Adaptive Water Resources Management Research Articles

Bayesian dynamic modelling for nonstationary hydroclimatic time series forecasting along with uncertainty quantification

AbstractForecasting of hydrologic time series, with the quantification of uncertainty, is an important tool for adaptive water resources management. Nonstationarity, caused by climate forcing and other factors, such as change in physical properties of catchment (urbanization, vegetation change, etc.), makes the forecasting task too difficult to model by traditional Box–Jenkins approaches. In this paper, the potential of the Bayesian dynamic modelling approach is investigated through an application to forecast a nonstationary hydroclimatic time series using relevant climate index information. The target is the time series of the volume of Devil's Lake, located in North Dakota, USA, for which it was proved difficult to forecast and quantify the associated uncertainty by traditional methods. Two different Bayesian dynamic modelling approaches are discussed, namely, a constant model and a dynamic regression model (DRM). The constant model uses the information of past observed values of the same time series, whereas the DRM utilizes the information from a causal time series as an exogenous input. Noting that the North Atlantic Oscillation (NAO) index appears to co‐vary with the time series of Devil's Lake annual volume, its use as an exogenous predictor is explored in the case study. The results of both the Bayesian dynamic models are compared with those from the traditional Box–Jenkins time series modelling approach. Although, in this particular case study, it is observed that the DRM performs marginally better than traditional models, the major strength of Bayesian dynamic models lies in the quantification of prediction uncertainty, which is of great value in hydrology, particularly under the recent climate change scenario. Copyright © 2008 John Wiley & Sons, Ltd.

Vulnerability of Korean water resources to climate change and population growth

Freshwater availability is affected by changes in climate and growth. We assessed the freshwater vulnerability for five major Korean river basins for 2015 and 2030. We used a regional climate model based on the IPCC SRES A2 scenario, US Geological Survey's Precipitation Rainfall Simulation Model, and population and industrial growth scenarios for impact assessment. The model simulation results suggest increasing spatial and temporal variations of water stress for the basins that are already developed. While freshwater is more vulnerable to growth scenarios than the climate change scenario, climate change alone could decrease mean annual runoff by 10% in four major river basins by 2030. As the first national assessment of climate change, we suggest possible adaptive water resource management and policy strategies for reducing climate related risks in Korea.

Property Right Effects on the Adaptive Management of Australian Water

Adaptive management is increasingly proclaimed as a key principle underlying the management of a range of natural resources, including water, within jurisdictions across Australia. However, it is often inferred that there is a potential conflict between the use of adaptive management principles and the economically efficient use of water resources. The National Water Initiative has again raised these issues following the inclusion of perpetual property rights for water in certain circumstances. This article examines the literature on adaptive management theory, and explores the extent to which the principles of adaptive management are consistent with the Council of Australian Governments (COAG) intentions regarding water property rights, as a means of improving the economic efficiency of water use. The article concludes that, counter-intuitively, some elements of the strengthening of water property rights may be conducive to adaptive management of Australia's water resources. However, significant challenges remain in both the refinement of water rights and altering the resource management philosophy to accord with all elements of adaptive management.

Property Right Effects on the Adaptive Management of Australian Water

Adaptive management is increasingly proclaimed as a key principle underlying the management of a range of natural resources, including water, within jurisdictions across Australia. However, it is often inferred that there is a potential conflict between the use of adaptive management principles and the economically efficient use of water resources. The National Water Initiative has again raised these issues following the inclusion of perpetual property rights for water in certain circumstances. This article examines the literature on adaptive management theory, and explores the extent to which the principles of adaptive management are consistent with the Council of Australian Governments (COAG) intentions regarding water property rights, as a means of improving the economic efficiency of water use. The article concludes that, counter-intuitively, some elements of the strengthening of water property rights may be conducive to adaptive management of Australia's water resources. However, significant challenges remain in both the refinement of water rights and altering the resource management philosophy to accord with all elements of adaptive management.

Low-input sustainable agriculture using ecological management practices

The use of chemicals for high crop productivity and compensation for soil, water and biological resource degradation contribute to the high production costs and other problems of U.S. agriculture. This has prompted strong interest by U.S. farmers in low-input sustainable agriculture. The principles that underlie a low-input sustainable agricultural system are: (1) adapting the agricultural system to the environment of the region, including soil, water, climate and biota present at the site; (2) optimizing the use of biological and chemical/physical resources in the agroecosystem. In this investigation, it was demonstrated that high corn yields could be maintained and input costs reduced by adaptive management of soil, water, energy and biological resources. For example, soil erosion was reduced from 18 t ha −1 year to 1 t ha −1 year −1 and pest control accomplished without the use of pesticides. This reduced the costs of corn production 33% while reducing fossil energy inputs by about 50%.