Runoff Projections Research Articles

Sensitivity of glacier runoff projections to baseline climate data in the Indus River basin

Quantifying the contribution of glacier runoff to water resources is particularly important in regions such High Mountain Asia, where glaciers provide a large percentage of seasonal river discharge and support large populations downstream. In remote areas, direct field measurements of glacier melt rates are difficult to acquire and rarely observed, so hydro-glaciological modeling and remote sensing approaches are needed. Here we present estimates of glacier melt contribution to the Upper Indus watershed over the last 40 years using a suite of seven reanalysis climate datasets that have previously been used in hydrological models for this region, a temperature-index melt model and > 29,000 km2 of ice cover. In particular, we address the uncertainty in estimates of meltwater flux that is introduced by the baseline climate dataset chosen, by comparing the results derived from each. Mean annual glacier melt contribution varies from 8 km3 yr-1 and 169 km3 yr-1, or between 4-78% of the total annual runoff in the Indus, depending on temperature dataset applied. Under projected scenarios of an additional 2-4°C of regional warming by 2100 AD, we find annual meltwater fluxes vary by >200% depending on the baseline climate dataset used and, importantly, span a range of positive and negative trends. Despite significant differences between climate datasets and the resulting spread in meltwater fluxes, the spatial pattern of melt is highly correlated and statistically robust across all datasets. This allows us to conclude with confidence that fewer than 10% of the >20,000 glaciers in the watershed contribute more than 80% of the total glacier runoff to the Indus. These are primarily large, low elevation glaciers in the Karakoram and Hindu Kush. Additional field observations to ground-truth modeled climate data will go far to reduce the uncertainty highlighted here and we suggest that efforts be focused on those glaciers identified to be most significant to water resources.

Uncertainties in runoff projections in southwestern Australian catchments using a global climate model with perturbed physics

Summary Future projections of water supply under climate change scenarios are fundamental for efficient water resource planning. However, runoff projections are affected by uncertainties in the modelling process that limit their utility to decision makers. The main source of uncertainty in runoff projections are the Global Climate Models (GCMs) used to produce future climate projections. The impact on projected runoff of this uncertainty has mainly been assessed through comparison of multi-model runs of future climate with little exploration of uncertainties inside the models due to different parameterisations. Here we investigate the uncertainty response of projected runoff due to perturbed physics parameter variations within a GCM using a novel 2500 member ensemble from the HadCM3L model. Our research evaluates the uncertainties in runoff modelling for southwest Western Australia, a Mediterranean climate region which has experienced reductions in precipitation during the last decades. Results for future projections in southwest Western Australian catchments indicate reductions in modelled precipitation between 0% and 40% and increases in temperature that fluctuate between 0.5 °C and 3 °C by 2050–2080 compared to 1970–2000, which lead to reductions in projected runoff of between 10% and 80%. This range of uncertainty for projected runoff is larger than that calculated for previous estimates of within-model uncertainties of runoff. The perturbed physics approach indicates that current water management assessments underestimate uncertainties in runoff projections.

Uncertainty of runoff projections under changing climate in Wami River sub-basin

Abstract Study Region The Wami River sub-basin is among the river sub-basins with a vital ecosystem in Tanzania. It comprises the Saadani National park and it has the very great potential of irrigation and rain fed agriculture. Study Focus The objective of this study was to evaluate the uncertainty of future streamflow in respect of increasing water demands and uncertain projected climate inputs, General Circulation Models (GCMs). The water demands were projected to the year 2039 and GCM precipitation was selected as the changing climatic variable. The CMIP5-GCMs were evaluated for their skills and those with the minimum skill scores above 75% were downscaled and used in projection of scenario RCP 8.5 precipitation. Then uncertainties of RCP 8.5 precipitation were estimated using a fuzzy extension principle and finally used to simulate uncertainties of future runoff using a rainfall-runoff model, Soil and Water Assessment Tool (SWAT). New Hydrological Insights for the Region The results of projected streamflow shows that the baseline annual climatology flow (ACF) is 98 m3/s and for the future, the median ACF is projected to be 81 m3/s. At 100% uncertainty of skilled projections, the ACF from the sub-basin is projected to range between −47% and +36% from the baseline ACF. However, the midstream of the sub-basin shows reliable water availability for foreseen water uses expansion up to the year 2039.

A Comparison Study of Runoff Projections for Yongdam Dam Watershed Using SWAT

In this study, reliable future runoff projections based on RCPs for Yongdam dam watershed was performed using SWAT model, which was validated by k-fold cross validation method, and investigated the factors that cause the differences with respect to runoff projections between this study and previous studies. As a result, annual average runoff compared to baseline runoff would increase 17.7% and 26.1% in 2040s and 2080s respectively under RCP8.5 scenario, and 21.9% and 44.6% in 2040s and 2080s respectively under RCP4.5 scenario. Comparing the results to previous studies, minimum and maximum differences between runoff projections over different studies were 10.3% and 53.2%, even though runoff was projected by the same rainfall-runoff model. SWAT model has 27 parameters and physically based complex structure, so it tends to make different results by the model users` setting. In the future, it is necessary to reduce the cause of difference to generate standard runoff scenarios.

Simulating the Impacts of Projected Climate Change on Streamflow Hydrology for the Chesapeake Bay Watershed

A gridded model was developed to simulate the hydrology of the Chesapeake Bay Watershed, the largest estuary in the United States. CMIP3 and CMIP5 climate projections were used to drive the model to assess changes in streamflow and watershed-wide hydrology. Index of agreement values indicated good model performance. Annual average temperature is projected to increase 1.9°C to 5.4°C by 2080 to 2099, with the greatest warming occurring in summer and fall in the northern part of the watershed. Annual total precipitation is projected to increase between 5.2 percent and 15.2 percent by 2080 to 2099, with the largest increases generally occurring in winter. Average evapotranspiration and rainfall are projected to increase while snowfall, snow water storage, and snowmelt decrease. Subsurface moisture is projected to decrease during the warmer months and the time to recharge increases and, in some cases, never actually occurs. Changes in annual runoff for all 346 climate projections averaged 0 percent (2020–2039), –1.5 percent (2050–2069), and –5.1 percent (2080–2099). There is a 48 percent, 52 percent, and 60 percent chance, respectively, for the future time periods that annual runoff will be less than baseline values (1950–1999). Extreme runoff projections are overwhelmingly associated with the negative end of the distribution. Runoff increases are confined to January through March and to higher elevations. This study is novel in its use of a large number of climate models, the gridded nature of the hydrologic model, and the simulation of several hydrologic variables, all of which allowed for the assessment of both uncertainty in the projections and variation across multiple spatial and temporal scales.

Ability of a land surface model to predict climate induced changes in northern Russian river runoff during the 21st century

Abstract. The objective of the present study is application of the land surface model SWAP to project climate change impact on northern Russian river runoff up to 2100 using meteorological projections from the atmosphere–ocean global climate model INMCM4.0. The study was performed for the Northern Dvina River and the Kolyma River characterized by different climatic conditions. The ability of both models to reproduce the observed river runoff was investigated. To apply SWAP for hydrological projections, the robustness of the model was evaluated. The river runoff projections up to 2100 were calculated for two greenhouse gas emission scenarios: RCP8.5 and RCP4.5 prepared for the phase five of the Coupled Model Intercomparison Project (CMIP5). For each scenario, several runoff projections were obtained using different models (INMCM4.0 and SWAP) and different post-processing techniques for correcting biases in meteorological forcing data. Differences among the runoff projections obtained for the same emission scenario and the same period illustrate uncertainties resulted from application of different models and bias-correcting techniques.

Implication of calibration period on modelling climate change impact on future runoff

Abstract. This paper explores the consideration and implication of calibration period on the modelled climate change impact on future runoff. The results show that modelled runoff and hydrologic responses can be influenced by the choice of historical data period used to calibrate and develop the hydrological model. Modelling approaches that do not take this into account may therefore underestimate the range and uncertainty in future runoff projections. Nevertheless, the uncertainty associated with the choice of hydrological models and consideration of calibration dataset for modelling climate change impact on runoff is likely to be small compared to the uncertainty in the future rainfall projections.

Estimation of catchment yield and associated uncertainties due to climate change in a mountainous catchment in Australia

This paper examines the impacts of climate change on future water yield with associated uncertainties in a mountainous catchment in Australia using a multi-model approach based on four global climate models (GCMs), 200 realisations (50 realisations from each GCM) of downscaled rainfalls, 2 hydrological models and 6 sets of model parameters. The ensemble projections by the GCMs showed that the mean annual rainfall is likely to reduce in the future decades by 2–5% in comparison with the current climate (1987–2012). The results of ensemble runoff projections indicated that the mean annual runoff would reduce in future decades by 35%. However, considerable uncertainty in the runoff estimates was found as the ensemble results project changes of the 5th (dry scenario) and 95th (wet scenario) percentiles by −73% to +27%, −73% to +12%, −77% to +21% and −80% to +24% in the decades of 2021–2030, 2031–2040, 2061–2070 and 2071–2080, respectively. Results of uncertainty estimation demonstrated that the choice of GCMs dominates overall uncertainty. Realisation uncertainty (arising from repetitive simulations for a given time step during downscaling of the GCM data to catchment scale) of the downscaled rainfall data was also found to be remarkably high. Uncertainty linked to the choice of hydrological models was found to be quite small in comparison with the GCM and realisation uncertainty. The hydrological model parameter uncertainty was found to be lowest among the sources of uncertainties considered in this study. Copyright © 2015 John Wiley & Sons, Ltd.

Uncertainty in Regional Climate Model Mean Runoff Projections under Climate Change: Case Study of Labrador's Churchill River Basin

ABSTRACTAn ensemble of seven climate models from the North American Regional Climate Change Assessment Program (NARCCAP) was used to examine uncertainty in simulated runoff changes from a base period (1971–2000) to a future period (2041–2070) for the Churchill River basin, Labrador, Canada. Three approximations for mean annual runoff from each ensemble member were included in the analysis: (i) atmospheric moisture convergence, (ii) the balance between precipitation and evaporation, and (iii) instantaneous runoff output from respective land-surface schemes. Using data imputation (i.e., reconstruction) and variance decomposition it was found that choice of regional climate model (RCM) made the greatest contribution to uncertainty in the climate change signal, whereas the boundary forcing of a general circulation model (GCM) played a smaller, though non-negligible, role. It was also found that choice of runoff approximation made a substantial contribution to uncertainty, falling between the contribution from RCM and GCM choice. The NARCCAP output and imputed data were used to calculate mean and median annual changes and results were presented via probability distribution functions to facilitate decision making. Mean and median increases in runoff for the basin were found to be 11.2% and 8.9%, respectively.

Climate and water availability indicators in Canada: Challenges and a way forward. Part III – Future scenarios

Following from Parts I and II of this series (this issue), some common approaches for developing and assessing future scenarios of water availability are reviewed, along with recent case studies of Canadian watersheds. The results of future changes in drought related to climate change are influenced by the choice of indicators. For the Standardized Precipitation Index (SPI), small changes in drought frequency and severity are projected over southern Canada, reflecting the influence of increases in future annual precipitation only. However, assessments using the Palmer Drought Severity Index (PDSI) reveal dramatic increases in the potential for future droughts since this indicator incorporates the combined influences of higher temperatures, soil moisture capacity and precipitation to estimate evapotranspiration. Regarding projected changes in runoff, watersheds in British Columbia tend to show increases in annual and winter runoff. Some watersheds show projected decreases in summer runoff. In the southern Prairies, most watersheds show projected decreases in annual and summer runoff. In Ontario and Quebec, results are mixed. Lake levels in the Great Lakes are projected to decline under most scenarios, but results differ between regional and global climate model-based scenarios due to differences in how lake evaporation is calculated. In New Brunswick, Labrador and northern Quebec, streamflow is projected to increase. Uncertainties in future projections emerge due to differences between climate scenario generating methods, and between hydrologic models used for the assessments. This paper concludes with some thoughts on addressing important research questions related to future scenarios of water availability in Canada. For scenario-based assessments, hydrologic model inter-comparisons might yield some useful insights into uncertainties in model structure that affect evaporation, evapotranspiration and snowmelt calculations. Scenarios developed for assessments should include both future climate and projected land use/cover changes and, where necessary, integration of potential reduction in glacier volume. Finally, as scenarios from regional climate models become more readily available, there may be more opportunity to explore how runoff projections could be applied to basin-scale routing models.

The use of CMIP5 data to simulate climate change impacts on flow regime within the Lake Champlain Basin

Abstract Study region Lake Champlain Basin, northwestern New England, USA. Study focus Our study uses regional hydrologic analyses and modeling to examine alternative possibilities that might emerge in the Lake Champlain Basin streamflow regime for various climate scenarios. Climate data as well as spatial data were processed to calibrate the Regional Hydro-Ecological Simulation System (RHESSys) model runoff simulations. The 21st century runoff simulations were obtained by driving the RHESSys model with climate data from the Coupled Model Intercomparison Project phase 5 (CMIP5) for representative concentration pathways RCP 4.5 and 8.5. New hydrological insights for the region Our analyses suggest that most of CMIP5 ensembles fail to capture both the trends and variability observed in historical precipitation when run in hindcast. This raises concerns of using such products in driving hydrologic models for the purpose of obtaining reliable runoff projections that can aid researchers in regional planning. A subset of five climate models among the CMIP5 ensembles have shown statistically significant trends in precipitation, but the magnitude of these trends is not adequately representative of those seen in observed annual precipitation. Adjusted precipitation forecasts project a streamflow regime described by an increase of about 30% in seven-day maximum flow, a four days increase in flooded days, a three orders of magnitude increase in base flow index, and a 60% increase in runoff predictability (Colwell index).

Hydro-environmental runoff projection under GCM scenario downscaled by Artificial Neural Network in the Namgang Dam watershed, Korea

Until recently, hydrological impacts and prediction caused by climate change have been popular issues. However, a basin-scale hydro-environmental study has begun to attract attention recently due to the difficulties in watershed model calibration and uncertainty propagation in the data relaying procedure from the GCM (General Circulation Model) process to watershed modeling process, which leads to unrealistic projections. In addition, reliable downscaling scheme is essential in utilizing the GCM model output for hydrological applications. The main objective of this study is to suggest a reliable ANN (Artificial Neural Network)-based GCM scenario and its application for hydro-environmental projection using a watershed model. In this report, the Namgang Dam watershed in the Nakdong river basin was selected as the case study. To examine the vulnerability of the Namgang dam watershed caused by climate change, the change in streamflow and pollutant material runoff due to climate change were predicted using the watershed model, SWAT (Soil Water Assessment Tool), based on the IPCC’s A1B GCM scenario, which is downscaled using the ANN and Nonstationary Quantile Mapping. The results of this study will be used for suggesting an effective counterplan from an engineering point of view, and developing an integrated water sources management system.

Surface Water Resources, Climate Change and Simulation Modeling

In the wake of changing climate the present water crisis seems to tighten its hold on the Mankind hence water resources estimation is integral part of planning, development and management of water resources of the country and the estimation of water resource is based on several hydrological and meteorological parameters. Rainfall is the main source of the ground and surface water resources. Recently due to anticipated climate change it is projected that spatial and temporal pattern of rainfall in different part of the country will be change and there will be increase in intensity of rainfall greater monsoon variability. This unprecedented change is expected to have severe impact on the on the water resource and finally on water resource estimation for future planning and management. Apart from climate change, both the ever increasing population and the rapidly changing land use patterns have left the major river basins of the India in a bleak uncertainty to keep up the required runoff. For planning and management, the climate and the hydrological modellers have begun working out runoff projections. During recent years, the Global Climate Models (GCMs) and Regional Climate Models (RCMs) driven hydrological models are in frequent use to draw such projections. But the projections have been often found to lack of reliability. Very recently, there is another emerging field of multi-model ensembles that has added feather to cap of the climate modeling community but this field is yet to be tried in many of the basin runoff-studies especially in the Indian perspective. There is a dire need for more research input assessing the future runoff as far as the Indian River basins are concerned. The climate models are being improved day by day so are the hydrological models. The multi-model ensembles are expected to bring out more reliability in the model outputs regarding the future runoff regimes of the basins than that could be brought about using individual models. The present study is a brief reviewof the model-based projections made for the some of the major river basins of the world. This attempt also seeks to bring forth the basin wise state-of-the-art research activities of such a kind so that the unexplored horizons of model based hydrological research could be taken up as newer research challenges like eg. in India there hasn’t yet been much basin scale studies conducted using multi-model ensembles. Therefore it is suggested that detailed studies to be taken up to assess the impact of climate change on the various parameters involved in estimation of water resources and asses water resource keeping in view the climate change for more realistic future planning and integrated water resource management.

Comparison of future runoff projections using Budyko framework and global hydrologic model: conceptual simplicity vs process complexity

Comparison of future runoff projections using Budyko framework and global hydrologic model: conceptual simplicity vs process complexity

Hydrological Response to Climate Change of the Upper Blue Nile River Basin: Based on IPCC Fifth Assessment Report (AR5)

Climate change is likely to affect the hydrology and water resources availability of upper Blue Nile River basin. Different water resource development projects are currently existed and under construction in the region. In order to understand the future impacts of climate change, we assessed the hydrological response of climate change of four catchments (Gilgel Abay, Gumer, Ribb, and Megech) of the upper Blue Nile River basin using new emission scenarios based on IPCC fifth assessment report (AR5). Five biased corrected 50 kms by 50 kms resolution GCMs (Global Circulation Model) output of RCP 4.5 and RCP 8.5 emission scenarios were used. The future projection period were divided in to two future horizons of 2030`s (2035-2064) and 2070`s (2071-2100). The Hydrologic Engineering Center-Hydrological Modelling System (HEC-HMS) was calibrated and validated for stream flow simulation. All the five GCMs projection showed that, maximum and minimum temperature increases in all months and seasons in the upper Blue Nile basin. The change in magnitude in RCP 8.5 emission is more than RCP 4.5 scenario as expected. There is considerable average monthly and seasonal precipitation change variability in magnitude and direction. Runoff is expected to increase in the future, at 2030`s average annual runoff projection change may increase up to +55.7% for RCP 4.5 and up to +74.8% for RCP 8.5 scenarios. At 2070`s average annual runoff percentage change increase by +73.5% and by +127.4% for RCP 4.5 and RCP 8.5 emission scenarios, respectively. Hence, the increase in flow volume in the basin may have a significant contribution for the sustainability of existed and undergoing water development projects. Moreover; it will help for small scale farmer holders to harness water for their crop productivity. However, a precaution of mitigation and adaptation measures ought to be developed for possible flooding in the flood plains area of the River basin.

Energy budget considerations for hydro-climatic impact assessment in Great Lakes watersheds

Given the large share of the water budget contributed by evapotranspiration (ET), accurately estimating ET is critical for hydro-climate change studies. Routinely, hydrologic models use temperature proxy relationships to estimate potential evapotranspiration (PET) when forced using GCM/RCM projections of precipitation and temperature. A limitation of this approach is that the temperature proxy relationships do not account for the conservation of energy needed to estimate ET consistently in climate change scenarios. In particular, PET methods using temperature as a proxy fail to account for the negative feedback of ET on surface temperature. Using several GCM projections and a hydrologic model developed for the Great Lakes basin watersheds, the NOAA Large Basin Runoff Model (LBRM), the importance of maintaining a consistent energy budget in hydrologic and climate models is demonstrated by comparing runoff projections from temperature proxy and energy conservation methods. Differences in hydrologic responses are related to watershed characteristics, hydrologic model parameters and climate variables. It is shown that the temperature proxy approach consistently leads to prediction of relatively large and potentially unrealistic reductions in runoff. Therefore, hydrologic projections adhering to energy conservation principles are recommended for use in climate change impact studies.

WATER AVAILABILITY IN SOUTHERN PORTUGAL FOR DIFFERENT CLIMATE CHANGE SCENARIOS SUBJECTED TO BIAS CORRECTION

Regional climate models provided precipitation and temperature time series for control (1961-1990) and scenario (2071-2100) periods. At southern Portugal, the climate models in the control period systematically present higher temperatures and lower precipitation than the observations. Therefore, the direct input of climate model data into hydrological models might result in more severe scenarios for future water availability. 
 Three bias correction methods (Delta Change, Direct Forcing and Hybrid) are analysed and their performances in water availability impact studies are assessed. The Delta Change method assumes that the observed series variability is maintained in the scenario period and is corrected by the evolution predicted by the climate models. The Direct Forcing method maintains the scenario series variability, which is corrected by the bias found in the control period, and the Hybrid method maintains the control model series variability, which is corrected by the bias found in the control period and by the evolution predicted by the climate models. 
 To assess the climate impacts in the water resources expected for the scenario period, a physically based spatially distributed hydrological model, SHETRAN, is used for runoff projections in a southern Portugal basin. The annual and seasonal runoff shows a runoff decrease in the scenario period, increasing the water shortage that is already experienced. The overall annual reduction varies between -80% and -35%. In general, the results show that the runoff reductions obtained with climate models corrected with the Delta Change method are highest but with a narrow range that varies between -80% and -52%.

WATER AVAILABILITY IN SOUTHERN PORTUGAL FOR DIFFERENT CLIMATE CHANGE SCENARIOS SUBJECTED TO BIAS CORRECTION

Regional climate models provided precipitation and temperature time series for control (1961-1990) and scenario (2071-2100) periods. At southern Portugal, the climate models in the control period systematically present higher temperatures and lower precipitation than the observations. Therefore, the direct input of climate model data into hydrological models might result in more severe scenarios for future water availability. 
 Three bias correction methods (Delta Change, Direct Forcing and Hybrid) are analysed and their performances in water availability impact studies are assessed. The Delta Change method assumes that the observed series variability is maintained in the scenario period and is corrected by the evolution predicted by the climate models. The Direct Forcing method maintains the scenario series variability, which is corrected by the bias found in the control period, and the Hybrid method maintains the control model series variability, which is corrected by the bias found in the control period and by the evolution predicted by the climate models. 
 To assess the climate impacts in the water resources expected for the scenario period, a physically based spatially distributed hydrological model, SHETRAN, is used for runoff projections in a southern Portugal basin. The annual and seasonal runoff shows a runoff decrease in the scenario period, increasing the water shortage that is already experienced. The overall annual reduction varies between -80% and -35%. In general, the results show that the runoff reductions obtained with climate models corrected with the Delta Change method are highest but with a narrow range that varies between -80% and -52%.

Hydrological Impacts of Warmer and Wetter Climate in Troutlake and Sturgeon River Basins in Central Canada

The impact of climate change on water availability in two river basins located in central Canada is investigated. Several statistical downscaling methods are used to generate temperature and precipitation scenarios from the third-generation Canadian Coupled General Circulation Model, forced with different emission scenarios. The hydrological model SLURP is used to simulate runoff. All downscaling methods agree that temperature will increase with time and that precipitation will also increase, although there is considerably more uncertainty in the magnitude of precipitation change. The study concludes that the change in total annual precipitation does not necessarily translate into similar changes in runoff. The seasonal distribution of precipitation changes is important for runoff, as is the increase in evapotranspiration. The choice of downscaling method appears to have a greater impact on runoff projections than the choice of emission scenario. Therefore, it is important to consider several downscaling methods when evaluating the impact of climate change on runoff.

Regional regression models for hydro‐climate change impact assessment

AbstractHydro‐climatic impacts in water resources systems are typically assessed by forcing a hydrologic model with outputs from general circulation models (GCMs) or regional climate models. The challenges of this approach include maintaining a consistent energy budget between climate and hydrologic models and also properly calibrating and verifying the hydrologic models. Subjective choices of loss, flow routing, snowmelt and evapotranspiration computation methods also increase watershed modelling uncertainty and thus complicate impact assessment. An alternative approach, particularly appealing for ungauged basins or locations where record lengths are short, is to predict selected streamflow quantiles directly from meteorological variable output from climate models using regional regression models that also include physical basin characteristics. In this study, regional regression models are developed for the western Great Lakes states using ordinary least squares and weighted least squares techniques applied to selected Great Lakes watersheds. Model inputs include readily available downscaled GCM outputs from the Coupled Model Intercomparison Project Phase 3. The model results provide insights to potential model weaknesses, including comparatively low runoff predictions from continuous simulation models that estimate potential evapotranspiration using temperature proxy information and comparatively high runoff projections from regression models that do not include temperature as an explanatory variable. Copyright © 2014 John Wiley & Sons, Ltd.