scholarly journals A Spatially Distributed Groundwater Metric for Describing Hydrologic Changes in a Regional Population of Wetlands North of Tampa Bay, Florida, from 1990 to 2015

2021 ◽  
Author(s):  
Geoffrey Fouad ◽  
Terrie M. Lee
Keyword(s):  
Land Surface ◽  
Flow Direction ◽  
Critical Role ◽  
Flow Equation ◽  
Wet Season ◽  
Drainage Basins ◽  
Spatially Distributed ◽  
Groundwater Condition ◽  
Regional Population ◽  
Condition Metric

Abstract A groundwater condition metric is presented and used to evaluate hydrologic changes in a regional population of wetlands in and around municipal well fields with large groundwater withdrawals. The approach compares a 26-year, monthly time series of groundwater potentiometric surfaces to light detection and ranging (LiDAR) land-surface elevations at 10,516 wetlands in a 1505-square-kilometer area. Elevation differences between the potentiometric surface and wetland land surface provide a flow direction (upward or downward) and a proxy for vertical hydraulic head difference in Darcy’s groundwater flow equation. The resulting metric quantifies the groundwater condition at a wetland through time as the potential for groundwater to discharge upward into a wetland or for water in a wetland to leak downward to recharge the underlying aquifer. The potential for wetland leakage across the regional wetland population decreased by 33% in the 13 years after cutbacks in groundwater withdrawals (2003-2015) compared to years before cutbacks (1990-2002). Inside well field properties, wetland leakage potential decreased by 24%. In the wet season month of September, wetlands with the potential to receive groundwater discharge increased to 21.6% of the regional population after cutbacks compared to 13.3% before cutbacks. When mapped across regional drainage basins, discharging wetlands formed spatial connections suggesting they play a critical role in generating streamflow.

scholarly journals Estimating and Monitoring Land Surface Phenology in Rangelands: A Review of Progress and Challenges

2021 ◽  
Vol 13 (11) ◽  
pp. 2060
Author(s):  
Trylee Nyasha Matongera ◽  
Onisimo Mutanga ◽  
Mbulisi Sibanda ◽  
John Odindi
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Critical Role ◽  
Spectral Characteristics ◽  
Vegetation Indices ◽  
Machine Learning Algorithms ◽  
Special Focus ◽  
Land Surface Phenology ◽  
Spectral Vegetation Indices ◽  
Satellite Sensors

Land surface phenology (LSP) has been extensively explored from global archives of satellite observations to track and monitor the seasonality of rangeland ecosystems in response to climate change. Long term monitoring of LSP provides large potential for the evaluation of interactions and feedbacks between climate and vegetation. With a special focus on the rangeland ecosystems, the paper reviews the progress, challenges and emerging opportunities in LSP while identifying possible gaps that could be explored in future. Specifically, the paper traces the evolution of satellite sensors and interrogates their properties as well as the associated indices and algorithms in estimating and monitoring LSP in productive rangelands. Findings from the literature revealed that the spectral characteristics of the early satellite sensors such as Landsat, AVHRR and MODIS played a critical role in the development of spectral vegetation indices that have been widely used in LSP applications. The normalized difference vegetation index (NDVI) pioneered LSP investigations, and most other spectral vegetation indices were primarily developed to address the weaknesses and shortcomings of the NDVI. New indices continue to be developed based on recent sensors such as Sentinel-2 that are characterized by unique spectral signatures and fine spatial resolutions, and their successful usage is catalyzed with the development of cutting-edge algorithms for modeling the LSP profiles. In this regard, the paper has documented several LSP algorithms that are designed to provide data smoothing, gap filling and LSP metrics retrieval methods in a single environment. In the future, the development of machine learning algorithms that can effectively model and characterize the phenological cycles of vegetation would help to unlock the value of LSP information in the rangeland monitoring and management process. Precisely, deep learning presents an opportunity to further develop robust software packages such as the decomposition and analysis of time series (DATimeS) with the abundance of data processing tools and techniques that can be used to better characterize the phenological cycles of vegetation in rangeland ecosystems.

scholarly journals A framework for quantifying hydrologic effects of soil structure across scales

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Sara Bonetti ◽  
Zhongwang Wei ◽  
Dani Or
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Soil Structure ◽  
Pedotransfer Functions ◽  
Small Scale ◽  
Spatial Correlations ◽  
Surface Parameterization ◽  
Exchange Processes ◽  
Local Soil ◽  
Spatially Distributed

AbstractEarth system models use soil information to parameterize hard-to-measure soil hydraulic properties based on pedotransfer functions. However, current parameterizations rely on sample-scale information which often does not account for biologically-promoted soil structure and heterogeneities in natural landscapes, which may significantly alter infiltration-runoff and other exchange processes at larger scales. Here we propose a systematic framework to incorporate soil structure corrections into pedotransfer functions, informed by remote-sensing vegetation metrics and local soil texture, and use numerical simulations to investigate their effects on spatially distributed and areal averaged infiltration-runoff partitioning. We demonstrate that small scale soil structure features prominently alter the hydrologic response emerging at larger scales and that upscaled parameterizations must consider spatial correlations between vegetation and soil texture. The proposed framework allows the incorporation of hydrological effects of soil structure with appropriate scale considerations into contemporary pedotransfer functions used for land surface parameterization.

scholarly journals Seasonal changes in water quality and macrophytes and the impact of cattle on tropical floodplain waterholes

2012 ◽  
Vol 63 (9) ◽  
pp. 788 ◽  
Author(s):  
N. E. Pettit ◽  
T. D. Jardine ◽  
S. K. Hamilton ◽  
V. Sinnamon ◽  
D. Valdez ◽  
...  
Keyword(s):  
Water Quality ◽  
Seasonal Changes ◽  
Aquatic Macrophyte ◽  
Plant Cover ◽  
Critical Role ◽  
Dry Season ◽  
Nutrient Concentrations ◽  
Wet Season ◽  
Dry Tropics ◽  
The Impact

The present study indicates the critical role of hydrologic connectivity in floodplain waterholes in the wet–dry tropics of northern Australia. These waterbodies provide dry-season refugia for plants and animals, are a hotspot of productivity, and are a critical part in the subsistence economy of many remote Aboriginal communities. We examined seasonal changes in water quality and aquatic plant cover of floodplain waterholes, and related changes to variation of waterhole depth and visitation by livestock. The waterholes showed declining water quality through the dry season, which was exacerbated by more frequent cattle usage as conditions became progressively drier, which also increased turbidity and nutrient concentrations. Aquatic macrophyte biomass was highest in the early dry season, and declined as the dry season progressed. Remaining macrophytes were flushed out by the first wet-season flows, although they quickly re-establish later during the wet season. Waterholes of greater depth were more resistant to the effects of cattle disturbance, and seasonal flushing of the waterholes with wet-season flooding homogenised the water quality and increased plant cover of previously disparate waterholes. Therefore, maintaining high levels of connectivity between the river and its floodplain is vital for the persistence of these waterholes.

scholarly journals Analysis of Urban Effects in Oklahoma City using a Dense Surface Observing Network

2016 ◽  
Vol 55 (3) ◽  
pp. 723-741 ◽  
Author(s):  
Xiao-Ming Hu ◽  
Ming Xue ◽  
Petra M. Klein ◽  
Bradley G. Illston ◽  
Sheng Chen
Keyword(s):  
Metropolitan Area ◽  
Land Surface ◽  
Critical Role ◽  
Central Business District ◽  
Temperature Inversion ◽  
Oklahoma City ◽  
Near Surface ◽  
Open Questions ◽  
The Stability ◽  
Business District

AbstractMany studies have investigated urban heat island (UHI) intensity for cities around the world, which is normally quantified as the temperature difference between urban location(s) and rural location(s). A few open questions still remain regarding the UHI, such as the spatial distribution of UHI intensity, temporal (including diurnal and seasonal) variation of UHI intensity, and the UHI formation mechanism. A dense network of atmospheric monitoring sites, known as the Oklahoma City (OKC) Micronet (OKCNET), was deployed in 2008 across the OKC metropolitan area. This study analyzes data from OKCNET in 2009 and 2010 to investigate OKC UHI at a subcity spatial scale for the first time. The UHI intensity exhibited large spatial variations over OKC. During both daytime and nighttime, the strongest UHI intensity is mostly confined around the central business district where land surface roughness is the highest in the OKC metropolitan area. These results do not support the roughness warming theory to explain the air temperature UHI in OKC. The UHI intensity of OKC increased prominently around the early evening transition (EET) and stayed at a fairly constant level throughout the night. The physical processes during the EET play a critical role in determining the nocturnal UHI intensity. The near-surface rural temperature inversion strength was a good indicator for nocturnal UHI intensity. As a consequence of the relatively weak near-surface rural inversion, the strongest nocturnal UHI in OKC was less likely to occur in summer. Other meteorological factors (e.g., wind speed and cloud) can affect the stability/depth of the nighttime boundary layer and can thus modulate nocturnal UHI intensity.

scholarly journals Dome effect of black carbon and its key influencing factors: A one-dimensional modelling study

2017 ◽  
Author(s):  
Zilin Wang ◽  
Xin Huang ◽  
Aijun Ding
Keyword(s):  
Boundary Layer ◽  
Air Pollution ◽  
Black Carbon ◽  
Rural Areas ◽  
Land Surface ◽  
Critical Role ◽  
Aerosol Layer ◽  
Near Surface ◽  
Haze Pollution ◽  
The Impact

Abstract. Black carbon (BC) has been identified to play a critical role in aerosol-planet boundary layer (PBL) interaction and further deterioration of near-surface air pollution in megacities, which has been named as its dome effect. However, the impacts of key factors that influence this effect, such as the vertical distribution and aging processes of BC, and also the underlying land surface, have not been quantitatively explored yet. Here, based on available in-situ measurements of meteorology and atmospheric aerosols together with the meteorology-chemistry online coupled model, WRF-Chem, we conduct a set of parallel simulations to quantify the roles of these factors in influencing the BC's dome effect and surface haze pollution, and discuss the main implications of the results to air pollution mitigation in China. We found that the impact of BC on PBL is very sensitive to the altitude of aerosol layer. The upper level BC, especially those near the capping inversion, is more essential in suppressing the PBL height and weakening the turbulence mixing. The dome effect of BC tends to be significantly intensified as BC aerosol mixed with scattering aerosols during winter haze events, resulting in a decrease of PBL height by more than 25 %. In addition, the dome effect is more substantial (up to 15 %) in rural areas than that in the urban areas with the same BC loading, indicating an unexpected regional impact of such kind of effect to air quality in countryside. This study suggests that China's regional air pollution would greatly benefit from BC emission reductions, especially those from the elevated sources from the chimneys and also the domestic combustions in rural areas, through weakening the aerosol-boundary layer interactions that triggered by BC.

scholarly journals A statistics-based temporal filter algorithm to map spatiotemporally continuous shortwave albedo from MODIS data

2013 ◽  
Vol 17 (6) ◽  
pp. 2121-2129 ◽  
Author(s):  
N. F. Liu ◽  
Q. Liu ◽  
L. Z. Wang ◽  
S. L. Liang ◽  
J. G. Wen ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Land Surface ◽  
Surface Albedo ◽  
Critical Role ◽  
Radiant Energy ◽  
High Temporal Resolution ◽  
Land Surface Parameter ◽  
Temporal Filter ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Land-surface albedo plays a critical role in the earth's radiant energy budget studies. Satellite remote sensing provides an effective approach to acquire regional and global albedo observations. Owing to cloud coverage, seasonal snow and sensor malfunctions, spatiotemporally continuous albedo datasets are often inaccessible. The Global LAnd Surface Satellite (GLASS) project aims at providing a suite of key land surface parameter datasets with high temporal resolution and high accuracy for a global change study. The GLASS preliminary albedo datasets are global daily land-surface albedo generated by an angular bin algorithm (Qu et al., 2013). Like other products, the GLASS preliminary albedo datasets are affected by large areas of missing data; beside, sharp fluctuations exist in the time series of the GLASS preliminary albedo due to data noise and algorithm uncertainties. Based on the Bayesian theory, a statistics-based temporal filter (STF) algorithm is proposed in this paper to fill data gaps, smooth albedo time series, and generate the GLASS final albedo product. The results of the STF algorithm are smooth and gapless albedo time series, with uncertainty estimations. The performance of the STF method was tested on one tile (H25V05) and three ground stations. Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODerate resolution Imaging Spectroradiometer (MODIS) product, the GLASS final albedo product has a higher temporal resolution and more competence in capturing the surface albedo variations. It is recommended that the quality flag should be always checked before using the GLASS final albedo product.

scholarly journals Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Balance Model ◽  
Near Surface

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

General Characteristics and Variability of Climate in the Amazon Basin and its Links to the Global Climate System

2001 ◽  
Author(s):  
Jose A. Marengo ◽  
Carlos A. Nobre
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Amazon Basin ◽  
Global Climate ◽  
River System ◽  
Climate System ◽  
Wet Season ◽  
Tropospheric Circulation ◽  
The Tropics

The Amazon region is of particular interest because it represents a large source of heat in the tropics and has been shown to have a significant impact on extratropical circulation, and it is Earth’s largest and most intense land-based convective center. During the Southern Hemisphere summer when convection is best developed, the Amazon basin is one of the wettest regions on Earth. Amazonia is of course not isolated from the rest of the world, and a global perspective is needed to understand the nature and causes of climatological anomalies in Amazonia and how they feed back to influence the global climate system. The Amazon River system is the single, largest source of freshwater on Earth. The flow regime of this river system is relatively unimpacted by humans (Vörösmarty et al. 1997 a, b) and is subject to interannual variability in tropical precipitation that ultimately is translated into large variations in downstream hydrographs (Marengo et al. 1998a, Vörösmarty et al. 1996, Richey et al. 1989a, b). The recycling of local evaporation and precipitation by the forest accounts for a sizable portion of the regional water budget (Nobre et al. 1991, Eltahir 1996), and as large areas of the basin are subject to active deforestation there is grave concern about how such land surface disruptions may affect the water cycle in the tropics (see reviews in Lean et al. 1996). Previous studies have emphasized either how large-scale atmospheric circulation or land surface conditions can directly control the seasonal changes in rainfall producing mechanisms. Studies invoking controls of convection and rainfall by large-scale circulation emphasize the relationship between the establishment of upper-tropospheric circulation over Bolivia and moisture transport from the Atlantic ocean for initiation of the wet season and its intensity (see reviews in Marengo et al. 1999). On the other hand, Eltahir and Pal (1996) have shown that Amazon convection is closely related to land surface humidity and temperature, while Fu et al. (1999) indicate that the wet season in the Amazon basin is controlled by both changes in land surface temperature and the sea surface temperature (SST) in the adjacent oceans, depending if the region is north-equatorial or southern Amazonia.

scholarly journals Seasonal Groundwater Quality Status and Nitrogen Contamination in the Shallow Aquifer System of the Kathmandu Valley, Nepal

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2184 ◽  
Author(s):  
Shakya ◽  
Nakamura ◽  
Kamei ◽  
Shrestha ◽  
Nishida
Keyword(s):  
Groundwater Quality ◽  
Nitrogen Compound ◽  
Shallow Aquifer ◽  
Kathmandu Valley ◽  
Nitrogen Compounds ◽  
Wet Season ◽  
Aquifer System ◽  
Spatially Distributed ◽  
Nitrogen Contamination ◽  
Dug Well

: The increasing concentration of nitrogen compounds in the groundwater is of a growing concern in terms of human health and groundwater quality. Although an excess of nitrogen compounds in the groundwater of the Kathmandu Valley has been reported, the seasonal variations of the fate of the nitrogen compounds and their relationships to the subsurface sediments are unknown. In this study, spatially distributed shallow dug well samples were collected during both the dry and wet seasons of 2016, and the nitrogen compound, chloride (Cl−), and iron (Fe2+) concentrations were analyzed. Two shallow dug wells and one deep tube well were monitored monthly for 2 years. Although NH4-N concentrations were similar in the clay-dominated areas during both seasons (1 and 0.9 mg-N/L), they were lower in the gravel-dominated areas during wet season (1.8 > 0.6 mg-N/L). The NO3-N concentration differed depending upon the soil type which increased during the wet season (clay 4.9 < 13.6 mg-N/L and gravel 2.5 < 6.8 mg-N/L). The Fe2+ concentration, however, was low during the wet season (clay 2.7 > 0.4 mg/L and gravel 2.8 > 0.3 mg/L). Long-term analysis showed higher fluctuation of nitrogen compounds in the gravel-bearing areas than in the clay-bearing areas.

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