scholarly journals Distributed hydrologic modeling of a sparsely monitored basin in Sardinia, Italy, through hydrometeorological downscaling

2013 ◽  
Vol 17 (10) ◽  
pp. 4143-4158 ◽  
Author(s):  
G. Mascaro ◽  
M. Piras ◽  
R. Deidda ◽  
E. R. Vivoni
Keyword(s):  
High Resolution ◽  
Water Resources ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Hydrologic Model ◽  
Complex Nature ◽  
Variability Modeling ◽  
Model Parameterization ◽  
Hydrologic Extremes

Abstract. The water resources and hydrologic extremes in Mediterranean basins are heavily influenced by climate variability. Modeling these watersheds is difficult due to the complex nature of the hydrologic response as well as the sparseness of hydrometeorological observations. In this work, we present a strategy to calibrate a distributed hydrologic model, known as TIN-based Real-time Integrated Basin Simulator (tRIBS), in the Rio Mannu basin (RMB), a medium-sized watershed (472.5 km2) located in an agricultural area in Sardinia, Italy. In the RMB, precipitation, streamflow and meteorological data were collected within different historical periods and at diverse temporal resolutions. We designed two statistical tools for downscaling precipitation and potential evapotranspiration data to create the hourly, high-resolution forcing for the hydrologic model from daily records. Despite the presence of several sources of uncertainty in the observations and model parameterization, the use of the disaggregated forcing led to good calibration and validation performances for the tRIBS model, when daily discharge observations were available. The methodology proposed here can be also used to disaggregate outputs of climate models and conduct high-resolution hydrologic simulations with the goal of quantifying the impacts of climate change on water resources and the frequency of hydrologic extremes within medium-sized basins.

scholarly journals Distributed hydrologic modeling of a sparsely-monitored basin in Sardinia, Italy, through hydrometeorological downscaling

2013 ◽  
Vol 10 (6) ◽  
pp. 7687-7732 ◽  
Author(s):  
G. Mascaro ◽  
M. Piras ◽  
R. Deidda ◽  
E. R. Vivoni
Keyword(s):  
High Resolution ◽  
Water Resources ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Hydrologic Model ◽  
Complex Nature ◽  
Variability Modeling ◽  
Model Parameterization ◽  
Hydrologic Extremes

Abstract. The water resources and hydrologic extremes in Mediterranean basins are heavily influenced by climate variability. Modeling these watersheds is difficult due to the complex nature of the hydrologic response as well as the sparseness of hydrometeorological observations. In this work, we present a strategy to calibrate a distributed hydrologic model, known as TIN-based Real-time Integrated Basin Simulator (tRIBS), in the Rio Mannu basin (RMB), a medium-sized watershed (472.5 km2) located in an agricultural area in Sardinia, Italy. In the RMB, precipitation, streamflow and meteorological data were collected within different historical periods and at diverse temporal resolutions. We designed two statistical tools for downscaling precipitation and potential evapotranspiration data to create the hourly, high-resolution forcing for the hydrologic model from daily records. Despite the presence of several sources of uncertainty in the observations and model parameterization, the use of the disaggregated forcing led to good calibration and validation performances for the tRIBS model, when daily discharge observations were available. The methodology proposed here can be also used to disaggregate outputs of climate models and conduct high-resolution hydrologic simulations with the goal of quantifying the impacts of climate change on water resources and the frequency of hydrologic extremes within medium-sized basins.

Quantitative estimation on contribution of climate changes and watershed characteristic changes to decreasing streamflow in the Huangshui Basin, China

2021 ◽  
Author(s):  
Xizhi Lv ◽  
Shaopeng Li ◽  
Yongxin Ni ◽  
Qiufen Zhang ◽  
Li Ma
Keyword(s):  
Water Resources ◽  
Climate Changes ◽  
Yellow River ◽  
Potential Evapotranspiration ◽  
Quantitative Estimation ◽  
Meteorological Data ◽  
Characteristic Parameter ◽  
Research Area ◽  
Watershed Characteristic ◽  
Streamflow Change

<p>In the past 60 years, climate changes and underlying surface of the watershed have affected the structure and characteristics of water resources to a different degree It is of great significance to investigate main drivers of streamflow change for development, utilization and planning management of water resources in river basins. In this study, the Huangshui Basin, a typical tributary of the upper Yellow River, is used as the research area. Based on the Budyko hypothesis, streamflow and meteorological data from 1958-2017 are used to quantitatively assess the relative contributions of changes in climate and watershed characteristic to streamflow change in research area. The results show that: the streamflow of Huangshui Basin shows an insignificant decreasing trend; the sensitivity coefficients of streamflow to precipitation, potential evapotranspiration and watershed characteristic parameter are 0.5502, -0.1055, and 183.2007, respectively. That is, an increase in precipitation by 1 unit will induce an increase of 0.5502 units in streamflow, and an increase in potential evapotranspiration by 1 unit will induce a decrease of 0.1055 units in streamflow, and an increase in the watershed characteristic parameter by 1 unit will induce a decrease of 183.2007 units in streamflow. Compared with the reference period (1958-1993), the streamflow decreased by 20.48mm (13.59%) during the change period (1994-2017), which can be attribution to watershed characteristic changes (accounting for 73.64%) and climate change (accounting for 24.48%). Watershed characteristic changes exert a dominant influence upon the reduction of streamflow in the Huangshui Basin.</p>

scholarly journals Comparing bias correction methods in downscaling meteorological variables for hydrologic impact study in an arid area in China

2014 ◽  
Vol 11 (11) ◽  
pp. 12659-12696 ◽  
Author(s):  
G. H. Fang ◽  
J. Yang ◽  
Y. N. Chen ◽  
C. Zammit
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Bias Correction ◽  
Meteorological Data ◽  
Hydrologic Model ◽  
Temperature Correction ◽  
Arid Area ◽  
Tarim River ◽  
Tarim River Basin ◽  
Impact Study

Abstract. Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River Basin, Northwest China, and expected to be vulnerable to climate change. Regional Climate Models (RCM) have been proved to provide more reliable results for regional impact study of climate change (e.g. on water resources) than GCM models. However, it is still necessary to apply bias correction before they are used for water resources research due to often considerable biases. In this paper, after a sensitivity analysis on input meteorological variables based on Sobol' method, we compared five precipitation correction methods and three temperature correction methods to the output of a RCM model with its application to the Kaidu River Basin, one of the headwaters of the Tarim River Basin. Precipitation correction methods include Linear Scaling (LS), LOCal Intensity scaling (LOCI), Power Transformation (PT), Distribution Mapping (DM) and Quantile Mapping (QM); and temperature correction methods include LS, VARIance scaling (VARI) and DM. These corrected precipitation and temperature were compared to the observed meteorological data, and then their impacts on streamflow were also compared by driving a distributed hydrologic model. The results show: (1) precipitation, temperature, solar radiation are sensitivity to streamflow while relative humidity and wind speed are not, (2) raw RCM simulations are heavily biased from observed meteorological data, which results in biases in the simulated streamflows, and all bias correction methods effectively improved theses simulations, (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g. SD, percentile values) while LOCI method performed best in terms of the time series based indices (e.g. Nash–Sutcliffe coefficient, R2), (4) for temperature, all bias correction methods performed equally well in correcting raw temperature. (5) For simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with these of corrected precipitation, i.e. PT and QM methods performed equally best in correcting flow duration curve and peak flow while LOCI method performed best in terms of the time series based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other area and other models.

Effects of Hydrologic Model Choice and Calibration on the Portrayal of Climate Change Impacts

2015 ◽  
Vol 16 (2) ◽  
pp. 762-780 ◽  
Author(s):  
Pablo A. Mendoza ◽  
Martyn P. Clark ◽  
Naoki Mizukami ◽  
Andrew J. Newman ◽  
Michael Barlage ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Hydrologic Model ◽  
Global Climate Models ◽  
Change Scenario ◽  
Hydrologic Models ◽  
Climate System Model

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.

scholarly journals Seasonal Forecasting of Global Hydrologic Extremes: System Development and Evaluation over GEWEX Basins

2015 ◽  
Vol 96 (11) ◽  
pp. 1895-1912 ◽  
Author(s):  
Xing Yuan ◽  
Joshua K. Roundy ◽  
Eric F. Wood ◽  
Justin Sheffield
Keyword(s):  
North American ◽  
Land Surface ◽  
Climate Models ◽  
Water Cycle ◽  
System Development ◽  
Research Programme ◽  
Hydrologic Model ◽  
Streamflow Prediction ◽  
Climate Services ◽  
Hydrologic Extremes

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).

scholarly journals Assessment and projection of the water budget over western Canada using convection-permitting weather research and forecasting simulations

2020 ◽  
Vol 24 (7) ◽  
pp. 3677-3697 ◽  
Author(s):  
Sopan Kurkute ◽  
Zhenhua Li ◽  
Yanping Li ◽  
Fei Huo
Keyword(s):  
Global Warming ◽  
Surface Water ◽  
High Resolution ◽  
Water Resources ◽  
Water Budget ◽  
Climate Models ◽  
Regional Climate ◽  
River Basins ◽  
Weather Research And Forecasting ◽  
Western Canada

Abstract. Water resources in cold regions in western Canada face severe risks posed by anthropogenic global warming as evapotranspiration increases and precipitation regimes shift. Although understanding the water cycle is key for addressing climate change issues, it is difficult to obtain high spatial- and temporal-resolution observations of hydroclimatic processes, especially in remote regions. Climate models are useful tools for dissecting and diagnosing these processes, especially the convection-permitting (CP) high-resolution regional climate simulation, which provides advantages over lower-resolution models by explicitly representing convection. In addition to better representing convective systems, higher spatial resolution also better represents topography, mountain meteorology, and highly heterogeneous geophysical features. However, there is little work with convection-permitting regional climate models conducted over western Canada. Focusing on the Mackenzie River and Saskatchewan River basins, this study investigated the surface water budget and atmospheric moisture balance in historical and representative concentration pathway (RCP8.5) projections using 4 km CP Weather Research and Forecasting (WRF). We compared the high-resolution 4 km CP WRF and three common reanalysis datasets, namely the North American Regional Reanalysis (NARR), the Japanese 55-year Reanalysis (JRA-55), and European Centre for Medium-Range Weather Forecasts reanalysis interim dataset (ERA-Interim). High-resolution WRF outperforms the reanalyses in balancing the surface water budget in both river basins with much lower residual terms. For the pseudo-global-warming scenario at the end of the 21st century with representative concentration pathway (RCP8.5) radiative forcing, both the Mackenzie River and Saskatchewan River basins show increases in the amplitude for precipitation and evapotranspiration and a decrease in runoff. The Saskatchewan River basin (SRB) shows a moderate increase in precipitation in the west and a small decrease in the east. Combined with a significant increase in evapotranspiration in a warmer climate, the Saskatchewan River basin would have a larger deficit of water resources than in the current climate based on the pseudo-global-warming (PGW) simulation. The high-resolution simulation also shows that the difference of atmospheric water vapour balance in the two river basins is due to flow orientation and topography differences at the western boundaries of the two basins. The sensitivity of water vapour balance to fine-scale topography and atmospheric processes shown in this study demonstrates that high-resolution dynamical downscaling is important for large-scale water balance and hydrological cycles.

scholarly journals Historical and future trends in wetting and drying in 291 catchments across China

2016 ◽  
Author(s):  
Zhongwang Chen ◽  
Huimin Lei ◽  
Hanbo Yang ◽  
Dawen Yang ◽  
Yongqiang Cao
Keyword(s):  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Meteorological Data ◽  
Coupled Model ◽  
Simulated Data ◽  
Aridity Index ◽  
Global Climate Models ◽  
Simple Method ◽  
Future Evolution

Abstract. The "dry gets drier, wet gets wetter" (DDWW) pattern is a popular catchphrase to summarize hydrologic changes under global warming. However, recent studies based on simulated data have failed to obtain a feasible DDWW pattern for runoff trends. This study tested the DDWW pattern using observed streamflow and meteorological data from 291 catchments in China from 1956 to 2000, interpreted it using a simple method derived from the Budyko hypothesis, and explored its future evolution according to the projections of five global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Similar to the DDWW pattern, the results show that catchments with an aridity index of φ  1 become drier, with nearly 80 % of the studied catchments following this pattern. However, the pattern does not hold in glacier regions due to the effects of melting ice and snow. Based on precipitation and potential evapotranspiration changes, the first-order differential of the Budyko hypothesis can provide a good estimate of runoff changes (R2 = 0.70). Therefore, the atmospheric forcing of water and energy is the key factor in interpreting the DDWW pattern. Over 80 % of the estimated trends have signs coincident with those of the measured trends, implying that the DDWW pattern can be assessed with estimated data. Precipitation is the controlling factor that leads to the DDWW pattern in nearly 90 % of catchments where observed and estimated signs are consistent. In the three tested scenarios (RCP2.6, RCP4.5 and RCP8.5), the different models produce significantly different predicted changes, even under the same scenario, whereas a given model yields similar results under different scenarios. Based on the projected results, the DDWW pattern no longer provides a reliable prediction. However, this conclusion remains tentative due to the large uncertainty of the simulations. The considerable differences between the observed and modelled meteorological data for the same period suggest that this conclusion should be adopted with caution.

scholarly journals Climate Change Impact on Water Resources in the Awash Basin, Ethiopia

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1560 ◽  
Author(s):  
Meron Taye ◽  
Ellen Dyer ◽  
Feyera Hirpa ◽  
Katrina Charles
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Availability ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Water Security ◽  
Baseline Period ◽  
Coupled Models ◽  
The Future ◽  
The Difference

Rapid growth of agriculture, industries and urbanization within the Awash basin, Ethiopia, as well as population growth is placing increasing demands on the basin’s water resources. In a basin known for high climate variability involving droughts and floods, climate change will likely intensify the existing challenges. To quantify the potential impact of climate change on water availability of the Awash basin in different seasons we have used three climate models from Coupled Models Inter-comparison Project phase 5 (CMIP5) and for three future periods (2006–2030, 2031–2055, and 2056–2080). The models were selected based on their performance in capturing historical precipitation characteristics. The baseline period used for comparison is 1981–2005. The future water availability was estimated as the difference between precipitation and potential evapotranspiration projections using the representative concentration pathway (RCP8.5) emission scenarios after the climate change signals from the climate models are transferred to the observed data. The projections for the future three periods show an increase in water deficiency in all seasons and for parts of the basin, due to a projected increase in temperature and decrease in precipitation. This decrease in water availability will increase water stress in the basin, further threatening water security for different sectors, which are currently increasing their investments in the basin such as irrigation. This calls for an enhanced water management strategy that is inclusive of all sectors that considers the equity for different users.

scholarly journals Evaluation of the impacts of future hydrological changes on the sustainable water resources management of the Richmond River catchment

2017 ◽  
Vol 9 (1) ◽  
pp. 137-155 ◽  
Author(s):  
Hashim Isam Jameel Al-Safi ◽  
P. Ranjan Sarukkalige
Keyword(s):  
Water Resources ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
River Catchment ◽  
Sustainable Water Resources Management ◽  
Hbv Model ◽  
Near Future

Abstract The conceptual rainfall–runoff (HBV model) is applied to evaluate impacts of future climate changes on the hydrological system of the Richmond River catchment, Australia. Daily observed rainfall, temperature and discharge and long-term monthly mean potential evapotranspiration from the hydro-meteorological stations within the catchment over the period 1972–2014 were used to run, calibrate and validate the HBV model before the simulation. Future climate signals were extracted from a multi-model ensemble of eight global climate models (GCMs) of the CMIP5 under three scenarios (RCP2.6, RCP4.5 and RCP8.5). The calibrated HBV model was forced with the downscaled rainfall and temperature to simulate future streamflow at catchment outlet for the near-future (2016–2035), mid (2046–2065) and late (2080–2099) 21st century. A baseline run, with baseline climate period 1971–2010, was used to represent current climate status. Almost all GCMs’ scenarios predict slight increase in annual mean rainfall during the beginning of the century and decrease towards the mid and late century. Modelling results also show positive trends in annual mean streamflow during the near-future (13–23%), and negative trends in the mid (2–6%) and late century (6–16%), under all scenarios compared to the baseline-run. Findings could assist in managing future water resources in the catchment.

scholarly journals Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China

2015 ◽  
Vol 19 (6) ◽  
pp. 2547-2559 ◽  
Author(s):  
G. H. Fang ◽  
J. Yang ◽  
Y. N. Chen ◽  
C. Zammit
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Bias Correction ◽  
Meteorological Data ◽  
Hydrologic Model ◽  
Temperature Correction ◽  
Arid Area ◽  
Tarim River ◽  
Tarim River Basin ◽  
Impact Study

Abstract. Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature correction methods in downscaling RCM simulations applied over the Kaidu River basin, one of the headwaters of the Tarim River basin. Precipitation correction methods applied include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and quantile mapping (QM), while temperature correction methods are LS, variance scaling (VARI) and DM. The corrected precipitation and temperature were compared to the observed meteorological data, prior to being used as meteorological inputs of a distributed hydrologic model to study their impacts on streamflow. The results show (1) streamflows are sensitive to precipitation, temperature and solar radiation but not to relative humidity and wind speed; (2) raw RCM simulations are heavily biased from observed meteorological data, and its use for streamflow simulations results in large biases from observed streamflow, and all bias correction methods effectively improved these simulations; (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g., standard deviation, percentile values) while the LOCI method performed best in terms of the time-series-based indices (e.g., Nash–Sutcliffe coefficient, R2); (4) for temperature, all correction methods performed equally well in correcting raw temperature; and (5) for simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with those of corrected precipitation; i.e., the PT and QM methods performed equally best in correcting flow duration curve and peak flow while the LOCI method performed best in terms of the time-series-based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other areas and models.

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