The mechanism of snow shift affect seasonal streamflow in the contiguous US

Mapping Intimacies ◽

10.5194/egusphere-egu21-16479 ◽

2021 ◽

Author(s):

Lina Wang ◽

Ross Woods

Keyword(s):

Climate Warming ◽

Regional Climate ◽

Hydrologic Model ◽

Hydrological Process ◽

Phase Partitioning ◽

Seasonal Flow ◽

Threshold Mechanism ◽

The Usa ◽

Climate Space ◽

Seasonal Streamflow

Climate warming has caused in a significant decrease in snowpack, increase in precipitation intensity and earlier melt onset. Based on earlier work published in 2014 on changes in streamflow resulting from a shift from snow towards rain, we analysed the sensitivity of seasonal streamflow to the average annual snow fraction in 253 catchments in CAMELS dataset, which have a record length more than 28 years and mean annual snow fraction larger than 15%. The result shows that places (or years) with higher mean annual snow fraction tend to have higher seasonal streamflow. We quantified seasonal sensitivity as a ratio of change in seasonal flow to change in annual snow fraction, for a given annual precipitation. &#160;There are 91%&#65292;57% and 51% catchments which showed a positive sensitivity value for Spring, Summer and Winter streamflow, respectively. According to the results of seasonal sensitivity analysis in climate space, we found the largest seasonal sensitivity normally happens at the same regional climate. Places with higher average annual snow fraction tend to have the largest sensitivity in summer, while for places with lower annual snow fraction this largest sensitivity occurs in spring.In order to explore the mechanism(s) by which snow fraction change affects seasonal streamflow, we summarized four hypothesised mechanisms from the literature: water-energy synchrony (Mechanism I), inputs exceed threshold (Mechanism II), demand-storage competition (Mechanism III), and energy partitioning (Mechanism IV). Most of the catchments in the western part of the contiguous US can be explained by the mechanism I, II, III and IV, while for catchments in the central US can be explained by mechanism II, III and IV. Catchments in the eastern part (and some scattered in the northern part) can be explained by mechanism III. &#160;Other types of evidence are required to further distinguish between mechanisms in much of the USA. in further research we will use detailed data or hydrologic model to reproduce the hydrological process to find what are the hydrological processes responsible for precipitation phase partitioning changing with climate warming to influence catchment response. These findings would provide an evidence for how does snow affect hydrology, which may help to understand the effect of climate warming on future water resources in snow-dominated regions.

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Improving runoff estimates from regional climate models: a performance analysis in Spain

Hydrology and Earth System Sciences ◽

10.5194/hess-16-1709-2012 ◽

2012 ◽

Vol 16 (6) ◽

pp. 1709-1723 ◽

Cited By ~ 18

Author(s):

D. González-Zeas ◽

L. Garrote ◽

A. Iglesias ◽

A. Sordo-Ward

Keyword(s):

Time Series ◽

Large Scale ◽

Climate Models ◽

Regional Climate ◽

Aridity Index ◽

Regional Climate Models ◽

Hydrologic Model ◽

Direct Runoff ◽

Interpolation Methods ◽

Basin Scale

Abstract. An important step to assess water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimise the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of natural runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behaviour of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evapotranspiration and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the "best estimator" of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber (1904) also gives good results.

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The role of conceptual hydrologic model calibration in climate change impact on water resources assessment

Journal of Water and Climate Change ◽

10.2166/wcc.2015.086 ◽

2015 ◽

Vol 7 (1) ◽

pp. 16-28 ◽

Cited By ~ 11

Author(s):

Andrijana Todorovic ◽

Jasna Plavsic

Keyword(s):

Climate Change ◽

Climate Models ◽

Regional Climate ◽

High Sensitivity ◽

Regional Climate Models ◽

Baseline Period ◽

Hydrologic Model ◽

Calibration Period ◽

Rainfall Runoff Model ◽

Parameter Values

Assessment of climate change (CC) impact on hydrologic regime requires a calibrated rainfall-runoff model, defined by its structure and parameters. The parameter values depend, inter alia, on the calibration period. This paper investigates influence of the calibration period on parameter values, model efficiency and streamflow projections under CC. To this end, a conceptual HBV-light model of the Kolubara River catchment in Serbia is calibrated against flows observed within 5 consecutive wettest, driest, warmest and coldest years and in the complete record period. The optimised parameters reveal high sensitivity towards calibration period. Hydrologic projections under climate change are developed by employing (1) five hydrologic models with outputs of one GCM–RCM chain (Global and Regional Climate Models) and (2) one hydrologic model with five GCM–RCM outputs. Sign and magnitude of change in projected variables, compared to the corresponding values simulated over the baseline period, vary with the hydrologic model used. This variability is comparable in magnitude to variability stemming from climate models. Models calibrated over periods with similar precipitation as the projected ones may result in less uncertain projections, while warmer climate is not expected to contribute to the uncertainty in flow projections. Simulations over prolonged dry periods are expected to be uncertain.

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Deployment, calibration, and efficiency of SHUD model in cold and arid watersheds

10.5194/egusphere-egu21-7949 ◽

2021 ◽

Author(s):

Lele Shu ◽

Hao Chen ◽

Xianhong Meng

Keyword(s):

Water Movement ◽

Yellow River ◽

Hydrologic Model ◽

Data Availability ◽

Heihe River ◽

Time Step ◽

Subsurface Hydrology ◽

The Usa ◽

The One ◽

Global Datasets

The hydrologic model is ideal for experimenting and understanding the water movement and storage in a watershed from the upper mountain to the river outlet. Nevertheless, the model's performance, suitability, and data availability are the primary challenge for a modeler. This study introduces the Simulator for Hydrologic Unstructured Domains (SHUD), a surface-subsurface integrated hydrological model using the semi-discrete Finite Volume Method. Though the SHUD applies a fine time-step (in minutes) and flexible spatial domain decomposition (m to km) to simulate the fully coupled surface-subsurface hydrology, the model can solve the watershed-scale problem efficiently and dependably. Plenty of applications in the USA proved the SHUD model's performance and suitability in the humid and data-rich watersheds. &#160;In this research, we demonstrate the SHUD model deployment in two data-scarce watersheds in the northwest of China with global datasets, validate the simulations against local observational data, and assess the SHUD model's efficiency and suitability. &#160;The one is the Upstream Heihe River (UHR), which is a typical semi-arid mountainous watershed. &#160;The other is Yellow River Source (YRS), the upstream of Yellow River, contributing more than 50% of total discharge. The results, figures, and analysis based on SHUD simulations under global datasets highlight the model's suitability and efficiency in data-limited watersheds, even ungaged ones. The SHUD model is a useful modeling platform for hydrology and water-related coupling studies.

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Simulating High-Elevation Hydropower with Regional Climate Warming in the West Slope, Sierra Nevada

Journal of Water Resources Planning and Management ◽

10.1061/(asce)wr.1943-5452.0000373 ◽

2014 ◽

Vol 140 (5) ◽

pp. 714-723 ◽

Cited By ~ 9

Author(s):

David E. Rheinheimer ◽

Joshua H. Viers ◽

Jack Sieber ◽

Michael Kiparsky ◽

Vishal K. Mehta ◽

...

Keyword(s):

Sierra Nevada ◽

Climate Warming ◽

Regional Climate ◽

High Elevation ◽

The West

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Improving runoff estimates from regional climate models: a performance analysis in Spain

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-9-175-2012 ◽

2012 ◽

Vol 9 (1) ◽

pp. 175-214

Author(s):

D. González-Zeas ◽

L. Garrote ◽

A. Iglesias ◽

A. Sordo-Ward

Keyword(s):

Time Series ◽

Large Scale ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Hydrologic Model ◽

Direct Runoff ◽

Interpolation Methods ◽

Basin Scale ◽

The Impact

Abstract. An important aspect to assess the impact of climate change on water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimize the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of naturalised runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behavior of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evaporation and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the "best estimator" of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber also gives good results.

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Transferability of the Xin'anjiang model based on similarity in climate and geography

Water Science & Technology Water Supply ◽

10.2166/ws.2021.055 ◽

2021 ◽

Author(s):

Yue Liu ◽

Jian-yun Zhang ◽

Amgad Elmahdi ◽

Qin-li Yang ◽

Xiao-xiang Guan ◽

...

Keyword(s):

Eastern China ◽

Hydrologic Model ◽

Hydrological Modelling ◽

Model Parameters ◽

Hydrological Process ◽

Hydrologic Models ◽

Ungauged Catchments ◽

Model Based ◽

Hydrological Cycles ◽

Xin’Anjiang Model

Abstract Hydrological experiments are essential to understand the hydrological cycles and promoting the development of hydrologic models. Model parameter transfers provide a new way of doing hydrological forecasts and simulations in ungauged catchments. To study the transferability of model parameters for hydrological modelling and the influence of parameter transfers on hydrological simulations, the Xin'anjiang model (XAJ model), which is a lumped hydrologic model based on a saturation excess mechanism, and has been widely applied in different climate regions of the world, was applied to a low hilly catchment in eastern China, the Chengxi Experimental Watershed (CXEW). The suitability of the XAJ model was tested in the eastern branch catchment of CXEW and the calibrated model parameters of the eastern branch catchment were then transferred to the western branch catchment and the entire watershed of the CXEW. The results show that the XAJ model performs well for the calibrated eastern branch catchment at both daily and monthly scales on hydrological modelling with the NSEs over 0.6 and the REs less than 2.0%. Besides, the uncalibrated catchments of the western branch catchment and the entire watershed of the CSEW share similarities in climate (the precipitation) and geography (the soil texture and vegetation cover) with the calibrated catchment, the XAJmodel and the transferred model parameters can capture the main features of the hydrological processes in both uncalibrated catchments (western catchments and entire watershed). This transferability of the model is useful for a scarce data region to simulate the hydrological process and its forecasting.

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Lack of influence of climate on present cost of water supply in the USA

Water Policy ◽

10.2166/wp.2004.0018 ◽

2004 ◽

Vol 6 (4) ◽

pp. 269-279

Author(s):

Paul H. Kirshen ◽

Andrea L. Larsen ◽

Richard M. Vogel ◽

William Moomaw

Keyword(s):

Water Supply ◽

Climatic Factors ◽

Regional Climate ◽

Climate Change Impacts ◽

Capital Expenditures ◽

Water Supply Systems ◽

Small Component ◽

The Usa ◽

Supply Costs ◽

Supply Systems

Previous studies have sought to develop econometric models of water supply systems, which can be used to predict future water supply costs; none, however, have investigated the influence of climatic factors. In this paper, climatic and other regional influences on the costs of water supply in the USA are explored using multivariate analysis of water supply costs from water supply utilities located throughout the USA. Results showed that over 90% of the variation in present water supply capital and operating costs for surface and ground water systems can be explained by variations in quantity of water delivered, with other variables, particularly regional climate, playing a negligible role. An analysis of the historic development of water supply in the USA showed that capital expenses for water supply systems are a relatively small component of the present total annual costs because: (1) the original capital expenditures were reduced for utilities due to large public subsidization; (2) repayment of capital expenditures is now complete owing to the long time period since the original investments; and (3) new policies encourage demand management instead of supply expansion. Therefore, the present costs of water supply are not related to climate and thus are not a useful guide to future costs in studies that evaluate climate change impacts.

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