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Mark R. Jury

Abstract

The Turks and Caicos Islands (TCI) climate is described using mesoscale ocean and atmosphere datasets with a focus on thermodynamic versus kinematic controls, the influence of the nearby island of Hispaniola, and factors affecting early colonization and fluctuations of marine resources. The key findings include the following: trade winds accelerate to 7 m s−1 north of Hispaniola and enhance anticyclonic subsidence; there is a dry-south/wet-north pattern of rainfall that opposes surface temperature and salinity fields; ocean currents near TCI are northwestward but there is a counterclockwise gyre near Haiti that guided colonization; conch catch increases when trade winds strengthen and SST declines; TCI's dry climate limits groundwater resources, food production, and population density; and Caicos Island sheds a wind wake that boosts SST and local convection, as evident in Quick Scatterometer (QuikSCAT) observations and operational model products. Further studies of small island climates will benefit from an ever-increasing stream of mesoscale datasets.

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Antonio Sérgio Cunha Freire, Maria Isabel Vitorino, Mário Augusto Gonçalves Jardim, Adriano Marlison Leão de Sousa, Adriano Costa Quaresma, Fábio Gomes de Oliveira, and Rafael do Nascimento Pereira

Abstract

The effects of diffuse solar radiation (DSR), precipitation, and air temperature on survival and mortality of seedlings of açai (Euterpe oleracea Mart.) were evaluated in an estuarine floodplain forest located in the environmental protection area of Combu Island, Belém, Pará, Brazil, in the period from April 2010 to January 2011. An automatic weather station was installed in the understory of Combu Island to collect from the elements, whose location was defined by taking into account the sheer number of seedlings of açai and the incidence of diffuse radiation through canopy sunflecks on the solar panel. Six plots of 2 m × 20 m were demarcated and divided into 10 subplots of 2 m × 2 m in the directions of north, south, east, and west and two others at random around the station. The seedlings with a height between 10 cm and 2 m were quantified and monitored biweekly for survival and mortality. Data were statistically analyzed by a Pearson correlation. Initially, 1072 individuals were recorded, with a significant survival rate of 764 (71.3%) and a mortality rate of 308 (28.7%); therefore, a positive correlation between precipitation and survival was seen, while DSR directly influenced the mortality in the months of May–July 2010, mainly in continuous days of radiation above 34.56 MJ m−2 day−1.

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D. W. Stahle, R. D. Griffin, D. M. Meko, M. D. Therrell, J. R. Edmondson, M. K. Cleaveland, L. N. Stahle, D. J. Burnette, J. T. Abatzoglou, K. T. Redmond, M. D. Dettinger, and D. R. Cayan

Abstract

Ancient blue oak trees are still widespread across the foothills of the Coast Ranges, Cascades, and Sierra Nevada in California. The most extensive tracts of intact old-growth blue oak woodland appear to survive on rugged and remote terrain in the southern Coast Ranges and on the foothills west and southwest of Mt. Lassen. In the authors' sampling of old-growth stands, most blue oak appear to have recruited to the canopy in the middle to late nineteenth century. The oldest living blue oak tree sampled was over 459 years old, and several dead blue oak logs had over 500 annual rings. Precipitation sensitive tree-ring chronologies up to 700 years long have been developed from old blue oak trees and logs. Annual ring-width chronologies of blue oak are strongly correlated with cool season precipitation totals, streamflow in the major rivers of California, and the estuarine water quality of San Francisco Bay. A new network of 36 blue oak chronologies records spatial anomalies in growth that arise from latitudinal changes in the mean storm track and location of landfalling atmospheric rivers. These long, climate-sensitive blue oak chronologies have been used to reconstruct hydroclimatic history in California and will help to better understand and manage water resources. The environmental history embedded in blue oak growth chronologies may help justify efforts to conserve these authentic old-growth native woodlands.

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Wondmagegn Yigzaw, Faisal Hossain, and Alfred Kalyanapu

Abstract

Since historical (predam) data are traditionally the sole criterion for dam design, future (postdam) meteorological and hydrological variability due to land-use and land-cover change cannot be considered for assessing design robustness. For example, postdam urbanization within a basin leads to definite and immediate increase in direct runoff and reservoir peak inflow. On the other hand, urbanization can strategically (i.e., gradually) alter the mesoscale circulation patterns leading to more extreme rainfall rates. Thus, there are two key pathways (immediate or strategic) by which the design flood magnitude can be compromised. The main objective of the study is to compare the relative contribution to increase in flood magnitudes through direct effects of land-cover change (urbanization and less infiltration) with gradual climate-based effects of land-cover change (modification in mesoscale storm systems). The comparison is cast in the form of a sensitivity study that looks into the response to the design probable maximum flood (PMF) from probable maximum precipitation (PMP). Using the American River watershed (ARW) and Folsom Dam as a case study, simulated peak floods for the 1997 (New Year's) flood event show that a 100% impervious watershed has the potential of generating a flood that is close to design PMF. On the other hand, the design PMP produces an additional 1500 m3 s−1 peak flood compared to the actual PMF when the watershed is considered 100% impervious. This study points to the radical need for consideration future land-cover changes up front during the dam design and operation formulation phase by considering not only the immediate effects but also the gradual climatic effects on PMF. A dynamic dam design procedure should be implemented that takes into account the change of land–atmospheric and hydrological processes as a result of land-cover modification rather than relying on historical records alone.

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Jason A. Hubbart and Chris Zell

Abstract

Assuming pro rata reductions in baseflow resulting from urban development may not be valid in all urbanizing watersheds. Anthropogenic offsets or compensatory contributions to baseflow (e.g., net exfiltration from sewer lines, wastewater effluents, and lawn irrigation) may mask or confound fundamental changes in hydrologic pathways. These offsets illustrate the complexities of urban flow processes and the need for improved understanding to mitigate urban development impacts. The authors used two dissimilar automated baseflow separation algorithms and Monte Carlo techniques to evaluate urban baseflow and estimation uncertainty using data from a representative urban watershed in the central United States. Three uncertainties affecting trend determinations were assessed, including algorithm structure, precipitation–runoff relationships, and baseflow algorithm parameterization. Results indicate that, despite ongoing population growth and development, annual streamflow metrics in the authors' representative watershed have not significantly increased or decreased (p > 0.05) from 1967 to 2010. However, several streamflow metrics featured shallow insignificant (p > 0.05) slopes in the direction hypothesized for an urbanizing (less pervious) watershed, including a downward slope for baseflow index (BFI) and increases in runoff volume coefficient. Median annual baseflow estimations differed by 29% between techniques (85.3 versus 118.9 mm yr−1). In the absence of direct tracer measurements, uncertainties associated with precipitation–runoff relationships, algorithm structure, and parameterization should be included in analyses evaluating alterations from baseline hydrologic conditions in urban watersheds. To advance application of separation algorithms for urban watersheds and support regulatory reductions in runoff volume, future work should include calibration of model parameters to available hydrogeologic and tracer data.

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M. Sekhar, M. Shindekar, Sat K. Tomer, and P. Goswami

Abstract

Climate change impact on a groundwater-dependent small urban town has been investigated in the semiarid hard rock aquifer in southern India. A distributed groundwater model was used to simulate the groundwater levels in the study region for the projected future rainfall (2012–32) obtained from a general circulation model (GCM) to estimate the impacts of climate change and management practices on groundwater system. Management practices were based on the human-induced changes on the urban infrastructure such as reduced recharge from the lakes, reduced recharge from water and wastewater utility due to an operational and functioning underground drainage system, and additional water extracted by the water utility for domestic purposes. An assessment of impacts on the groundwater levels was carried out by calibrating a groundwater model using comprehensive data gathered during the period 2008–11 and then simulating the future groundwater level changes using rainfall from six GCMs [Institute of Numerical Mathematics Coupled Model, version 3.0 (INM-CM.3.0); L'Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4); Model for Interdisciplinary Research on Climate, version 3.2 (MIROC3.2); ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G); Hadley Centre Coupled Model, version 3 (HadCM3); and Hadley Centre Global Environment Model, version 1 (HadGEM1)] that were found to show good correlation to the historical rainfall in the study area. The model results for the present condition indicate that the annual average discharge (sum of pumping and natural groundwater outflow) was marginally or moderately higher at various locations than the recharge and further the recharge is aided from the recharge from the lakes. Model simulations showed that groundwater levels were vulnerable to the GCM rainfall and a scenario of moderate reduction in recharge from lakes. Hence, it is important to sustain the induced recharge from lakes by ensuring that sufficient runoff water flows to these lakes.

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Brandon L. Parkes, Hannah L. Cloke, Florian Pappenberger, Jeff Neal, and David Demeritt

Abstract

Flood simulation models and hazard maps are only as good as the underlying data against which they are calibrated and tested. However, extreme flood events are by definition rare, so the observational data of flood inundation extent are limited in both quality and quantity. The relative importance of these observational uncertainties has increased now that computing power and accurate lidar scans make it possible to run high-resolution 2D models to simulate floods in urban areas. However, the value of these simulations is limited by the uncertainty in the true extent of the flood. This paper addresses that challenge by analyzing a point dataset of maximum water extent from a flood event on the River Eden at Carlisle, United Kingdom, in January 2005. The observation dataset is based on a collection of wrack and water marks from two postevent surveys. A smoothing algorithm for identifying, quantifying, and reducing localized inconsistencies in the dataset is proposed and evaluated showing positive results. The proposed smoothing algorithm can be applied in order to improve flood inundation modeling assessment and the determination of risk zones on the floodplain.

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Jinyang Du and Qiang Liu

Abstract

Knowledge of the spatial distribution and temporal changes of the land surface parameters at the Three Gorges Dam (TGD) region is essential to understanding the changes of hydrological processes and climate systems possibly brought by TGD. Based on accumulated observations for years from a spaceborne passive microwave radiometer, this study presents and analyzes the spatial and temporal distribution of soil moisture in the TGD region. Major drought and flood events are identified from the satellite-derived soil moisture products. Moreover, the areas around the largest freshwater lakes of China, the Dongting and Poyang Lakes, are frequently subjected to drought events, which might be partially related to the impoundment of TGD since the year 2006. Data analysis further reveals a statistically significant drying trend in May in the middle and lower reaches of the Yangtze River over the years 2003–11. These analyses indicate that water shortage becomes a realistic challenge for the once water abundant Yangtze River region, and more considerations on the possible consequences brought by climate changes are needed for the operation of TGD.

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M. P. Maneta and N. L. Silverman

Abstract

Studies seeking to understand the impacts of climate variability and change on the hydrology of a region need to take into account the dynamics of vegetation and its interaction with the hydrologic and energy cycles. Yet, most of the hydrologic models used for these kinds of studies assume that vegetation is static. This paper presents a dynamic, spatially explicit model that couples a vertical energy balance scheme (surface and canopy layer) to a hydrologic model and a forest growth component to capture the dynamic interactions between energy, vegetation, and hydrology at hourly to daily time scales. The model is designed to be forced with outputs from regional climate models. Lateral water transfers are simulated using a 1D kinematic wave model. Infiltration is simulated using the Green and Ampt approximation to Richard's equation. The dynamics of soil moisture and energy drives carbon assimilation and forest growth, which in turn affect the distribution of energy and water through leaf dynamics by altering light interception, shading, and enhanced transpiration. The model is demonstrated in two case studies simulating energy, water, and vegetation dynamics at two different spatial and temporal scales.

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Lunche Wang, Wei Gong, Yingying Ma, and Miao Zhang

Abstract

Net primary productivity (NPP) is an important component of the carbon cycle and a key indicator of ecosystem performance. The aim of this study is to construct a more accurate regional vegetation NPP estimation model and explore the relationship between NPP and climatic factors (air temperature, rainfall, sunshine hours, relative humidity, air pressure, global radiation, and surface net radiation). As a key variable in NPP modeling, photosynthetically active radiation (PAR) was obtained by finding a linear relationship between PAR and horizontal direct radiation, scattered radiation, and net radiation with high accuracy. The fraction of absorbed photosynthetically active radiation (FPAR) was estimated by enhanced vegetation index (EVI) instead of the widely used normalized difference vegetation index (NDVI). Stress factors of temperature/humidity for different types of vegetation were also considered in the simulation of light use efficiencies (LUE). The authors used EVI datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2011 and geographic information techniques to reveal NPP variations in Wuhan. Time lagged serial correlation analysis was employed to study the delayed and continuous effects of climatic factors on NPP. The results showed that the authors’ improved model can simulate vegetation NPP in Wuhan effectively, and it may be adopted or used in other regions of the world that need to be further tested. The results indicated that air temperature and air pressure contributed significantly to the interannual changes of plant NPP while rainfall and global radiation were major climatic factors influencing seasonal NPP variations. A significant positive 32-day lagged correlation was observed between seasonal variation of NPP and rainfall (P < 0.01); the influence of changing climate on NPP lasted for 64 days. The impact of air pressure, global radiation, and net radiation on NPP persisted for 48 days, while the effects of sunshine hours and air temperature on NPP only lasted for 16 and 32 days, respectively.

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