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1
Keljo, Kurt S. "Effects of Hydrologic Pulsing and Vegetation on Invertebrate Communities in Wetlands." Land 11, no. 9 (September 13, 2022): 1554. http://dx.doi.org/10.3390/land11091554.
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Constructed, mitigation wetlands in the midwestern United States are frequently dominated by a Typha spp. monoculture and their hydrologies are often determined by adjustable control structures. Wetlands provide habitat for multiple macroinvertebrate species, which in turn provide food for other organisms inhabiting the wetlands, such as waterfowl. This study examined the impacts of plant diversity and manipulated hydrology on macroinvertebrate communities. Forty 1-m2 wetland mesocosms were either planted with a monoculture of Typha spp. or with a more diverse plant community of Schoenoplectus tabernaemontani, Juncus effusus, and Sparganium eurycarpum. They were also assigned to one of four hydrologic regimes: steady state, pulsing, deep spring/shallow fall, and shallow spring/deep summer. After one year, macroinvertebrates were sampled in the mesocosms. Mesocosms with deep spring hydrologies were found to have greater taxon diversity than those with other hydrologies, but Chironomidae biomass was the lowest under the deep spring hydrology. Culicidae and Chironomidae were found in higher numbers in mixed vegetation than in Typha spp. Taxon richness and Chironomid biomass were significantly higher in mixed vegetation mesocosms than in Typha spp. monocultures. Results suggest vegetation diversity and hydrological regimes impact macroinvertebrate communities, with potential implications for constructed wetland design and management.
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Keeland, B. D., and R. R. Sharitz. "Seasonal growth patterns of Nyssasylvatica var biflora, Nyssaaquatica, and Taxodiumdistichum s affected by hydrologic regime." Canadian Journal of Forest Research 25, no. 7 (July 1, 1995): 1084–96. http://dx.doi.org/10.1139/x95-120.
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Hydrologic regime is a major influence on the growth of wetland plants. We examined seasonal growth patterns of three wetland tree species, Nyssasylvatica var. biflora (Walter) Sargent, Nyssaaquatica L., and Taxodiumdistichum (L.) Rich., to determine responses to variations in hydrologie regime. Five study sites were chosen in two river-floodplain swamps to represent a gradient of hydrologie regimes, and the weekly changes in diameter of over 600 mature trees at these sites were measured with dendrometer bands throughout two growing seasons. Total growth, time of growth cessation, and length of the growth phase of canopy trees of all three species differed significantly among hydrologie regimes. Nyssasylvatica var. biflora and N. aquatica achieved greatest growth under deep periodic flooding. Maximum growth of T. distichum occurred with shallow permanent flooding. Subcanopy trees differed less among hydrologic regimes than canopy trees. These results suggest that modifications of natural hydrologie regimes can cause short-term changes in tree growth and have long-term effects on the dynamics of forested wetlands.
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Thompson, S. E., M. Sivapalan, C. J. Harman, V. Srinivasan, M. R. Hipsey, P. Reed, A. Montanari, and G. Blöschl. "Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene." Hydrology and Earth System Sciences Discussions 10, no. 6 (June 20, 2013): 7897–961. http://dx.doi.org/10.5194/hessd-10-7897-2013.
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Abstract. Globally, many different kinds of water resources management issues call for policy and infrastructure based responses. Yet responsible decision making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal-to-century long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle – a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management.
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Shukla, S., J. Sheffield, E. F. Wood, and D. P. Lettenmaier. "On the sources of global land surface hydrologic predictability." Hydrology and Earth System Sciences Discussions 10, no. 2 (February 12, 2013): 1987–2013. http://dx.doi.org/10.5194/hessd-10-1987-2013.
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Abstract. Global seasonal hydrologic prediction is crucial to mitigating the impacts of droughts and floods, especially in the developing world. Hydrologic prediction skill at seasonal lead times (i.e. 1–6 months) comes from knowledge of initial hydrologic conditions (IHCs – primarily the state of initial soil moisture and snow) and seasonal climate forecast skill (FS). In this study we quantify the contributions of IHCs and FS to seasonal hydrologic prediction skill globally on a relative basis throughout the year. We do so by conducting two model-based experiments using the Variable Infiltration Capacity (VIC) macroscale hydrology model, one based on Ensemble Streamflow Prediction (ESP) and another based on Reverse-ESP (rESP), both for a 47 yr reforecast period (1961–2007). We compare cumulative runoff (CR), soil moisture (SM) and snow water equivalent (SWE) forecasts obtained from each experiment with a control simulation forced with observed atmospheric forcings over the reforecast period and estimate the ratio of Root Mean Square Error (RMSE) of both experiments for each forecast initialization date and lead time. We find that in general, the contributions of IHCs are greater than the contribution of FS over the Northern (Southern) Hemisphere during the forecast period starting in October and January (April and July). Over snow dominated regions in the Northern Hemisphere the IHCs dominate the CR forecast skill for up to 6 months lead time during the forecast period starting in April. Based on our findings we argue that despite the limited FS (mainly for precipitation) better estimates of the IHCs could lead to improvement in the current level of seasonal hydrologic forecast skill over many regions of the globe at least during some parts of the year.
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Ehsan Bhuiyan, Md Abul, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier. "Assessment of precipitation error propagation in multi-model global water resource reanalysis." Hydrology and Earth System Sciences 23, no. 4 (April 15, 2019): 1973–94. http://dx.doi.org/10.5194/hess-23-1973-2019.
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Abstract. This study focuses on the Iberian Peninsula and investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modeling, in global water resource reanalysis. Analysis is based on ensemble hydrologic simulations for a period spanning 11 years (2000–2010). To simulate the hydrological variables of surface runoff, subsurface runoff, and evapotranspiration, we used four land surface models (LSMs) – JULES (Joint UK Land Environment Simulator), ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems), SURFEX (Surface Externalisée), and HTESSEL (Hydrology – Tiled European Centre for Medium-Range Weather Forecasts – ECMWF – Scheme for Surface Exchanges over Land) – and one global hydrological model, WaterGAP3 (Water – a Global Assessment and Prognosis). Simulations were carried out for five precipitation products – CMORPH (the Climate Prediction Center Morphing technique of the National Oceanic and Atmospheric Administration, or NOAA), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), 3B42V(7), ECMWF reanalysis, and a machine-learning-based blended product. As a reference, we used a ground-based observation-driven precipitation dataset, named SAFRAN, available at 5 km, 1 h resolution. We present relative performances of hydrologic variables for the different multi-model and multi-forcing scenarios. Overall, results reveal the complexity of the interaction between precipitation characteristics and different modeling schemes and show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure. Surface runoff is strongly sensitive to precipitation uncertainty, and the degree of sensitivity depends significantly on the runoff generation scheme of each model examined. Evapotranspiration fluxes are comparatively less sensitive for this study region. Finally, our results suggest that there is no single model–forcing combination that can outperform all others consistently for all variables examined and thus reinforce the fact that there are significant benefits to exploring different model structures as part of the overall modeling approaches used for water resource applications.
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Thompson, S. E., M. Sivapalan, C. J. Harman, V. Srinivasan, M. R. Hipsey, P. Reed, A. Montanari, and G. Blöschl. "Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene." Hydrology and Earth System Sciences 17, no. 12 (December 12, 2013): 5013–39. http://dx.doi.org/10.5194/hess-17-5013-2013.
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Abstract. Globally, many different kinds of water resources management issues call for policy- and infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal- to century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle – a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges from the perspectives of hydrologic science research. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management. Fully realizing the potential of this approach will ultimately require detailed integration of social science and physical science understanding of water systems, and is a priority for the developing field of sociohydrology.
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Shukla, S., J. Sheffield, E. F. Wood, and D. P. Lettenmaier. "On the sources of global land surface hydrologic predictability." Hydrology and Earth System Sciences 17, no. 7 (July 16, 2013): 2781–96. http://dx.doi.org/10.5194/hess-17-2781-2013.
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Abstract. Global seasonal hydrologic prediction is crucial to mitigating the impacts of droughts and floods, especially in the developing world. Hydrologic predictability at seasonal lead times (i.e., 1–6 months) comes from knowledge of initial hydrologic conditions (IHCs) and seasonal climate forecast skill (FS). In this study we quantify the contributions of two primary components of IHCs – soil moisture and snow water content – and FS (of precipitation and temperature) to seasonal hydrologic predictability globally on a relative basis throughout the year. We do so by conducting two model-based experiments using the variable infiltration capacity (VIC) macroscale hydrology model, one based on ensemble streamflow prediction (ESP) and another based on Reverse-ESP (Rev-ESP), both for a 47 yr re-forecast period (1961–2007). We compare cumulative runoff (CR), soil moisture (SM) and snow water equivalent (SWE) forecasts from each experiment with a VIC model-based reference data set (generated using observed atmospheric forcings) and estimate the ratio of root mean square error (RMSE) of both experiments for each forecast initialization date and lead time, to determine the relative contribution of IHCs and FS to the seasonal hydrologic predictability. We find that in general, the contributions of IHCs to seasonal hydrologic predictability is highest in the arid and snow-dominated climate (high latitude) regions of the Northern Hemisphere during forecast periods starting on 1 January and 1 October. In mid-latitude regions, such as the Western US, the influence of IHCs is greatest during the forecast period starting on 1 April. In the arid and warm temperate dry winter regions of the Southern Hemisphere, the IHCs dominate during forecast periods starting on 1 April and 1 July. In equatorial humid and monsoonal climate regions, the contribution of FS is generally higher than IHCs through most of the year. Based on our findings, we argue that despite the limited FS (mainly for precipitation) better estimates of the IHCs could lead to improvement in the current level of seasonal hydrologic forecast skill over many regions of the globe at least during some parts of the year.
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Bisbing, Sarah M., and David V. D’Amore. "Nitrogen dynamics vary across hydrologic gradients and by forest community composition in the perhumid coastal temperate rainforest of southeast Alaska." Canadian Journal of Forest Research 48, no. 2 (February 2018): 180–91. http://dx.doi.org/10.1139/cjfr-2017-0178.
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Nitrogen (N) limitation constrains plant growth, but complex interactions among species and ecosystems hinder our ability to identify primary drivers of N availability. Hydrologic, biogeochemical, and ecological processes interact spatially and temporally, requiring measurements of N across diverse ecosystem types and as a function of both site conditions and vegetation composition. We measured initial exchangeable and mineralized N along a hydrologic gradient in the Alaskan perhumid coastal temperate rainforest to test a conceptual model of linkages between N availability and landscape, hydrologic, and ecosystem characteristics in temperate forests. Mineralization was closely associated with inorganic N concentrations. Inorganic N as NH4+ generally increased with increasing depth to groundwater but was strongly determined by plant–water interactions. Exchangeable and mineralized N were closely linked to tree species, forest biomass, and hydrologic regime regardless of ecosystem type. The emergence of tree species as indicators of N cycling highlights the effect that species have on nutrient dynamics, while the trend of increasing inorganic N with increasing soil saturation points to the role of hydrology in driving N availability. Our research quantified N dynamics for an understudied, yet critical, system and provides a framework for exploring feedbacks among soil saturation, forest composition, and nutrient cycling in temperate forests.
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Herman, J. D., J. B. Kollat, P. M. Reed, and T. Wagener. "Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models." Hydrology and Earth System Sciences 17, no. 7 (July 24, 2013): 2893–903. http://dx.doi.org/10.5194/hess-17-2893-2013.
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Abstract. The increase in spatially distributed hydrologic modeling warrants a corresponding increase in diagnostic methods capable of analyzing complex models with large numbers of parameters. Sobol' sensitivity analysis has proven to be a valuable tool for diagnostic analyses of hydrologic models. However, for many spatially distributed models, the Sobol' method requires a prohibitive number of model evaluations to reliably decompose output variance across the full set of parameters. We investigate the potential of the method of Morris, a screening-based sensitivity approach, to provide results sufficiently similar to those of the Sobol' method at a greatly reduced computational expense. The methods are benchmarked on the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) over a six-month period in the Blue River watershed, Oklahoma, USA. The Sobol' method required over six million model evaluations to ensure reliable sensitivity indices, corresponding to more than 30 000 computing hours and roughly 180 gigabytes of storage space. We find that the method of Morris is able to correctly screen the most and least sensitive parameters with 300 times fewer model evaluations, requiring only 100 computing hours and 1 gigabyte of storage space. The method of Morris proves to be a promising diagnostic approach for global sensitivity analysis of highly parameterized, spatially distributed hydrologic models.
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Herman, J. D., J. B. Kollat, P. M. Reed, and T. Wagener. "Technical note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models." Hydrology and Earth System Sciences Discussions 10, no. 4 (April 5, 2013): 4275–99. http://dx.doi.org/10.5194/hessd-10-4275-2013.
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Abstract. The increase in spatially distributed hydrologic modeling warrants a corresponding increase in diagnostic methods capable of analyzing complex models with large numbers of parameters. Sobol' sensitivity analysis has proven to be a valuable tool for diagnostic analyses of hydrologic models. However, for many spatially distributed models, the Sobol' method requires a prohibitive number of model evaluations to reliably decompose output variance across the full set of parameters. We investigate the potential of the method of Morris, a screening-based sensitivity approach, to provide results sufficiently similar to those of the Sobol' method at a greatly reduced computational expense. The methods are benchmarked on the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) model over a six-month period in the Blue River Watershed, Oklahoma, USA. The Sobol' method required over six million model evaluations to ensure reliable sensitivity indices, corresponding to more than 30 000 computing hours and roughly 180 gigabytes of storage space. We find that the method of Morris is able to correctly identify sensitive and insensitive parameters with 300 times fewer model evaluations, requiring only 100 computing hours and 1 gigabyte of storage space. Method of Morris proves to be a promising diagnostic approach for global sensitivity analysis of highly parameterized, spatially distributed hydrologic models.
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Xu, Xiaoyong, Jonathan Li, and Bryan A. Tolson. "Progress in integrating remote sensing data and hydrologic modeling." Progress in Physical Geography: Earth and Environment 38, no. 4 (June 5, 2014): 464–98. http://dx.doi.org/10.1177/0309133314536583.
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Remote sensing and hydrologic modeling are two key approaches to evaluate and predict hydrology and water resources. Remote sensing technologies, due to their ability to offer large-scale spatially distributed observations, have opened up new opportunities for the development of fully distributed hydrologic and land-surface models. In general, remote sensing data can be applied to land-surface and hydrologic modeling through three strategies: model inputs (basin information, boundary conditions, etc.), parameter estimation (model calibration), and state estimation (data assimilation). There has been an intensive global research effort to integrate remote sensing and land/hydrologic modeling over the past few decades. In particular, in recent years significant progress has been made in land/hydrologic remote sensing data assimilation. Hence there is a demand for an up-to-date review on these efforts. This paper presents an overview of research efforts to combine hydrologic/land models and remote sensing products (mainly including precipitation, surface soil moisture, snow cover, snow water equivalent, leaf area index, and evapotranspiration) over the past decade. This paper also discusses the major challenges remaining in this field, and recommends the directions for further research efforts.
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Chu, Vena W. "Greenland ice sheet hydrology." Progress in Physical Geography: Earth and Environment 38, no. 1 (November 26, 2013): 19–54. http://dx.doi.org/10.1177/0309133313507075.
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Understanding Greenland ice sheet (GrIS) hydrology is essential for evaluating response of ice dynamics to a warming climate and future contributions to global sea level rise. Recently observed increases in temperature and melt extent over the GrIS have prompted numerous remote sensing, modeling, and field studies gauging the response of the ice sheet and outlet glaciers to increasing meltwater input, providing a quickly growing body of literature describing seasonal and annual development of the GrIS hydrologic system. This system is characterized by supraglacial streams and lakes that drain through moulins, providing an influx of meltwater into englacial and subglacial environments that increases basal sliding speeds of outlet glaciers in the short term. However, englacial and subglacial drainage systems may adjust to efficiently drain increased meltwater without significant changes to ice dynamics over seasonal and annual scales. Both proglacial rivers originating from land-terminating glaciers and subglacial conduits under marine-terminating glaciers represent direct meltwater outputs in the form of fjord sediment plumes, visible in remotely sensed imagery. This review provides the current state of knowledge on GrIS surface water hydrology, following ice sheet surface meltwater production and transport via supra-, en-, sub-, and proglacial processes to final meltwater export to the ocean. With continued efforts targeting both process-level and systems analysis of the hydrologic system, the larger picture of how future changes in Greenland hydrology will affect ice sheet glacier dynamics and ultimately global sea level rise can be advanced.
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Kuentz, A., T. Mathevet, J. Gailhard, and B. Hingray. "Building long-term and high spatio-temporal resolution precipitation and air temperature reanalyses by mixing local observations and global atmospheric reanalyses: the ANATEM method." Hydrology and Earth System Sciences Discussions 12, no. 1 (January 12, 2015): 311–61. http://dx.doi.org/10.5194/hessd-12-311-2015.
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Abstract. Improving the understanding of past climatic or hydrologic variability has received a large attention in different fields of geosciences, such as glaciology, dendrochronology, sedimentology or hydrology. Based on different proxies, each research community produces different kind of climatic or hydrologic reanalyses, at different spatio-temporal scales and resolution. When considering climate or hydrology, numerous studies aim at characterising variability, trends or breaks using observed time-series of different regions or climate of world. However, in hydrology, these studies are usually limited to reduced temporal scale (mainly few decades, seldomly a century) because they are limited to observed time-series, that suffers from a limited spatio-temporal density. This paper introduces a new model, ANATEM, based on a combination of local observations and large scale climatic informations (such as 20CR Reanalysis). This model allow to build long-term air temperature and precipitation time-series, with a high spatio-temporal resolution (daily time-step, few km2). ANATEM was tested on the air temperature and precipitation time-series of 22 watersheds situated on the Durance watershed, in the french Alps. Based on a multi-criteria and multi-scale diagnostic, the results show that ANATEM improves the performances of classical statistical models. ANATEM model have been validated on a regional level, improving spatial homogeneity of performances and on independent long-term time-series, being able to capture the regional low-frequency variabilities over more than a century (1883–2010).
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Kuentz, A., T. Mathevet, J. Gailhard, and B. Hingray. "Building long-term and high spatio-temporal resolution precipitation and air temperature reanalyses by mixing local observations and global atmospheric reanalyses: the ANATEM model." Hydrology and Earth System Sciences 19, no. 6 (June 15, 2015): 2717–36. http://dx.doi.org/10.5194/hess-19-2717-2015.
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Abstract. Efforts to improve the understanding of past climatic or hydrologic variability have received a great deal of attention in various fields of geosciences such as glaciology, dendrochronology, sedimentology and hydrology. Based on different proxies, each research community produces different kinds of climatic or hydrologic reanalyses at different spatio-temporal scales and resolutions. When considering climate or hydrology, many studies have been devoted to characterising variability, trends or breaks using observed time series representing different regions or climates of the world. However, in hydrology, these studies have usually been limited to short temporal scales (mainly a few decades and more rarely a century) because they require observed time series (which suffer from a limited spatio-temporal density). This paper introduces ANATEM, a method that combines local observations and large-scale climatic information (such as the 20CR Reanalysis) to build long-term probabilistic air temperature and precipitation time series with a high spatio-temporal resolution (1 day and a few km2). ANATEM was tested on the reconstruction of air temperature and precipitation time series of 22 watersheds situated in the Durance River basin, in the French Alps. Based on a multi-criteria and multi-scale diagnosis, the results show that ANATEM improves the performance of classical statistical models – especially concerning spatial homogeneity – while providing an original representation of uncertainties which are conditioned by atmospheric circulation patterns. The ANATEM model has been also evaluated for the regional scale against independent long-term time series and was able to capture regional low-frequency variability over more than a century (1883–2010).
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Kim, Dawun, Daeun Kim, Seok-koo Kang, and Minha Choi. "Prediction of future hydrologic variables of Asia using RCP scenario and global hydrology model." Journal of Korea Water Resources Association 49, no. 6 (June 30, 2016): 551–63. http://dx.doi.org/10.3741/jkwra.2016.49.6.551.
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Perra, Enrica, Monica Piras, Roberto Deidda, Claudio Paniconi, Giuseppe Mascaro, Enrique R. Vivoni, Pierluigi Cau, Pier Andrea Marras, Ralf Ludwig, and Swen Meyer. "Multimodel assessment of climate change-induced hydrologic impacts for a Mediterranean catchment." Hydrology and Earth System Sciences 22, no. 7 (July 30, 2018): 4125–43. http://dx.doi.org/10.5194/hess-22-4125-2018.
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Abstract. This work addresses the impact of climate change on the hydrology of a catchment in the Mediterranean, a region that is highly susceptible to variations in rainfall and other components of the water budget. The assessment is based on a comparison of responses obtained from five hydrologic models implemented for the Rio Mannu catchment in southern Sardinia (Italy). The examined models – CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TOPographic Kinematic APproximation and Integration (TOPKAPI), TIN-based Real time Integrated Basin Simulator (tRIBS), and WAter balance SImulation Model (WASIM) – are all distributed hydrologic models but differ greatly in their representation of terrain features and physical processes and in their numerical complexity. After calibration and validation, the models were forced with bias-corrected, downscaled outputs of four combinations of global and regional climate models in a reference (1971–2000) and future (2041–2070) period under a single emission scenario. Climate forcing variations and the structure of the hydrologic models influence the different components of the catchment response. Three water availability response variables – discharge, soil water content, and actual evapotranspiration – are analyzed. Simulation results from all five hydrologic models show for the future period decreasing mean annual streamflow and soil water content at 1 m depth. Actual evapotranspiration in the future will diminish according to four of the five models due to drier soil conditions. Despite their significant differences, the five hydrologic models responded similarly to the reduced precipitation and increased temperatures predicted by the climate models, and lend strong support to a future scenario of increased water shortages for this region of the Mediterranean basin. The multimodel framework adopted for this study allows estimation of the agreement between the five hydrologic models and between the four climate models. Pairwise comparison of the climate and hydrologic models is shown for the reference and future periods using a recently proposed metric that scales the Pearson correlation coefficient with a factor that accounts for systematic differences between datasets. The results from this analysis reflect the key structural differences between the hydrologic models, such as a representation of both vertical and lateral subsurface flow (CATHY, TOPKAPI, and tRIBS) and a detailed treatment of vegetation processes (SWAT and WASIM).
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Astuti, Anik Juli Dwi, Sofie Annys, Mekete Dessie, Jan Nyssen, and Stefaan Dondeyne. "To What Extent Is Hydrologic Connectivity Taken into Account in Catchment Studies in the Lake Tana Basin, Ethiopia? A Review." Land 11, no. 12 (November 30, 2022): 2165. http://dx.doi.org/10.3390/land11122165.
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Knowledge of hydrologic connectivity is important to grasp the hydrological response at a basin scale, particularly as changes in connectivity can have a negative effect on the environment. In the context of a changing climate, being able to predict how changes in connectivity will affect runoff and sediment transport is particularly relevant for land-use planning. Many studies on hydrology, geomorphology and climatology have been conducted in the Lake Tana Basin in Ethiopia, which is undergoing rapid development and significant environmental changes. This systematic literature review aims at assessing to what extent the hydrologic connectivity has been taken into account in such research, and to identify research gaps relevant to land and water management. On the Web of Science and Scopus databases, 135 scientific articles covering those topics were identified. Aspects of hydrologic connectivity were mostly implicitly taken into account based on process-based, statistical and descriptive models. Amongst the drivers of changing connectivity, the climate was covered by a large majority of publications (64%). Components of structural hydrologic connectivity were accounted for by considering geomorphology (54%) and soils (47%), and to a lesser extent, hydrography (16%) and geology (12%). Components of functional connectivity were covered by looking at surface water fluxes (61%), sediment fluxes (18%) and subsurface water fluxes (13%). While numerous studies of the Lake Tana Basin accounted for the hydrologic connectivity implicitly, these related predominantly to functional components. The structural components are given less attention, while in the context of a changing climate, better insights into their influence on the hydrologic seem most relevant. Better knowledge of the static aspect of connectivity is particularly important for targeting appropriate soil and water conservation strategies. Being able to explicitly assess the ‘structural connectivity’ is therefore of direct relevance for land management and land-use policy.
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Fan, Ying, Gonzalo Miguez-Macho, Esteban G. Jobbágy, Robert B. Jackson, and Carlos Otero-Casal. "Hydrologic regulation of plant rooting depth." Proceedings of the National Academy of Sciences 114, no. 40 (September 18, 2017): 10572–77. http://dx.doi.org/10.1073/pnas.1712381114.
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Plant rooting depth affects ecosystem resilience to environmental stress such as drought. Deep roots connect deep soil/groundwater to the atmosphere, thus influencing the hydrologic cycle and climate. Deep roots enhance bedrock weathering, thus regulating the long-term carbon cycle. However, we know little about how deep roots go and why. Here, we present a global synthesis of 2,200 root observations of >1,000 species along biotic (life form, genus) and abiotic (precipitation, soil, drainage) gradients. Results reveal strong sensitivities of rooting depth to local soil water profiles determined by precipitation infiltration depth from the top (reflecting climate and soil), and groundwater table depth from below (reflecting topography-driven land drainage). In well-drained uplands, rooting depth follows infiltration depth; in waterlogged lowlands, roots stay shallow, avoiding oxygen stress below the water table; in between, high productivity and drought can send roots many meters down to the groundwater capillary fringe. This framework explains the contrasting rooting depths observed under the same climate for the same species but at distinct topographic positions. We assess the global significance of these hydrologic mechanisms by estimating root water-uptake depths using an inverse model, based on observed productivity and atmosphere, at 30″ (∼1-km) global grids to capture the topography critical to soil hydrology. The resulting patterns of plant rooting depth bear a strong topographic and hydrologic signature at landscape to global scales. They underscore a fundamental plant–water feedback pathway that may be critical to understanding plant-mediated global change.
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Mendoza, Pablo A., Martyn P. Clark, Naoki Mizukami, Andrew J. Newman, Michael Barlage, Ethan D. Gutmann, Roy M. Rasmussen, Balaji Rajagopalan, Levi D. Brekke, and Jeffrey R. Arnold. "Effects of Hydrologic Model Choice and Calibration on the Portrayal of Climate Change Impacts." Journal of Hydrometeorology 16, no. 2 (April 1, 2015): 762–80. http://dx.doi.org/10.1175/jhm-d-14-0104.1.
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Abstract The assessment of climate change impacts on water resources involves several methodological decisions, including choices of global climate models (GCMs), emission scenarios, downscaling techniques, and hydrologic modeling approaches. Among these, hydrologic model structure selection and parameter calibration are particularly relevant and usually have a strong subjective component. The goal of this research is to improve understanding of the role of these decisions on the assessment of the effects of climate change on hydrologic processes. The study is conducted in three basins located in the Colorado headwaters region, using four different hydrologic model structures [PRMS, VIC, Noah LSM, and Noah LSM with multiparameterization options (Noah-MP)]. To better understand the role of parameter estimation, model performance and projected hydrologic changes (i.e., changes in the hydrology obtained from hydrologic models due to climate change) are compared before and after calibration with the University of Arizona shuffled complex evolution (SCE-UA) algorithm. Hydrologic changes are examined via a climate change scenario where the Community Climate System Model (CCSM) change signal is used to perturb the boundary conditions of the Weather Research and Forecasting (WRF) Model configured at 4-km resolution. Substantial intermodel differences (i.e., discrepancies between hydrologic models) in the portrayal of climate change impacts on water resources are demonstrated. Specifically, intermodel differences are larger than the mean signal from the CCSM–WRF climate scenario examined, even after the calibration process. Importantly, traditional single-objective calibration techniques aimed to reduce errors in runoff simulations do not necessarily improve intermodel agreement (i.e., same outputs from different hydrologic models) in projected changes of some hydrological processes such as evapotranspiration or snowpack.
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Weiskel, P. K., D. M. Wolock, P. J. Zarriello, R. M. Vogel, S. B. Levin, and R. M. Lent. "Hydroclimatic regimes: a distributed water-balance framework for hydrologic assessment, classification, and management." Hydrology and Earth System Sciences 18, no. 10 (October 1, 2014): 3855–72. http://dx.doi.org/10.5194/hess-18-3855-2014.
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Abstract. Runoff-based indicators of terrestrial water availability are appropriate for humid regions, but have tended to limit our basic hydrologic understanding of drylands – the dry-subhumid, semiarid, and arid regions which presently cover nearly half of the global land surface. In response, we introduce an indicator framework that gives equal weight to humid and dryland regions, accounting fully for both vertical (precipitation + evapotranspiration) and horizontal (groundwater + surface-water) components of the hydrologic cycle in any given location – as well as fluxes into and out of landscape storage. We apply the framework to a diverse hydroclimatic region (the conterminous USA) using a distributed water-balance model consisting of 53 400 networked landscape hydrologic units. Our model simulations indicate that about 21% of the conterminous USA either generated no runoff or consumed runoff from upgradient sources on a mean-annual basis during the 20th century. Vertical fluxes exceeded horizontal fluxes across 76% of the conterminous area. Long-term-average total water availability (TWA) during the 20th century, defined here as the total influx to a landscape hydrologic unit from precipitation, groundwater, and surface water, varied spatially by about 400 000-fold, a range of variation ~100 times larger than that for mean-annual runoff across the same area. The framework includes but is not limited to classical, runoff-based approaches to water-resource assessment. It also incorporates and reinterprets the green- and blue-water perspective now gaining international acceptance. Implications of the new framework for several areas of contemporary hydrology are explored, and the data requirements of the approach are discussed in relation to the increasing availability of gridded global climate, land-surface, and hydrologic data sets.
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Vu, T. T., J. Kiesel, B. Guse, and N. Fohrer. "Towards an improved understanding of hydrological change – linking hydrologic metrics and multiple change point tests." Journal of Water and Climate Change 10, no. 4 (November 16, 2018): 743–58. http://dx.doi.org/10.2166/wcc.2018.068.
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Abstract Understanding the connections between climate, anthropogenic impacts, and hydrology is fundamental for assessing future climate change. However, a comprehensive methodology is lacking to understand significant changes in the discharge regime and their causes. We propose an approach that links change point tests with hydrologic metrics applied to two Vietnamese catchments where both climatic and anthropogenic changes are observed. The change points in discharge series are revealed by six widely used change point tests. Then, 171 hydrologic metrics are investigated to evaluate all possible hydrological changes that occurred between the pre- and post-change point period. The tests showed sufficient capabilities to detect hydrological changes caused by precipitation alterations and damming. Linking the change point tests to the hydrological metrics had three benefits: (1) the significance of each detected change point was evaluated, (2) we found which test responds to which hydrologic metric, and (3) we were able to disentangle the hydrological impacts of the climatic and anthropogenic changes. Due to its objectivity, the presented method can improve the interpretation of anthropogenic changes and climate change impacts on the hydrological system.
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Foster, Tammy E., and J. Renee Brooks. "Long-term trends in growth of Pinus palustris and Pinus elliottii along a hydrological gradient in central Florida." Canadian Journal of Forest Research 31, no. 10 (October 1, 2001): 1661–70. http://dx.doi.org/10.1139/x01-100.
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Forest species composition in Florida is sensitive to changes in hydrology that accompany small shifts in elevation. In this study, we use dendrochronological techniques to determine how the growth of Pinus elliottii var. elliottii Engelm. (slash pine) and Pinus palustris Mill. (longleaf pine) along a hydrologic gradient from mesic flatwoods to xeric sandhills responds to fluctuations in climate (temperature, precipitation, river flow, and Palmer drought severity index). Interspecies and intraspecies comparisons of growth responses were made between a xeric P. palustris plot, a transition zone plot containing both species, and a mesic P. elliottii plot. Growth of P. elliottii individuals was negatively correlated with increased water availability on sites with a shallow water table (<1 m) but positively correlated on sites with a deeper water table. The basal area increment (BAI) of P. elliottii individuals on the drier site was 41% lower than the BAI of individuals on the wetter site. In contrast, the growth response of P. palustris, which only grows in the dryer sites, was similar along the hydrologic gradient, with growth being positively related to water availability and only a 16% lower BAI on the driest site.
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Anandhi, Aavudai, Christy Crandall, and Chance Bentley. "Hydrologic Characteristics of Streamflow in the Southeast Atlantic and Gulf Coast Hydrologic Region during 1939–2016 and Conceptual Map of Potential Impacts." Hydrology 5, no. 3 (August 7, 2018): 42. http://dx.doi.org/10.3390/hydrology5030042.
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Streamflow is one the most important variables controlling and maintaining aquatic ecosystem integrity, diversity, and sustainability. This study identified and quantified changes in 34 hydrologic characteristics and parameters at 30 long term (1939–2016) discharge stations in the Southeast Atlantic and Gulf Coast Hydrologic Region (Region 3) using Indicators of Hydrologic Alteration (IHA) variables. The southeastern United States (SEUS) is a biodiversity hotspot, and the region has experienced a number of rapid land use/land cover changes with multiple primary drivers. Studies in the SEUS have been mostly localized on specific rivers, reservoir catchments and/or species, but the overall region has not been assessed for the long-term period of 1939–2016 for multiple hydrologic characteristic parameters. The objectives of the study were to provide an overview of multiple river basins and 31 hydrologic characteristic parameters of streamflow in Region 3 for a longer period and to develop a conceptual map of impacts of selected stressors and changes in hydrology and climate in the SEUS. A seven step procedure was used to accomplish these objectively: Step 1: Download data from the 30 USGS gauging stations. Steps 2 and 3: Select and analyze the 31 IHA parameters using boxplots, scatter plots, and PDFs. Steps 4 and 5: Synthesize the drivers of changes and alterations and the various change points in streamflow in the literature. Step 6: Synthesize the climate of the SEUS in terms of temperature and precipitation changes. Step 7: Develop a conceptual map of impacts of selected stressors on hydrology using Driver–Pressure–State-Impact–Response (DPSIR) framework and IHA parameters. The 31 IHA parameters were analyzed. The meta-analysis of literature in the SEUS revealed the precipitation changes observed ranged from −30% to +35% and temperature changes from −2 °C to 6 °C by 2099. The fiftieth percentile of the Global Climate Models (GCM) predict no precipitation change and an increase in the temperature of 2.5 °C in the region by 2099. Among the GCMs, the 5th and 95th percentile of precipitation changes range between −40% and 110% and temperature changes between −2 °C and 6 °C by 2099. Meta-analysis of land use/land cover show the region has experienced changes. A number of rapid land use/land cover changes in 1957, 1970, and 1998 are some of the change points documented in the literature for precipitation and streamflow in the region. A conceptual map was developed to represent the impacts of selected drivers and the changes in hydrology and climate in the study region for three land use/land cover categories in three different periods.
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Burke, Marianne K., B. Graeme Lockaby, and William H. Conner. "Aboveground production and nutrient circulation along a flooding gradient in a South Carolina Coastal Plain forest." Canadian Journal of Forest Research 29, no. 9 (September 15, 1999): 1402–18. http://dx.doi.org/10.1139/x99-111.
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Relative to effects of flooding, little is known about the influence of hydrology-nutrient interactions on aboveground net primary production (NPP) in forested wetlands. We found that nutrient circulation and NPP were closely related along a complex physical, chemical, and hydrologic gradient in a bottomland hardwood forest with four distinct communities. Aboveground biomass, NPP, biomass partitioning to stem production, growth efficiency, and soil macronutrient availability were greatest in the flooded zone, possibly because of the stable hydrologic regime. In the wet transition zone, trees were least productive, nutrient use efficiency was highest, and N retranslocation from foliage before abscission was "complete." Wet and dry transition zones had the lowest litterfall quality. Soil organic matter was negatively correlated with extractable NH4-N plus NO3-N before in situ incubations and positively correlated with litterfall lignin/N ratios. Lignin/P and C/N ratios were positively correlated with exchangeable soil Ca and Mg, cation exchange capacity, and clay content and negatively correlated with extractable soil P. We concluded that periodic flooding and associated widely fluctuating soil chemistry resulted in disequilibrium between the plant community and environmental conditions, which led to nutrient deficiency and low NPP in the transition zones compared with the continuously flooded and mesic zones.
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Voisin, Nathalie, Andrew W. Wood, and Dennis P. Lettenmaier. "Evaluation of Precipitation Products for Global Hydrological Prediction." Journal of Hydrometeorology 9, no. 3 (June 1, 2008): 388–407. http://dx.doi.org/10.1175/2007jhm938.1.
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Abstract Accurate precipitation data are critical for hydrologic prediction, yet outside the developed world in situ networks are so sparse as to make alternative methods of precipitation estimation essential. Several such alternative precipitation products that would be adequate to drive hydrologic prediction models at regional and global scales are evaluated. As a benchmark, a gridded station-based dataset is used, which is compared with the global 40-yr ECMWF Re-Analysis (ERA-40), and a satellite-based dataset [i.e., the Global Precipitation Climatology Project One-Degree Daily (GPCP 1DD)]. Each dataset, with a common set of other meteorological forcings aside from precipitation, was used to force the Variable Infiltration Capacity (VIC) macroscale hydrology model globally for the 1997–99 period for which the three datasets overlapped. The three precipitation datasets and simulated hydrological variables (i.e., soil moisture, runoff, evapotranspiration, and snow water equivalent) are compared in terms of the implied water balances of the continents, and for prediction of streamflow for nine large river basins. The evaluations are in general agreement with previous but more local evaluations of precipitation products and water balances: the precipitation datasets agree reasonably on the seasonality but less on monthly anomalies. Furthermore, the largest differences in precipitation are in mountainous regions and regions where in situ networks are sparse (such as Africa). Derived runoff is highly sensitive to differences in precipitation forcings. At a global level, all three simulations result in water budgets that are within the range of other water balance climatologies. Although uncertainties in the three datasets preclude an evaluation of which one has the lowest errors, overall ERA-40 is preferred because of its agreement with the station-based dataset in locations where the station density is high, its periodic availability, and its temporal resolution.
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Kollet, Stefan, Fabian Gasper, Slavko Brdar, Klaus Goergen, Harrie-Jan Hendricks-Franssen, Jessica Keune, Wolfgang Kurtz, et al. "Introduction of an Experimental Terrestrial Forecasting/Monitoring System at Regional to Continental Scales Based on the Terrestrial Systems Modeling Platform (v1.1.0)." Water 10, no. 11 (November 21, 2018): 1697. http://dx.doi.org/10.3390/w10111697.
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Operational weather and flood forecasting has been performed successfully for decades and is of great socioeconomic importance. Up to now, forecast products focus on atmospheric variables, such as precipitation, air temperature and, in hydrology, on river discharge. Considering the full terrestrial system from groundwater across the land surface into the atmosphere, a number of important hydrologic variables are missing especially with regard to the shallow and deeper subsurface (e.g., groundwater), which are gaining considerable attention in the context of global change. In this study, we propose a terrestrial monitoring/forecasting system using the Terrestrial Systems Modeling Platform (TSMP) that predicts all essential states and fluxes of the terrestrial hydrologic and energy cycles from groundwater into the atmosphere. Closure of the terrestrial cycles provides a physically consistent picture of the terrestrial system in TSMP. TSMP has been implemented over a regional domain over North Rhine-Westphalia and a continental domain over Europe in a real-time forecast/monitoring workflow. Applying a real-time forecasting/monitoring workflow over both domains, experimental forecasts are being produced with different lead times since the beginning of 2016. Real-time forecast/monitoring products encompass all compartments of the terrestrial system including additional hydrologic variables, such as plant available soil water, groundwater table depth, and groundwater recharge and storage.
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Levine, Xavier J., and William R. Boos. "A Mechanism for the Response of the Zonally Asymmetric Subtropical Hydrologic Cycle to Global Warming." Journal of Climate 29, no. 21 (October 13, 2016): 7851–67. http://dx.doi.org/10.1175/jcli-d-15-0826.1.
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Abstract Time-mean, zonally asymmetric circulations (hereafter referred to as stationary circulations) maintain intense hydrologic contrasts in Earth’s subtropics in the present climate, especially between monsoon regions and deserts during local summer. Such zonal contrasts in hydrology generally increase in comprehensive GCM simulations of a warming climate, yet a full understanding of stationary circulations and their contribution to the hydrologic cycle in present and future climates is lacking. This study uses an idealized moist GCM to investigate the response of subtropical stationary circulations to global warming. Stationary circulations are forced by a prescribed subtropical surface heat source, and atmospheric infrared opacity is varied to produce a wide range of climates with global-mean surface temperatures between 267 and 319 K. The strength of stationary circulations varies nonmonotonically with global mean temperature in these simulations. Zonal asymmetries in precipitation increase with temperature in climates colder than or comparable to that of Earth but remain steady or weaken in warmer climates. A novel mechanism is proposed in which this behavior is caused by the changes in tropopause height and zonal SST gradients expected to occur with global warming. Casting this mechanism in terms of the first-baroclinic mode of the tropical troposphere produces a theory that quantitatively captures the nonmonotonic dependence of stationary circulation strength on global mean temperature. Zonally asymmetric changes in precipitation minus surface evaporation (P − E) are predicted by combining this dynamical theory with the tropospheric moisture changes expected if relative humidity remains constant.
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Sun, Fubao, Michael L. Roderick, and Graham D. Farquhar. "Rainfall statistics, stationarity, and climate change." Proceedings of the National Academy of Sciences 115, no. 10 (February 20, 2018): 2305–10. http://dx.doi.org/10.1073/pnas.1705349115.
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There is a growing research interest in the detection of changes in hydrologic and climatic time series. Stationarity can be assessed using the autocorrelation function, but this is not yet common practice in hydrology and climate. Here, we use a global land-based gridded annual precipitation (hereafter P) database (1940–2009) and find that the lag 1 autocorrelation coefficient is statistically significant at around 14% of the global land surface, implying nonstationary behavior (90% confidence). In contrast, around 76% of the global land surface shows little or no change, implying stationary behavior. We use these results to assess change in the observed P over the most recent decade of the database. We find that the changes for most (84%) grid boxes are within the plausible bounds of no significant change at the 90% CI. The results emphasize the importance of adequately accounting for natural variability when assessing change.
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Wilkie, K. M. K., B. Chapligin, H. Meyer, S. Burns, S. Petsch, and J. Brigham-Grette. "Modern isotope hydrology and controls on δD of plant leaf waxes at Lake El'gygytgyn, NE Russia." Climate of the Past Discussions 8, no. 4 (August 16, 2012): 3719–64. http://dx.doi.org/10.5194/cpd-8-3719-2012.
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Abstract. Stable isotope data from lipid biomarkers and diatom silica recovered from lake sediment cores hold great promise for paleoclimate and paleohydrological reconstructions. However, these records rely on accurate calibration with modern precipitation and hydrologic processes. Here we investigate the stable isotopic composition of modern precipitation, streams, lake water and ice cover, and use these data to constrain isotope systematics of the Lake El'gygytgyn basin hydrology. Compound specific hydrogen isotope ratios determined from modern vegetation are compared with modern precipitation and lake core top sediments. Multi-species net (apparent) fractionation values between source water (precipitation) and leaf wax lipids (mean value is −105 ± 13‰) agree with previous results in arid environments and provide a basis for application of this proxy downcore. We conclude that although there may be some bias towards winter precipitation signal, overall leaf wax lipids record annual average precipitation within the El'gygytgyn Basin.
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Neupane, Ram P., Jan F. Adamowski, Joseph D. White, and Sandeep Kumar. "Future streamflow simulation in a snow-dominated Rocky Mountain headwater catchment." Hydrology Research 49, no. 4 (November 9, 2017): 1172–90. http://dx.doi.org/10.2166/nh.2017.024.
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Abstract The Rocky Mountains in North America are comprised of headwater snow catchments that provide sustained seasonal flow downstream. Changes in streamflow over the last half century in these basins may be associated with changing climate with increased temperature and variable precipitation, shifting seasonal hydrology. We investigated potential changes in future hydrology in a Rocky Mountain headwater catchment by simulating water budgets of the Athabasca River located in Jasper National Park, Canada. Potential hydrologic changes were predicted using a calibrated version of the Soil and Water Assessment Tool (SWAT). Future discharge and other parts of the catchment water budget were projected based on the global circulation model (GCM) derived from the Special Report on Emission Scenarios (SRES) for the latter part of the century (2081–2099). A projected decrease in future precipitation resulted in reduced mean annual streamflow, by up to 86%, compared to the baseline period for the catchment. Projected summer streamflow decreased from 58 to 39%. Streamflow increased from 13 to 26% during the spring, dampening the dominance of summer peak-flow hydrology. Colder winters for the future scenarios increase the overall proportion of precipitation as winter snowfall. However, dramatically lower precipitation estimated for this basin will drive water limits for the future.
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Sheffield, Justin, Gopi Goteti, and Eric F. Wood. "Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling." Journal of Climate 19, no. 13 (July 1, 2006): 3088–111. http://dx.doi.org/10.1175/jcli3790.1.
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Abstract Understanding the variability of the terrestrial hydrologic cycle is central to determining the potential for extreme events and susceptibility to future change. In the absence of long-term, large-scale observations of the components of the hydrologic cycle, modeling can provide consistent fields of land surface fluxes and states. This paper describes the creation of a global, 50-yr, 3-hourly, 1.0° dataset of meteorological forcings that can be used to drive models of land surface hydrology. The dataset is constructed by combining a suite of global observation-based datasets with the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. Known biases in the reanalysis precipitation and near-surface meteorology have been shown to exert an erroneous effect on modeled land surface water and energy budgets and are thus corrected using observation-based datasets of precipitation, air temperature, and radiation. Corrections are also made to the rain day statistics of the reanalysis precipitation, which have been found to exhibit a spurious wavelike pattern in high-latitude wintertime. Wind-induced undercatch of solid precipitation is removed using the results from the World Meteorological Organization (WMO) Solid Precipitation Measurement Intercomparison. Precipitation is disaggregated in space to 1.0° by statistical downscaling using relationships developed with the Global Precipitation Climatology Project (GPCP) daily product. Disaggregation in time from daily to 3 hourly is accomplished similarly, using the Tropical Rainfall Measuring Mission (TRMM) 3-hourly real-time dataset. Other meteorological variables (downward short- and longwave radiation, specific humidity, surface air pressure, and wind speed) are downscaled in space while accounting for changes in elevation. The dataset is evaluated against the bias-corrected forcing dataset of the second Global Soil Wetness Project (GSWP2). The final product provides a long-term, globally consistent dataset of near-surface meteorological variables that can be used to drive models of the terrestrial hydrologic and ecological processes for the study of seasonal and interannual variability and for the evaluation of coupled models and other land surface prediction schemes.
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Kuechler, Rony R., Lydie M. Dupont, and Enno Schefuß. "Hybrid insolation forcing of Pliocene monsoon dynamics in West Africa." Climate of the Past 14, no. 1 (January 16, 2018): 73–84. http://dx.doi.org/10.5194/cp-14-73-2018.
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Abstract. The Pliocene is regarded as a potential analogue for future climate with conditions generally warmer-than-today and higher-than-preindustrial atmospheric CO2 levels. Here we present the first orbitally resolved records of continental hydrology and vegetation changes from West Africa for two Pliocene time intervals (5.0–4.6 Ma, 3.6–3.0 Ma), which we compare with records from the last glacial cycle (Kuechler et al., 2013). Our results indicate that changes in local insolation alone are insufficient to explain the full degree of hydrologic variations. Generally two modes of interacting insolation forcings are observed: during eccentricity maxima, when precession was strong, the West African monsoon was driven by summer insolation; during eccentricity minima, when precession-driven variations in local insolation were minimal, obliquity-driven changes in the summer latitudinal insolation gradient became dominant. This hybrid monsoonal forcing concept explains orbitally controlled tropical climate changes, incorporating the forcing mechanism of latitudinal gradients for the Pliocene, which probably increased in importance during subsequent Northern Hemisphere glaciations.
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Herman, J. D., J. B. Kollat, P. M. Reed, and T. Wagener. "From maps to movies: high resolution time-varying sensitivity analysis for spatially distributed watershed models." Hydrology and Earth System Sciences Discussions 10, no. 8 (August 19, 2013): 10775–808. http://dx.doi.org/10.5194/hessd-10-10775-2013.
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Abstract. Distributed watershed models are now widely used in practice to simulate runoff responses at high spatial and temporal resolutions. Counter to this purpose, diagnostic analyses of distributed models currently aggregate performance measures in space and/or time and are thus disconnected from the models' operational and scientific goals. To address this disconnect, this study contributes a novel approach for computing and visualizing time-varying global sensitivity indices for spatially distributed model parameters. The high-resolution model diagnostics employ the method of Morris to identify evolving patterns in dominant model processes at sub-daily timescales over a six-month period. The method is demonstrated on the United States National Weather Service's Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) in the Blue River watershed, Oklahoma, USA. Three hydrologic events are selected from within the six-month period to investigate the patterns in spatiotemporal sensitivities that emerge as a function of forcing patterns as well as wet-to-dry transitions. Surprisingly, events with similar magnitudes and durations exhibit significantly different performance controls in space and time, indicating that the diagnostic inferences drawn from representative events will be heavily biased by the a priori selection of those events. By contrast, this study demonstrates high-resolution time-varying sensitivity analysis, requiring no assumptions regarding representative events and allowing modelers to identify transitions between modeled hydrologic regimes a posteriori. The proposed approach details the dynamics of parameter sensitivity in nearly continuous time, providing critical diagnostic insights into the underlying model processes driving predictions. Furthermore, the approach offers the potential to identify transition points between hydrologic regimes under nonstationarity.
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Beltaos, Spyros, and Brian C. Burrell. "Climatic change and river ice breakup." Canadian Journal of Civil Engineering 30, no. 1 (February 1, 2003): 145–55. http://dx.doi.org/10.1139/l02-042.
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The flow hydrograph, thickness of the winter ice cover, and stream morphology are three climate-influenced factors that govern river ice processes in general and ice breakup and jamming in particular. Considerable warming and changes in precipitation patterns, as predicted by general circulation models (GCMs) for various increased greenhouse-gas scenarios, would affect the length and duration of the ice season and the timing and severity of ice breakup. Climate-induced changes to river ice processes and the associated hydrologic regimes can produce physical, biological, and socioeconomic effects. Current knowledge of climatic impacts on the ice breakup regime of rivers and the future effects of a changing climate are discussed.Key words: breakup, climate change, global warming, greenhouse effect, hydrology, ice, ice jam, impacts, prediction, river ice.
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Drăguşin, V., M. Staubwasser, D. L. Hoffmann, V. Ersek, B. P. Onac, and D. Veres. "Constraining Holocene hydrological changes in the Carpathian-Balkan region using speleothem δ<sup>18</sup>O and pollen-based temperature reconstructions." Climate of the Past Discussions 10, no. 1 (January 22, 2014): 381–427. http://dx.doi.org/10.5194/cpd-10-381-2014.
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Abstract. Here we present a new speleothem isotope record (POM2) from Ascunsă Cave (Romania) that provides new data on past climate changes in the Carpathian-Balkan region from 8.2 ka until present. This paper describes an approach towards constraining the effect of temperature changes on calcite δ18O values in stalagmite POM2 over the course of the Middle Holocene (6–4 ka), and across the 8.2 and 3.2 ka rapid climate change events. Independent pollen temperature reconstructions are used to constrain the temperature-dependent component of total isotopic change in speleothem calcite. This includes the temperature-dependent composition of rain water attained during vapour condensation and during calcite precipitation at the given cave temperature. The only prior assumptions are that pollen-derived average annual temperature reflects average cave temperature, and that pollen-derived coldest and warmest month temperatures reflect the range of condensation temperatures of rain at the cave site. This approach constrains a range of values between which speleothem isotopic changes should be found if controlled only by surface temperature variations at the cave site. Deviations of measured δ18Oc values from the calculated range are interpreted towards large-scale hydrologic change independent of local temperature. Following this approach, we show that an additional 0.6‰ enrichment of δ18Oc in the POM2 stalagmite was caused by changing hydrological patterns in SW Romania during the Middle Holocene. Further, by extending the calculations to other speleothem records from around the entire Mediterranean Basin, it appears that all Eastern Mediterranean speleothems recorded a similar isotopic enrichment due to changing hydrology, whereas all changes recorded in speleothems from the Western Mediterranean are fully explained by temperature variation alone. This highlights a different hydrological evolution between the two sides of the Mediterranean. Our results also demonstrate that during the 8.2 ka event, POM2 stable isotope data fit the temperature-constrained isotopic variability, with only little hydrologic change at most. In the case of the 3.2 ka event, the hydrological factor is more evident. This implies a potentially different rainfall pattern in the Southern Carpathian region during this event at the end of the Bronze Age. This study brings new evidence for disturbances in Eastern Mediterranean hydrology during the Holocene, bearing importance for the understanding of climate pressure on agricultural activities in this area.
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Ben Khediri, Wiem, and Gilles Drogue. "Quel est l’impact de l’échantillonnage spatial des précipitations et de l’évapotranspiration potentielle sur le pouvoir prédictif d’un modèle hydrologique empirique ?" Climatologie 12 (2015): 1–24. http://dx.doi.org/10.4267/climatologie.1095.
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Evaluer le pouvoir prédictif d’un modèle pluie-débit est crucial en hydrologie de surface car cela permet de borner les limites de son utilisation en extrapolation, autrement dit dans des conditions hydro-météorologiques et géographiques différentes de celles de la phase d’apprentissage du modèle. En outre, ce pouvoir prédictif est susceptible d’être dépendant de la connaissance climatique des bassins et de la complexité de la relation pluie-débit. Pour tester la réaction d’un modèle hydrologique empirique à la stratégie d’échantillonnage de ses variables d’entrée climatiques, une étude de sensibilité a été appliquée au modèle hydrologique global GR4J. Celui-ci a fait l’objet d’un calage dynamique en utilisant une information climatique d’origine et de densité spatiale variables pour le calcul de ses entrées atmosphériques (précipitations et évapotranspiration potentielle). Les hydrogrammes journaliers calculés après recalage ont été comparés aux hydrogrammes journaliers observés sur un échantillon de 148 bassins faisant l’objet d’un suivi hydrométrique dans la partie française du bassin Rhin-Meuse. Les résultats de l’analyse montrent que le modèle GR4J réagit fortement au changement d’entrées de précipitations (précipitations au poste vs précipitations distribuées) en améliorant la définition des paramètres et en identifiant mieux le comportement hydrologique du bassin modélisé en conditions jaugées comme en conditions non jaugées. A l’inverse, le modèle GR4J montre une insensibilité au changement de densité spatiale du réseau de postes météorologiques utilisé pour calculer l’évapotranspiration potentielle prescrite au modèle et ne tire donc pas partie d’une concentration de postes pour simuler les débits en conditions jaugées comme en conditions non jaugées.
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Voisin, Nathalie, Florian Pappenberger, Dennis P. Lettenmaier, Roberto Buizza, and John C. Schaake. "Application of a Medium-Range Global Hydrologic Probabilistic Forecast Scheme to the Ohio River Basin." Weather and Forecasting 26, no. 4 (August 1, 2011): 425–46. http://dx.doi.org/10.1175/waf-d-10-05032.1.
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Abstract A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003–07. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis temperatures and winds, and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF Ensemble Prediction System (EPS) 10-day ensemble forecast. A parallel setup was used where ECMWF EPS forecasts were interpolated to the spatial scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effects of the initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The hydrologic prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. The initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.
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Elshafei, Y., M. Sivapalan, M. Tonts, and M. R. Hipsey. "A prototype framework for models of socio-hydrology: identification of key feedback loops with application to two Australian case-studies." Hydrology and Earth System Sciences Discussions 11, no. 1 (January 14, 2014): 629–89. http://dx.doi.org/10.5194/hessd-11-629-2014.
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Abstract. It is increasingly acknowledged that, in order to sustainably manage global freshwater resources, it is critical that we better understand the nature of human-hydrology interactions at the broader catchment system-scale. Yet to date, a generic conceptual framework for building models of catchment systems that include adequate representation of socioeconomic systems – and the dynamic feedbacks between human and natural systems – has remained elusive. In an attempt to work towards such a model, this paper outlines a generic framework for a model of socio-hydrology that posits a novel construct, a composite Community Sensitivity state variable, as a key link to elucidate the drivers of behavioural response in a hydrological context. The framework provides for both macro-scale contextual parameters, which allow it to be applied across climate, socioeconomic and political gradients, and catchment-specific conditions, by way of tailored "closure relationships", in order to ensure that site-specific and application-specific contexts of socio-hydrologic problems can be accommodated. To demonstrate how such a framework would be applied, two different socio-hydrological case studies, taken from the Australian experience, are presented and discussed. It is envisioned that the application of this framework across study sites and gradients will aid in developing our understanding of the fundamental interactions and feedbacks in such complex human-hydrology systems, and allow hydrologists to participate in the growing field of social-ecological systems modelling.
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Raleigh, M. S., J. D. Lundquist, and M. P. Clark. "Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework." Hydrology and Earth System Sciences Discussions 11, no. 12 (December 16, 2014): 13745–95. http://dx.doi.org/10.5194/hessd-11-13745-2014.
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Abstract. Physically based models provide insights into key hydrologic processes, but are associated with uncertainties due to deficiencies in forcing data, model parameters, and model structure. Forcing uncertainty is enhanced in snow-affected catchments, where weather stations are scarce and prone to measurement errors, and meteorological variables exhibit high variability. Hence, there is limited understanding of how forcing error characteristics affect simulations of cold region hydrology. Here we employ global sensitivity analysis to explore how different error types (i.e., bias, random errors), different error distributions, and different error magnitudes influence physically based simulations of four snow variables (snow water equivalent, ablation rates, snow disappearance, and sublimation). We use Sobol' global sensitivity analysis, which is typically used for model parameters, but adapted here for testing model sensitivity to co-existing errors in all forcings. We quantify the Utah Energy Balance model's sensitivity to forcing errors with 1 520 000 Monte Carlo simulations across four sites and four different scenarios. Model outputs were generally (1) more sensitive to forcing biases than random errors, (2) less sensitive to forcing error distributions, and (3) sensitive to different forcings depending on the relative magnitude of errors. For typical error magnitudes, precipitation bias was the most important factor for snow water equivalent, ablation rates, and snow disappearance timing, but other forcings had a significant impact depending on forcing error magnitudes. Additionally, the relative importance of forcing errors depended on the model output of interest. Sensitivity analysis can reveal which forcing error characteristics matter most for hydrologic modeling.
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Loaiciga, Hugo A., Juan B. Valdes, Richard Vogel, Jeff Garvey, and Harry Schwarz. "Global warming and the hydrologic cycle." Journal of Hydrology 174, no. 1-2 (January 1996): 83–127. http://dx.doi.org/10.1016/0022-1694(95)02753-x.
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McMahon, T. A., M. C. Peel, and D. J. Karoly. "Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation." Hydrology and Earth System Sciences 19, no. 1 (January 21, 2015): 361–77. http://dx.doi.org/10.5194/hess-19-361-2015.
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Abstract. The objective of this paper is to identify better performing Coupled Model Intercomparison Project phase 3 (CMIP3) global climate models (GCMs) that reproduce grid-scale climatological statistics of observed precipitation and temperature for input to hydrologic simulation over global land regions. Current assessments are aimed mainly at examining the performance of GCMs from a climatology perspective and not from a hydrology standpoint. The performance of each GCM in reproducing the precipitation and temperature statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the Climatic Research Unit (CRU) 3.10 gridded data set and re-sampled to the resolution of each GCM for comparison. Observed and GCM-based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen–Geiger climate type were compared. The main metrics for assessing GCM performance were the Nash–Sutcliffe efficiency (NSE) index and root mean square error (RMSE) between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following better performing GCMs from a hydrologic perspective: HadCM3 (Hadley Centre for Climate Prediction and Research), MIROCm (Model for Interdisciplinary Research on Climate) (Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change), MIUB (Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model and Data group), MPI (Max Planck Institute for Meteorology) and MRI (Japan Meteorological Research Institute). The future response of these GCMs was found to be representative of the 44 GCM ensemble members which confirms that the selected GCMs are reasonably representative of the range of future GCM projections.
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Masood, M., P. J. F. Yeh, N. Hanasaki, and K. Takeuchi. "Model study of the impacts of future climate change on the hydrology of Ganges–Brahmaputra–Meghna basin." Hydrology and Earth System Sciences 19, no. 2 (February 4, 2015): 747–70. http://dx.doi.org/10.5194/hess-19-747-2015.
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Abstract. The intensity, duration, and geographic extent of floods in Bangladesh mostly depend on the combined influences of three river systems, the Ganges, Brahmaputra and Meghna (GBM). In addition, climate change is likely to have significant effects on the hydrology and water resources of the GBM basin and may ultimately lead to more serious floods in Bangladesh. However, the assessment of climate change impacts on the basin-scale hydrology by using well-calibrated hydrologic modeling has seldom been conducted in the GBM basin due to the lack of observed data for calibration and validation. In this study, a macroscale hydrologic model H08 has been applied over the basin at a relatively fine grid resolution (10 km) by integrating the fine-resolution DEM (digital elevation model) data for accurate river networks delineation. The model has been calibrated via the analysis of model parameter sensitivity and validated based on long-term observed daily streamflow data. The impacts of climate change (considering a high-emissions path) on runoff, evapotranspiration, and soil moisture are assessed by using five CMIP5 (Coupled Model Intercomparison Project Phase 5) GCMs (global circulation models) through three time-slice experiments; the present-day (1979–2003), the near-future (2015–2039), and the far-future (2075–2099) periods. Results show that, by the end of 21st century, (a) the entire GBM basin is projected to be warmed by ~4.3 °C; (b) the changes of mean precipitation (runoff) are projected to be +16.3% (+16.2%), +19.8% (+33.1%), and +29.6% (+39.7%) in the Brahmaputra, Ganges, and Meghna, respectively; and (c) evapotranspiration is projected to increase for the entire GBM (Brahmaputra: +16.4%, Ganges: +13.6%, Meghna: +12.9%) due to increased net radiation as well as warmer temperature. Future changes of hydrologic variables are larger in the dry season (November–April) than in the wet season (May–October). Amongst the three basins, the Meghna shows the highest increase in runoff, indicating higher possibility of flood occurrence. The uncertainty due to the specification of key model parameters in model predictions is found to be low for estimated runoff, evapotranspiration and net radiation. However, the uncertainty in estimated soil moisture is rather large with the coefficient of variation ranging from 14.4 to 31% among the three basins.
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Raleigh, M. S., J. D. Lundquist, and M. P. Clark. "Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework." Hydrology and Earth System Sciences 19, no. 7 (July 20, 2015): 3153–79. http://dx.doi.org/10.5194/hess-19-3153-2015.
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Abstract. Physically based models provide insights into key hydrologic processes but are associated with uncertainties due to deficiencies in forcing data, model parameters, and model structure. Forcing uncertainty is enhanced in snow-affected catchments, where weather stations are scarce and prone to measurement errors, and meteorological variables exhibit high variability. Hence, there is limited understanding of how forcing error characteristics affect simulations of cold region hydrology and which error characteristics are most important. Here we employ global sensitivity analysis to explore how (1) different error types (i.e., bias, random errors), (2) different error probability distributions, and (3) different error magnitudes influence physically based simulations of four snow variables (snow water equivalent, ablation rates, snow disappearance, and sublimation). We use the Sobol' global sensitivity analysis, which is typically used for model parameters but adapted here for testing model sensitivity to coexisting errors in all forcings. We quantify the Utah Energy Balance model's sensitivity to forcing errors with 1 840 000 Monte Carlo simulations across four sites and five different scenarios. Model outputs were (1) consistently more sensitive to forcing biases than random errors, (2) generally less sensitive to forcing error distributions, and (3) critically sensitive to different forcings depending on the relative magnitude of errors. For typical error magnitudes found in areas with drifting snow, precipitation bias was the most important factor for snow water equivalent, ablation rates, and snow disappearance timing, but other forcings had a more dominant impact when precipitation uncertainty was due solely to gauge undercatch. Additionally, the relative importance of forcing errors depended on the model output of interest. Sensitivity analysis can reveal which forcing error characteristics matter most for hydrologic modeling.
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Trettin, C. C., R. Laiho, K. Minkkinen, and J. Laine. "Influence of climate change factors on carbon dynamics in northern forested peatlands." Canadian Journal of Soil Science 86, Special Issue (March 1, 2006): 269–80. http://dx.doi.org/10.4141/s05-089.
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Peatlands are carbon-accumulating wetland ecosystems, developed through an imbalance among organic matter production and decomposition processes. Soil saturation is the principal cause of anoxic conditions that constrain organic matter decay. Accordingly, changes in the hydrologic regime will affect the carbon (C) dynamics in forested peatlands. Our objective is to review ecological studies and experiments on managed peatlands that provide a basis for assessing the effects of an altered hydrology on C dynamics. We conclude that climate change influences will be mediated primarily through the hydrologic cycle. A lower water table resulting from altered precipitation patterns and increased atmospheric temperature may be expected to decrease soil CH4 and increase CO2 emissions from the peat surface. Correspondingly, the C balance in forested peatlands is also sensitive to management and restoration prescriptions. Increases in soil CO2 efflux do not necessarily equate with net losses from the soil C pool. While the fundamentals of the C balance in peatlands are well-established, the combined affects of global change stressors and management practices are best considered using process-based biogeochemical models. Long-term studies are needed both for validation and to provide a framework for longitudinal assessments of the peatland C cycle. Key words: Peatland, carbon cycle, methane, forest, wetland.
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Hoch, Jannis M., Arjen V. Haag, Arthur van Dam, Hessel C. Winsemius, Ludovicus P. H. van Beek, and Marc F. P. Bierkens. "Assessing the impact of hydrodynamics on large-scale flood wave propagation – a case study for the Amazon Basin." Hydrology and Earth System Sciences 21, no. 1 (January 9, 2017): 117–32. http://dx.doi.org/10.5194/hess-21-117-2017.
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Abstract. Large-scale flood events often show spatial correlation in neighbouring basins, and thus can affect adjacent basins simultaneously, as well as result in superposition of different flood peaks. Such flood events therefore need to be addressed with large-scale modelling approaches to capture these processes. Many approaches currently in place are based on either a hydrologic or a hydrodynamic model. However, the resulting lack of interaction between hydrology and hydrodynamics, for instance, by implementing groundwater infiltration on inundated floodplains, can hamper modelled inundation and discharge results where such interactions are important. In this study, the global hydrologic model PCR-GLOBWB at 30 arcmin spatial resolution was one-directionally and spatially coupled with the hydrodynamic model Delft 3D Flexible Mesh (FM) for the Amazon River basin at a grid-by-grid basis and at a daily time step. The use of a flexible unstructured mesh allows for fine-scale representation of channels and floodplains, while preserving a coarser spatial resolution for less flood-prone areas, thus not unnecessarily increasing computational costs. In addition, we assessed the difference between a 1-D channel/2-D floodplain and a 2-D schematization in Delft 3D FM. Validating modelled discharge results shows that coupling PCR-GLOBWB to a hydrodynamic routing scheme generally increases model performance compared to using a hydrodynamic or hydrologic model only for all validation parameters applied. Closer examination shows that the 1-D/2-D schematization outperforms 2-D for r2 and root mean square error (RMSE) whilst having a lower Kling–Gupta efficiency (KGE). We also found that spatial coupling has the significant advantage of a better representation of inundation at smaller streams throughout the model domain. A validation of simulated inundation extent revealed that only those set-ups incorporating 1-D channels are capable of representing inundations for reaches below the spatial resolution of the 2-D mesh. Implementing 1-D channels is therefore particularly of advantage for large-scale inundation models, as they are often built upon remotely sensed surface elevation data which often enclose a strong vertical bias, hampering downstream connectivity. Since only a one-directional coupling approach was tested, and therefore important feedback processes are not incorporated, simulated discharge and inundation extent for both coupled set-ups is generally overpredicted. Hence, it will be the subsequent step to extend it to a two-directional coupling scheme to obtain a closed feedback loop between hydrologic and hydrodynamic processes. The current findings demonstrating the potential of one-directionally and spatially coupled models to obtain improved discharge estimates form an important step towards a large-scale inundation model with a full dynamic coupling between hydrology and hydrodynamics.
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Tang, G., and P. J. Bartlein. "Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances." Hydrology and Earth System Sciences 16, no. 8 (August 7, 2012): 2547–65. http://dx.doi.org/10.5194/hess-16-2547-2012.
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Abstract. Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981–2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981–2006 (R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15%) with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled monthly soil moisture for the state of Illinois (US) agreed well (R2 = 0.79, p < 0.01) with observed data for the years 1984–2001. Overall, this study justifies both the feasibility of incorporating satellite-based land covers into a DGVM and the reliability of LH to simulate land-surface water balances. To better estimate surface/river runoff at mid-to-high latitudes, we recommended that LPJ-DGVM considers the effects of solar radiation on snowmelt.
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Yuan, Xing, Joshua K. Roundy, Eric F. Wood, and Justin Sheffield. "Seasonal Forecasting of Global Hydrologic Extremes: System Development and Evaluation over GEWEX Basins." Bulletin of the American Meteorological Society 96, no. 11 (November 1, 2015): 1895–912. http://dx.doi.org/10.1175/bams-d-14-00003.1.
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Abstract Seasonal hydrologic extremes in the form of droughts and wet spells have devastating impacts on human and natural systems. Improving understanding and predictive capability of hydrologic extremes, and facilitating adaptations through establishing climate service systems at regional to global scales are among the grand challenges proposed by the World Climate Research Programme (WCRP) and are the core themes of the Regional Hydroclimate Projects (RHP) under the Global Energy and Water Cycle Experiment (GEWEX). An experimental global seasonal hydrologic forecasting system has been developed that is based on coupled climate forecast models participating in the North American Multimodel Ensemble (NMME) project and an advanced land surface hydrologic model. The system is evaluated over major GEWEX RHP river basins by comparing with ensemble streamflow prediction (ESP). The multimodel seasonal forecast system provides higher detectability for soil moisture droughts, more reliable low and high f low ensemble forecasts, and better “real time” prediction for the 2012 North American extreme drought. The association of the onset of extreme hydrologic events with oceanic and land precursors is also investigated based on the joint distribution of forecasts and observations. Climate models have a higher probability of missing the onset of hydrologic extremes when there is no oceanic precursor. But oceanic precursor alone is insufficient to guarantee a correct forecast—a land precursor is also critical in avoiding a false alarm for forecasting extremes. This study is targeted at providing the scientific underpinning for the predictability of hydrologic extremes over GEWEX RHP basins and serves as a prototype for seasonal hydrologic forecasts within the Global Framework for Climate Services (GFCS).
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Baker, Matthew E., and Burton V. Barnes. "Landscape ecosystem diversity of river floodplains in northwestern Lower Michigan, U.S.A." Canadian Journal of Forest Research 28, no. 9 (September 1, 1998): 1405–18. http://dx.doi.org/10.1139/x98-107.
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We present a classification and comparison of river floodplains using an ecological, multifactor approach integrating physiography, hydrology, soil, and vegetation within a relatively homogenous macroclimate. Aerial photographs and field reconnaissance were used to locate 22 river valley transects along nine major rivers in the Manistee National Forest, northwestern Lower Michigan. Distinct ecosystems along each transect were sampled extensively. Twenty-three floodplain ecosystem types were identified and classified primarily on the basis of physiographic systems and fluvial landforms within a regional context. Physiographic systems are broad-scale, surficial landforms characterized by distinctive form, parent material, soil, hydrologic regimes, and vegetation. We examined landscape ecosystem differences between different physiographic systems, within a physiographic system, and on a single fluvial landform. Different physiographic systems have different kinds and patterns of floodplain ecosystems in successive valley segments along a river. Within a physiographic system, the physiographic position of different fluvial landforms and ecosystem types within a single fluvial landform leads to marked ecosystem diversity laterally away from the river. The results indicate that physiography is an important determinant of floodplain ecosystem diversity and that an ecological, multifactor approach is useful in distinguishing floodplain ecosystems at multiple scales within a regional context.
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Jean, Martin, and André Bouchard. "Tree-ring analysis of wetlands of the upper St. Lawrence River, Quebec: response to hydrology and climate." Canadian Journal of Forest Research 26, no. 3 (March 1, 1996): 482–91. http://dx.doi.org/10.1139/x26-054.
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A dendrochronological analysis of three tree species colonizing a swamp along the St. Lawrence River was undertaken to (a) study the extent to which water-level fluctuations have an impact on tree growth in comparison to climatic variations; (b) compare the responses of three species (Acerrubrum L., Larixlaricina (Du Roi) K. Koch, and Thujaoccidentalis L.) with hydrologic and climatic variations; and (c) examine the duration of the influence of water-level fluctuations on tree growth. Tree cores from 78 stands were cross-dated and verified with COFECHA and a master chronology for each species was produced using ARSTAN. Response function analyses were used to measure the influence of climate (temperature and precipitation) and water level on tree growth. Water-level fluctuations have a significant influence on A. rubrum growth, accounting for 30% of the tree growth variation. A significant relationship exists between L. laricina and water-level fluctuations, but only 9% of the tree growth is explained by hydrology. No significant relationship was found between water levels and T. occidentalis growth. Climatic fluctuations are a more important influence on growth for all three species, accounting for 46% to 51% of the tree growth variation not explained by water levels.
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Valipour, Mohammad, Sayed M. Bateni, and Changhyun Jun. "Global Surface Temperature: A New Insight." Climate 9, no. 5 (May 12, 2021): 81. http://dx.doi.org/10.3390/cli9050081.
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