A5044742757- Hydrology and Watershed Management Studies
- Water resources management and optimization
- Transboundary Water Resource Management
- Geophysics and Gravity Measurements
- Hydrology and Drought Analysis
- Water-Energy-Food Nexus Studies
- Hydrological Forecasting Using AI
- Climate variability and models
- Oceanographic and Atmospheric Processes
- Groundwater and Isotope Geochemistry
- Methane Hydrates and Related Phenomena
- Flood Risk Assessment and Management
- Climate change impacts on agriculture
- Complex Systems and Time Series Analysis
- Reservoir Engineering and Simulation Methods
- Hydrology and Sediment Transport Processes
- Computational Physics and Python Applications
- Groundwater flow and contamination studies
- Geomagnetism and Paleomagnetism Studies
- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Environmental Monitoring and Data Management
Goethe University Frankfurt
2020-2023
Wageningen University & Research
2016
International Institute for Applied Systems Analysis
2016
Abstract. WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well flows storage thus resources on all land areas the Earth. Since 1996, it has served to assess stress both historically in future, particular under climate change. It improved our understanding continental variations, with focus overexploitation depletion resources. In this paper, we describe most recent version 2.2d, including models, linking computes net abstractions from...
Abstract. WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well flows storage thus resources on all land areas the Earth. Since 1996, it has served to assess stress both historically in future, particular under climate change. It improved our understanding continental variations, with focus overexploitation depletion resources. In this paper, we describe most recent version 2.2d, including models, linking computes net abstractions from...
Abstract. Global hydrological models enhance our understanding of the Earth system and support sustainable management water, food energy in a globalized world. They integrate process knowledge with multitude model input data (e.g., precipitation, soil properties, location extent surface waterbodies) to describe state Earth. However, they do not fully utilize observations output variables streamflow water storage) reduce quantify uncertainty through processes like parameter estimation. For...
Increases in water demand often result unsustainable use, leaving insufficient amounts of for the environment. Therefore, water-saving strategies have been introduced to environmental policy agenda many (semi)-arid regions. As such interventions failed reach their objectives, a comprehensive tool is needed assess them. We constructive framework proposed by estimating five key components balance an area: (1) Demand; (2) Availability; (3) Withdrawal; (4) Depletion and (5) Outflow. The was...
Abstract. Global hydrological models enhance our understanding of the Earth system and support sustainable management water, food energy in a globalized world. They integrate process knowledge with multitude model input data (e.g., precipitation, land cover soil properties location extent surface water bodies) that describe state Earth. However, they do not fully utilize observations output variables streamflow storage) to decrease uncertainty by, e.g., parameter estimation. For pilot region...
<p>Freshwater availability is of vital importance for humans, freshwater biota and ecosystem functions. In the past decades, global hydrological models (GHMs) were developed to improve understanding situation in a globalized word, by filling gaps observational coverage assessing scenarios future under consideration different socioeconomic developments climate change. The Water Global Assessment Prognosis (WaterGAP) model was one first GHMs evaluate resources their use both...
To assure the success of water projects, providing accurate rainfall data has great importance. Recognition all processes that create surface is first step in projects. Principle this understanding based on information from climate and precipitation characteristics. So, necessity projects regional programming undeniable. Collection stations a region or basin called network. An efficient network which provides us with trustable due to proper raingauges density. an acceptable estimation needed...
<p><span>Global hydrological models simulate water storages and fluxes of the cycle, </span><span>motivated to assess problems such as scarcity, high flows more generally impact anthropogenic change on global system. </span><span>However, include many uncertainties due model inputs (e.g. climate forcing data), parameters, structure </span><span>which can lead</span>...
<p>Several applications, from water resource management to the prediction of extreme events, require a realistic representation global cycle. Global hydrological models simulate continental fluxes and individual storages. However, they poorly reproduce observations discharge total storage anomalies (TWSA). To improve realism simulations, TWSA derived Gravity Recovery Climate Experiment (GRACE) mission are usually assimilated into models.<br>However, while...
<p>The predictive ability of a hydrological model depends among others on how well the is calibrated by parameter adjustment. When calibrating spatially distributed models such as global in which river basins are represented laterally connected grid cells mostly 0.5° latitude longitude, it not appropriate and possible to adjust parameters each cell individually. This mainly due lack high-resolution observations but also required computational effort. It needs be...
<p>In this research we evaluated the WaterGAP Global Hydrological Model (WGHM) parameter uncertainties and predictive intervals for multi-type variables, including streamflow, total water storage anomaly (TWSA) snow cover based on Generalized Likelihood Uncertainty Estimation (GLUE) method, a large river basin in North America, Mississippi basin. The GLUE approach is built Monte Carlo concept, which simulations are performed all sets. sets sampled from prior range of parameters...