not only by increased temperatures but also by altered river flow regimes. However, with one exception, transferable quantitative relations between flow alterations and ecosystem responses have not yet been derived. While discharge decreases are generally considered to be detrimental for ecosystems, the effect of future discharge increases is unclear. As a first step towards a global-scale analysis of climate change impacts on freshwater ecosystems, we quantified the impact of climate change on five ecologically relevant river flow indicators, using the global water model WaterGAP 2.1g to simulate monthly time series of river discharge with a spatial resolution of 0.5 degrees. Four climate change scenarios based on two global climate modelsand two greenhouse gas emissions scenarios were evaluated. We compared the impact of climate change by the 2050s to the impact of water withdrawals and dams on natural flow regimes that had occurred by 2002. Climate change was computed to alter seasonal flow regimes significantly (i.e. by more than 10%) on 90% of the global land area (excluding Greenland and Antarctica), as compared to only one quarter of the land area that had suffered from significant seasonal flow regime alterations due to dams and water withdrawals. Due to climate change, the timing of the maximum mean monthly river discharge will be shifted by at least one month on one third on the global land area, more often towards earlier months (mainly due to earlier snowmelt). Dams and withdrawals had caused comparable shifts on less than 5% of the land area only. Long-term average annual river discharge is predicted to significantly increase on one half of the land area, and to significantly decrease on one quarter. Dams and withdrawals had led to significant decreases on one sixth of the land area, and nowhere to increases. Thus, by the 2050s, climate change will have impacted ecologically relevant river flow characteristics much more strongly than dams and water withdrawals have up to now. The only exception refers to the decrease of the statistical low flow Q90, with significant decreases both by past water withdrawals and future climate change on one quarter of the land area. Considering long-term average river discharge, only a few regions, including Spain, Italy, Iraq, Southern India, Western China, the Australian Murray Darling Basin and the High Plains Aquifer in the USA, all of them with extensive irrigation, are expected to be less affected by climate change than by past anthropogenic flow alterations. In some of these regions, climate change will exacerbate the discharge reduction. Emissions scenario B2 leads to only slightly reduced alterations of river flow regimes as compared to scenario A2 even though emissions are much smaller. The differences in alterations resulting from the two applied climate models are larger than those resulting from the two emissions scenarios. Based on general knowledge about ecosystem responses to flow alterations and data related to flow alterations by dams and water withdrawals, we expect that the computed climate change induced river flow alterations will impact freshwater ecosystems more strongly than past anthropogenic alterations

Global-scale estimation of diffuse groundwater recharge : model tuning to local data for semi-arid and arid regions and assessment of climate change impact

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.Die Höhe der Grundwasserneubildung ist oft limitierend für die nachhaltige Nutzung von Grundwasserressourcen. Um das Wassermanagement in der globalisierten Welt zu unterstützen ist es notwendig, die Grundwasserneubildung räumlich differenziert abzuschätzen. In diesem Forschungsbericht werden Modellierungsergebnisse der Grundwasserneubildung in einer räumlichen Auflösung von 0.5° x 0.5° auf globaler Skala vorgestellt. Die Ergebnisse basieren auf Berechnungen des globalen hydrologischen Modells WGHM (WaterGAP Global Hydrology Model), dessen Ergebnisse für semi-aride und aride Gebiete durch Anpassung an unabhängige Punktmessungen verbessert wurden. Diese Anpassung führte zu einer Verringerung der Grundwasserneubildung. Die Unterschiede der Modellergebnisse zu Schätzungen der Grundwasserneubildung auf dem Länderniveau haben sich durch diesen Ansatz verringert. Mittels des verbesserten Modells wurde der Einfluss des Klimawandels auf die Grundwasserneubildung bei Verwendung von zwei unterschiedlichen Treibhausgasszenarien und zwei unterschiedlichen Klimaszenarien quantifiziert

Integrated Scenarios of Regional Development in Two Semi-Arid States of North-Eastern Brazil

Scenario analysis of the future is an important tool for supporting sustainability-oriented regional planning. To assist regional planning in two federal states in semi-arid North-eastern Brazil, Ceará and Piauí, we developed integrated qualitative¿quantitative scenarios that show potential developments of the agricultural and water resources situation as well as the internal migration until the year 2025. In these states, regional development is negatively influenced by the high seasonality of rainfall and El-Niño-related drought years. Two reference scenarios, 'Coastal Boom and Cash Crops' and 'Decentralisation - Integrated Rural Development' were developed. First, story lines were created and the development of the driving forces was quantified. Then, an integrated model, which includes modules for simulating water availability, water demand, and agricultural production and income, was applied to compute the temporal development of relevant system indicators in each of the 332 municipalities of Ceará and Piauí. These indicators encompass the fraction of the irrigation water demand than can be satisfied, the volume of water which is stored in the reservoirs at the beginning of the dry season, agricultural productivity and production as well as the internal migration among scenario regions. In addition, the impact of certain policy measures was assessed in the context of both reference scenarios. Reference and intervention scenarios were derived by an interdisciplinary group of scientists and were discussed and refined during policy workshops with planning agencies of Ceará

Simulating river flow velocity on global scale

Flow velocity in rivers has a major impact on residence time of water and thus on high and low water as well as on water quality. For global scale hydrological modeling only very limited information is available for simulating flow velocity. Based on the Manning-Strickler equation, a simple algorithm to model temporally and spatially variable flow velocity was developed with the objective of improving flow routing in the global hydrological model of Water- GAP. An extensive data set of flow velocity measurements in US rivers was used to test and to validate the algorithm before integrating it into WaterGAP. In this test, flow velocity was calculated based on measured discharge and compared to measured velocity. Results show that flow velocity can be modeled satisfactorily at selected river cross sections. It turned out that it is quite sensitive to river roughness, and the results can be optimized by tuning this parameter. After the validation of the approach, the tested flow velocity algorithm has been implemented into the WaterGAP model. A final validation of its effects on the model results is currently performed

A digital global map of artificially drained agricultural areas : documentation

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.Landwirtschaftliche Drainagen, z.B. durch Gräben oder unterirdische Dränrohre, werden angewandt um hohe Grundwasserstände zu kontrollieren und damit einhergehende Vernässung und Versalzung des Bodens zu vermeiden. Neben anderen Faktoren beeinflussen Drainagen die Nährstoffbilanz durch Erhöhung der Stickstoffauswaschung sowie Veringerung von Denitrifikation. Um den terrestrischen Stickstofftransport simulieren zu können, wurde ein globaler Datensatz der landwirtschaftlichen Dränageflächen in einer Auflösung von 5' x 5' erstellt. Die Karte zeigt den Anteil der Zellflächen mit künstlicher Drainage. Daten zu Drainageflächen in Ländern sowie subnationalen Einheiten wurden mit globalen Datensätzen zur Verteilung der landwirtschaftlichen Flächen (Ramankutty et al., 1998) sowie zur Verteilung bewässerter Flächen (Siebert et al., 2005) kombiniert. Für 11 Länder konnten subnationale Statistiken zur Dränagefläche verwendet werden. Karten mit Umrissen der Dränageflächen standen für sechs Länder zur Verfügung. Insgesamt wurden global 167 Mio ha Fläche als landwirtschaftliche Dränageflächen ausgewiesen. Auf Grund der geringen Auflösung der Eingangsdaten wird die Verwendung des Datensatzes nur für globale oder kontinentale Studien empfohlen. Dieser Bericht beschreibt den Datensatz selbst, die Methodik zur Erzeugung des Datensatzes sowie die Informationsquellen und diskutiert die Unsicherheit

Global patterns of cropland use intensity

This study presents a global scale analysis of cropping intensity, crop duration and fallow land extent computed by using the global dataset on monthly irrigated and rainfed crop areas MIRCA2000. MIRCA2000 was mainly derived from census data and crop calendars from literature. Global cropland extent was 16 million km2 around the year 2000 of which 4.4 million km2 (28%) was fallow, resulting in an average cropping intensity of 0.82 for total cropland extent and of 1.13 when excluding fallow land. The lowest cropping intensities related to total cropland extent were found for Southern Africa (0.45), Central America (0.49) and Middle Africa (0.54), while highest cropping intensities were computed for Eastern Asia (1.04) and Southern Asia (1.0). In remote or arid regions where shifting cultivation is practiced, fallow periods last 3–10 years or even longer. In contrast, crops are harvested two or more times per year in highly populated, often irrigated tropical or subtropical lowlands where multi-cropping systems are common. This indicates that intensification of agricultural land use is a strategy that may be able to significantly improve global food security. There exist large uncertainties regarding extent of cropland, harvested crop area and therefore cropping intensity at larger scales. Satellite imagery and remote sensing techniques provide opportunities for decreasing these uncertainties and to improve the MIRCA2000 inventory