Future Water

Wageningen, Netherlands

Future Water

Wageningen, Netherlands
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Hunink J.E.,Future Water | Eekhout J.P.C.,CSIC - Center of Edafology and Applied Biology of the Segura | de Vente J.,CSIC - Center of Edafology and Applied Biology of the Segura | Contreras S.,Future Water | And 2 more authors.
Remote Sensing | Year: 2017

The parameterization of crop coefficients (kc) is critical for determining a water balance. We used satellite-based and literature-based methods to derive kc values for a distributed hydrologic model. We evaluated the impact of different kc parametrization methods on the water balance and simulated hydrologic response at the basin and sub-basin scale. The hydrological model SPHY was calibrated and validated for a period of 15 years for the upper Segura basin (~2500 km2) in Spain, which is characterized by a wide range of terrain, soil, and ecosystem conditions. The model was then applied, using six kc parameterization methods, to determine their spatial and temporal impacts on actual evapotranspiration, streamflow, and soil moisture. The parameterization methods used include: (i) Normalized Difference Vegetation Index (NDVI) observations from MODIS; (ii) seasonally-averaged NDVI patterns, cell-based and landuse-based; and (iii) literature-based tabular values per land use type. The analysis shows that the influence of different kc parametrization methods on basin-level streamflow is relatively small and constant throughout the year, but it has a bigger effect on seasonal evapotranspiration and soil moisture. In the autumn especially, deviations can go up to about 15% of monthly streamflow. At smaller, sub-basin scale, deviations from the NDVI-based reference run can be more than 30%. Overall, the study shows that modeling of future hydrological changes can be improved by using remote sensing information for the parameterization of crop coefficients. © 2017 by the authors.


Van Leuken J.P.G.,National Institute for Public Health and the Environment RIVM | Van Leuken J.P.G.,University Utrecht | Swart A.N.,National Institute for Public Health and the Environment RIVM | Brandsma J.,Future Water | And 8 more authors.
One Health | Year: 2016

Airborne pathogenic transmission from sources to humans is characterised by atmospheric dispersion and influence of environmental conditions on deposition and reaerosolisation. We applied a One Health approach using human, veterinary and environmental data regarding the 2009 epidemic in The Netherlands, and investigated whether observed human Q fever incidence rates were correlated to environmental risk factors.We identified 158 putative sources (dairy goat and sheep farms) and included 2339 human cases. We performed a high-resolution (1 × 1 km) zero-inflated regression analysis to predict incidence rates by Coxiella burnetii concentration (using an atmospheric dispersion model and meteorological data), and environmental factors - including vegetation density, soil moisture, soil erosion sensitivity, and land use data - at a yearly and monthly time-resolution.With respect to the annual data, airborne concentration was the most important predictor variable (positively correlated to incidence rate), followed by vegetation density (negatively). The other variables were also important, but to a less extent. High erosion sensitive soils and the land-use fractions "city" and "forest" were positively correlated. Soil moisture and land-use "open nature" were negatively associated. The geographical prediction map identified the largest Q fever outbreak areas. The hazard map identified highest hazards in a livestock dense area. We conclude that environmental conditions are correlated to human Q fever incidence rate. Similar research with data from other outbreaks would be needed to more firmly establish our findings. This could lead to better estimations of the public health risk of a C. burnetii outbreak, and to more detailed and accurate hazard maps that could be used for spatial planning of livestock operations. © 2016 The Authors.


van Leuken J.P.G.,National Institute for Public Health and the Environment RIVM | van Leuken J.P.G.,University Utrecht | Swart A.N.,National Institute for Public Health and the Environment RIVM | Droogers P.,Future Water | And 5 more authors.
Aerobiologia | Year: 2016

The most recent IPCC report presented further scientific evidence for global climate change in the twenty-first century. Important secondary effects of climate change include those on water resource availability, agricultural yields, urban healthy living, biodiversity, ecosystems, food security, and public health. The aim of this explorative study was to determine the range of expected airborne pathogen concentrations during a single outbreak or release in a future climate compared to a historical climatic period (1981–2010). We used five climate scenarios for the periods 2016–2045 and 2036–2065 defined by the Royal Netherlands Meteorological Institute and two conversion tools to create hourly future meteorological data sets. We modelled season-averaged airborne pathogen concentrations by means of an atmospheric dispersion model and compared these data to historical (1981–2010) modelled concentrations. Our results showed that modelled concentrations were modified several percentage points on average as a result of climate change. On average, concentrations were reduced in four out of five scenarios. Wind speed and global radiation were of critical importance, which determine horizontal and vertical dilution. Modelled concentrations decreased on average, but large positive and negative hourly averaged effects were calculated (from −67 to +639 %). This explorative study shows that further research should include pathogen inactivation and more detailed probability functions on precipitation, snow, and large-scale circulation. © 2016 The Author(s)


PubMed | University of Florida, University Utrecht, Future Water and National Institute for Public Health and the Environment RIVM
Type: Journal Article | Journal: Aerobiologia | Year: 2016

The most recent IPCC report presented further scientific evidence for global climate change in the twenty-first century. Important secondary effects of climate change include those on water resource availability, agricultural yields, urban healthy living, biodiversity, ecosystems, food security, and public health. The aim of this explorative study was to determine the range of expected airborne pathogen concentrations during a single outbreak or release in a future climate compared to a historical climatic period (1981-2010). We used five climate scenarios for the periods 2016-2045 and 2036-2065 defined by the Royal Netherlands Meteorological Institute and two conversion tools to create hourly future meteorological data sets. We modelled season-averaged airborne pathogen concentrations by means of an atmospheric dispersion model and compared these data to historical (1981-2010) modelled concentrations. Our results showed that modelled concentrations were modified several percentage points


Cheema M.J.M.,University of Agriculture | Immerzeel W.W.,Future Water | Immerzeel W.W.,University Utrecht | Bastiaanssen W.G.M.,Technical University of Delft | Bastiaanssen W.G.M.,Competence Center
Groundwater | Year: 2014

Groundwater abstraction and depletion were assessed at a 1-km resolution in the irrigated areas of the Indus Basin using remotely sensed evapotranspiration (ET) and precipitation; a process-based hydrological model and spatial information on canal water supplies. A calibrated Soil and Water Assessment Tool (SWAT) model was used to derive total annual irrigation applied in the irrigated areas of the basin during the year 2007. The SWAT model was parameterized by station corrected precipitation data (R) from the Tropical Rainfall Monitoring Mission, land use, soil type, and outlet locations. The model was calibrated using a new approach based on spatially distributed ET fields derived from different satellite sensors. The calibration results were satisfactoryand strong improvements were obtained in the Nash-Sutcliffe criterion (0.52 to 0.93), bias (-17.3% to -0.4%), and the Pearson correlation coefficient (0.78 to 0.93). Satellite information on R and ET was then combined with model results of surface runoff, drainage, and percolation to derive groundwater abstraction and depletion at a nominal resolution of 1km. It was estimated that in 2007, 68km3 (262mm) of groundwater was abstracted in the Indus Basin while 31km3 (121mm) was depleted. The mean error was 41mm/year and 62mm/year at 50% and 70% probability of exceedance, respectively. Pakistani and Indian Punjab and Haryana were the most vulnerable areas to groundwater depletion and strong measures are required to maintain aquifer sustainability. © 2013, National Ground Water Association.


Simons G.W.H.,Technical University of Delft | Bastiaanssen W.G.M.,Technical University of Delft | Immerzeel W.W.,Future Water | Immerzeel W.W.,University Utrecht
Journal of Hydrology | Year: 2015

Unraveling the interaction between water users in a river basin is essential for sound water resources management, particularly in a context of increasing water scarcity and the need to save water. While most attention from managers and decision makers goes to allocation and withdrawals of surface water resources, reuse of non-consumed water gets only marginal attention despite the potentially significant volumes. As a consequence, claims of water saving are often grossly exaggerated. It is the purpose of this paper to explore the processes associated with water reuse in a river basin among users of varying nature and review existing methods for directly or indirectly describing non-consumed water, recoverable flow and/or water reuse. First a conceptual representation of processes surrounding water withdrawals and associated definitions is discussed, followed by a section on connectivity between individual withdrawals and the complex dynamics arising from dependencies and tradeoffs within a river basin. The current state-of-the-art in categorizing basin hydrological flows is summarized and its applicability to a water system where reuse occurs is explored. The core of the paper focuses on a selection and demonstration of existing indicators developed for assessing water reuse and its impacts. It is concluded that although several methods for analyses of water reuse and recoverable flows have been developed, a number of essential aspects of water reuse are left out of existing indicators. Moreover, a proven methodology for obtaining crucial quantitative information on recoverable flows is currently lacking. Future studies should aim at spatiotemporal tracking of the recoverable portion of water withdrawals and showing the dependency of multiple water users on such flows to water policy makers. © 2015 Elsevier B.V.


Droogers P.,Future Water | Immerzeel W.W.,Future Water | Terink W.,Future Water | Hoogeveen J.,FAO | And 3 more authors.
Hydrology and Earth System Sciences | Year: 2012

Changes in water resources availability can be expected as consequences of climate change, population growth, economic development and environmental considerations. A two-stage modeling approach is used to explore the impact of these changes in the Middle East and North Africa (MENA) region. An advanced, physically based, distributed, hydrological model is applied to determine the internal and external renewable water resources for the current situation and under future changes. Subsequently, a water allocation model is used to combine the renewable water resources with sectoral water demands. Results show that total demand in the region will increase to 393 km3 yr-1 in 2050, while total water shortage will grow to 199 km3 yr -1 in 2050 for the average climate change projection, an increase of 157 km3 yr-1. This increase in shortage is the combined impact of an increase in water demand by 50% with a decrease in water supply by 12%. Uncertainty, based on the output of the nine GCMs applied, reveals that expected water shortage ranges from 85 km3 yr-1 to 283 km3 yr-1∼in 2050. The analysis shows that 22% of the water shortage can be attributed to climate change and 78% to changes in socio-economic factors. © 2012 Author(s).

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