Modification of the National Weather Service Distributed Hydrologic Model for subsurface water exchanges between grids

To account for spatial variability of precipitation, as well as basin physiographic properties, the National Weather Service (NWS) has developed a distributed version of its hydrologic component, termed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM). Because channels are the only source of water exchange between neighboring computational elements, the absence of such exchange has been identified as a weakness in the model. The primary objective of this paper is to modify the model structure to account for subsurface water exchanges without dramatically altering the conceptual framework of the water balance module. The subsurface exchanges are established by partitioning the slow response components released from the lower layer storages into two parts: the first part involves the grid's conceptual channel, while the second is added to the lower layer storages of the downstream pixel. Realizing the deficiency of the water balance module to locate the lower zone layers in sufficient depths, a complementary study is conducted to test the feasibility of further improvement in the modified model by equally shifting downward the lower zone layers of all pixels over the basin. The Baron Fork at Eldon, Oklahoma, is chosen as the test basin. Ten years of grid-based multisensor precipitation data are used to investigate the effects of the modification, plus shifting the lower zone layers on model performance. The results show that the modified-shifted HL-RDHM can markedly improve the streamflow simulations at the interior point, as well as very high peak-flow simulations at the basin's outlet. Copyright 2011 by the American Geophysical Union

Cross-country typologies and development strategies to end hunger in Africa

The key motivation behind this study is to explore the many patterns of interactions between economic and non-economic factors in sub-Saharan Africa (hereafter referred to as Africa) in order to map out a typology of different types of country situations and thus, corresponding future options to develop strategies to end hunger and poverty in the region. The study builds on the earlier work of Irma Adelman and Cynthia Morris who argued that economic development is a dynamic, multi-faceted, nonlinear, and malleable process, a process explained by the many complex interactions between social, economic, political and institutional changes. As in Adelman and Morris, we use factor analysis to reduce a large number of variables into a manageable set of key factors. Next, using the newly developed classification and regression tree technique (CART), we link the outcome variables, such as per capital GDP and the prevalence of child malnutrition, with this smaller set of factors. This overcomes the limitations of Adelman and Morris. work that mixed the outcome and explanatory variables in their analysis. The analysis helps identify the most important factors for each outcome indicator, which provides guidance for defining the development of a typology and exploring future strategy options associated with each country type.

Simulating California reservoir operation using the classification and regression-tree algorithm combined with a shuffled cross-validation scheme

The controlled outflows from a reservoir or dam are highly dependent on the decisions made by the reservoir operators, instead of a natural hydrological process. Difference exists between the natural upstream inflows to reservoirs and the controlled outflows from reservoirs that supply the downstream users. With the decision maker's awareness of changing climate, reservoir management requires adaptable means to incorporate more information into decision making, such as water delivery requirement, environmental constraints, dry/wet conditions, etc. In this paper, a robust reservoir outflow simulation model is presented, which incorporates one of the well-developed data-mining models (Classification and Regression Tree) to predict the complicated human-controlled reservoir outflows and extract the reservoir operation patterns. A shuffled cross-validation approach is further implemented to improve CART's predictive performance. An application study of nine major reservoirs in California is carried out. Results produced by the enhanced CART, original CART, and random forest are compared with observation. The statistical measurements show that the enhanced CART and random forest overperform the CART control run in general, and the enhanced CART algorithm gives a better predictive performance over random forest in simulating the peak flows. The results also show that the proposed model is able to consistently and reasonably predict the expert release decisions. Experiments indicate that the release operation in the Oroville Lake is significantly dominated by SWP allocation amount and reservoirs with low elevation are more sensitive to inflow amount than others

Finding High-Dimensional D-OptimalDesigns for Logistic Models via Differential Evolution

D-optimal designs are frequently used in controlled experiments to obtain the most accurateestimate of model parameters at minimal cost. Finding them can be a challenging task, especially whenthere are many factors in a nonlinear model. As the number of factors becomes large and interact withone another, there are many more variables to optimize and the D-optimal design problem becomes highdimensionaland non-separable. Consequently, premature convergence issues arise. Candidate solutions gettrapped in local optima and the classical gradient-based optimization approaches to search for the D-optimaldesigns rarely succeed. We propose a specially designed version of differential evolution (DE) which is arepresentative gradient-free optimization approach to solve such high-dimensional optimization problems.The proposed specially designed DE uses a new novelty-based mutation strategy to explore the variousregions in the search space. The exploration of the regions will be carried out differently from the previouslyexplored regions and the diversity of the population can be preserved. The proposed novelty-based mutationstrategy is collaborated with two common DE mutation strategies to balance exploration and exploitationat the early or medium stage of the evolution. Additionally, we adapt the control parameters of DE as theevolution proceeds. Using logistic models with several factors on various design spaces as examples, oursimulation results show our algorithm can find D-optimal designs efficiently and the algorithm outperformsits competitors. As an application, we apply our algorithm and re-design a 10-factor car refueling experimentwith discrete and continuous factors and selected pairwise interactions. Our proposed algorithm was able toconsistently outperform the other algorithms and find a more efficient D-optimal design for the problem

Pegging To The Dollar And The Euro

The newly-launched euro is bound to attract some "trackers"- that is, countries that attempt to maintain exchange rate stability against the euro. In this paper, we ask whether the existence of trackers should be a matter of concern for the European Union. To gain some insight, we review the historical experience of the US with respect to dollar trackers. We identify and analyse the countries most likely to track the euro. Although the aggregate size of potential euro-trackers is small relative to the euro zone, we argue that this does not justify an attitude of benign neglect. Rather, we make recommendations for EU policy towards euro-trackers, arguing in favour of some limited and conditional support for stable bilateral exchange rates.

Federal Aid to the States: Historical Cause of Government Growth and Bureaucracy

In recent years, members of Congress have inserted thousands of pork-barrel spending projects into bills to reward interests in their home states. But such parochial pork is only a small part of a broader problem of rising federal spending on traditionally state and local activities. Federal spending on aid to the states increased from $286 billion in fiscal 2000 to an estimated$449 billion in fiscal 2007 and is the third-largest item in the federal budget after Social Security and national defense. The number of different aid programs for the states soared from 463 in 1990, to 653 in 2000, to 814 by 2006. The theory behind aid to the states is that federal policymakers can design and operate programs in the national interest to efficiently solve local problems. In practice, most federal politicians are not inclined to pursue broad, national goals; they are consumed by the competitive scramble to secure subsidies for their states. At the same time, federal aid stimulates overspending by the states, requires large bureaucracies to administer, and comes with a web of complex regulations that limit state flexibility. At all levels of the aid system, the focus is on spending and regulations, not on delivering quality services. And by involving all levels of government in just about every policy area, the aid system creates a lack of accountability. When every government is responsible for an activity, no government is responsible, as was evident in the aftermath of Hurricane Katrina. The failings of federal aid have long been recognized, but reforms and cuts have not been pursued for years. Aid has spawned a web of interlocking interests that block reform, including elected officials at three levels of government, armies of government employees, and thousands of trade associations representing the recipients of aid. Yet the system desperately needs to be scaled back, not least because the rising costs of federal programs for the elderly are putting a squeeze on the federal budget. To help spur reform, this study examines the historical growth of the aid system and describes its failings. Congress should reconsider the need for aid and begin terminating activities that could be better performed by state and local governments and the private sector