Hydrological impacts of climate change on rice cultivated riparian wetlands in the Upper Meghna River Basin (Bangladesh and India)

ABSTRACT

Riparian depressional wetlands (haors) in the Upper Meghna River Basin of Bangladesh are invaluable agricultural resources. They are completely flooded between June and November and planted with Boro rice when floodwater recedes in December. However, early harvest period (April/May) floods frequently damage ripening rice. A calibrated/validated Soil and Water Assessment Tool for riparian wetland (SWATrw) model is perturbed with bias free (using an improved quantile mapping approach) climate projections from 17 general circulation models (GCMs) for the period 2031–2050. Projected mean annual rainfall increases (200–500 mm or 7–10%). However, during the harvest period lower rainfall (21–75%) and higher evapotranspiration (1–8%) reduces river discharge (5–18%) and wetland inundation (inundation fraction declines of 0.005–0.14). Flooding risk for Boro rice consequently declines (rationalized flood risk reductions of 0.02–0.12). However, the loss of cultivable land (15.3%) to increases in permanent haor inundation represents a major threat to regional food security.     

Assessing climate change impacts on the ecohydrology of the Jinghe River basin in the Loess Plateau,China

Abstract

Quantifying the impacts of climate change on the hydrology and ecosystem is important in the study of the Loess Plateau, China, which is well known for its high erosion rates and ecosystem sensitivity to global change. A distributed ecohydrological model was developed and applied in the Jinghe River basin of the Loess Plateau. This model couples the vegetation model, BIOME BioGeochemicalCycles (BIOME-BGC) and the distributed hydrological model, Water and Energy transfer Process in Large river basins (WEP-L). The WEP-L model provided hydro-meteorological data to BIOME-BGC, and the vegetation parameters of WEP-L were updated at a daily time step by BIOME-BGC. The model validation results show good agreement with field observation data and literature values of leaf area index (LAI), net primary productivity (NPP) and river discharge. Average climate projections of 23 global climate models (GCMs), based on three emissions scenarios, were used in simulations to assess future ecohydrological responses in the Jinghe River basin. The results show that global warming impacts would decrease annual discharge and flood season discharge, increase annual NPP and decrease annual net ecosystem productivity (NEP). Increasing evapotranspiration (ET) due to air temperature increase, as well as increases in precipitation and LAI, are the main reasons for the decreasing discharge. The increase in annual NPP is caused by a greater increase in gross primary productivity (GPP) than in plant respiration, whilst the decrease in NEP is caused by a larger increase in heterotrophic respiration than in NPP. Both the air temperature increase and the precipitation increase may affect the changes in NPP and NEP. These results present a serious challenge for water and land management in the basin, where mitigation/adaption measures for climate change are desired.

Editor Z.W. Kundzewicz; Associate editor D. Yang

Citation Peng, H., Jia, Y.W., Qiu, Y.Q., and Niu, C.W., 2013. Assessing climate change impacts on the ecohydrology of the Jinghe River basin in the Loess Plateau, China. Hydrological Sciences Journal, 58 (3), 651–670.     

Investigating the uncertainty and transferability of parameters in SWAT model under climate change

ABSTRACT

There is an implicit assumption in most work that the parameters calibrated based on observations remain valid for future climatic conditions. However, this might not be true due to parameter instability. This paper investigates the uncertainty and transferability of parameters in a hydrological model under climate change. Parameter transferability is investigated with three parameter sets identified for different climatic conditions, which are: wet, intermediate and dry. A parameter set based on the baseline period (1961–1990) is also investigated for comparison. For uncertainty analysis, a k-simulation set approach is proposed instead of employing the traditional optimization method which uses a single best-fit parameter set. The results show that the parameter set from the wet sub-period performs the best when transferred into wet climate condition, while the parameter set from the baseline period is the most appropriate when transferred into dry climate condition. The largest uncertainty of simulated daily high flows for 2011–2040 is from the parameter set trained in the dry sub-period, while that of simulated daily medium and low flows lies in the parameter set from the intermediate calibration sub-period. For annual changes in the future period, the uncertainty with the parameter set from the intermediate sub-period is the largest, followed by the wet sub-period and dry sub-period. Compared with high and medium flows/runoffs, the uncertainty of low flows/runoffs is much smaller for both simulated daily flows and annual runoffs. For seasonal runoffs, the largest uncertainty is from the intermediate sub-period, while the smallest is from the dry sub-period. Apart from that, the largest uncertainty can be observed for spring runoffs and the lowest one for autumn runoffs. Compared with the traditional optimization method, the k-simulation set approach shows many more advantages, particularly being able to provide uncertainty information to decision support for watershed management under climate change.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR not assigned     

Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?

ABSTRACT

This paper assesses how various sources of uncertainty propagate through the uncertainty cascade from emission scenarios through climate models and hydrological models to impacts, with a particular focus on groundwater aspects from a number of coordinated studies in Denmark. Our results are similar to those from surface water studies showing that climate model uncertainty dominates the results for projections of climate change impacts on streamflow and groundwater heads. However, we found uncertainties related to geological conceptualization and hydrological model discretization to be dominant for projections of well field capture zones, while the climate model uncertainty here is of minor importance. How to reduce the uncertainties on climate change impact projections related to groundwater is discussed, with an emphasis on the potential for reducing climate model biases through the use of fully coupled climate–hydrology models.

Editor D. Koutsoyiannis; Associate editor not assigned     

Hydrological response to future land-use change and climate change in a tropical catchment

Hydrological response to expected future changes in land use and climate in the Samin catchment (278 km²) in Java, Indonesia, was simulated using the Soil and Water Assessment Tool model. We analysed changes between the baseline period 1983–2005 and the future period 2030–2050 under both land-use change and climate change. We used the outputs of a bias-corrected regional climate model and six global climate models to include climate model uncertainty. The results show that land-use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual streamflow and surface runoff. The findings of this study will be useful for water resource managers to mitigate future risks associated with land-use and climate changes in the study catchment.     

Uncertainty assessment in river flow projections for Ethiopia’s Upper Awash Basin using multiple GCMs and hydrological models

ABSTRACT

Uncertainty in climate change impacts on river discharge in the Upper Awash Basin, Ethiopia, is assessed using five MIKE SHE hydrological models, six CMIP5 general circulation models (GCMs) and two representative concentration pathways (RCP) scenarios for the period 2071–2100. Hydrological models vary in their spatial distribution and process representations of unsaturated and saturated zones. Very good performance is achieved for 1975–1999 (NSE: 0.65–0.8; r: 0.79–0.93). GCM-related uncertainty dominates variability in projections of high and mean discharges (mean: –34% to +55% for RCP4.5, – 2% to +195% for RCP8.5). Although GCMs dominate uncertainty in projected low flows, inter-hydrological model uncertainty is considerable (RCP4.5: –60% to +228%, RCP8.5: –86% to +337%). Analysis of variance uncertainty attribution reveals that GCM-related uncertainty occupies, on average, 68% of total uncertainty for median and high flows and hydrological models no more than 1%. For low flows, hydrological model uncertainty occupies, on average, 18% of total uncertainty; GCM-related uncertainty remains substantial (average: 28%).     

Changes to flow regime on the Niger River at Koulikoro under a changing climate

Abstract

A significant decrease in mean river flow as well as shifts in flood regimes have been reported at several locations along the River Niger. These changes are the combined effect of persistent droughts, damming and increased consumption of water. Moreover, it is believed that climate change will impact on the hydrological regime of the river in the next decades and exacerbate existing problems. While decision makers and stakeholders are aware of these issues, it is hard for them to figure out what actions should be taken without a quantitative estimate of future changes. In this paper, a Soil and Water Assessment Tool (SWAT) model of the Niger River watershed at Koulikoro was successfully calibrated, then forced with the climate time series of variable length generated by nine regional climate models (RCMs) from the AMMA-ENSEMBLES experiment. The RCMs were run under the SRES A1B emissions scenario. A combination of quantile-quantile transformation and nearest-neighbour search was used to correct biases in the distributions of RCM outputs. Streamflow time series were generated for the 2026–2050 period (all nine RCMs), and for the 2051–2075 and 2076–2100 periods (three out of nine RCMs) based on the availability of RCM simulations. It was found that the quantile-quantile transformation improved the simulation of both precipitation extremes and ratio of monthly dry days/wet days. All RCMs predicted an increase in temperature and solar radiation, and a decrease in average annual relative humidity in all three future periods relative to the 1981–1989 period, but there was no consensus among them about the direction of change of annual average wind speed, precipitation and streamflow. When all model projections were averaged, mean annual precipitation was projected to decrease, while the total precipitation in the flood season (August, September, October) increased, driving the mean annual flow up by 6.9% (2026–2050), 0.9% (2051–2075) and 5.6% (2076–2100). A t-test showed that changes in multi-model annual mean flow and annual maximum monthly flow between all four periods were not statistically significant at the 95% confidence level.     

GCM-related uncertainty for river flows and inundation under climate change: the Inner Niger Delta

ABSTRACT

A semi-distributed hydrological model of the Niger River above and including the Inner Delta is developed. GCM-related uncertainty in climate change impacts are investigated using seven GCMs for a 2°C increase in global mean temperature, the hypothesised threshold of “dangerous” climate change. Declines in precipitation predominate, although some GCMs project increases for some sub-catchments, whilst PET increases for all scenarios. Inter-GCM uncertainty in projected precipitation is three to five times that of PET. With the exception of one GCM (HadGEM1), which projects a very small increase (3.9%), river inflows to the Delta decline. There is considerable uncertainty in the magnitude of these reductions, ranging from 0.8% (HadCM3) to 52.7% (IPSL). Whilst flood extent for HadGEM1 increases (mean annual peak +1405 km²/+10.2%), for other GCMs it declines. These declines range from almost negligible changes to a 7903 km² (57.3%) reduction in the mean annual peak.

Editor Z.W. Kundzewicz; Associate editor not assigned     

Groundwater contamination risks from conservative point source pollutants in a future climate

ABSTRACT

The groundwater contamination risk in future climates was investigated at three locations in Sweden. Solute transport penetration depths were simulated using the HYDRUS-1D model using historical data and an ensemble of climate projections including two global climate models (GCMs), three emission scenarios and one regional climate model. Most projections indicated increasing precipitation and evapotranspiration until mid-century with a further increase at end-century. Results showed both increasing and decreasing groundwater contamination risks depending on emission scenario and GCM. Generally, the groundwater contamination risk is likely to be unchanged until mid-century, but higher at the end of the century. Soil and site specific relationships between Δ(P – PET) (i.e. change in the difference between precipitation, P, and potential evapotranspiration, PET) and changes in solute transport depths were determined. Using this, changes in solute transport depths for other climate projections can be assessed.     

Extreme value statistics for annual minimum and trough-under-threshold precipitation at different spatio-temporal scales

Abstract

The aim of this paper is to quantify meteorological droughts and assign return periods to these droughts. Moreover, the relation between meteorological and hydrological droughts is explored. This has been done for the River Meuse basin in Western Europe at different spatial and temporal scales to enable comparison between different data sources (e.g. stations and climate models). Meteorological drought is assessed in two ways: using annual minimum precipitation amounts as a function of return period, and using troughs under threshold as a function of return period. The Weibull extreme value type 3 distribution has been fitted to both sources of information. Results show that the trough-under-threshold precipitation is larger than the annual minimum precipitation for a specific return period. Annual minimum precipitation values increase with spatial scale, being most pronounced for small temporal scales. The uncertainty in annual minimum point precipitation varies between 68% for the 30-day precipitation with a return period of 100 years, and 8% for the 120-day precipitation with a return period of 10 years. For spatially-averaged values, these numbers are slightly lower. The annual discharge deficit is significantly related to the annual minimum precipitation.

Citation Booij, M. J. & de Wit, M. J. M. (2010) Extreme value statistics for annual minimum and trough-under-threshold precipitation at different spatio-temporal scales. Hydrol. Sci. J. 55(8), 1289–1301.     

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 5^th (dry scenario) and 95^th (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.     

Integrating downscaled CMIP5 data with a physically based hydrologic model to estimate potential climate change impacts on streamflow processes in a mixed‐use watershed

Climatic changes have altered surface water regimes worldwide, and climate projections suggest that such alterations will continue. To inform management decisions, climate projections must be paired with hydrologic models to develop quantitative estimates of watershed scale water regime changes. Such modeling approaches often involve downscaling climate model outputs, which are generally presented at coarse spatial scales. In this study, Coupled Model Intercomparison Project Phase 5 climate model projections were analyzed to determine models representing severe and conservative climate scenarios for the study watershed. Based on temperature and precipitation projections, output from GFDL‐ESM2G (representative concentration pathway 2.6) and MIROC‐ESM (representative concentration pathway 8.5) were selected to represent conservative (Δ_C) and severe (Δ_S) change scenarios, respectively. Climate data were used as forcing for the soil and water assessment tool to analyze the potential effects of climate change on hydrologic processes in a mixed‐use watershed in central Missouri, USA. Results showed annual streamflow decreases ranging from ?5.9% to ?26.8% and evapotranspiration (ET) increases ranging from +7.2% to +19.4%. During the mid‐21st century, sizeable decreases to summer streamflow were observed under both scenarios, along with large increases of fall, spring, and summer ET under Δ_S. During the late 21st century period, large decreases of summer streamflow under both scenarios, and large increases to spring (Δ_S), fall (Δ_S) and summer (Δ_C) ET were observed. This study demonstrated the sensitivity of a Midwestern watershed to future climatic changes utilizing projections from Coupled Model Intercomparison Project Phase 5 models and presented an approach that used multiple climate model outputs to characterize potential watershed scale climate impacts.     

Climatic control on river discharge simulations,Zackenberg River drainage basin,northeast Greenland

A spatially distributed, physically based, hydrologic modeling system (MIKE SHE) was applied to quantify intra‐ and inter‐annual discharge from the snow and glacierized Zackenberg River drainage basin (512 km²; 20% glacier cover) in northeast Greenland. Evolution of snow accumulation, distribution by wind‐blown snow, blowing‐snow sublimation, and snow and ice surface melt were simulated by a spatially distributed, physically based, snow‐evolution modelling system (SnowModel) and used as input to MIKE SHE. Discharge simulations were performed for three periods 1997–2001 (calibration period), 2001–2005 (validation period), and 2071–2100 (scenario period). The combination of SnowModel and MIKE SHE shows promising results; the timing and magnitude of simulated discharge were generally in accordance with observations (R² = 0·58); however, discrepancies between simulated and observed discharge hydrographs do occur (maximum daily difference up to 44·6 m³ s^?1 and up to 9% difference between observed and simulated cumulative discharge). The model does not perform well when a sudden outburst of glacial dammed water occurs, like the 2005 extreme flood event. The modelling study showed that soil processes related to yearly change in active layer depth and glacial processes (such as changes in yearly glacier area, seasonal changes in the internal glacier drainage system, and the sudden release of glacial bulk water storage) need to be determined, for example, from field studies and incorporated in the models before basin runoff can be quantified more precisely. The SnowModel and MIKE SHE model only include first‐order effects of climate change. For the period 2071–2100, future IPCC A2 and B2 climate scenarios based on the HIRHAM regional climate model and HadCM3 atmosphere–ocean general circulation model simulations indicated a mean annual Zackenberg runoff about 1·5 orders of magnitude greater (around 650 mmWE year^?1) than from today 1997–2005 (around 430 mmWE year^?1), mainly based on changes in negative glacier net mass balance. Copyright © 2007 John Wiley & Sons, Ltd.     

Parameter transferability under changing climate: case study with a land surface model in the Durance watershed,France

Abstract

In physically-based land surface models, the parameters can all be prescribed a priori but calibration can be used to enhance the realism of the simulations in well instrumented domains. In such a case, the transferability of calibrated parameters under non-stationary conditions needs to be addressed, especially in the context of climate change. To this end, we used the Catchment Land Surface Model (CLSM) in the Upper Durance watershed located in the French Alps, which experienced a significant increase in temperature over the last century. The CLSM is forced by a 50-year meteorological dataset of good quality. Four parameters of the CLSM (one related to snow processes and three to soil properties) are calibrated against discharge observations with a multi-objective algorithm. First, the robustness of the CLSM parameterizations is tested by the Differential Split Sample Test (DSST). The simulations show good performances over a wide range of retrospective climatic conditions, except when the parameters are calibrated over a period with a large contribution of snowmelt to annual mean discharge. Then, the use of a climate change scenario reveals that the parameterizations of soil moisture processes in the CLSM are responsible for an increasing dispersion among simulations when facing dry and warm conditions. However, the differences between the simulated changes of river discharge remain very small. This work shows that calibration conveys some uncertainties, but they are moderate in the studied case, and pertain to the most conceptual parameterizations of this physically-based model.     

Simulating monthly streamflow for the Upper Changjiang,China, under climatic change scenarios / Simulation du débit mensuel du Haut Changjiang,en Chine,sous des scénarios de changement climatique

Abstract

The potential effect of climatic change on the flow of the Upper Changjiang (or Yangtze River) above the Three Gorges, China, was simulated with the SLURP hydrological model, using ERA40 data from 1961–1990 to simulate the baseline streamflow, and employing scenario temperature and precipitation changes depicted by two global climate models: the Hadley Centre and the Canadian climate model (CCCma) for both the B2 scenario (moderate emission of greenhouse gases) and the A2 scenario (more intense emission), for the 2021–2050 and 2071–2100 time horizons. In general, temperature and precipitation changes are more pronounced for the latter than for the former period. Winter low flows will not change but summer high flow may be augmented by increased precipitation. By mid-century, temperature increase will reduce streamflow according to CCCma, but not so under the Hadley Centre scenario. By the end of the century, precipitation will be great enough to overcome the influence of warming to raise discharge from most parts of the basin. The Min and the Jinsha rivers warrant much attention, the former because of its large flow contribution and the latter because of its sensitivity to climate forcing.     

Global projections of changing risks of floods and droughts in a changing climate

Abstract

Simulated daily discharge derived from a relatively high-resolution (approximately 1.1-degree) general circulation model was used to investigate future projections of extremes in river discharge under global warming. The frequency of floods was projected to increase over many regions, except those including North America and central to western Eurasia. The drought frequency was projected to increase globally, while regions such as northern high latitudes, eastern Australia, and eastern Eurasia showed a decrease or no significant changes. Changes in flood and drought are not explained simply by changes in annual precipitation, heavy precipitation, or differences between precipitation and evapotranspiration. Several regions were projected to have increases in both flood frequency and drought frequency. Such regions show a decrease in the number of precipitation days, but an increase in days with heavy rain. Several regions show shifts in the flood season from springtime snowmelt to the summer period of heavy precipitation.     

Climate change and uncertainty assessment over a hydroclimatic transect of Michigan

Predictions of a warmer climate over the Great Lakes region due to global change generally agree on the magnitude of temperature changes, but precipitation projections exhibit dependence on which General Circulation Models and emission scenarios are chosen. To minimize model- and scenario-specific biases, we combined information provided by the 3rd phase of the Coupled Model Intercomparison Project database. Specifically, the results of 12 GCMs for three emission scenarios B1, A1B, and A2 were analyzed for mid- (2046–2065) and end-century (2081–2100) intervals, for six locations of a hydroclimatic transect of Michigan. As a result of Bayesian Weighted Averaging, total annual precipitation averaged over all locations and the three emission scenarios increases by 7 % (mid-)–10 % (end-century), as compared to the control period (1961–1990). The projected changes across seasons are non-uniform and precipitation decreases by 3 % (mid-)–5 % (end-) for the months of August and September are likely. Further, average temperature is very likely to increase by 2.02–2.85 °C by the mid-century and 2.58–4.73 °C by the end-century. Three types of non-additive uncertainty sources due to climate models, anthropogenic forcings, and climate internal variability are addressed. When compared to the emission uncertainty, the relative magnitudes of the uncertainty types for climate model ensemble and internal variability are 149 and 225 % for mean monthly precipitation, and they are respectively 127 and 123 % for mean monthly temperature. A decreasing trend of the frost days and an increasing trend of the growing season length are identified. Also, a significant increase in the magnitude and frequency of heavy rainfall events is projected, with relatively more pronounced changes for heavy hourly rainfall as compared to daily events. Quantifying the inherent natural uncertainty and projecting hourly-based extremes, the study results deliver useful information for water resource stakeholders interested in impacts of climate change on hydro-morphological processes.     

Simulation of the hydrological impacts of climate change on a restored floodplain

Thirty UK Climate Projections 2009 (UKCP09) scenarios are simulated using a MIKE SHE/MIKE 11 model of a restored floodplain in eastern England. Annual precipitation exhibits uncertainty in direction of change. Extreme changes (10 and 90% probability) range between ?27 and +30%. The central probability projects small declines (相似文献   

Climate models and hydrological parameter uncertainties in climate change impacts on monthly runoff and daily flow duration curve of a Mediterranean catchment

ABSTRACT

Climate models and hydrological parameter uncertainties were quantified and compared while assessing climate change impacts on monthly runoff and daily flow duration curve (FDC) in a Mediterranean catchment. Simulations of the Soil and Water Assessment Tool (SWAT) model using an ensemble of behavioural parameter sets derived from the Generalized Likelihood Uncertainty Estimation (GLUE) method were approximated by feed-forward artificial neural networks (FF-NN). Then, outputs of climate models were used as inputs to the FF-NN models. Subsequently, projected changes in runoff and FDC were calculated and their associated uncertainty was partitioned into climate model and hydrological parameter uncertainties. Runoff and daily discharge of the Chiba catchment were expected to decrease in response to drier and warmer climatic conditions in the 2050s. For both hydrological indicators, uncertainty magnitude increased when moving from dry to wet periods. The decomposition of uncertainty demonstrated that climate model uncertainty dominated hydrological parameter uncertainty in wet periods, whereas in dry periods hydrological parametric uncertainty became more important.

Editor M.C. Acreman; Associate editor S. Kanae     

Drying climate in Ghana over the period 1960–2005: evidence from the resampling-based Mann-Kendall test at local and regional levels

Abstract

Trends in rainfall series were investigated at 16 stations in Ghana over the period 1960–2005. Time series were first de-correlated using an effective pre-whitening methodology and then submitted to the resampling-based Mann-Kendall test. Field significances were assessed using the regional average Kendall statistic. Although no significant changes were observed in annual rainfall, the analysis reveals: (a) a reduction in the number of wet season days totalling less than 20 mm of rainfall, between latitudes 6° and 9.5°N; (b) a delay (about 0.5 d year^‐1) in the wet season onset at several locations throughout the country; and (c) a lengthening (about 0.1 d year^‐1) of rainless periods during the wet season in the south and centre of Ghana. All these changes, which remained insignificant at more than half of the individual stations, were found to be regionally significant at the 95% confidence level. The results highlight the importance of evaluating regional significance when investigating climate trends.

Editor Z.W. Kundzewicz

Citation Lacombe, G., McCartney, M., and Forkuor, G., 2012. Drying climate in Ghana over the period 1960–2005: evidence from the resampling-based Mann-Kendall test at local and regional levels. Hydrological Sciences Journal, 57 (8), 1594–1609.