Publications
44 results found
Fatichi S, Ivanov VY, Paschalis A, et al., 2016, Uncertainty partition challenges the predictability of vital details of climate change, EARTHS FUTURE, Vol: 4, Pages: 240-251, ISSN: 2328-4277
Paschalis A, Katul GG, Fatichi S, et al., 2016, Matching ecohydrological processes and scales of banded vegetation patterns in semiarid catchments, WATER RESOURCES RESEARCH, Vol: 52, Pages: 2259-2278, ISSN: 0043-1397
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- Citations: 17
Ghannam K, Nakai T, Paschalis A, et al., 2016, Persistence and memory timescales in root-zone soil moisture dynamics, WATER RESOURCES RESEARCH, Vol: 52, Pages: 1427-1445, ISSN: 0043-1397
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- Citations: 54
Paschalis A, Fatichi S, Katul GG, et al., 2015, Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes, JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES, Vol: 120, Pages: 1716-1740, ISSN: 2169-8953
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- Citations: 36
Fatichi S, Katul GG, Ivanov VY, et al., 2015, Abiotic and biotic controls of soil moisture spatiotemporal variability and the occurrence of hysteresis, WATER RESOURCES RESEARCH, Vol: 51, Pages: 3505-3524, ISSN: 0043-1397
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- Citations: 49
Kianfar B, Fatichi S, Paschalis A, et al., 2015, Does climate change have an impact on Swiss urban drainage infrastructures?
Precipitation extremes are particularly relevant when analyzing rainfall/runoff processes in urban drainage systems, and in the light of a changing climate various attempts are being made to predict future extremes based on climate modelling. However, results remain highly uncertain so far. In this study we aim to quantify the potential impact of climate change on rainfall extremes considering inherent natural precipitation variability. Ultimately, this information can be integrated in early design adaption strategies for drainage networks in order to minimize adverse socio-economic impact of urban flooding.
Fatichi S, Ivanov VY, Paschalis A, et al., 2015, Partitioning sources of uncertainty in local climate change projections
Impact studies and practical applications demand for climate change predictions of meteorological forcing at local spatial scales and fine temporal resolutions. Concurrently, climate models are typically more reliable at the global and regional scales, but they may have significant biases at the scales of "human action", e.g., few square kilometres and sub-daily scale. Therefore, there is a demand for advanced techniques that offer the capability of transferring predictions of climate models and relative uncertainty to scales commensurate with practical applications and for higher order statistics.
Paschalis A, Fatichi S, Katul GG, et al., 2015, On the effects of temporal meteorological variability on ecosystem water and carbon fluxes across scales: A modeling approach
Climate varies across a wide range of temporal and spatial scales and this variability affects and is affected by ecosystem responses. There is strong evidence from observations and climate model projections that due to anthropogenic influences, climate variability is expected to be significantly altered (e.g. scarcer and stronger rainfall events in arid places etc.). This will have an impact on the water and carbon cycles and thus on food production and security, timber production, flood management, irrigation practices etc.
Peleg N, Blumensaat F, Fatichi S, et al., 2015, High-resolution stochastic generation of rainfall for urban drainage model applications
The STREAP (Space-Time Realizations of Areal Precipitation) is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the rainfall spatio-temporal structure and statistical characteristics (Paschalis et al., 2014; Paschalis et al., 2013). It enables a generation of rain fields at sub-kilometer and minute scale in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. High-resolution rainfall ensembles are generated stochastically to simulate (1) the current climate conditions and (2) projected future climates based on different scenarios derived from various global climate models. The STREAP model has a potential of serving as a useful tool for testing the existing urban drainage systems and for future planning.
Paschalis A, Fatichi S, Molnar P, et al., 2014, On the effects of small scale space-time variability of rainfall on basin flood response, JOURNAL OF HYDROLOGY, Vol: 514, Pages: 313-327, ISSN: 0022-1694
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- Citations: 107
Paschalis A, Molnar P, Fatichi S, et al., 2014, On temporal stochastic modeling of precipitation, nesting models across scales, ADVANCES IN WATER RESOURCES, Vol: 63, Pages: 152-166, ISSN: 0309-1708
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- Citations: 42
Paschalis A, Molnar P, Fatichi S, et al., 2013, A stochastic model for high-resolution space-time precipitation simulation, WATER RESOURCES RESEARCH, Vol: 49, Pages: 8400-8417, ISSN: 0043-1397
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- Citations: 101
Paschalis A, Molnar P, Burlando P, 2012, Temporal dependence structure in weights in a multiplicative cascade model for precipitation, WATER RESOURCES RESEARCH, Vol: 48, ISSN: 0043-1397
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- Citations: 17
Koutsoyiannis D, Paschalis A, Theodoratos N, 2011, Two-dimensional Hurst-Kolmogorov process and its application to rainfall fields, JOURNAL OF HYDROLOGY, Vol: 398, Pages: 91-100, ISSN: 0022-1694
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- Citations: 16
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