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Journal articles on the topic 'Stochastic hydrological forcing'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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1

Feng, Xue, Amilcare Porporato, and Ignacio Rodriguez-Iturbe. "Stochastic soil water balance under seasonal climates." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 471, no. 2174 (2015): 20140623. http://dx.doi.org/10.1098/rspa.2014.0623.

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The analysis of soil water partitioning in seasonally dry climates necessarily requires careful consideration of the periodic climatic forcing at the intra-annual timescale in addition to daily scale variabilities. Here, we introduce three new extensions to a stochastic soil moisture model which yields seasonal evolution of soil moisture and relevant hydrological fluxes. These approximations allow seasonal climatic forcings (e.g. rainfall and potential evapotranspiration) to be fully resolved, extending the analysis of soil water partitioning to account explicitly for the seasonal amplitude an

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Bertassello, L. E., E. Bertuzzo, G. Botter, et al. "Dynamic spatio-temporal patterns of metapopulation occupancy in patchy habitats." Royal Society Open Science 8, no. 1 (2021): 201309. http://dx.doi.org/10.1098/rsos.201309.

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Spatio-temporal dynamics in habitat suitability and connectivity among mosaics of heterogeneous wetlands are critical for biological diversity and species persistence in aquatic patchy landscapes. Despite the recognized importance of stochastic hydroclimatic forcing in driving wetlandscape hydrological dynamics, linking such effects to emergent dynamics of metapopulation poses significant challenges. To fill this gap, we propose here a dynamic stochastic patch occupancy model (SPOM), which links parsimonious hydrological and ecological models to simulate spatio-temporal patterns in species occ

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Peterson, T. J., and A. W. Western. "Multiple hydrological attractors under stochastic daily forcing: 1. Can multiple attractors exist?" Water Resources Research 50, no. 4 (2014): 2993–3009. http://dx.doi.org/10.1002/2012wr013003.

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Peterson, T. J., A. W. Western, and R. M. Argent. "Multiple hydrological attractors under stochastic daily forcing: 2. Can multiple attractors emerge?" Water Resources Research 50, no. 4 (2014): 3010–29. http://dx.doi.org/10.1002/2012wr013004.

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Pham, Minh Tu, Hilde Vernieuwe, Bernard De Baets, and Niko E. C. Verhoest. "A coupled stochastic rainfall–evapotranspiration model for hydrological impact analysis." Hydrology and Earth System Sciences 22, no. 2 (2018): 1263–83. http://dx.doi.org/10.5194/hess-22-1263-2018.

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Abstract. A hydrological impact analysis concerns the study of the consequences of certain scenarios on one or more variables or fluxes in the hydrological cycle. In such an exercise, discharge is often considered, as floods originating from extremely high discharges often cause damage. Investigating the impact of extreme discharges generally requires long time series of precipitation and evapotranspiration to be used to force a rainfall-runoff model. However, such kinds of data may not be available and one should resort to stochastically generated time series, even though the impact of using

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Janatian, Nasime, Kalle Olli, and Peeter Nõges. "Phytoplankton responses to meteorological and hydrological forcing at decadal to seasonal time scales." Hydrobiologia 848, no. 11 (2021): 2745–59. http://dx.doi.org/10.1007/s10750-021-04594-x.

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AbstractOne of the challenges for predicting global change effects on aquatic ecosystems is the vague understanding of the mechanisms of multiple controlling factors affecting phytoplankton dynamics at different time scales. Here we distinguish between hydrometeorological forcing of phytoplankton dynamics at time scales from days to decades based on a 54-year monthly phytoplankton time series from a large shallow Lake Võrtsjärv (58°16′N, 26°02′E) in Estonia, combined with daily data on forcing factors—thermal-, wind-, light- and water-level regimes. By using variance partitioning with linear m

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Sordo-Ward, Alvaro, Ivan Gabriel-Martín, Paola Bianucci, Giuseppe Mascaro, Enrique R. Vivoni, and Luis Garrote. "Stochastic Hybrid Event Based and Continuous Approach to Derive Flood Frequency Curve." Water 13, no. 14 (2021): 1931. http://dx.doi.org/10.3390/w13141931.

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This study proposes a methodology that combines the advantages of the event-based and continuous models, for the derivation of the maximum flow and maximum hydrograph volume frequency curves, by combining a stochastic continuous weather generator (the advanced weather generator, abbreviated as AWE-GEN) with a fully distributed physically based hydrological model (the TIN-based real-time integrated basin simulator, abbreviated as tRIBS) that runs both event-based and continuous simulation. The methodology is applied to Peacheater Creek, a 64 km2 basin located in Oklahoma, United States. First,

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Portoghese, I., E. Bruno, and M. Vurro. "From regional climate simulations to the hydrological information needed for basin scale impact studies." Advances in Geosciences 26 (June 30, 2010): 25–31. http://dx.doi.org/10.5194/adgeo-26-25-2010.

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Abstract. The accuracy of local downscaling of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes because the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows, and groundwater recharge. In this study, the output of a regional climate model (RCM) is downscaled using a stochastic modelling of the point rainfall process able to adequately reproduce the daily rainfall intermittency which is one of the crucial aspects for the hydrological process

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Gelfan, A., V. A. Semenov, E. Gusev, et al. "Large-basin hydrological response to climate model outputs: uncertainty caused by internal atmospheric variability." Hydrology and Earth System Sciences 19, no. 6 (2015): 2737–54. http://dx.doi.org/10.5194/hess-19-2737-2015.

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Abstract. An approach is proposed to assess hydrological simulation uncertainty originating from internal atmospheric variability. The latter is one of three major factors contributing to uncertainty of simulated climate change projections (along with so-called "forcing" and "climate model" uncertainties). Importantly, the role of internal atmospheric variability is most visible over spatio-temporal scales of water management in large river basins. Internal atmospheric variability is represented by large ensemble simulations (45 members) with the ECHAM5 atmospheric general circulation model. E

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Toth, E. "Catchment classification based on characterisation of streamflow and precipitation time-series." Hydrology and Earth System Sciences Discussions 9, no. 9 (2012): 10805–28. http://dx.doi.org/10.5194/hessd-9-10805-2012.

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Abstract. The formulation of objective procedures for the delineation of homogeneous groups of catchments is a fundamental issue in both operational and research hydrology. For assessing catchment similarity, a variety of hydrological information may be considered; in this paper, gauged sites are characterised by a set of streamflow signatures that include a representation, albeit simplified, of the properties of fine time-scale flow series and in particular of the dynamic components of the data, in order to keep into account the sequential order and the stochastic nature of the streamflow pro

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Gelfan, A., V. A. Semenov, E. Gusev, et al. "Large-basin hydrological response to climate model outputs: uncertainty caused by the internal atmospheric variability." Hydrology and Earth System Sciences Discussions 12, no. 2 (2015): 2305–48. http://dx.doi.org/10.5194/hessd-12-2305-2015.

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Abstract. An approach is proposed to assess hydrological simulation uncertainty originating from internal atmospheric variability. The latter is one of three major factors contributing to the uncertainty of simulated climate change projections (along with so-called "forcing" and "climate model" uncertainties). Importantly, the role of the internal atmospheric variability is the most visible over the spatial–temporal scales of water management in large river basins. The internal atmospheric variability is represented by large ensemble simulations (45 members) with the ECHAM5 atmospheric general

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Toth, E. "Catchment classification based on characterisation of streamflow and precipitation time series." Hydrology and Earth System Sciences 17, no. 3 (2013): 1149–59. http://dx.doi.org/10.5194/hess-17-1149-2013.

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Abstract. The formulation of objective procedures for the delineation of homogeneous groups of catchments is a fundamental issue in both operational and research hydrology. For assessing catchment similarity, a variety of hydrological information may be considered; in this paper, gauged sites are characterised by a set of streamflow signatures that include a representation, albeit simplified, of the properties of fine time-scale flow series and in particular of the dynamic components of the data, in order to keep into account the sequential order and the stochastic nature of the streamflow pro

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Rios Gaona, Manuel F., Katerina Michaelides, and Michael Bliss Singer. "STORM v.2: A simple, stochastic rainfall model for exploring the impacts of climate and climate change at and near the land surface in gauged watersheds." Geoscientific Model Development 17, no. 13 (2024): 5387–412. http://dx.doi.org/10.5194/gmd-17-5387-2024.

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Abstract. Climate change is expected to have major impacts on land surface and subsurface processes through its expression in the hydrological cycle, but the impacts to any particular basin or region are highly uncertain. Non-stationarities in the frequency, magnitude, duration, and timing of rainfall events have important implications for human societies, water resources, and ecosystems. The conventional approach for assessing the impacts of climate change is to downscale global climate model output and use it to drive regional and local models that express the climate within hydrology near t

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Gómez-Beas, Raquel, Eva Contreras, María José Polo, and Cristina Aguilar. "Stochastic Flow Analysis for Optimization of the Operationality in Run-of-River Hydroelectric Plants in Mountain Areas." Energies 17, no. 7 (2024): 1705. http://dx.doi.org/10.3390/en17071705.

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The highly temporal variability of the hydrological response in Mediterranean areas affects the operation of hydropower systems, especially in run-of-river (RoR) plants located in mountainous areas. Here, the water flow regime strongly determines failure, defined as no operating days due to inflows below the minimum operating flow. A Bayesian dynamics stochastic model was developed with statistical modeling of both rainfall as the forcing agent and water inflows to the plants as the dependent variable using two approaches—parametric adjustments and non-parametric methods. Failure frequency ana

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Quenum, Gandomè Mayeul Leger Davy, Joël Arnault, Nana Ama Browne Klutse, Zhenyu Zhang, Harald Kunstmann, and Philip G. Oguntunde. "Potential of the Coupled WRF/WRF-Hydro Modeling System for Flood Forecasting in the Ouémé River (West Africa)." Water 14, no. 8 (2022): 1192. http://dx.doi.org/10.3390/w14081192.

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Since the beginning of the 2000s, most of the West-African countries, particularly Benin, have experienced an increased frequency of extreme flood events. In this study, we focus on the case of the Ouémé river basin in Benin. To investigate flood events in this basin for early warning, the coupled atmosphere–hydrology model system WRF-Hydro is used, and analyzed for the period 2008–2010. Such a coupled model allows exploration of the contribution of atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro to correctly

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Do, Hong Xuan, Fang Zhao, Seth Westra, et al. "Historical and future changes in global flood magnitude – evidence from a model–observation investigation." Hydrology and Earth System Sciences 24, no. 3 (2020): 1543–64. http://dx.doi.org/10.5194/hess-24-1543-2020.

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Abstract. To improve the understanding of trends in extreme flows related to flood events at the global scale, historical and future changes of annual maxima of 7 d streamflow are investigated, using a comprehensive streamflow archive and six global hydrological models. The models' capacity to characterise trends in annual maxima of 7 d streamflow at the continental and global scale is evaluated across 3666 river gauge locations over the period from 1971 to 2005, focusing on four aspects of trends: (i) mean, (ii) standard deviation, (iii) percentage of locations showing significant trends and

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Gabriel-Martin, Sordo-Ward, Garrote, and García. "Dependence Between Extreme Rainfall Events and the Seasonality and Bivariate Properties of Floods. A Continuous Distributed Physically-Based Approach." Water 11, no. 9 (2019): 1896. http://dx.doi.org/10.3390/w11091896.

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This paper focuses on proposing the minimum number of storms necessary to derive the extreme flood hydrographs accurately through event-based modelling. To do so, we analyzed the results obtained by coupling a continuous stochastic weather generator (the Advanced WEather GENerator) with a continuous distributed physically-based hydrological model (the TIN-based real-time integrated basin simulator), and by simulating 5000 years of hourly flow at the basin outlet. We modelled the outflows in a basin named Peacheater Creek located in Oklahoma, USA. Afterwards, we separated the independent rainfa

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Arnold, S., S. Attinger, K. Frank, and A. Hildebrandt. "Parameterization and uncertainty in coupled ecohydrological models." Hydrology and Earth System Sciences Discussions 6, no. 3 (2009): 4155–207. http://dx.doi.org/10.5194/hessd-6-4155-2009.

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Abstract. In this paper we develop and apply a conceptual ecohydrological model to investigate the effects of model structure and parameter uncertainty on the prediction of vegetation structure and hydrological dynamics. The model is applied for a typical water limited riparian ecosystem along an ephemeral river: the middle section of the Kuiseb River in Namibia. We modelled this system by coupling an ecological model with a conceptual hydrological model. The hydrological model is storage based with stochastical forcing from the flood. The ecosystem is modelled with a population model, and rep

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Arnold, S., S. Attinger, K. Frank, and A. Hildebrandt. "Uncertainty in parameterisation and model structure affect simulation results in coupled ecohydrological models." Hydrology and Earth System Sciences 13, no. 10 (2009): 1789–807. http://dx.doi.org/10.5194/hess-13-1789-2009.

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Abstract. In this paper we develop and apply a conceptual ecohydrological model to investigate the effects of model structure and parameter uncertainty on the simulation of vegetation structure and hydrological dynamics. The model is applied for a typical water limited riparian ecosystem along an ephemeral river: the middle section of the Kuiseb River in Namibia. We modelled this system by coupling an ecological model with a conceptual hydrological model. The hydrological model is storage based with stochastical forcing from the flood. The ecosystem is modelled with a population model, and rep

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Manzoni, Stefano, Annalisa Molini, and Amilcare Porporato. "Stochastic modelling of phytoremediation." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 467, no. 2135 (2011): 3188–205. http://dx.doi.org/10.1098/rspa.2011.0209.

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Leaching of heavy metals and other contaminants from soils poses a significant environmental threat as it affects the quality of downstream water bodies. Quantifying these losses is particularly important when employing phytoremediation approaches to reduce soil contamination, as contaminant escaping the system through leaching cannot be taken up by vegetation. Despite its undoubted importance, the role of such hydrologic forcing has seldom been fully considered in models describing the long-term contaminant mass balance during phytoremediation. The partitioning of contaminants between leachin

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Park, Jeryang, Gianluca Botter, James W. Jawitz, and P. Suresh C. Rao. "Stochastic modeling of hydrologic variability of geographically isolated wetlands: Effects of hydro-climatic forcing and wetland bathymetry." Advances in Water Resources 69 (July 2014): 38–48. http://dx.doi.org/10.1016/j.advwatres.2014.03.007.

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Bennett, James C., Quan J. Wang, David E. Robertson, Andrew Schepen, Ming Li, and Kelvin Michael. "Assessment of an ensemble seasonal streamflow forecasting system for Australia." Hydrology and Earth System Sciences 21, no. 12 (2017): 6007–30. http://dx.doi.org/10.5194/hess-21-6007-2017.

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Abstract. Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean–land–atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall foreca

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Koutsoyiannis, D., A. Efstratiadis, and K. P. Georgakakos. "Uncertainty Assessment of Future Hydroclimatic Predictions: A Comparison of Probabilistic and Scenario-Based Approaches." Journal of Hydrometeorology 8, no. 3 (2007): 261–81. http://dx.doi.org/10.1175/jhm576.1.

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Abstract During the last decade, numerous studies have been carried out to predict future climate based on climatic models run on the global scale and fed by plausible scenarios about anthropogenic forcing to climate. Based on climatic model output, hydrologic models attempt then to predict future hydrologic regimes at regional scales. Much less systematic work has been done to estimate climatic uncertainty and to assess the climatic and hydrologic model outputs within an uncertainty perspective. In this study, a stochastic framework for future climatic uncertainty is proposed, based on the fo

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Sugimoto, Takayuki, András Bárdossy, Geoffrey G. S. Pegram, and Johannes Cullmann. "Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts." Hydrology and Earth System Sciences 20, no. 7 (2016): 2705–20. http://dx.doi.org/10.5194/hess-20-2705-2016.

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Abstract. Global climate change can have impacts on characteristics of rainfall–runoff events and subsequently on the hydrological regime. Meanwhile, the catchment itself changes due to anthropogenic influences. However, it is not easy to prove the link between the hydrology and the forcings. In this context, it might be meaningful to detect the temporal changes of catchments independent from climate change by investigating existing long-term discharge records. For this purpose, a new stochastic system based on copulas for time series analysis is introduced in this study.A statistical tool lik

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Hwang, S., and W. D. Graham. "Development and comparative evaluation of a stochastic analog method to downscale daily GCM precipitation." Hydrology and Earth System Sciences 17, no. 11 (2013): 4481–502. http://dx.doi.org/10.5194/hess-17-4481-2013.

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Abstract. There are a number of statistical techniques that downscale coarse climate information from general circulation models (GCMs). However, many of them do not reproduce the small-scale spatial variability of precipitation exhibited by the observed meteorological data, which is an important factor for predicting hydrologic response to climatic forcing. In this study a new downscaling technique (Bias-Correction and Stochastic Analog method; BCSA) was developed to produce stochastic realizations of bias-corrected daily GCM precipitation fields that preserve both the spatial autocorrelation

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Slater, Andrew G., and Martyn P. Clark. "Snow Data Assimilation via an Ensemble Kalman Filter." Journal of Hydrometeorology 7, no. 3 (2006): 478–93. http://dx.doi.org/10.1175/jhm505.1.

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Abstract A snow data assimilation study was undertaken in which real data were used to update a conceptual model, SNOW-17. The aim of this study is to improve the model’s estimate of snow water equivalent (SWE) by merging the uncertainties associated with meteorological forcing data and SWE observations within the model. This is done with a view to aiding the estimation of snowpack initial conditions for the ultimate objective of streamflow forecasting via a distributed hydrologic model. To provide a test of this methodology, the authors performed experiments at 53 stations in Colorado. In eac

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Hwang, S., and W. D. Graham. "Development and comparative evaluation of a stochastic analog method to downscale daily GCM precipitation." Hydrology and Earth System Sciences Discussions 10, no. 2 (2013): 2141–81. http://dx.doi.org/10.5194/hessd-10-2141-2013.

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Abstract. There are a number of statistical techniques that downscale coarse climate information from global circulation models (GCM). However, many of them do not reproduce the small-scale spatial variability of precipitation exhibited by the observed meteorological data which can be an important factor for predicting hydrologic response to climatic forcing. In this study a new downscaling technique (bias-correction and stochastic analog method, BCSA) was developed to produce stochastic realizations of bias-corrected daily GCM precipitation fields that preserve the spatial autocorrelation str

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Grouillet, Benjamin, Denis Ruelland, Pradeebane Vaittinada Ayar, and Mathieu Vrac. "Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean." Hydrology and Earth System Sciences 20, no. 3 (2016): 1031–47. http://dx.doi.org/10.5194/hess-20-1031-2016.

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Abstract. This paper analyzes the sensitivity of a hydrological model to different methods to statistically downscale climate precipitation and temperature over four western Mediterranean basins illustrative of different hydro-meteorological situations. The comparison was conducted over a common 20-year period (1986&amp;ndsh;2005) to capture different climatic conditions in the basins. The daily GR4j conceptual model was used to simulate streamflow that was eventually evaluated at a 10-day time step. Cross-validation showed that this model is able to correctly reproduce runoff in both dry

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Grouillet, B., D. Ruelland, P. V. Ayar, and M. Vrac. "Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean." Hydrology and Earth System Sciences Discussions 12, no. 10 (2015): 10067–108. http://dx.doi.org/10.5194/hessd-12-10067-2015.

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Abstract. This paper analyzes the sensitivity of a hydrological model to different methods to statistically downscale climate precipitation and temperature over four western Mediterranean basins illustrative of different hydro-meteorological situations. The comparison was conducted over a common 20 year period (1986–2005) to capture different climatic conditions in the basins. Streamflow was simulated using the GR4j conceptual model. Cross-validation showed that this model is able to correctly reproduce runoff in both dry and wet years when high-resolution observed climate forcings are used as

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Steinman, Byron A., Michael F. Rosenmeier, and Mark B. Abbott. "The isotopic and hydrologic response of small, closed-basin lakes to climate forcing from predictive models: Simulations of stochastic and mean state precipitation variations." Limnology and Oceanography 55, no. 6 (2010): 2246–61. http://dx.doi.org/10.4319/lo.2010.55.6.2246.

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Lewis, Sophie C. "Assessing the Stationarity of Australian Precipitation Extremes in Forced and Unforced CMIP5 Simulations." Journal of Climate 31, no. 1 (2017): 131–45. http://dx.doi.org/10.1175/jcli-d-17-0393.1.

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Abstract Knowledge of the range of precipitation variability and extremes is restricted in regions such as Australia, where instrumental records are short and paleoclimatic records are limited in spatial and temporal extent and resolution. In such comparatively data-poor regions, there is limited context for understanding the statistical unusualness of recently observed extreme events, such as heavy rain and drought, and the influence of stochastic and anthropogenic forcings on their magnitude. This study attempts to further understandings of the range of forced and unforced variability using

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Maggioni, Viviana, Humberto J. Vergara, Emmanouil N. Anagnostou, Jonathan J. Gourley, Yang Hong, and Dimitrios Stampoulis. "Investigating the Applicability of Error Correction Ensembles of Satellite Rainfall Products in River Flow Simulations." Journal of Hydrometeorology 14, no. 4 (2013): 1194–211. http://dx.doi.org/10.1175/jhm-d-12-074.1.

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Abstract This study uses a stochastic ensemble-based representation of satellite rainfall error to predict the propagation in flood simulation of three quasi-global-scale satellite rainfall products across a range of basin scales. The study is conducted on the Tar-Pamlico River basin in the southeastern United States based on 2 years of data (2004 and 2006). The NWS Multisensor Precipitation Estimator (MPE) dataset is used as the reference for evaluating three satellite rainfall products: the Tropical Rainfall Measuring Mission (TRMM) real-time 3B42 product (3B42RT), the Climate Prediction Cen

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Bellier, Joseph, Michael Scheuerer, and Thomas M. Hamill. "Precipitation Downscaling with Gibbs Sampling: An Improved Method for Producing Realistic, Weather-Dependent, and Anisotropic Fields." Journal of Hydrometeorology 21, no. 11 (2020): 2487–505. http://dx.doi.org/10.1175/jhm-d-20-0069.1.

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AbstractDownscaling precipitation fields is a necessary step in a number of applications, especially in hydrological modeling where the meteorological forcings are frequently available at too coarse resolution. In this article, we review the Gibbs sampling disaggregation model (GSDM), a stochastic downscaling technique originally proposed by Gagnon et al. The method is capable of introducing realistic, weather-dependent, and possibly anisotropic fine-scale details, while preserving the mean rain rate over the coarse-scale pixels. The main developments compared to the former version are (i) an

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Bowers, Corinne, Katherine A. Serafin, and Jack Baker. "A performance-based approach to quantify atmospheric river flood risk." Natural Hazards and Earth System Sciences 22, no. 4 (2022): 1371–93. http://dx.doi.org/10.5194/nhess-22-1371-2022.

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Abstract. Atmospheric rivers (ARs) are a class of meteorologic phenomena that cause significant precipitation and flooding on the US West Coast. This work presents a new Performance-based Atmospheric River Risk Analysis (PARRA) framework that adapts existing concepts from probabilistic risk analysis and performance-based engineering for application in the context of AR-driven fluvial flooding. The PARRA framework is a chain of physically based models that link the atmospheric forcings, hydrologic impacts, and economic consequences of AR-driven fluvial flood risk together at consistent “pinch p

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Tseng, Kai-Chih, and Yun-Hsuan Ho. "The subseasoanl predictability of the western North Pacific subtropical high and the 2020 record-breaking event." npj Climate and Atmospheric Science 7, no. 1 (2024). http://dx.doi.org/10.1038/s41612-024-00596-3.

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AbstractThe western North Pacific subtropical high (WNPSH), a prominent feature in the North Pacific during the boreal summer, exerts significant socioeconomic consequences by influencing hydrological extremes such as tropical cyclones, the Meiyu front, and summer heat waves over East Asia. Accurately forecasting the characteristics of the WNPSH over extended timescales is crucial, but subseasonal prediction in this specific context is still in its early stages due to the complex dynamics involved. In this study, we investigate the optimal predictable pattern of the WNPSH using linear stochast

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Bertassello, Leonardo E., Antoine F. Aubeneau, Gianluca Botter, James W. Jawitz, and P. S. C. Rao. "Emergent dispersal networks in dynamic wetlandscapes." Scientific Reports 10, no. 1 (2020). http://dx.doi.org/10.1038/s41598-020-71739-8.

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Abstract The connectivity among distributed wetlands is critical for aquatic habitat integrity and to maintain metapopulation biodiversity. Here, we investigated the spatiotemporal fluctuations of wetlandscape connectivity driven by stochastic hydroclimatic forcing, conceptualizing wetlands as dynamic habitat nodes in dispersal networks. We hypothesized that spatiotemporal hydrologic variability influences the heterogeneity in wetland attributes (e.g., size and shape distributions) and wetland spatial organization (e.g., gap distances), in turn altering the variance of the dispersal network to

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Rusli, Steven Reinaldo, and Theo Senjaya. "Assessing basin’s dynamic hydrological characteristics using statistical analysis on rainfall – river discharge observation data." Journal of the Civil Engineering Forum, January 17, 2025, 97–108. https://doi.org/10.22146/jcef.13242.

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Hydrological studies often rely on physical-based modelling approaches to simulate water cycles. However, such an approach requires extensive basin physical data inputs, including features, attributes, and properties that are quantifiable, which often are lacking in data-scarce areas. Therefore, this study explores an alternative viewpoint by using simple statistical analysis to assess the dynamic basin’s hydrological characteristics. We collate and divide the rainfall and discharge observation data in the Upper Citarum River basin into three periods: period 1 (2000–2005), period 2 (2000–2010)

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Toth, E. "Catchment classification based on characterisation of streamflow and precipitation time series." March 15, 2013. https://doi.org/10.5194/hess-17-1149-2013.

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Abstract. The formulation of objective procedures for the delineation of homogeneous groups of catchments is a fundamental issue in both operational and research hydrology. For assessing catchment similarity, a variety of hydrological information may be considered; in this paper, gauged sites are characterised by a set of streamflow signatures that include a representation, albeit simplified, of the properties of fine time-scale flow series and in particular of the dynamic components of the data, in order to keep into account the sequential order and the stochastic nature of the streamflow pro

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Wang, Zhenqiang, Meredith Leung, Sudarshana Mukhopadhyay, et al. "A hybrid statistical-dynamical framework for compound coastal flooding analysis." Environmental Research Letters, November 25, 2024. http://dx.doi.org/10.1088/1748-9326/ad96ce.

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Abstract Compound coastal flooding due to astronomic, atmospheric, oceanographic, and hydrologic forcings poses severe threats to coastal communities. While physics-driven approaches are able to dynamically simulate temporally and spatially varying compound flooding generated by multiple partially correlated drivers, computational burdens limit their capability to explore the full range of conditions that contribute to compound coastal hazards. Data-driven statistical approaches address some of these computational challenges, however they are also unable to explore all possible forcing combina

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Shabestanipour, Ghazal, Zachary Brodeur, Benjamin Manoli, Abigail Birnbaum, Scott Steinschneider, and Jonathan R. Lamontagne. "Risk-based hydrologic design under climate change using stochastic weather and watershed modeling." Frontiers in Water 6 (March 21, 2024). http://dx.doi.org/10.3389/frwa.2024.1310590.

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Water resources planning and management requires the estimation of extreme design events. Anticipated climate change is playing an increasingly prominent role in the planning and design of long-lived infrastructure, as changes to climate forcings are expected to alter the distribution of extremes in ways and to extents that are difficult to predict. One approach is to use climate projections to force hydrologic models, but this raises two challenges. First, global climate models generally focus on much larger scales than are relevant to hydrologic design, and regional climate models that bette

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