- Effects of rainfall data resolution on watershed-scale model performance
in predicting runoff
- Authors: Huiliang Wang; Xuyong Li Shaonan Hao
Abstract: The hydrologic simulation program-FORTRAN (HSPF) model is widely used to develop management strategies for water resources, but its effectiveness is limited by predictive uncertainties associated with model input data. This study evaluated the effect of rainfall data resolution on the model performance when predicting runoff. We examined hourly, 3-hourly, 12-hourly, and 24-hourly temporal resolutions, and spatial resolutions from seven to one rain gauges. We used a statistical sensitivity analysis to test the effect of resolution on model accuracy, and a dynamic sensitivity analysis to test the effect on model parameters. Our results indicate that the model performance reduces when using a coarser rainfall resolution. The model used the corresponding parameters to absorb the effect of various resolution changes and reduced their impact on the runoff simulations. We used the paired-samples t-test to examine the significance of the rainfall data resolution to the model parameters, which revealed that the model accuracy was more sensitive to the temporal resolution. Our statistical analysis of the dispersion examined the parameter values. It showed that one parameter was sensitive to temporal resolution and three parameters were sensitive to spatial resolution. This study provided useful information for determining HSPF model parameters using rainfall data at different resolutions.
- Statistical downscaling of general circulation model outputs to
evaporation, minimum temperature and maximum temperature using a
key-predictand and key-station approach
- Authors: D. A. Sachindra; F. Huang, A. F. Barton B. J. C. Perera
Abstract: A key-predictand and key-station approach was employed in downscaling general circulation model outputs to monthly evaporation, minimum temperature (T
min) and maximum temperature (T
max) at five observation stations concurrently. T
max was highly correlated (magnitudes above 0.80 at p ≤ 0.05) with evaporation and T
min at each individual station, hence T
max was identified as the key predictand. One station was selected as the key station, as T
max at that station showed high correlations with evaporation, T
min and T
max at all stations. Linear regression relationships were developed between the key predictand at the key station and evaporation, T
min and T
max at all stations using observations. A downscaling model was developed at the key station for T
max. Then, outputs of this downscaling model at the key station were introduced to the linear regression relationships to produce projections of monthly evaporation, T
min and T
max at all stations. This key-predictand and key-station approach was proved to be effective as the statistics of the predictands simulated by this approach were in close agreement with those of observations. This simple multi-station multivariate downscaling approach enabled the preservation of the cross-correlation structures of each individual predictand among the stations and also the cross-correlation structures between different predictands at individual stations.
- Assessing potential climate change impacts on the seasonality of runoff in
an Alpine watershed
- Abstract: The aim of this study is to investigate potential impacts of climate change on the seasonality of runoff in a mountainous watershed, located in the Austrian Alps. In order to consider the full range of possible climate variation, hypothetical climate change scenarios were used to force a hydrological model to simulate runoff time series for potential future climate conditions. The variation of runoff seasonality is illustrated with a three-dimensional representation of daily discharge data, directional statistics of annual flood peaks and the analysis of seasonal occurrence of runoff peaks. The results show that changes in temperature and precipitation patterns could have considerable effects on seasonal runoff variability in the investigated watershed. Generally, a possible increase in temperature may cause an increase in seasonal variability of runoff. Further, annual flood peaks are projected to occur throughout the entire year in the investigated Alpine watershed, whereas moderate high flows may increase in winter (December–February).
- Precipitation trends in Victoria, Australia
- Authors: Siti Nazahiyah Rahmat; Niranjali Jayasuriya Muhammed A. Bhuiyan
Abstract: Annual rainfall series trends were investigated for more than 100 years of data using two non-parametric trend tests Mann–Kendall (MK) and Sen's slope (Q) for five selected meteorological stations in Victoria, Australia. The annual rainfall time series showed no significant trends for any of the five stations. To assess the sensitivity of trends to the length of the time periods considered, the annual rainfall analysis was repeated using recent data from approximately half the data set between 1949 and 2011. Contrasting results from the original full data set analysis were revealed. All five stations showed decreasing trends with two stations showing significant trends suggesting that this recent time period has added more low precipitation data to the time series. The year of abrupt changes for all the five stations identified using the sequential MK test varied. Conclusions drawn from this paper, point to the importance of selecting the time series data length in identifying trends and abrupt changes. Due to the climate variability, trend testing results might be biased and strongly dependent on the data period selected. Therefore, use of the full data set available would be required in order to improve understanding of change or to undertake any further studies.
- Ranking general circulation models for India using TOPSIS
- Authors: K. Srinivasa Raju; D. Nagesh Kumar
Abstract: Eleven general circulation models/global climate models (GCMs) – BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1 – are evaluated for Indian climate conditions using the performance indicator, skill score (SS). Two climate variables, temperature T (at three levels, i.e. 500, 700, 850 mb) and precipitation rate (Pr) are considered resulting in four SS-based evaluation criteria (T500, T700, T850, Pr). The multicriterion decision-making method, technique for order preference by similarity to an ideal solution, is applied to rank 11 GCMs. Efforts are made to rank GCMs for the Upper Malaprabha catchment and two river basins, namely, Krishna and Mahanadi (covered by 17 and 15 grids of size 2.5° × 2.5°, respectively). Similar efforts are also made for India (covered by 73 grid points of size 2.5° × 2.5°) for which an ensemble of GFDL2.0, INGV-ECHAM4, UKMO-HADCM3, MIROC3, BCCR-BCCM2.0 and GFDL2.1 is found to be suitable. It is concluded that the proposed methodology can be applied to similar situations with ease.
- Climate change related increase of storminess near Hel Peninsula, Gulf of
- Abstract: The paper deals with the growing threat of erosion to the south Baltic coast, caused by the intensification of a wind-induced wave climate and sea level rise, which is expected to continue until 2100 as a result of climate change. In the analysis, a deep-water wave prognostic point is located about 13 km north-east of the Hel Peninsula, situated in the NW part of the Gulf of Gdańsk. The study comprises the analyses of wind velocity, storm surge, wave height, wave set-up and wave run-up. A significant predicted increase in wave heights during extreme storms, compared with the wave climate reconstructed for 1958–2001, combined with anticipated higher storm surges, is expected to result in a lower resilience of the sea shore to erosion and flooding. Although nourishment operations conducted along the open sea shore of the Hel Peninsula have proved efficient and successful, nourishment needs will have to be adequately recalculated in future to ensure sufficient protection of this coastal segment.
- Tools for assessing sea level rise vulnerability
- Authors: Frederick Bloetscher; Thomas Romah
Abstract: Increasing sea level has the potential to place important infrastructure we rely on every day at risk, yet we lack good data to make decisions on what to do, when, and with what priority. The objectives of the research were to develop a method for estimating the time scales for various increments of sea level rise (SLR) throughout the 21st century, develop an accurate methodology for predicting impacts of SLR at the local level, and develop recommendations as to how existing data sources can be utilized to identify infrastructure vulnerable to SLR. The methodology was applied to southeast Florida using data from the Florida Department of Transportation, the United States Geological Survey, the National Oceanic and Atmospheric Administration and other sources, integrated with low resolution light detection and ranging data, topographic data, and aerial photographic maps to identify potentially vulnerable infrastructure. Overlaying high resolution light detection and ranging data onto a base map enabled creation of mapping tools to evaluate potentially vulnerable infrastructure. Using these recommendations, a protocol was developed to use groundwater adjusted models in southeast Florida which indicated potential underestimation of the risk of damage to public infrastructure and private and public buildings.
- Impact of global climate change on fish growth, digestion and
physiological status: developing a hypothesis for cause and effect
- Authors: S. K. Mazumder; M. De, A. G. Mazlan, C. C. Zaidi, S. M. Rahim K. D. Simon
Abstract: Global climate change is impacting and will continue to impact on marine and estuarine fish and fisheries. Data trends show climate change effects ranging from fish growth, digestion physiology and performance in marine and freshwater ecosystems. The present study was designed to develop a concept for a cause and effect understanding with respect to climate-induced temperature and salinity changes and to explain ecological findings based on physiological processes. The concept is based on a wide comparison of fish species. The preliminary conclusion can be drawn that warming will cause a shift of distribution limits for fish species with a change in growth performance, gastric evacuation performance and physiology, or even extinction of the species in the world. In association with the elevated seawater temperature growth performance will also be changed with water quality parameters, for example, salinity. Our interpretations of evidence include many uncertainties about the future of affected fish species. Therefore, it is essential to conduct research on the physiology and ecology of marine, estuarine and freshwater fishes, particularly in the tropics where comparatively little research has been conducted and where temperature fluctuation is comparatively lower. As a broader and deeper information base accumulates, researchers will be able to make more accurate predictions and forge relevant solutions.
- Effects of regional afforestation on global climate
- Authors: Ye Wang; Xiaodong Yan Zhaomin Wang
Abstract: Carbon (C) sequestration following afforestation is regarded as economically, politically, and technically feasible for fighting global warming, whereas the afforested area which will contribute more efficiently as sinks for CO2 is still uncertain. To compare the benefits for C sequestration combined with its biogeochemical effects, an earth system model of intermediate complexity, the McGill Paleoclimate Model-2 (MPM-2) is used to identify the biogeophysical effects of regional afforestation on shaping global climate. An increase in forest in China has led to a prominent global warming during summer around 45° N. Conversely, the forest expansion in the USA causes a noticeable increase in global mean annual temperature during winter. Afforestation in the USA and China brings about a decrease in annual mean meridional oceanic heat transport, while the afforestation in low latitudes of the southern hemisphere causes an increase. These local and global impacts suggest that regional tree plantations may produce a differential effect on the Earth's climate, and even exert an opposite effect on the annual mean meridional oceanic heat transport; they imply that its spatial variation of biogeophysical feedbacks needs to be considered when evaluating the benefits of afforestation.
- Climate change impact on legumes' water production function in the
northeast of Iran
- Authors: N. Sayari; M. Bannayan, A. Alizadeh, A. Farid, M. R. Hessami Kermani E. Eyshi Rezaei
Abstract: Enhanced understanding of the climate impact on crops' production is necessary to cope with expected climate variability and change. This study was conducted to find any robust association between crop yield and evapotranspiration using historical data (1986–2005) and subsequently employ the acquired relationship to project crop yield under future climate conditions for two agricultural centers in northeast Iran. Three legume crops of chickpea, lentil, and bean were selected in this study. The future precipitation and temperature data were projected by downscaling outputs of global climate model HadCM3 (A2 scenario) by LARS-WG stochastic weather generator. The data were downscaled for the baseline (1961–1990) and two time periods (2011–2030 and 2080–2099) as near and far future conditions. Projected temperature under A2 scenario showed increasing trend changed from 4 to 26% during the legumes' growth period compared to baseline. In addition, projected annual precipitation change was between −14 and 10% range under different time periods in contrast to baseline. There was a nonlinear relationship between crop yields and the seasonal values of crop evapotranspiration for all crops. The results showed that seasonal evapotranspiration would increase under climate change conditions across study locations. Crop yield would also increase for chickpea but not for lentil and bean for the far future in Sabzevar location compared to baseline. In conclusion, increasing the temperature and decreasing the precipitation may have a negative effect on legumes' yield in northeast Iran, especially for far future conditions. Therefore, planning effective adaptation and mitigation strategies would be necessary for northeast Iran.
- Hydrological projections based on the coupled
hydrological–hydraulic modeling in the complex river network
region: a case study in the Taihu basin, China
- Authors: Liu Liu; Zongxue Xu
Abstract: Water resources in the Taihu basin, China, are not only facing the effects of a changing climate but also consequences of an intensive urbanization process with the abandonment of rural activities and the resulting changes in land use/land-cover. In the present work, the impact of climate change and urbanization on hydrological processes was assessed using an integrated modeling system, coupling the distributed hydrological model variable infiltration capacity and the hydraulic model ISIS, while future climate scenarios were projected using the regional climate model providing regional climate for impact studies. Results show a significant increasing trend of impervious surface area, while other types of land cover exhibit decreasing trends in 2021–2050. Furthermore, mean annual runoff under different future climate scenarios will increase, especially during flood seasons, consistent with the changes in precipitation and evapotranspiration for both spatial and temporal distribution. Maximum and mean flood water levels under two future scenarios will be higher than levels under the baseline scenario (1961–1990), and the return periods of storms resulting in the same flood water level will decrease significantly in comparison to the baseline scenario, implying more frequent occurrence of extreme floods in future. These results are significant to future flood control efforts and waterlog drainage planning in the Taihu basin.
- Long-term variation of water vapor content and precipitation in the Haihe
- Authors: Chun Chang; Ping Feng, Fawen Li Yunming Gao
Abstract: Based on the Haihe river basin National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data from 1948 to 2010 and the precipitation data of 53 hydrological stations during 1957–2010, this study analyzed the variation of water vapor content and precipitation, and investigated the correlation between them using several statistical methods. The results showed that the annual water vapor content decreased drastically from 1948 to 2010. It was comparatively high from the late 1940s to the late 1960s and depreciated from the early 1970s. From the southeast to the northwest of the Haihe river basin, there was a decrease in water vapor content. For vertical distribution, water vapor content from the ground to 700 hPa pressure level accounted for 72.9% of the whole atmospheric layer, which indicated that the water vapor of the Haihe river basin was mainly in the air close to the ground. The precipitation in the Haihe river basin during 1957–2010 decreased very slightly. According to the correlation analysis, the precipitation and water vapor content changes showed statistically positive correlation, in addition, their break points were both in the 1970s. Furthermore, the high consistency between the precipitation efficiency and precipitation demonstrates that water vapor content is one of the important factors in the formation of precipitation.
- Statistical characteristics of rainfall in the Onkaparinga catchment in
- Authors: M. Mamunur Rashid; Simon Beecham Rezaul K. Chowdhury
Abstract: The main objective of this study was to investigate the statistical characteristics of point rainfall and the novelty of the work was the development of a hybrid probability distribution that can model the full spectrum of daily rainfall in the Onkaparinga catchment in South Australia. Daily rainfall data from 1960 to 2010 at 13 rainfall stations were considered. Spatial dependency among the rainfall maxima was assessed using madograms. Relatively strong and significant autocorrelation coefficients were observed for rainfall depths at finer (daily and monthly) temporal resolutions. The performance of different distribution models was examined considering their ability to regenerate various statistics such as standard deviation, skewness, frequency distribution, percentiles and extreme values. Model efficiency statistics of modelled percentiles of daily rainfall were found to be useful for optimum threshold selection in a hybrid of the gamma and generalized Pareto distributions. The hybrid and the mixed exponential distributions were found to be more efficient than any single distribution (Weibull, gamma and exponential) for simulating the full range of daily rainfall across the catchment. The outcomes from this study will assist water engineers and hydrologists to understand the spatial and temporal characteristics of point rainfall in the Onkaparinga catchment and will hopefully contribute to the improvement of rainfall modelling and downscaling techniques.
- Robust method for estimating grain yield in western Kenya during the
- Authors: Edward M. Mugalavai; Emmanuel C. Kipkorir
Abstract: Uncertainties caused by climate change and population explosion require suitable methods for estimating grain yield during the growing seasons. This paper evaluates the applicability of the AquaCrop model in the region of western Kenya. The objectives of the study were to: simulate the long-term maize crop yields for the region using AquaCrop model for variable climate scenarios, and estimate the expected yield for the ongoing season. Climate was classified into below normal (<x̅ − 1∂), normal (between x̅ − 1∂ and x̅ + 1∂) and above normal (>x̅ + 1∂) conditions based on the Kenya Meteorological Department (KMD) convention. Simulation of grain yield was based on model calibration results, periodic KMD forecasts and the long-term mean for the seasons. The calibrated model is able to estimate both long-term seasonal grain yield and expected harvest for the ongoing season based on climatic conditions that are compared with the long-term seasonal characteristics and complemented by meteorological forecasts. The ongoing season yield simulation was based on persistence theory of Markov processes whose results strongly correlated (r = 0.9) with actual seasonal observed yield.
- Influences of land use and climate changes on hydrologic system in the
northeastern river basin of Thailand
- Authors: Nuanchan Singkran; Jaruporn Tosang, Doungjai Waijaroen, Naree Intharawichian, Ornanong Vannarart, Pitchaya Anantawong, Karika Kunta, Poonsak Wisetsopa, Tanomkwan Tipvong, Naruekamon Janjirawuttikul, Fatah Masthawee, Sanguanpran Amornpatanawat Sukrit Kirtsaeng
Abstract: This study was a first attempt to portray the effects of land use and climate changes (CCs) on the hydrologic system in the Lamtakhong Basin in northeastern Thailand, which has been disturbed by various human activities, making it difficult to determine these impacts on hydrologic conditions. The hydrologic Soil and Water Assessment Tool model was set up with land use and soil data of 2002 and observed flow and weather data during 1999–2000. After the model was calibrated and validated against observed flow data during 2001–2009, its land use change scenario with input land use data of 2011 and its CC scenario with input weather data during 2010–2065 were simulated. The results showed that changing land use over the 10-year period had trivial influences on the hydrologic system, whereas changing climate over the 56-year period appeared to affect both water yields and flows. Water scarcity will tend to take place across the Lamtakhong Basin in the near future. Longer periods of severe droughts and floods might occasionally occur, particularly downstream. These findings will be useful for land and water resources managers and policy-makers to manage land and water resources in the river basin.