TWO PRACTICAL APPROACHES FOR DETERMINING THE CONFIDENCE INTERVAL OF RAINFALL DEPTH PERCENTILES1

ABSTRACT: A simple simulation type approach and a statistical method are proposed for determining the confidence interval of the T‐year frequency rainfall percentiles (or precipitation extremes) for generalized extreme value (GEV) distributions. The former method is based on the Monte Carlo testing procedure. To generate realizations, the covariance structure of the three parameters of GEV is investigated using an observed information matrix of the likelihood function. For distributions with realistic parameters, the correlation between the location and the scale parameters is practically constant when the shape parameter varies around values close to its optimal value. The latter method is based on likelihood ratio statistics. In the case where the joint confidence surface for shape parameters and estimates is plotted with lines of best estimates, the region where the estimated best percentile value can be chosen as a possible estimate is part of the joint confidence surface. The projection of this bounded region on axis of percentile is defined as the effective confidence interval in this research. The use of this effective interval as the confidence interval of the percentile of T‐year frequency rainfall is particularly recommended because it is stable for T and it reflects variations in all three parameters of GEV appropriately.     

GENETIC PROGRAMMING: A NEW PARADIGM IN RAINFALL RUNOFF MODELING1

ABSTRACT: Genetic Programming (GP) is a domain‐independent evolutionary programming technique that evolves computer programs to solve, or approximately solve, problems. To verify GP's capability, a simple example with known relation in the area of symbolic regression, is considered first. GP is then utilized as a flow forecasting tool. A catchment in Singapore with a drainage area of about 6 km² is considered in this study. Six storms of different intensities and durations are used to train GP and then verify the trained GP. Analysis of the GP induced rainfall and runoff relationship shows that the cause and effect relationship between rainfall and runoff is consistent with the hydrologic process. The result shows that the runoff prediction accuracy of symbolic regression based models, measured in terms of root mean square error and correlation coefficient, is reasonably high. Thus, GP induced rainfall runoff relationships can be a viable alternative to traditional rainfall runoff models.     

AN INTEGRATIVE APPROACH TOWARDS UNDERSTANDING ECOLOGICAL RESPONSES TO DAM REMOVAL: THE MANATAWNY CREEK STUDY1

ABSTRACT: Dam removal has been proposed as an effective method of river restoration, but few integrative studies have examined ecological responses to the removal of dams. In 1999, we initiated an interdisciplinary study to determine ecological responses to the removal of a 2 m high dam on lower Manatawny Creek in southeastern Pennsylvania. We used an integrative monitoring program to assess the physical, chemical, and biological responses to dam removal. Following removal in 2000, increased sediment transport has led to major changes in channel form in the former impoundment and downstream reaches. Water quality did not change markedly following removal, probably because of the impoundment's short hydraulic residence time (less than two hours at base flow) and infrequent temperature stratification. When the impoundment was converted to a free flowing reach, the composition of the benthic macroinvertebrate and fish assemblages in this portion of Manatawny Creek shifted dramatically from lentic to lotic taxa. Some fish species inhabiting the free flowing reach downstream from the dam were negatively affected by large scale sediment transport and habitat alteration following dam removal, but this appears to be a short term response. Based on our observations and experiences in this study, we provide a list of issues to evaluate when considering future dam removals.     

APPLICATION OF TABU SEARCH TO GROUND WATER PARAMETER ZONATION1

ABSTRACT: The spatial distribution of hydrogeologic parameter is an important issue in ground water simulation. One of the methods is to divide an area into several zones such that parameters are assumed to be constant within zone. The purpose of this study is to apply Tabu Search (TS) to find the best zonation of parameters that can result in the best ground water simulation. The initial zonation can be determined as the Thiessen method, and then zonation is optimized by T.S. The mean square error between simulated and observed hydraulic heads was used as the objective function. A designed confined aquifer with known zonation was used as an example to test the proposed method. Results indicated that Tabu Search can locate the optimal zonation successfully and avoid being trapped by local optimal zonations. Besides this, four other arbitrary initial zonations can be directed to the optimal zonation by TS, which proves the robustness of the proposed method. The method proposed in this study is feasible and expected to work well in the field problems with sufficient sampling of concerned parameters.     

The workload and performance relationship in the real world: a study of police officers in a field shooting exercise.

We examined the relationship between perceived workload and performance by evaluating the responses of police officers to 4 different draw-and-shoot tasks in a night field training exercise which was part of their regular training regimen. Sixty-two police officers volunteered to participate. Results demonstrated an associative trend among 3 tasks where shooting performance decreased and workload increased as the tasks became more complex. However, performance on 1 specific shooting task did not correlate with any of the other 3 tasks, and in this 1 exceptional case, insensitivities were observed in which workload increased but performance remained constant.     

Consequences of Buffelgrass Pasture Development for Primary Productivity,Perennial Plant Richness,and Vegetation Structure in the Drylands of Sonora,Mexico

Abstract: In large parts of northern Mexico native plant communities are being converted to non‐native buffelgrass (Pennisetum ciliare) pastures, and this conversion could fundamentally alter primary productivity and species richness. In Sonora, Mexico land conversion is occurring at a regional scale along a rainfall‐driven gradient of primary productivity, across which native plant communities transition from desert scrub to thorn scrub. We used a paired sampling design to compare a satellite‐derived index of primary productivity, richness of perennial plant species, and canopy‐height profiles of native plant communities with buffelgrass pastures. We sampled species richness across a gradient of primary productivity in desert scrub and thorn scrub vegetation to examine the influence of site productivity on the outcomes of land conversion. We also examined the influence of pasture age on species richness of perennial plants. Index values of primary productivity were lower in buffelgrass pastures than in native vegetation, which suggests a reduction in primary productivity. Land conversion reduced species richness by approximately 50% at local and regional scales, reduced tree and shrub cover by 78%, and reduced canopy height. Land conversion disproportionately reduced shrub species richness, which reflects the common practice among Sonoran ranchers of conserving certain tree and cactus species. Site productivity did not affect the outcomes of land conversion. The age of a buffelgrass pasture was unrelated to species richness within the pasture, which suggests that passive recovery of species richness to preconversion levels is unlikely. Our findings demonstrate that land conversion can result in large losses of plant species richness at local and regional scales and in substantial changes to primary productivity and vegetation structure, which casts doubt on the feasibility of restoring native plant communities without active intervention on the part of land managers.     

Karst Hydrological Processes and Grey System Model1

Hao, Yonghong, Jiaojuan Zhao, Huamin Li, Bibo Cao, Zhongtang Li, and Tian‐Chyi J. Yeh, 2012. Karst Hydrological Processes and Grey System Model. Journal of the American Water Resources Association (JAWRA) 48(4): 656‐666. DOI: 10.1111/j.1752‐1688.2012.00640.x Abstract: The karst hydrological processes are the response of karst groundwater system to precipitation. This study provided a concept model of karst hydrological processes. The hydraulic response time of spring discharge to precipitation includes the time that precipitation penetrates through the vadose zone, and the subsequent groundwater pressure wave propagates to a spring outlet. Due to heterogeneities in karst aquifers, the hydraulic response time is different in different areas. By using grey system theory, we proposed a karst hydrological model that offers a calculation of hydraulic response time, and a response model of spring discharge to precipitation. Then, we applied the models to the Liulin Springs Basin, China. In the south part of the Liulin Springs Basin, where large fields of carbonate rocks outcrop with intensive karstification, the hydraulic response time is one year. In the north, where the Ordovician karst aquifer is covered by Quaternary loess sediments, the response time is seven years. The grey system GM(1,3) response model of spring discharge to precipitation was applied in consideration of the hydraulic response time. The model calibration showed that the average error was 6.55%, and validation showed that the average error was 12.19%.     

Neural Network Input Selection for Hydrological Forecasting Affected by Snowmelt1

Abstract: Snowmelt largely affects runoff in watersheds in Nordic countries. Neural networks (NN) are particularly attractive for streamflow forecasting whereas they rely at least on daily streamflow and precipitation observations. The selection of pertinent model inputs is a major concern in NNs implementation. This study investigates performance of auxiliary NN inputs that allow short‐term streamflow forecasting without resorting to a deterministic snowmelt routine. A case study is presented for the Rivière des Anglais watershed (700 km²) located in Southern Québec, Canada. Streamflow (Q), precipitations (rain R and snow S, or total P), temperature (T) and snow lying (A) observations, combined with climatic and snowmelt proxy data, including snowmelt flow (Q_SM) obtained from a deterministic model, were tested. NN implemented with antecedent Q and R produced the largest gains in performance. Introducing increments of A and T to the NNs further improved the performance. Long‐term averages, seasonal data, and Q_SM failed to improve the networks.