A hydrochemical modelling framework for combined assessment of spatial and temporal variability in stream chemistry: application to Plynlimon, Wales

Abstract. Recent concern about the risk to biota from acidification in upland areas, due to air pollution and land-use change (such as the planting of coniferous forests), has generated a need to model catchment hydro-chemistry to assess environmental risk and define protection strategies. Previous approaches have tended to concentrate on quantifying either spatial variability at a regional scale or temporal variability at a given location. However, to protect biota from ‘acid episodes’, an assessment of both temporal and spatial variability of stream chemistry is required at a catchment scale. In addition, quantification of temporal variability needs to represent both episodic event response and long term variability caused by deposition and/or land-use change. Both spatial and temporal variability in streamwater chemistry are considered in a new modelling methodology based on application to the Plynlimon catchments, central Wales. A two-component End-Member Mixing Analysis (EMMA) is used whereby low and high flow chemistry are taken to represent ‘groundwater’ and ‘soil water’ end-members. The conventional EMMA method is extended to incorporate spatial variability in the two end-members across the catchments by quantifying the Acid Neutralisation Capacity (ANC) of each in terms of a statistical distribution. These are then input as stochastic variables to a two-component mixing model, thereby accounting for variability of ANC both spatially and temporally. The model is coupled to a long-term acidification model (MAGIC) to predict the evolution of the end members and, hence, the response to future scenarios. The results can be plotted as a function of time and space, which enables better assessment of the likely effects of pollution deposition or land-use changes in the future on the stream chemistry than current methods which use catchment average values. The model is also a useful basis for further research into linkage between hydrochemistry and intra-catchment biological diversity. Keywords: hydrochemistry, End-Member Mixing Analysis (EMMA), uplands, acidification

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Analysis of Long-Term Solar Resource Variability Using NSRDB Version 3

10.5194/ems2021-193 ◽

2021 ◽

Author(s):

Manajit Sengupta ◽

Aron Habte

Keyword(s):

Solar Radiation ◽

Spatial Variability ◽

Temporal Variability ◽

Radiative Transfer Model ◽

Transfer Model ◽

Spatial And Temporal Variability ◽

Cloud Optical Depth ◽

Resource Variability ◽

Solar Resource

<p>Understanding long-term solar resource variability is essential for planning and deployment of solar energy systems. These variabilities occur due to deterministic effects such as sun cycle and nondeterministic such as complex weather patterns. The NREL&#8217;s National Solar Radiation Database (NSRDB) provides long term solar resource data covering 1998- 2019 containing more than 2 million pixels over the Americas and gets updated on an annual basis. This dataset is satellite-based and uses a two-step physical model for it&#8217;s development. In the first step we retrieve cloud properties such as cloud mask, cloud type, cloud optical depth and effective radius. The second step uses a fast radiative transfer model to compute solar radiation. &#160;This dataset is ideal for studying solar resource variability. For this study, NSRDB version 3 which contains data from 1998-2017 on a half hourly and 4x4 km temporal and spatial resolution was used. The study analyzed the spatial and temporal trend of solar resource of global horizontal irradiance (GHI) and direct normal irradiance (DNI) using long-term 20-years NSRDB data. The coefficient of variation (COV) was used to analyze the spatio-temporal interannual and seasonal variabilities. The spatial variability was analyzed by comparing the center pixel to neighboring pixels. The spatial variability result showed higher COV as the number of neighboring pixels increased. Similarly, the temporal variability for the NSRDB domain ranges on average from &#177;10% for GHI and &#177;20% for DNI. Furthermore, the long-term variabilities were also analyzed using the K&#246;ppen-Geiger climate classification. This assisted in the interpretation of the result by reducing the originally large number of pixels into a smaller number of groups. This presentation will provided a unique look at long-term spatial and temporal variability of solar radiation using high-resolution satellite-based datasets.</p>

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Interannual climate variability data improves niche estimates in species distribution models

10.1101/2021.08.30.458152 ◽

2021 ◽

Author(s):

Dirk Nikolaus Karger ◽

Bianca Saladin ◽

Rafael O. Wueest ◽

Catherine H. Graham ◽

Damaris Zurell ◽

...

Keyword(s):

Climate Variability ◽

Spatial Variability ◽

Species Distribution ◽

Temporal Variability ◽

Species Distribution Models ◽

Essential Element ◽

Spatial And Temporal Variability ◽

Distribution Models ◽

Mammal Species

Aim: Climate is an essential element of species' niche estimates in many current ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values. Yet, climate can also be described as spatial or temporal variability for variables like temperature or precipitation. Such variability, spatial or temporal, offers additional insights into niche properties. Here, we test to what degree spatial variability and long-term temporal variability in temperature and precipitation improve SDM predictions globally. Location: Global. Time period: 1979-2013. Major taxa studies: Mammal, Amphibians, Reptiles. Methods: We use three different SDM algorithms, and a set of 833 amphibian, 779 reptile, and 2211 mammal species to quantify the effect of spatial and temporal climate variability in SDMs. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). Results: Mean performance of SDMs with climatic means as predictors was TSS=0.71 and AUC=0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS=0.74, mean AUC=0.92), as does the inclusion of temporal variability (mean TSS=0.80, mean AUC=0.94). Including both spatial and temporal variability in SDMs shows similarly high TSS and AUC scores. Main conclusions: Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in exotherm groups such as amphibians and reptiles, while for endotermic mammals no such improvement was observed. These results indicate that more detailed information about temporal climate variability offers a highly promising avenue for improving niche estimates and calls for a new set of standard bioclimatic predictors in SDM research.

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Evaluation and interpretation of regional and site-specific hydrochemical data bases for water quality assessment

Hydrology and Earth System Sciences ◽

10.5194/hess-3-565-1999 ◽

1999 ◽

Vol 3 (4) ◽

pp. 565-580 ◽

Cited By ~ 2

Author(s):

M. G. Hutchins ◽

B. Reynolds ◽

B. Smith ◽

G. N. Wiggans ◽

T. R. Lister

Keyword(s):

Land Use ◽

Temporal Variability ◽

Stream Water ◽

Monitoring Data ◽

Spatial And Temporal Variability ◽

Stream Chemistry ◽

Stream Order ◽

Time Step ◽

Data Set ◽

Site Specific

Abstract. The spatial distribution of stream water composition, as determined by the Geochemical Baseline Survey of the Environment (G-BASE) conducted by the British Geological Survey (BGS) can be successfully related under baseflow conditions to bedrock geochemistry. Further consideration of results in conjunction with site-specific monitoring data enables factors controlling both spatial and temporal variability in major element composition to be highlighted and allows the value of the survey to be enhanced. Hence, chemical data (i) from streams located on Lower Silurian (Llandovery) bedrock at 1 km2 resolution collected as part of the G-BASE survey of Wales and the West Midlands and (ii) from catchment monitoring studies located in upland mid-Wales (conducted by Institute of Terrestrial Ecology), have been considered together as an example. Classification of the spatial survey data set in terms of potentially controlling factors was carried out so as to illustrate the level of explanation they could give in terms of observed spatial chemical variability. It was therefore hypothesised that on a geological lithostratigraphic series of limited geochemical contrast, altitude and land-use factors provide better explanation of this variability than others such as lithology at sampling site and stream order. At an individual site, temporal variability was also found to be of considerable significance and, at a monthly time-step, is explicable in terms of factors such as antecedent conditions and seasonality. Data suggest that the degree of this variability may show some relationship with stream order and land-use. Monitoring data from the region also reveal that relationships between stream chemistry and land-use may prove to be strong not only at base flow but also in storm flow conditions. In a wider context, predictions of the sensitivity of stream water to acidification based on classifications of soil and geology are successful on a regional scale. However, the study undertaken here has shown that use of such classification schemes on a catchment scale results in considerable uncertainty associated with prediction. Uncertainties are due to the large degree of variability in stream chemistry encountered both spatially within geological units and temporally at individual sampling sites.

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Drivers of spatial and temporal variability of streamflow in the Incomati River Basin

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-8879-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 8879-8921

Author(s):

A. M. L. Saraiva Okello ◽

I. Masih ◽

S. Uhlenbrook ◽

G. W. P. Jewitt ◽

P. van der Zaag ◽

...

Keyword(s):

Land Use ◽

Statistical Analysis ◽

Water Resources ◽

Flow Regime ◽

Temporal Variability ◽

Irrigated Agriculture ◽

Spatial And Temporal Variability ◽

Natural Flow Regime ◽

Natural Flow

Abstract. The Incomati is a semi-arid trans-boundary river basin in southern Africa, with a high variability of streamflow and competing water demands from irrigated agriculture, energy, forestry and industries. These sectors compete with environmental flows and basic human water needs, resulting in a "stressed" water resources system. The impacts of these demands, relative to the natural flow regime, appear significant. However, despite being a relatively well-gauged basin in South Africa, the natural flow regime and its spatial and temporal variability are poorly understood and remain poorly described, resulting in a limited knowledge base for water resources planning and management decisions. Thus, there is an opportunity to improve water management, if it can be underpinned by a better scientific understanding of the drivers of streamflow availability and variability in the catchment. In this study, long-term rainfall and streamflow records were analysed. Statistical analysis, using annual anomalies, was conducted on 20 rainfall stations, for the period of 1950 to 2011. The Spearman Test was used to identify any trends in the records at annual and monthly time scales. The variability of rainfall across the basin was confirmed to be high, both intra- and inter-annually. The statistical analysis of rainfall data revealed no significant trend of increase or decrease for the studied period. Observed flow data from 33 gauges was screened and analyzed, using the Indicators of Hydrologic Alteration (IHA) approach. Long-term analyses were conducted to identify temporal/spatial variability and trends in streamflow records. Temporal variability was high, with the coefficient of variation of annual flows in the range of 1 to 3.6. Significant declining trends in October flows, and low flows indicators were also identified at most gauging stations of the Komati and Crocodile sub-catchments, however no trends were evident on the other parameters, including high flows. The trends were mapped, using GIS and were compared to historical and current land use. These results suggest that land use and flow regulation are larger drivers of temporal changes in the streamflow than climatic forces. Indeed, over the past 40 years, the areas under commercial forestry and irrigated agriculture have increased over four times.

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Spatial and Temporal Trends of Irrigated Cotton Yield in the Southern High Plains

Agronomy ◽

10.3390/agronomy8120298 ◽

2018 ◽

Vol 8 (12) ◽

pp. 298 ◽

Cited By ~ 2

Author(s):

Wenxuan Guo

Keyword(s):

Spatial Variability ◽

Temporal Variability ◽

Yield Variability ◽

High Plains ◽

Spatial And Temporal Variability ◽

Cotton Yield ◽

Site Specific ◽

Growing Seasons ◽

Specific Management

Understanding spatial and temporal variability patterns of crop yield and their relationship with soil properties can provide decision support to optimize crop management. The objectives of this study were to (1) determine the spatial and temporal variability of cotton (Gossypium hirsutum L.) lint yield over different growing seasons; (2) evaluate the relationship between spatial and temporal yield patterns and apparent soil electrical conductivity (ECa). This study was conducted in eight production fields, six with 50 ha and two with 25 ha, on the Southern High Plains (SHP) from 2000 to 2003. Cotton yield and ECa data were collected using a yield monitor and an ECa mapping system, respectively. The amount and pattern of spatial and temporal yield variability varied with the field. Fields with high variability in ECa exhibited a stronger association between spatial and temporal yield patterns and ECa, indicating that soil properties related to ECa were major factors influencing yield variability. The application of ECa for site-specific management is limited to fields with high spatial variability and with a strong association between yield spatial and temporal patterns and ECa variation patterns. For fields with low variability in yield, spatial and temporal yield patterns might be more influenced by weather or other factors in different growing seasons. Fields with high spatial variability and a clear temporal stability pattern have great potential for long-term site-specific management of crop inputs. For unstable yield, however, long-term management practices are difficult to implement. For these fields with unstable yield patterns, within season site-specific management can be a better choice. Variable rate application of water, plant growth regulators, nitrogen, harvest aids may be implemented based on the spatial variability of crop growth conditions at specific times.

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CH4and N2O fluxes in the Colorado shortgrass steppe: 2. Long-term impact of land use change

Global Biogeochemical Cycles ◽

10.1029/96gb03612 ◽

1997 ◽

Vol 11 (1) ◽

pp. 29-42 ◽

Cited By ~ 97

Author(s):

A. R. Mosier ◽

W. J. Parton ◽

D. W. Valentine ◽

D. S. Ojima ◽

D. S. Schimel ◽

...

Keyword(s):

Land Use ◽

Land Use Change ◽

Shortgrass Steppe ◽

N2o Fluxes ◽

Long Term Impact

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The Effects of Long‐Term Land‐Use Change on Soil Properties in Perth, Ontario Canada

Inquiry@Queen's Undergraduate Research Conference Proceedings ◽

10.24908/iqurcp.8271 ◽

2016 ◽

Author(s):

Trina Stephens

Keyword(s):

Land Use ◽

Organic Matter ◽

North America ◽

Land Use Change ◽

Soil Properties ◽

Carbon Storage ◽

Organic Matter Content ◽

Matter Content ◽

Topographic Gradients

Land‐use change can have a major impact on soil properties, leading to long‐term changes in soilnutrient cycling rates and carbon storage. While a substantial amount of research has been conducted onland‐use change in tropical regions, empirical evidence of long‐term conversion of forested land toagricultural land in North America is lacking. Pervasive deforestation for the sake of agriculturethroughout much of North America is likely to have modified soil properties, with implications for theglobal climate. Here, we examined the response of physical, chemical and biological soil properties toconversion of forest to agricultural land (100 years ago) on Roebuck Farm near Perth, Ontario, Canada.Soil samples were collected at three sites from under forest and agricultural vegetative cover on bothhigh‐ and low‐lying topographic positions (12 locations in total; soil profile sampled to a depth of 40cm).Our results revealed that bulk density, pH, and nitrate concentrations were all higher in soils collectedfrom cultivate sites. In contrast, samples from forested sites exhibited greater water‐holding capacity,porosity, organic matter content, ammonia concentrations and cation exchange capacity. Many of these characteristics are linked to greater organic matter abundance and diversity in soils under forestvegetation as compared with agricultural soils. Microbial activity and Q10 values were also higher in theforest soils. While soil properties in the forest were fairly similar across topographic gradients, low‐lyingpositions under agricultural regions had higher bulk density and organic matter content than upslopepositions, suggesting significant movement of material along topographic gradients. Differences in soilproperties are attributed largely to increased compaction and loss of organic matter inputs in theagricultural system. Our results suggest that the conversion of forested land cover to agriculture landcover reduces soil quality and carbon storage, alters long‐term site productivity, and contributes toincreased atmospheric carbon dioxide concentrations.

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Response of phosphorus fractions to land-use change followed by long-term fertilization in a sub-alpine humid soil of Qinghai–Tibet plateau

Journal of Soils and Sediments ◽

10.1007/s11368-018-2132-y ◽

2018 ◽

Vol 19 (3) ◽

pp. 1109-1119 ◽

Cited By ~ 2

Author(s):

Xiaolei Sun ◽

Meng Li ◽

Guoxi Wang ◽

Marios Drosos ◽

Fulai Liu ◽

...

Keyword(s):

Land Use ◽

Land Use Change ◽

Phosphorus Fractions ◽

Tibet Plateau ◽

Qinghai Tibet Plateau

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Warming increases carbon and nutrient fluxes from sediments in streams across land use

Biogeosciences ◽

10.5194/bg-10-1193-2013 ◽

2013 ◽

Vol 10 (2) ◽

pp. 1193-1207 ◽

Cited By ~ 24

Author(s):

S.-W. Duan ◽

S. S. Kaushal

Keyword(s):

Land Use ◽

Organic Matter ◽

Land Use Change ◽

Sulfate Reduction ◽

Organic Matter Content ◽

Soluble Reactive Phosphorus ◽

Overlying Water ◽

Sediment Fluxes ◽

Urban Sites

Abstract. Rising water temperatures due to climate and land use change can accelerate biogeochemical fluxes from sediments to streams. We investigated impacts of increased streamwater temperatures on sediment fluxes of dissolved organic carbon (DOC), nitrate, soluble reactive phosphorus (SRP) and sulfate. Experiments were conducted at 8 long-term monitoring sites across land use (forest, agricultural, suburban, and urban) at the Baltimore Ecosystem Study Long-Term Ecological Research (LTER) site in the Chesapeake Bay watershed. Over 20 yr of routine water temperature data showed substantial variation across seasons and years. Lab incubations of sediment and overlying water were conducted at 4 temperatures (4 °C, 15 °C, 25 °C, and 35 °C) for 48 h. Results indicated: (1) warming significantly increased sediment DOC fluxes to overlying water across land use but decreased DOC quality via increases in the humic-like to protein-like fractions, (2) warming consistently increased SRP fluxes from sediments to overlying water across land use, (3) warming increased sulfate fluxes from sediments to overlying water at rural/suburban sites but decreased sulfate fluxes at some urban sites likely due to sulfate reduction, and (4) nitrate fluxes showed an increasing trend with temperature at some forest and urban sites but with larger variability than SRP. Sediment fluxes of nitrate, SRP and sulfate were strongly related to watershed urbanization and organic matter content. Using relationships of sediment fluxes with temperature, we estimate a 5 °C warming would increase mean sediment fluxes of SRP, DOC and nitrate-N across streams by 0.27–1.37 g m−2 yr−1, 0.03–0.14 kg m−2 yr−1, and 0.001–0.06 kg m−2 yr−1. Understanding warming impacts on coupled biogeochemical cycles in streams (e.g., organic matter mineralization, P sorption, nitrification, denitrification, and sulfate reduction) is critical for forecasting shifts in carbon and nutrient loads in response to interactive impacts of climate and land use change.

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