Impact and uncertainties of climate change on the hydrology of the Mara River basin,Kenya/Tanzania     

Shimelis Behailu Dessu  Assefa Mekonnen Melesse 《水文研究》2013,27(20):2973-2986

The impact and uncertainty of climate change on the hydrology of the Mara River basin (MRB) was assessed. Sixteen global circulation models (GCMs) were evaluated, and five were selected for the assessment of future climate scenarios in the basin. Observed rainfall and temperature data for the control period (1961–1990) were combined with expected GCMs output using the delta and direct statistical downscaling methods and three greenhouse gas emission scenarios (A1B, A2 and B1). Uncertainties of climate change were addressed through compare and contrast of results across diverse GCMs, future climate scenarios and the two downscaling methods. Both methods produced a relatively similar annual rainfall amount, but their monthly and daily pattern showed considerable differences. The relative advantages and disadvantages of implementing one method over the other were also explored. The hydrologic impact of climate change in the basin was assessed using Soil and Water Assessment Tool. The model was calibrated and validated with observed data in the control period with (Nash–Sutcliff efficiency, coefficient of determination) results of (calibration: 0.68, 0.69) and (validation: 0.43, 0.44) at Mara Mines. Results have shown a statistically significant increase in flow volume of the Mara River flow at Mara Mines for the year 2046–2065 and 2081–2100. With due attention to the limitations, findings of this study have a wider application for water resources sustainability analysis in the MRB in the face of uncertainties due to climate change. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Assessing the results of scenarios of climate and land use changes on the hydrology of an Italian catchment: modelling study   总被引：1，自引：0，他引：1  

Daniela R. D'Agostino  Liuzzi Giuliana Trisorio  Nicola Lamaddalena  Ragab Ragab 《水文研究》2010,24(19):2693-2704

Hydrological models are recognized as valid scientific tools to study water quantity and quality and provide support for the integrated management and planning of water resources at different scales. In common with many catchments in the Mediterranean, the study catchment has many problems such as the increasing gap between water demand and supply, water quality deterioration, scarcity of available data, lack of measurements and specific information. The application of hydrological models to investigate hydrological processes in this type of catchments is of particular relevance for water planning strategies to address the possible impact of climate and land use changes on water resources. The distributed catchment scale model (DiCaSM) was selected to study the impact of climate and land use changes on the hydrological cycle and the water balance components in the Apulia region, southern Italy, specifically in the Candelaro catchment (1780 km²). The results obtained from this investigation proved the ability of DiCaSM to quantify the different components of the catchment water balance and to successfully simulate the stream flows. In addition, the model was run with the climate change scenarios for southern Italy, i.e. reduced winter rainfall by 5–10%, reduced summer rainfall by 15–20%, winter temperature rise by 1·25–1·5 °C and summer temperature rise by 1·5–1·75 °C. The results indicated that by 2050, groundwater recharge in the Candelaro catchment would decrease by 21–31% and stream flows by 16–23%. The model results also showed that the projected durum wheat yield up to 2050 is likely to decrease between 2·2% and 10·4% due to the future reduction in rainfall and increase in temperature. In the current study, the reliability of the DiCaSM was assessed when applied to the Candelaro catchment; those parameters that may cause uncertainty in model output were investigated using a generalized likelihood uncertainty estimation (GLUE) methodology. The results showed that DiCaSM provided a small level of uncertainty and subsequently, a higher confidence level. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

Evaluation of a spatial rainfall generator for generating high resolution precipitation projections over orographically complex terrain   总被引：1，自引：1，他引：0  

Corrado?CameraEmail author  Adriana?Bruggeman  Panos?Hadjinicolaou  Silas?Michaelides  Manfred?A.?Lange 《Stochastic Environmental Research and Risk Assessment (SERRA)》2017,31(3):757-773

Space–time variability of precipitation plays a key role as driver of many environmental processes. The objective of this study is to evaluate a spatiotemporal (STG) Neyman–Scott Rectangular Pulses (NSRP) generator over orographically complex terrain for statistical downscaling of climate models. Data from 145 rain gauges over a 5760-km² area of Cyprus for 1980–2010 were used for this study. The STG was evaluated for its capacity to reproduce basic rainfall statistical properties, spatial intermittency, and extremes. The results were compared with a multi-single site NRSP generator (MSG). The STG performed well in terms of average annual rainfall (+1.5 % in comparison with the 1980–2010 observations), but does not capture spatial intermittency over the study area and extremes well. Daily events above 50 mm were underestimated by 61 %. The MSG produced a similar error (+1.1 %) in terms of average annual rainfall, while the daily extremes (>50-mm) were underestimated by 11 %. A gridding scheme based on scaling coefficients was used to interpolate the MSG data. Projections of three Regional Climate Models, downscaled by MSG, indicate a 1.5–12 % decrease in the mean annual rainfall over Cyprus for 2020–2050. Furthermore, the number of extremes (>50-mm) for the 145 stations is projected to change between ?24 and +2 % for the three models. The MSG modelling approach maintained the daily rainfall statistics at all grid cells, but cannot create spatially consistent daily precipitation maps, limiting its application to spatially disconnected applications. Further research is needed for the development of spatial non-stationary NRSP models.  相似文献   

Modelling blue and green water availability under climate change in the Beninese Basin of the Niger River Basin,West Africa          下载免费PDF全文

Djigbo Félicien Badou  Bernd Diekkrüger  Evison Kapangaziwiri  Mamadou L. Mbaye  Yacouba Yira  Emmanuel A. Lawin  Ganiyu T. Oyerinde  Abel Afouda 《水文研究》2018,32(16):2526-2542

The aim of this study was to quantify climate change impact on future blue water (BW) and green water (GW) resources as well as the associated uncertainties for 4 subbasins of the Beninese part of the Niger River Basin. The outputs of 3 regional climate models (HIRHAM5, RCSM, and RCA4) under 2 emission scenarios (RCP4.5 and RCP8.5) were downscaled for the historical period (1976–2005) and for the future (2021–2050) using the Statistical DownScaling Model (SDSM). Comparison of climate variables between these 2 periods suggests that rainfall will increase (1.7% to 23.4%) for HIRHAM5 and RCSM under both RCPs but shows mixed trends (?8.5% to 17.3%) for RCA4. Mean temperature will also increase up to 0.48 °C for HIRHAM5 and RCSM but decrease for RCA4 up to ?0.37 °C. Driven by the downscaled climate data, future BW and GW were evaluated with hydrological models validated with streamflow and soil moisture, respectively. The results indicate that GW will increase in all the 4 investigated subbasins, whereas BW will only increase in one subbasin. The overall uncertainty associated with the evaluation of the future BW and GW was quantified through the computation of the interquartile range of the total number of model realizations (combinations of regional climate models and selected hydrological models) for each subbasin. The results show larger uncertainty for the quantification of BW than GW. To cope with the projected decrease in BW that could adversely impact the livelihoods and food security of the local population, recommendations for the development of adequate adaptation strategies are briefly discussed.  相似文献   

Uncertainty analysis of downscaling methods in assessing the influence of climate change on hydrology     

Fen Ouyang  Haishen Lü  Yonghua Zhu  Jianyun Zhang  Zhongbo Yu  Xi Chen  Min Li 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(4):991-1010

Five downscaling techniques, namely the statistical downscaling model, the automated statistical downscaling method, the change factor (CF) method, the advanced CF method, the Weather generator (LarsWG5) method, are applied to the upstream basin of the Huaihe River. Changes in regional climate scenarios and hydrology variables are compared in future periods to investigate the uncertainty associated with the downscaling techniques. Paired-sample T test is applied to evaluation the significant of the difference of the means between the observed data and the downscaled data in the future. The Xinanjiang rainfall–runoff model is employed to simulate the rainfall–runoff relation. The results demonstrate that the downscaling techniques utilized herein predict an increased tendency in the future. The increases range of maximum temperature (T_max) is between 3.7 and 4.7 °C until the time period of 2070–2099 (2080s). While, the increases range of minimum temperature (T_min) is between 2.8 and 4.9 °C until 2080s. The research presented herein determined that there is an increase predicted for the peaks over threshold (discussed in the paper) and a decrease predicted for the peaks below the threshold (discussed in the paper) in the future, which illustrates that the temperature would rise gradually in the future. Precipitation changes are not as obvious as temperatures changes and tend to be influence by the season. Most downscaling techniques predict increases, and others indict decreases. The annual mean precipitation range changes between 3.2 and 53.3 %, and moreover, these changes vary from season to season.  相似文献   

Effect of climate change on runoff of a glacierized Himalayan basin     

Pratap Singh  Manohar Arora  N. K. Goel 《水文研究》2006,20(9):1979-1992

The continuous increase in the emission of greenhouse gases has resulted in global warming, and substantial changes in the global climate are expected by the end of the current century. The reductions in mass, volume, area and length of glaciers on the global scale are considered as clear signals of a warmer climate. The increased rate of melting under a warmer climate has resulted in the retreating of glaciers. On the long‐term scale, greater melting of glaciers during the coming years could lead to the depletion of available water resources and influence water flows in rivers. It is also very likely that such changes have occurred in Himalayan glaciers, but might have gone unnoticed or not studied in detail. The water resources of the Himalayan region may also be highly vulnerable to such climate changes, because more than 50% of the water resources of India are located in the various tributaries of the Ganges, Indus and the Brahmaputra river system, which are highly dependent on snow and glacier runoff. In the present study, the snowmelt model SNOWMOD has been used to simulate the melt runoff from a highly glacierized small basin for the summer season. The model simulated the distribution and volume of runoff with reasonably good accuracy. Based on a 2‐year simulation, it is found that, on average, the contributions of glacier melt and rainfall in the total runoff are 87% and 13% respectively. The impact of climate change on the monthly distribution of runoff and total summer runoff has been studied with respect to plausible scenarios of temperature and rainfall, both individually and in combined scenarios. The analysis included six temperature scenarios ranging between 0·5 and 3 °C, and four rainfall scenarios (?10%, ?5%, 5%, 10%). The combined scenarios were generated using temperature and rainfall scenarios. The combined scenarios represented a combination of warmer and drier and a combination of warmer and wetter conditions in the study area. The results indicate that, for the study basin, runoff increased linearly with increase in temperature and rainfall. For a temperature rise of 2 °C, the increase in summer streamflow is computed to be about 28%. Changes in rainfall by ±10% resulted in corresponding changes in streamflow by ±3·5%. For the range of climatic scenarios considered, the changes in runoff are more sensitive to changes in temperature, compared with rainfall, which is likely due to the major contribution of melt water in runoff. Such studies are needed for proper assessment of available water resources under a changing climate in the Himalayan region. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

Non-stationary frequency analysis of heavy rainfall events in southern France     

Yves Tramblay  Luc Neppel  Julie Carreau  Kenza Najib 《水文科学杂志》2013,58(2):280-294

Abstract

Heavy rainfall events often occur in southern French Mediterranean regions during the autumn, leading to catastrophic flood events. A non-stationary peaks-over-threshold (POT) model with climatic covariates for these heavy rainfall events is developed herein. A regional sample of events exceeding the threshold of 100 mm/d is built using daily precipitation data recorded at 44 stations over the period 1958–2008. The POT model combines a Poisson distribution for the occurrence and a generalized Pareto distribution for the magnitude of the heavy rainfall events. The selected covariates are the seasonal occurrence of southern circulation patterns for the Poisson distribution parameter, and monthly air temperature for the generalized Pareto distribution scale parameter. According to the deviance test, the non-stationary model provides a better fit to the data than a classical stationary model. Such a model incorporating climatic covariates instead of time allows one to re-evaluate the risk of extreme precipitation on a monthly and seasonal basis, and can also be used with climate model outputs to produce future scenarios. Existing scenarios of the future changes projected for the covariates included in the model are tested to evaluate the possible future changes on extreme precipitation quantiles in the study area.

Editor Z.W. Kundzewicz; Associate editor K. Hamed

Citation Tramblay, Y., Neppel, L., Carreau, J., and Najib, K., 2013. Non-stationary frequency analysis of heavy rainfall events in southern France. Hydrological Sciences Journal, 58 (2), 280–294.  相似文献   

Impact of climate change on the hydrology and water salinity in the Anzali Wetland,northern Iran     

Mostafa Naderi  Masoud Saatsaz 《水文科学杂志》2020,65(4):552-570

ABSTRACT

The impact of climate change on hydrology and water salinity of a valuable coastal wetland (Anzali) in northern Iran is assessed using daily precipitation and temperature data from 19 models of Coupled Model Inter-comparison Project Phase 5. The daily data are transiently downscaled using the Long Ashton Research Station Weather Generator to three climatic stations. The temperature is projected to increase by +1.6, +1.9 and +2.7°C and precipitation to decrease by 10.4%, 12.8% and 12.2% under representative concentration pathway (RCP) scenarios RCP2.6, RCP4.5 and RCP8.5, respectively. The wetland hydrology and water salinity are assessed using the water balance approach and mixing equation, respectively. The upstream river flow modelled by the Soil and Water Assessment Tool is projected to reduce by up to 18%, leading to reductions in wetland volume (154 × 10⁶ m³), area (57.47 km²) and depth (2.77 m) by 34%, 21.1% and 20.2%, respectively, under climate change, while the mean annual total dissolved solids (1675 mg/L) would increase by 49%. The reduced volume and raised salinity may affect the wetland ecology.  相似文献   

Projection of glacier runoff in Yarkant River basin and Beida River basin,Western China     

Shiqiang Zhang  Xin Gao  Xiaowen Zhang  Stefan Hagemann 《水文研究》2012,26(18):2773-2781

Potential changes in glacier area, mass balance and runoff in the Yarkant River Basin (YRB) and Beida River Basin (BRB) are projected for the period from 2011 to 2050 employing the modified monthly degree‐day model forced by climate change projection. Future monthly air temperature and precipitation were derived from the simple average of 17, 16 and 17 General Circulation Model (GCM) projections following the A1B, A2 and B1 scenarios, respectively. These data were downscaled to each station employing the Delta method, which computes differences between current and future GCM simulations and adds these changes to observed time series. Model parameters calibrated with observations or results published in the literature between 1961 and 2006 were kept unchanged. Annual glacier runoff in YRB is projected to increase until 2050, and the total runoff over glacier area in 1970 is projected to increase by about 13%–35% during 2011–2050 relative to the average during 1961–2006. Annual glacier runoff and the total runoff over glacier area in 1970 in BRB is projected to increase initially and then to reach a tipping point during 2011–2030. There are prominent increases in summer, but only small increase in May and October of glacier runoff in YRB, and significant increases during late spring and early summer and significant decreases in July and late summer of glacier runoff in BRB. This study highlights the great differences among basins in their response to future climate warming. The specific runoff from areas exposed after glacier retreat relative to 1970 is projected to general increasing, which must be considered when evaluating the potential change of glacier runoff. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

Projections of future deterioration in UK river quality are hampered by climatic uncertainty under extreme conditions     

M.G. Hutchins  R.J. Williams  C. Prudhomme  M.J. Bowes  H.E. Brown  A.J. Waylett 《水文科学杂志》2013,58(16):2818-2833

ABSTRACT

A modelling study was undertaken to quantify effects that the climate likely to prevail in the 2050s might have on water quality in two contrasting UK rivers. In so doing, it pinpointed the extent to which time series of climate model output, for some variables derived following bias correction, are fit for purpose when used as a basis for projecting future water quality. Working at daily time step, the method involved linking regional climate model (HadRM3-PPE) projections, Future Flows Hydrology (rainfall–runoff modelling) and the QUESTOR river network water quality model. In the River Thames, the number of days when temperature, dissolved oxygen, biochemical oxygen demand and phytoplankton exceeded undesirable values (>25°C, <6 mg L^?1, >4 mg L^?1 and >0.03 mg L^?1, respectively) was estimated to increase by 4.1–26.7 days per year. The changes do not reflect impacts of any possible change in land use or land management. In the River Ure, smaller increases in occurrence of undesirable water quality are likely to occur in the future (by 1.0–11.5 days per year) and some scenarios suggested no change. Results from 11 scenarios of the hydroclimatic inputs revealed considerable uncertainty around the levels of change, which prompted analysis of the sensitivity of the QUESTOR model to simulations of current climate and hydrology. Hydrological model errors were deemed of less significance than those associated with the derivation and downscaling of driving climatic variables (rainfall, air temperature and solar radiation). Errors associated with incomplete understanding of river water quality interactions with the aquatic ecosystem were found likely to be more substantial than those associated with hydrology, but less than those related to climate model inputs. These errors are largely a manifestation of uncertainty concerning the extent to which phytoplankton biomass is controlled by invertebrate grazers, particularly in mid-summer; and the degree to which this varies from year to year. The quality of data from climate models for generating flows and defining driving variables at the extremes of their distributions has been highlighted as the major source of uncertainty in water quality model outputs.