Global climate change and its impacts on water resources planning and management: assessment and challenges

Population explosion and its many associated effects (e.g. urbanization, water pollution, deforestation) have already caused enormous stress on the world’s fresh water resources and, in turn, environment, health, and economy. According to latest World Health Organization estimates, about 900 million people still lack access to safe drinking water, about 2.5 billion people lack access to proper sanitation, millions of people die every year from water-related disasters and diseases, and economic losses in the order of billions of dollars occur due to water-related disasters. With the global climate change anticipated to have threatening consequences on our water resources and environment both at the global level and at local/regional levels (e.g. increases in the number and magnitude of floods and droughts, increases in sea levels), a general assessment is that the future state of our water resources will be a lot worse than it is now. The facts that over 300 rivers around the world are being shared by two or more nation states and that there are already numerous conflicts in the planning, development, and management of water resources in these basins further complicate matters for future water resources planning. In view of these, any sincere effort towards proper management of our future water resources and resolving potential future water-related conflicts will need to overcome many challenges. These challenges are both biophysical science-related and human science-related. The biophysical science challenges include: identification of the actual causes of climate change, development of global climate models (GCMs) that can adequately incorporate these causes to generate dependable future climate projections at larger scales, formulation of appropriate techniques to downscale the GCM outputs to local conditions for hydrologic predictions, and reliable estimation of the associated uncertainties in all these. The human science challenges have social, political, economic, and environmental facets that often act in an interconnected manner; proper ‘communication’ of (or lack thereof) our climate-water ‘scientific’ research activities to fellow scientists and engineers, policy makers, economists, industrialists, farmers, and the public at large crucially contributes to these challenges. The present study is intended to review the current state of our water resources and the climate change problem and to detail the challenges in dealing with the potential impacts of climate change on our water resources.     

Dynamic characteristics of monthly rainfall in the Korean Peninsula under climate change

Global climate change is one of the most serious issues we are facing today. While its exact impacts on our water resources are hard to predict, there is a general consensus among scientists that it will result in more frequent and more severe hydrologic extremes (e.g. floods, droughts). Since rainfall is the primary input for hydrologic and water resource studies, assessment of the effects of climate change on rainfall is essential for devising proper short-term emergency measures as well as long-term management strategies. This is particularly the case for a region like the Korean Peninsula, which is susceptible to both floods (because of its mountainous terrain and frequent intense rainfalls during the short rainy season) and droughts (because of its smaller area, long non-rainy season, and lack of storage facilities). In view of this, an attempt is made in the present study to investigate the potential impacts of climate change on rainfall in the Korean Peninsula. More specifically, the dynamics of ‘present rainfall’ and ‘future rainfall’ at the Seoul meteorological station in the Han River basin are examined and compared; monthly scale is considered in both cases. As for ‘present rainfall,’ two different data sets are used: (1) observed rainfall for the period 1971–1999; and (2) rainfall for the period 1951–1999 obtained through downscaling of coarse-scale climate outputs produced by the Bjerknes Center for Climate Research-Bergen Climate Model Version 2 (BCCR-BCM2.0) climate model with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (IPCC SRES) 20th Century Climate in Coupled Models (20C3M) scenario. The ‘future rainfall’ (2000–2099) is obtained through downscaling of climate outputs projected by the BCCR-BCM2.0 with the A2 emission scenario. For downscaling of coarse-scale climate outputs to basin-scale rainfall, a K-nearest neighbor (K-NN) technique is used. Examination of the nature of rainfall dynamics is made through application of four methods: autocorrelation function, phase space reconstruction, correlation dimension, and close returns plot. The results are somewhat mixed, depending upon the method, as to whether the rainfall dynamics are chaotic or stochastic; however, the dynamics of the future rainfall seem more on the chaotic side than on the stochastic side, and more so when compared to that of the present rainfall.     

Assessment of change in design flood frequency under climate change using a multivariate downscaling model and a precipitation-runoff model

Precipitation and runoff are key elements in the hydrologic cycle because of their important roles in water supply, flood prevention, river restoration, and ecosystem management. Global climate change, widely accepted to be happening, is anticipated to have enormous consequences on future hydrologic patterns. Studies on the potential changes in global, regional, and local hydrologic patterns under global climate change scenarios have been an intense area of research in recent years. The present study contributes to this research topic through evaluation of design flood under climate change. The study utilizes a weather state-based, stochastic multivariate model as a conditional probability model for simulating the precipitation field. An important premise of this study is that large-scale climatic patterns serve as a major driver of persistent year-to-year changes in precipitation probabilities. Since uncertainty estimation in the study of climate change is needed to examine the reliability of the outcomes, this study also applies a Bayesian Markov chain Monte Carlo scheme to the widely used SAC-SMA (Sacramento soil moisture accounting) precipitation-runoff model. A case study is also performed with the Soyang Dam watershed in South Korea as the study basin. Finally, a comprehensive discussion on design flood under climate change is made.     

Climate change and implications for agriculture in Niger

Five-year moving averages of annual rainfall for 21 locations in Niger showed a decline in the annual rainfall after 1960. Correlation coefficients of the moving averages of monthly rainfall with annual rainfall showed significant correlations between the decline in the annual rainfall with decreased rainfall in August. Analysis of daily rainfall data for rainy season parameters of interest to agriculture suggested that from 1965 there was a significant decrease in the amount of rainfall and in the number of rainy days in the months of July and August, resulting in a decreased volume of rainfall for each rainstorm. In comparison to the period 1945–64, major shifts have occurred in the average dates of onset and ending of rains during 1965–88. The length of the growing season was reduced by 5–20 days across different locations in Niger. The standard deviation for the onset and ending of the rains as well as the length of the growing season has increased, implying that cropping has become more risky. Water balance calculations also demonstrated that the probability of rainfall exceeding potential evapotranspiration decreased during the growing season. The implications of these changes for agriculture in Niger are discussed using field data.     

Derivation of the aerodynamic roughness parameters for a Sahelian savannah site using the eddy correlation technique

Vertical exchange of heat, moisture and momentum above the earth's surface depends strongly on the turbulence generated by surface roughness. This roughness is best specified through the roughness length and the zero plane displacement. The ratio of windspeed to friction velocity was measured at four heights using the eddy correlation technique at a fallow savannah site in the Sahel. The change in this ratio with height was used to derive the zero plane displacement and the roughness length of the surface, together with an estimate of the error in each parameter. These were estimated as 0.93 ± 0.35 m and 0.17 ± 0.01 m, respectively. The method appears to be a more robust alternative to wind profile derivation.     

Hydrologic complexity and classification: a simple data reconstruction approach

Technological advances, by facilitating extensive data collection, better data sharing, formulation of sophisticated methods, and development of complex models, have brought hydrologic research to a whole new level. Despite these obvious advances, there are also concerns about their general use in practice. On the one hand, it is natural to develop more complex models than perhaps needed (i.e. representations having too many parameters and requiring too much data); on the other hand, it is often difficult to ‘translate’ results from one specific situation to another. Recent studies have addressed these concerns, albeit in different forms, such as dominant processes, thresholds, model integration, and model simplification. A common aspect in some of these studies is that they recognize the need for a globally agreed upon ‘classification system’ in hydrology. The present study explores this classification issue further from a simple phase‐space data reconstruction perspective. The reconstruction involves representation of the given multidimensional hydrologic system using only an available single‐variable series through a delay coordinate procedure. The ‘extent of complexity’ of the system (defined especially in the context of variability of relevant data) is identified by the ‘region of attraction of trajectories’ in the phase space, which is then used to classify the system as potentially low‐, medium‐ or high‐dimensional. A host of river‐related data, representing different geographic and climatic regions, temporal scales, and processes, are studied. Yielding ‘attractors’ that range from ‘very clear’ ones to ‘very blurred’ ones, depending on data, the results indicate the usefulness of this simple reconstruction concept for studying hydrologic system complexity and classification. Copyright © 2007 John Wiley & Sons, Ltd.     

Determination of suspended sediments particle size distribution using image capturing method

Suspended sediments deposition at estuary affects marine life in coastal ecosystem. Particle size distribution (PSD) is used to find settling velocity of suspended sediments. In this study, a new image capturing system for size analysis (ICS4S) method using digital camera-based image capturing technique for determining PSD is proposed and validated. Image of suspended sediments is acquired using a low-cost setup developed, and ImageJ software is used for image processing. The PSD results obtained using ICS4S method is well correlated with hydrometer test and the Shen method. The proposed ICS4S method is easy to understand and implement both in laboratory and field.     

Analysis of stability of earthen dams in kachchh region, Gujarat, India

The Kachchh region of Gujarat, India bore the brunt of a disastrous earthquake of magnitude M_w = 7.6 that occurred on January 26, 2001. The major cause of failure of various structures including earthen dams was noted to be the presence of liquefiable alluvium in the foundation soil. Results of back-analysis of failures of Chang, Tappar, Kaswati and Rudramata earth dams using pseudo-static limit equilibrium approach presented in this paper confirm that the presence of liquefiable layer contributed to lesser factors of safety leading to a base type of failure that was also observed in the field. Following the earthquake, earth dams have been rehabilitated by the concerned authority and it is imperative that the reconstructed sections of earth dams be reanalyzed. It is also increasingly realized that risk assessment of dams in view of the large-scale investment made and probabilistic analysis is necessary. In this study, it is demonstrated that the probabilistic approach when used in conjunction with deterministic approach helps in providing a rational solution for quantification of safety of the dam and in the estimation of risk associated with the dam construction.     

Suspended sediment load estimation and the problem of inadequate data sampling: a fractal view

Suspended sediment load estimation at high resolutions is an extremely difficult task, because: (1) it depends on the availability of high‐resolution water discharge and suspended sediment concentration measurements, which are often not available; (2) any errors in the measurements of these two components could significantly influence the accuracy of suspended sediment load estimation; and (3) direct measurements are very expensive. The purpose of this study is to approach this sampling problem from a new perspective of fractals (or scaling), which could provide important information on the transformation of suspended sediment load data from one scale to another. This is done by investigating the possible presence of fractal behaviour in the daily suspended sediment load data for the Mississippi River basin (at St. Louis, Missouri). The presence of fractal behaviour is investigated using five different methods, ranging from general to specific and from mono‐fractal to multi‐fractal: (1) autocorrelation function; (2) power spectrum; (3) probability distribution function; (4) box dimension; and (5) statistical moment scaling function. The results indicate the presence of multi‐fractal behaviour in the suspended sediment load data, suggesting the possibility of transformation of data from one scale to another using a multi‐dimensional model. Copyright © 2005 John Wiley & Sons, Ltd.