Nonlinear dynamics and recurrence analysis of extreme precipitation for observed and general circulation model generated climates

A statistical framework based on nonlinear dynamics theory and recurrence quantification analysis of dynamical systems is proposed to quantitatively identify the temporal characteristics of extreme (maximum) daily precipitation series. The methodology focuses on both observed and general circulation model (GCM) generated climates for present (1961–2000) and future (2061–2100) periods which correspond to 1xCO₂ and 2xCO₂ simulations. The daily precipitation has been modelled as a stochastic process coupled with atmospheric circulation. An automated and objective classification of daily circulation patterns (CPs) based on optimized fuzzy rules was used to classify both observed CPs and ECHAM4 GCM‐generated CPs for 1xCO₂ and 2xCO₂ climate simulations (scenarios). The coupled model ‘CP‐precipitation’ was suitable for precipitation downscaling. The overall methodology was applied to the medium‐sized mountainous Mesochora catchment in Central‐Western Greece. Results reveal substantial differences between the observed maximum daily precipitation statistical patterns and those produced by the two climate scenarios. A variable nonlinear deterministic behaviour characterizes all climate scenarios examined. Transitions’ patterns differ in terms of duration and intensity. The 2xCO₂ scenario contains the strongest transitions highlighting an unusual shift between floods and droughts. The implications of the results to the predictability of the phenomenon are also discussed. Copyright © 2013 John Wiley & Sons, Ltd.     

Downscaling two versions of a general circulation model to estimate local hydroclimatic factors under climate change

Abstract

The regional hydroclimatological effect of global climate change has been estimated and compared using a semi-empirical downscaling method with two versions (T21 and T42) of the general circulation model (GCM) developed at the Max Planck Institute for Meteorology, Germany. The comparisons were performed with daily mean temperature and daily precipitation amounts for the continental climate of the state of Nebraska, USA. Both the T21 and the T42 versions resulted in an increase of daily mean temperature under a 2 x C02 climatess. The magnitude of warming was substantially greater for T21 than for T42, except for February and June and at some stations in July where the T42 model suggested greater warming. Both GCMs resulted in a slight decrease in precipitation frequency and an increase in the amount of precipitation on wet days. Here, the T42 model again led to smaller changes. Different locations within Nebraska exhibited somewhat different temperature and precipitation responses with both GCM versions.     

Regional precipitation and temperature scenarios for climate change

Abstract

To investigate the consequences of climate change on the water budget in small catchments, it is necessary to know the change of local precipitation and temperature. General Circulation Models (GCM) cannot provide regional climate parameters yet, because of their coarse resolution and imprecise modelling of precipitation. Therefore downscaling of precipitation and temperature has to be carried out from the GCM grids to a small scale of a few square kilometres. Daily rainfall and temperature are modelled as processes conditioned on atmospheric circulation. Rainfall is linked to the circulation patterns (CPs) using conditional probabilities and conditional rainfall amount distribution. Both temperature and precipitation are downscaled to several locations simultaneously taking into account the CP dependent spatial correlation. Temperature is modelled using a simple autoregressive approach, conditioned on atmospheric circulation and local areal precipitation. The model uses the classification scheme of the German Weather Service and a fuzzy rule-based classification. It was applied in the Aller catchment for validation using observed rainfall and temperature, and observed classified geopotential pressure heights. GCM scenarios of the ECHAM model were used to make climate change predictions (using classified GCM geopotential heights); simulated values agree fairly well with historical data. Results for different GCM scenarios are shown.     

Utility of high-resolution climate model simulations for water resources prediction over the Korean Peninsula: a sensitivity study / Utilité de simulations de modèle climatique à haute résolution pour la prévision des ressources en eau dans la Péninsule Coréenne: étude de sensibilité

Abstract

Abstract The utility of simulations of Global Climate Models (GCMs) for regional water resources prediction and management on the Korean Peninsula was assessed by a probabilistic measure. Global Climate Model simulations of an indicator variable (e.g. surface precipitation or temperature) were used for discriminating high vs low regional observations of a target variable (e.g. watershed precipitation or reservoir inflow). The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two distributions. High resolution Atmospheric Model Intercomparison Project-II (AMIP-II) type GCM simulations performed by the European Centre for Medium-Range Weather Forecasts (ECMWF) and AMIP-I type GCM simulations performed by the Korean Meteorological Research Institute (METRI) were used to obtain information for the indicator variables. Observed mean areal precipitation and temperature, and watershed-outlet discharge values for seven major river basins in Korea were used as the target variables. The results suggest that the use of the climate model nodal output from both climate models in the vicinity of the target basin with monthly resolution will be beneficial for water resources planning and management analysis that depends on watershed mean areal precipitation and temperature, and outlet discharge.     

A spatial temporal downscaling approach to development of IDF relations for Perth airport region in the context of climate change

ABSTRACT

Downscaling of climate projections is the most adapted method to assess the impacts of climate change at regional and local scales. This study utilized both spatial and temporal downscaling approaches to develop intensity–duration–frequency (IDF) relations for sub-daily rainfall extremes in the Perth airport area. A multiple regression-based statistical downscaling model tool was used for spatial downscaling of daily rainfall using general circulation models (GCMs) (Hadley Centre’s GCM and Canadian Global Climate Model) climate variables. A simple scaling regime was identified for 30 minutes to 24 hours duration of observed annual maximum (AM) rainfall. Then, statistical properties of sub-daily AM rainfall were estimated by scaling an invariant model based on the generalized extreme value distribution. RMSE, Nash-Sutcliffe efficiency coefficient and percentage bias values were estimated to check the accuracy of downscaled sub-daily rainfall. This proved the capability of the proposed approach in developing a linkage between large-scale GCM daily variables and extreme sub-daily rainfall events at a given location. Finally IDF curves were developed for future periods, which show similar extreme rainfall decreasing trends for the 2020s, 2050s and 2080s for both GCMs.

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

Quantitative assessment of the role of doubled CO<Subscript>2</Subscript> and associated climate change in the vegetation dynamics and hydrological cycle in the Sino-Mongolia arid and semi-arid region

The effects of elevated CO₂ on vegetation dynamics and the hydrological cycle have been widely studied at the site level. However, quantitative assessments of these effects on a regional scale remain a challenge. We conducted numerical simulations to predict the possible responses of vegetation and the hydrological cycle in the Sino-Mongolia arid and semi-arid region (SMASR) to doubled CO₂ and its associated climate change using the Community Earth System Model in tandem with a dynamic global vegetation model. The results showed that the doubled CO₂ had a positive effect on the leaf area index of the SMASR, but its associated climate change exerted a negative effect in most parts of the SMASR. Although climate change had a weak negative effect on ground runoff at the regional scale, a 4.74 mm increase was predicted under the combined effect of doubled CO₂ and climate change, largely due to the positive effect of doubled CO₂. Spatially, the evident increase in ground runoff, which primarily occurred in the southeastern part of the SMASR, resulted from decreased ground evaporation and canopy transpiration under the doubled CO₂ condition. A negative effect was predicted in the central west as a result of increased temperature and a changed precipitation under doubled CO₂. These findings implied that the condition of water resources would be improved slightly under a doubled CO₂ condition, whereas there would be a larger spatial heterogeneity in relation to different sensitivities of vegetation and hydrological variables to doubled CO₂ and associated climate change.     

Measured effects of new lake surfaces on regional precipitation

Abstract

Although often modelled, empirical evidence for regional water balance shifts, due to local land-use changes, is rare. The same holds for the quantification of such effects by measurement. The flooding of former open-cast mining areas in Lusatia, eastern Germany, delivers a unique opportunity to address this topic in a well-gauged region. During two decades, flooding changed about 60 km² of lignite pits to lake surfaces. To quantify possible shifts in the regional precipitation pattern, the background of general precipitation dynamics within the research area was separated from all raingauge records using principal component analysis (PCA). Linear models with the dominating PCA component as independent variable were fitted to the single station records. The residuals of these fits represent the local deviations from the general dynamics, and they contain the signals of climate alterations within the region. The analysis of these residuals revealed a shifting precipitation pattern with significant increases (up to 10% of the former mean annual precipitation, which is approximately 650 mm) on the lee side of the developing lake area. Further analysis showed that most of the observed changes are due to more frequent and intense convective storms. Water balance estimations indicate that the additional evaporation approximately equals the precipitation increase.     

Assessing regression‐based statistical approaches for downscaling precipitation over North America

This paper assesses linear regression‐based methods in downscaling daily precipitation from the general circulation model (GCM) scale to a regional climate model (RCM) scale (45‐ and 15‐km grids) and down to a station scale across North America. Traditional downscaling experiments (linking reanalysis/dynamical model predictors to station precipitation) as well as nontraditional experiments such as predicting dynamic model precipitation from larger‐scale dynamic model predictors or downscaling dynamic model precipitation from predictors at the same scale are conducted. The latter experiments were performed to address predictability limit and scale issues. The results showed that the downscaling of daily precipitation occurrence was rarely successful at all scales, although results did constantly improve with the increased resolution of climate models. The explained variances for downscaled precipitation amounts at the station scales were low, and they became progressively better when using predictors from a higher‐resolution climate model, thus showing a clear advantage in using predictors from RCMs driven by reanalysis at its boundaries, instead of directly using reanalysis data. The low percentage of explained variances resulted in considerable underestimation of daily precipitation mean and standard deviation. Although downscaling GCM precipitation from GCM predictors (or RCM precipitation from RCM predictors) cannot really be considered downscaling, as there is no change in scale, the exercise yields interesting information as to the limit in predictive ability at the station scale. This was especially clear at the GCM scale, where the inability of downscaling GCM precipitation from GCM predictors demonstrates that GCM precipitation‐generating processes are largely at the subgrid scale (especially so for convective events), thus indicating that downscaling precipitation at the station scale from GCM scale is unlikely to be successful. Although results became better at the RCM scale, the results indicate that, overall, regression‐based approaches did not perform well in downscaling precipitation over North America. Copyright © 2013 John Wiley & Sons, Ltd.     

A study on the impact of climate change on streamflow at the watershed scale in the humid tropics

Abstract

Climate change is recognized to be one of the most serious challenges facing mankind today. Driven by anthropogenic activities, it is known to be a direct threat to our food and water supplies and an indirect threat to world security. Increase in the concentration of carbon dioxide and other greenhouse gases in the atmosphere will certainly affect hydrological regimes. The consequent global warming is expected to have major implications on water resources management. The objective of this research is to present a general approach for evaluating the impacts of potential climate change on streamflow in a river basin in the humid tropical zone of India. Large-scale global climate models (GCMs) are the best available tools to provide estimates of the effect of rising greenhouse gases on rainfall and temperature. However the spatial resolution of these models (250 km?×?250 km) is not compatible with that of watershed hydrological models. Hence the outputs from GCMs have to be downscaled using regional climate models (RCMs), so as to project the output of a GCM to a finer resolution (50 km?×?50 km). In the present work, the projections of a GCM for two scenarios, A2 and B2 are downscaled by a RCM to project future climate in a watershed. Projections for two important climate variables, viz. rainfall and temperature are made. These are then used as inputs for a physically-based hydrological model, SWAT, in order to evaluate the effect of climate change on streamflow and vegetative growth in a humid tropical watershed.

Citation Raneesh, K. Y. & Santosh, G. T. (2011) A study on the impact of climate change on streamflow at the watershed scale in the humid tropics. Hydrol. Sci. J. 56(6), 946–965.     

Impact of climate change on water resources in Yongdam Dam Basin,Korea

The main purpose of this study is to investigate and evaluate the impact of climate change on the runoff and water resources of Yongdam basin, Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The downscaled values are used to modify the parameters of a stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series is fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of 2CO₂. This approach is applied to the Yongdam dam basin in the southern part of Korea. The results show that under the condition of 2CO₂, about 7.6% of annual mean streamflow is reduced when it is compared with the current condition. Seasonal streamflows in the winter and autumn are increased, while streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern An erratum to this article can be found at     

Climate impacts on global irrigation requirements under 19 GCMs,simulated with a vegetation and hydrology model

Abstract

This study quantifies global changes in irrigation requirements for areas presently equipped for irrigation of major crop types, using climate projections from 19 GCMs up to the 2080s. Analysis is based on results from the global eco-hydrological model LPJmL that simulates the complex and dynamic interplay of direct and indirect climate change effects upon irrigation requirements. We find a decrease in global irrigation demand by ～17% in the ensemble median, due to a combination of beneficial CO₂ effects on plants, shorter growing periods and regional precipitation increases. In contrast, increases of >20% are projected with a high likelihood (i.e. in more than two thirds of the climate change scenarios) for some regions, including southern Europe, and, with a lower likelihood, for parts of Asia and North America as well. If CO₂ effects were not accounted for, however, global irrigation demand would hardly change, and increases would prevail in most regions except for southern Asia (where higher precipitation is projected). We stress that the CO₂ effects may not be realized everywhere, that irrigation requirements will probably increase further due to growing global food demand (not considered here), and that a significant amount of water to meet future irrigation requirements will have to be taken from fossil groundwater, environmental flow reserves or diverted rivers.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Konzmann, M., Gerten, D., and Heinke, J., 2013. Climate impacts on global irrigation requirements under 19 GCMs, simulated with a vegetation and hydrology model. Hydrological Sciences Journal, 58 (1), 1–18.     

Carbon sinks/sources in the Yellow and East China Seas—Air-sea interface exchange,dissolution in seawater,and burial in sediments

The sinks/sources of carbon in the Yellow Sea(YS) and East China Sea(ECS), which are important continental shelf seas in China, could exert a great influence on coastal ecosystem dynamics and the regional climate change process. The CO_2 exchange process across the seawater-air interface, dissolved and particulate carbon in seawater, and carbon burial in sediments were studied to understand the sinks/sources of carbon in the continental shelf seas of China. The YS and the ECS generally have different patterns of seasonal air-sea CO_2 exchange. In the YS, regions west of 124°E can absorb CO_2 from the atmosphere during spring and winter, and release CO_2 to the atmosphere during summer and autumn. The entire YS is considered as a CO_2 source throughout the year with respect to the atmosphere, but there are still uncertainties regarding the exact air-sea CO_2 exchange flux. Surface temperature and phytoplankton production were the key controlling factors of the air-sea CO_2 exchange flux in the offshore region and nearshore region of the YS, respectively. The ECS can absorb CO_2 during spring, summer, and winter and release CO_2 to the atmosphere during autumn. The annual average exchange rate in the ECS was-4.2±3.2 mmol m~(-2) d~(-1) and it served as an obvious sink for atmospheric CO_2 with an air-sea exchange flux of 13.7×10~6 t. The controlling factors of the air-sea CO_2 exchange in the ECS varied significantly seasonally. Storage of dissolved inorganic carbon(DIC) and dissolved organic carbon(DOC) in the YS and the ECS were 425×10~6 t and 1364×10~6 t, and 28.2×10~6 t and 54.1×10~6 t,respectively. Long-term observation showed that the DOC content in the YS had a decreasing trend, indicating that the "practical carbon sink" in the YS was decreasing. The total amount of particulate organic carbon(POC) stored in the YS and ECS was10.6×10~6 t, which was comparable to the air-sea CO_2 flux in these two continental shelf seas. The amounts of carbon sequestered by phytoplankton in the YS and the ECS were 60.42×10~6 t and 153.41×10~6 t, respectively. Artificial breeding of macroalgae could effectively enhance blue carbon sequestration, which could fix 0.36×10~6–0.45×10~6 t of carbon annually. Organic carbon(OC) buried in the sediments of the YS was estimated to be 4.75×10~6 t, and OC of marine origin was 3.03×10~6 t, accounting for5.0% of the TOC fixed by phytoplankton primary production. In the ECS, the corresponding depositional flux of OC in the sediment was estimated to be 7.4×10~6 t yr~(-1), and the marine-origin OC was 5.5×10~6 t, accounting for 5.4% of the phytoplankton primary production. Due to the relatively high average depositional flux of OC in the sediment, the YS and ECS have considerable potential to store a vast amount of "blue carbon."     

Impact of the spatial variability of daily precipitation on hydrological projections: A comparison of GCM‐ and RCM‐driven cases in the Han River basin,Korea

In this study, we investigate the impact of the spatial variability of daily precipitation on hydrological projections based on a comparative assessment of streamflow simulations driven by a global climate model (GCM) and two regional climate models (RCMs). A total of 12 different climate input datasets, that is, the raw and bias‐corrected GCM and raw and bias‐corrected two RCMs for the reference and future periods, are fed to a semidistributed hydrological model to assess whether the bias correction using quantile mapping and dynamical downscaling using RCMs can improve streamflow simulation in the Han River basin, Korea. A statistical analysis of the daily precipitation demonstrates that the precipitation simulated by the GCM fails to capture the large variability of the observed daily precipitation, in which the spatial autocorrelation decreases sharply within a relatively short distance. However, the spatial variability of precipitation simulated by the two RCMs shows better agreement with the observations. After applying bias correction to the raw GCM and raw RCMs outputs, only a slight change is observed in the spatial variability, whereas an improvement is observed in the precipitation intensity. Intensified precipitation but with the same spatial variability of the raw output from the bias‐corrected GCM does not improve the heterogeneous runoff distributions, which in turn regulate unrealistically high peak downstream streamflow. GCM‐simulated precipitation with a large bias correction that is necessary to compensate for the poor performance in present climate simulation appears to distort streamflow patterns in the future projection, which leads to misleading projections of climate change impacts on hydrological extremes.     

Climate change in Ireland from precipitation and streamflow observations

On the basis of General Circulation Model (GCM) experiments with increased CO₂, many parts of the northern latitudes including western Europe, are expected to have enhanced hydrologic cycles. Using observations of precipitation and streamflow from Ireland, we test for climatic and hydrologic change in this maritime climate of the northeast Atlantic. Five decades of hourly precipitation (at eight sites) and daily streamflow at four rivers in Ireland were investigated for patterns of climate variability. An increase in annual precipitation was found to occur after 1975. This increase in precipitation is most noticeable on the West of the island. Precipitation increases are significant in March and October and are associated with increases in the frequency of wet hours with no change in the hourly intensities. Analysis of streamflow data shows the same trends. Furthermore, analysis of extreme rainfall events show that a much greater proportion of extremes have occurred in the period since 1975. A change also occurred in the North Atlantic Oscillation (NAO) index around 1975. The increased NAO since 1975 is associated with increased westerly airflow circulation in the Northeast Atlantic and is correlated with the wetter climate in Ireland. These climatic changes have implications for water resources management particularly flood analysis and protection.     

Modeling the effects of climate change projections on streamflow in the Nooksack River basin,Northwest Washington

The Nooksack River has its headwaters in the North Cascade Mountains and drains an approximately 2000 km² watershed in northwestern Washington State. The timing and magnitude of streamflow in a snowpack‐dominated drainage basin such as the Nooksack River basin are strongly influenced by temperature and precipitation. Projections of future climate made by general circulation models (GCMs) indicate increases in temperature and variable changes in precipitation for the Nooksack River basin. Understanding the response of the river to climate change is crucial for regional water resources planning because municipalities, tribes, and industry depend on the river for water use and for fish habitat. We combine three different climate scenarios downscaled from GCMs and the Distributed‐Hydrology‐Soil‐Vegetation Model to simulate future changes to timing and magnitude of streamflow in the higher elevations of the Nooksack River. Simulations of future streamflow and snowpack in the basin project a range of magnitudes, which reflects the variable meteorological changes indicated by the three GCM scenarios and the local natural variability employed in the modeling. Simulation results project increased winter flows, decreased summer flows, decreased snowpack, and a shift in timing of the spring melt peak and maximum snow water equivalent. These results are consistent with previous regional studies, but the magnitude of increased winter flows and total annual runoff is higher. Increases in temperature dominate snowpack declines and changes to spring and summer streamflow, whereas a combination of increases in temperature and precipitation control increased winter streamflow. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

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     

A watershed-scale study of climate change impacts on groundwater recharge (Annapolis Valley,Nova Scotia,Canada)

Abstract

The potential impacts of future climate change on the evolution of groundwater recharge are examined at a local scale for a 546-km² watershed in eastern Canada. Recharge is estimated using the infiltration model Hydrologic Evaluation of Landfill Performance (HELP), with inputs derived from five climate runs generated by a regional climate model in combination with the A2 greenhouse gas emissions scenario. The model runs project an increase in annual recharge over the 2041–2070 period. On a seasonal basis, however, a marked decrease in recharge during the summer and a marked increase during the winter are observed. The results suggest that increased evapotranspiration resulting from higher temperatures does not offset the large increase in winter infiltration. In terms of individual water budget components, clear differences are obtained for the different climate change scenarios. Monthly recharge values are also found to be quite variable, even for a given climate scenario. These findings are compared with results from two regional-scale studies.

Editor D. Koutsoyiannis; Associate editor M. Besbes     

Carbon and water cycling in a Bornean tropical rainforest under current and future climate scenarios

We examined how the projected increase in atmospheric CO₂ and concomitant shifts in air temperature and precipitation affect water and carbon fluxes in an Asian tropical rainforest, using a combination of field measurements, simplified hydrological and carbon models, and Global Climate Model (GCM) projections. The model links the canopy photosynthetic flux with transpiration via a bulk canopy conductance and semi-empirical models of intercellular CO₂ concentration, with the transpiration rate determined from a hydrologic balance model. The primary forcing to the hydrologic model are current and projected rainfall statistics. A main novelty in this analysis is that the effect of increased air temperature on vapor pressure deficit (D) and the effects of shifts in precipitation statistics on net radiation are explicitly considered. The model is validated against field measurements conducted in a tropical rainforest in Sarawak, Malaysia under current climate conditions. On the basis of this model and projected shifts in climatic statistics by GCM, we compute the probability distribution of soil moisture and other hydrologic fluxes. Regardless of projected and computed shifts in soil moisture, radiation and mean air temperature, transpiration was not appreciably altered. Despite increases in atmospheric CO₂ concentration (C_a) and unchanged transpiration, canopy photosynthesis does not significantly increase if C_i/C_a is assumed constant independent of D (where C_i is the bulk canopy intercellular CO₂ concentration). However, photosynthesis increased by a factor of 1.5 if C_i/C_a decreased linearly with D as derived from Leuning stomatal conductance formulation [R. Leuning. Plant Cell Environ 1995;18:339–55]. How elevated atmospheric CO₂ alters the relationship between C_i/C_a and D needs to be further investigated under elevated atmospheric CO₂ given its consequence on photosynthesis (and concomitant carbon sink) projections.     

Assessing uncertainty in best management practice effectiveness under future climate scenarios

Uncertainty of best management practice (BMP) performance in future climates is an important consideration for water resources managers. The objective of this study was to quantify the level of uncertainty in performance of seven agricultural BMPs due to climate change in reducing sediment, total nitrogen, and total phosphorus loads. The Soil and Water Assessment Tool coupled with mid‐21^st century climate data from the Community Climate System Model were used to develop climate change scenarios for the Tuttle Creek Lake Watershed of Kansas and Nebraska. Uncertainty level of each BMP was determined using Latin Hypercube Sampling, a constrained Monte Carlo sampling technique. Samples were taken from distributions of several variables (monthly precipitation, temperature, CO₂, and BMP implementation parameters). Cumulative distribution functions were constructed for each BMP, pollutant, and climate scenario combination. Results demonstrated that BMP performance uncertainty is amplified in the extreme climate scenario. Among BMPs, native grass replacement generally had higher uncertainty level but also had the greatest reductions. This study highlights the importance of incorporating uncertainty analysis into mitigation strategies aiming to reduce negative impacts of climate change on water resources. Copyright © 2013 John Wiley & Sons, Ltd.