Identification of Priority Areas for Integrated Management of Semiarid Watersheds in the Ecuadorian Andes

Integrated watershed management (IWM) is a priority, especially in semiarid regions that are concurrently affected by population growth, land use change, soil erosion, and poor governance. In developing countries, IWM is often done without any support tool, scientific data, or deep knowledge of territory characteristics. The aim of this study was to present a case study to apply a decision support tool to prioritize areas for territory management. A simple, quantitative multi‐criteria analysis was applied in a semiarid basin of the Ecuadorian Andes to identify the zones of greatest concern for implementation of resource conservation and management practices at a local and regional scale. In addition to describing the current state of the conditions of this basin, our results suggest scenarios of change in relation to official population projections based on spatial analysis of land use change. Analysis resulted in a scattered distribution of priority values within the watershed, so a hierarchical rule was incorporated to define priorities at the subwatershed (SW) scale. Our analysis identified four SW of very high priority and urgent need to implement management practices. Based on projections of future change due to population growth and land cover change, the number of subbasins that require more attention was doubled. Finally, this study includes zones for management or conservation of the land, according to the Sustainable Development Goals.     

Forest ecosystems of the volga basin under conditions of global climate warming: Local ecological prediction

Prediction based on one of the latest extreme prognostic models, the Hadley Centre Model HadCM3 (version A2) has been performed using an original method of discrete empirical statistical modeling of ecosystems. Probabilistic scenarios of the expected changes in summer soil moisture content until the mid-22nd century and corresponding structural and functional changes in forest ecosystems for different zonal/regional conditions of the Volga basin are described.     

Importance of Crop Yield in Calibrating Watershed Water Quality Simulation Tools1

Surendran Nair, Sujithkumar, Kevin W. King, Jonathan D. Witter, Brent L. Sohngen, and Norman R. Fausey, 2011. Importance of Crop Yield in Calibrating Watershed Water Quality Simulation Tools. Journal of the American Water Resources Association (JAWRA) 47(6):1285–1297. DOI: 10.1111/j.1752‐1688.2011.00570.x Abstract: Watershed‐scale water‐quality simulation tools provide a convenient and economical means to evaluate the environmental impacts of conservation practices. However, confidence in the simulation tool’s ability to accurately represent and capture the inherent variability of a watershed is dependent upon high quality input data and subsequent calibration. A four‐stage iterative and rigorous calibration procedure is outlined and demonstrated for Soil Water Analysis Tool (SWAT) using data from Upper Big Walnut Creek (UBWC) watershed in central Ohio, USA. The four stages and the sequence of their application were: (1) parameter selection, (2) hydrology calibration, (3) crop yield calibration, and (4) nutrient loading calibration. Following the calibration, validation was completed on a 10 year period. Nash‐Sutcliffe efficiencies for streamflow over the validation period were 0.5 for daily, 0.86 for monthly, and 0.87 for annual. Prediction efficiencies for crop yields during the validation period were 0.69 for corn, 0.54 for soybeans, and 0.61 for wheat. Nitrogen loading prediction efficiency was 0.66. Compared to traditional calibration approaches (no crop yield calibration), the four‐stage approach (with crop yield calibration) produced improved prediction efficiencies, especially for nutrient balances.     

PRESENCE AND DISTRIBUTION OF CHLORINATED ORGANIC COMPOUNDS IN STREAMBED SEDIMENTS,NEW JERSEY1

ABSTRACT: Concentrations of 18 hydrophobic chlorinated organic compounds in streambed sediments from 100 sites throughout New Jersey were examined to determine (1) which compounds were detected most frequently, (2) whether detection frequencies differed among selected drainage basins, and (3) whether concentrations differed significantly among selected drainage basins. Twelve drainage basins across New Jersey that contain a range of land-use patterns and population densities were selected to represent various types and degrees of development. To ensure an adequate number of samples for statistical comparison among drainage basins, the 12 selected basins were consolidated into seven drainage areas on the basis of similarities in land-use patterns and population densities. Additionally, data for three classes of chlorinated organic compounds in streambed sediments from 255 sites throughout New Jersey were examined to determine whether the presence of these compounds in streambed sediments is related to the type and degree of development within the drainage area of each sampling site. Chlorinated organic compounds detected most frequently within the seven representative drainage areas were DDT, DDE, DDD, chlordane, dieldrin, and PCBs. DDT, DDE, and DDD, which were the most widely distributed organic compounds, were detected in about 60 to 100 percent of the samples from all drainage areas but one (where the detection rate for these compounds was about 20 to 40 percent). Chiordane and dieldrin were detected in about 80 to 100 percent of samples from highly urbanized and populated drainage areas; detection frequencies for these compounds tended to be smaller in less developed and populated areas. PCBs were detected in about 40 to 85 percent of samples from all drainage areas; detection frequencies were highest in the most heavily developed and populated areas. Analysis of variance on rank-transformed organic compound concentrations normalized to sediment organic carbon content was used to evaluate differences in concentrations among the seven representative drainage areas. Chlordane and PCBs were the chlorinated organic compounds with the most highly elevated concentrations in streambed sediments across the State. Median normalized concentrations of all six of the most frequently detected chlorinated organic compounds were highest in the most heavily urbanized and populated drainage area and lowest in the less populated, predominantly agricultural or forested areas. Concentrations of DDT and DDE, however, did not differ significantly among most of the drainage areas. Concentrations of DDD, chlordane, dieldrin, and PCBs differed significantly among drainage areas. The highest median normalized concentrations were found in samples from the most heavily urbanized and populated areas, and the lowest were in samples from the least developed, most heavily forested area. Logistic regression was used to examine relations between the presence of hydrophobic chlorinated organic compounds in streambed sediments at specified concentrations and variables that characterize the type and degree of development within the drainage areas of 255 sites across New Jersey. The explanatory variables found most useful for predicting the presence of chlorinated organic compounds in streambed sediments include total population and amounts (in square kilometers) of various land-use categories. Logistic regression equations were developed to identify significant relations between population and amounts of specific land-use categories within drainage areas and the probability of detecting chlorinated organic contaminants in streambed sediments. These relations can be used to assist in the identification of geographic regions of primary concern for contamination of bed sediments by chlorinated organic compounds across the State.     

Predicting Bird Species Distributions in Reconstructed Landscapes

Abstract:  Landscape optimization for biodiversity requires prediction of species distributions under alternative revegetation scenarios. We used Bayesian model averaging with logistic regression to predict probabilities of occurrence for 61 species of birds within highly fragmented box–ironbark forests of central Victoria, Australia. We used topographic, edaphic, and climatic variables as predictors so that the models could be applied to areas where vegetation has been cleared but may be replanted. Models were evaluated with newly acquired, independent data collected in large blocks of remnant native vegetation. Successful predictions were obtained for 18 of 45 woodland species (40%). Model averaging produced more accurate predictions than "single best" models. Models were most successful for smaller-bodied species that probably depend on particular vegetation types. Predictions for larger, generalist species, and seasonal migrants were less successful, partly because of changes in species distributions between model building (1995–1997) and validation (2004–2005) surveys. We used validated models to project occurrence probabilities for individual species across a 12,000-km² region, assuming native vegetation was present. These predictions are intended to be used as inputs, along with landscape context and temporal dynamics, into optimization algorithms to prioritize revegetation. Longer-term data sets to accommodate temporal dynamics are needed to improve the predictive accuracy of models.     

MODELING FLOW IN THE EVERGLADES AGRICULTURAL AREA IRRIGATION/DRAINAGE CANAL NETWORK1

ABSTRACT: The south Florida ecosystem and Lake Okeechobee are important water resource areas that have degraded due to changes in hydroperiod, water supply, and water quality. Approximately 56 percent of the total phosphorus in water discharged from the Everglades Agricultural Area (EAA) is in particulate form. Currently, farm-level best management practices are being implemented in the effort to reduce total phosphorus and sediment in off-farm discharges. The objective of this work was to develop and calibrate a model describing water movement in primary EAA canals as a first step to development of a water quality (i.e., nutrient, sediment) model. The Netherlands-developed mechanistic flow and water quality model (DUFLOW) was adapted for the EAA. Flow, stage, geometry, canal network, and meteorological data, October 13, 1993, to February 13, 1994, were used to adapt and calibrate the DUFLOW model for EAA water level and flow in primary canals. Direct runoff discharge into the primary canals from farm-pump stations was used as runoff input for the model. The model results are comparable to an independently-calculated water balance for the EAA. The calibrated flow model will be the basis for the calibration of sediment and chemical transport in the future.     

ANN OUTPUT UPDATING OF LUMPED CONCEPTUAL RAINFALL/RUNOFF FORECASTING MODELS1

ABSTRACT: Artificial neural networks (ANNs) are tested for the output updating of one‐day‐ahead and three‐day‐ahead streamflow forecasts derived from three lumped conceptual rainfall/runoff (R‐R) models: the GR4J, the IHAC, and the TOPMO. ANN output updating proved superior to a parameter updating scheme and to the ‘simple’ output updating scheme, which always replicates the last observed forecast error. In fact, ANN output updating was able to compensate for large differences in the initial performance of the three tested lumped conceptual R‐R models, which the other tested updating approaches were not able to achieve. This is done mainly by incorporating input vectors usually exploited for ANN R‐R modeling such as previous rainfall and streamflow observations, in addition to the previous observed error. For one‐day‐ahead forecasts, the performance of all three lumped conceptual R‐R models, used in conjunction with ANN output updating, was equivalent to that of the ANN R‐R model. For three‐day‐ahead forecasts, the performance of the ANN‐output‐updated conceptual models was even superior to that of the ANN R‐R model, revealing that the conceptual models are probably performing some tasks that the ANN R‐R model cannot map. However, further testing is needed to substantiate the last statement.     

ESTIMATING AQUIFER PARAMETERS FROM A HORIZONTAL WELL PUMPING TEST IN AN UNCONFINED AQUIFER1

ABSTRACT: A pumping test on a phreatic glacial till aquifer was performed near Ames, Iowa, in November 1990. The head in a horizontal well was pumped down rapidly and then held constant for the duration of the 30-hour test. Throughout the test, the flow rate at the pumped well and the head at an adjacent vertical observation well were recorded. The pumping test data were used to determine the hydraulic conductivity and specific yield of the aquifer. The results indicate a hydraulic conductivity of 2.23 × 10^?5 cm/s and a representative specific yield of 0.03. Hydraulic conductivity was calculated by a simple integration of Darcy's Law after extrapolating the data to steady state. Specific yield was determined by use of several methods from the literature and a new method proposed by the author. The results show that specific yield increases with time, and that each method is within an order of magnitude of the others.     

喷氨同时脱除NO和N_2O过程的化学动力学模拟

本文采用化学动力学模拟的方法,对广泛应用于燃煤锅炉的喷氨脱硝技术进行了研究,首次发现在燃煤锅炉的烟气中喷入氨气不仅可以降低NO_x的排放量.而且可以同时降低N_2O的排放量.文中还就喷氨初期的烟气温度、烟气中的含氧量和水份、NO和N_2O的初始浓度、烟气中的CO含量以及喷氨量对喷氨同时脱除NO和N_2O效果的影响进行了计算分析,确定了喷氨同时脱除NO和N_2O的最佳条件.对喷氨过程的化学反应机理进行的分析表明,该过程之所以能同时脱除NO和N_2O,是因为在NH_3的分解和NO的还原过程中产生了一定浓度的H和OH离子,从而加速了N_2O的热分解过程.     

精馏过程动态建模与安全控制研究进展

介绍了精馏过程的动态建模与安全控制等方面的研究现状,提出了基于塔板力学模型动态建模与安全分析技术,通过对精馏塔动态特性分析,可准确反映精馏过程的动态变化。根据动态响应规律,建立基于智能调控的先进性控制系统,指导精馏塔、阀门、泵等设备进行变频调节,从而保证精馏塔的稳定运行。