scholarly journals SWMM-UrbanEVA: A Model for the Evapotranspiration of Urban Vegetation

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 243
Author(s):  
Birgitta Hörnschemeyer ◽  
Malte Henrichs ◽  
Mathias Uhl
Keyword(s):  
Model Performance ◽  
Soil Parameters ◽  
Suitable Model ◽  
Area Index ◽  
Fully Integrated ◽  
Model Efficiency ◽  
Spatio Temporal ◽  
Shading Effects ◽  
Moisture Conditions

Urban hydrology has so far lacked a suitable model for a precise long-term determination of evapotranspiration (ET) addressing shading and vegetation-specific dynamics. The proposed model “SWMM-UrbanEVA” is fully integrated into US EPA’s Stormwater Management Model (SWMM) and consists of two submodules. Submodule 1, “Shading”, considers the reduction in potential ET due to shading effects. Local variabilities of shading impacts can be addressed for both pervious and impervious catchments. Submodule 2, “Evapotranspiration”, allows the spatio-temporal differentiated ET simulation of vegetation and maps dependencies on vegetation, soil, and moisture conditions which are necessary for realistically modeling vegetation’s water balance. The model is tested for parameter sensitivities, validity, and plausibility of model behaviour and shows good model performance for both submodules. Depending on location and vegetation, remarkable improvements in total volume errors Vol (from Vol = 0.59 to −0.04% for coniferous) and modeling long-term dynamics, measured by the Nash–Sutcliffe model efficiency (NSE) (from NSE = 0.47 to 0.87 for coniferous) can be observed. The most sensitive model inputs to total ET are the shading factor KS and the crop factor KC. Both must be derived very carefully to minimize volume errors. Another focus must be set on the soil parameters since they define the soil volume available for ET. Process-oriented differentiation between ET fluxes interception evaporation, transpiration, and soil evaporation, using the leaf area index, behaves realistically but shows a lack in volume errors. Further investigations on process dynamics, validation, and parametrization are recommended.

scholarly journals Effect of year-to-year variability of leaf area index on variable infiltration capacity model performance and simulation of streamflow during drought

2014 ◽  
Vol 11 (9) ◽  
pp. 10515-10552 ◽  
Author(s):  
Z. K. Tesemma ◽  
Y. Wei ◽  
M. C. Peel ◽  
A. W. Western
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Model Performance ◽  
Hydrologic Model ◽  
Variable Infiltration Capacity ◽  
Infiltration Capacity ◽  
Area Index ◽  
Vic Model ◽  
Monthly Streamflow

Abstract. This study assessed the effect of using observed monthly leaf area index (LAI) on hydrologic model performance and the simulation of streamflow during drought using the variable infiltration capacity (VIC) hydrological model in the Goulburn–Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) observed monthly LAI dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash–Sutcliffe efficiency, the logarithm transformed flow Nash–Sutcliffe efficiency and the percentage bias. Finally, the percentage deviation of the simulated monthly streamflow using the observed monthly LAI from simulated streamflow using long-term mean monthly LAI was computed. The VIC model predicted monthly streamflow in the selected sub-catchments with model efficiencies ranging from 61.5 to 95.9% during calibration (1982–1997) and 59 to 92.4% during validation (1998–2012). Our results suggest systematic improvements from 4 to 25% in the Nash–Sutcliffe efficiency in pasture dominated catchments when the VIC model was calibrated with the observed monthly LAI instead of the long-term mean monthly LAI. There was limited systematic improvement in tree dominated catchments. The results also suggest that the model overestimation or underestimation of streamflow during wet and dry periods can be reduced to some extent by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

On the significance of global greening trends with multiple testing – an application to five data products

2020 ◽  
Author(s):  
José Cortés ◽  
Miguel Mahecha ◽  
Markus Reichstein ◽  
Alexander Brenning
Keyword(s):  
Multiple Testing ◽  
Hypothesis Test ◽  
Grid Cell ◽  
Kendall Test ◽  
Environmental Data ◽  
Area Index ◽  
Data Products ◽  
Spatio Temporal ◽  
Significant Patterns

<p>The statistical analysis of environmental data from remote sensing and Earth system simulations often entails the analysis of gridded spatio-temporal data, where a hypothesis test is performed for each grid cell. When the whole image or set of grid cells is analyzed for a global effect, the problem of multiple testing arises – this applies to the study of global greening trends, which have been widely reported. Although there is a consensus on the greening patterns, there is still much debate about the attribution to CO2 fertilization, temperature rise, and land use intensification. We argue that none of the studies uses a proper statistical methodology and hence fail to identify the hotspots of “real greening". To perform statistical inference, we need to account for this multiplicity of hypothesis tests. In this work, we demonstrate how to address this issue with a permutation method based on clustering, which allows us to make robust inference on regions or patterns, using the Mann-Kendall Test as the basis. The method is illustrated by comparing global greening trends derived from five different data products which contain global data for Leaf Area Index and/or Fraction of Absorbed Photosynthetically Active Radiation: GIMMS 3g, NOAA CDR, Land Long Term Data Record, LTDR MOD15A2, and SPOT/PROBA-V data. We find that many greening trends detected in earlier studies do not withstand our rigorous significance testing. Yet we do find consistent greening trends in South East China. Our results show substantial differences in statistically significant patterns of greening and browning among the products used, but greatly reduce the focal areas of greening that should be investigated in detail with proper trend-attribution methods. </p>

scholarly journals Spatially Distributed Hydrological Modelling of a Western Africa Basin

10.29007/1xw5 ◽  
2018 ◽  
Author(s):  
Khalidou M. Bâ ◽  
Vitali Diaz ◽  
Miguel Angel Gómez-Albores ◽  
Carlos Díaz-Delgado ◽  
Nancy Nájera-Mota ◽  
...  
Keyword(s):  
Model Performance ◽  
Tropical Rainfall Measuring Mission ◽  
Coefficient Of Determination ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Temporal Behaviour ◽  
Western Africa ◽  
Spatially Distributed ◽  
Model Efficiency ◽  
Spatio Temporal

Distributed hydrological simulations aid to investigate the spatio-temporal behaviour of hydrological variables. However, data to feed hydrological models are not always available mainly due to lack of gauges or high retrieval fees. In this research, two 0.25- degree daily precipitation databases from the Tropical Rainfall Measuring Mission (TRMM) were tested to simulate daily runoff in the basin of the main Upper Niger River tributary. Precipitation data are TRMM and TRMM Real Time (RT) 3B42V7. For runoff simulation, the grid-based hydrological model CEQUEAU was chosen. To estimate the evaporation in the model, temperatures were retrieved from the third-generation reanalysis ERA-Interim. From gauges and both TRMM data, monthly basin precipitation was calculated and compared to analyse the performance of TRMM to estimate rainfall. Runoff was simulated with each of these three precipitation products. In each case, the daily ERA-Interim temperatures were used. By Nash-Sutcliffe model Efficiency (NSE) and coefficient of determination (R2), model performance was evaluated through comparison of daily discharges with simulations for both calibration and validation periods. Results show correlation of TRMM by 0.95 and TRMMRT by 0.91 with gauge data. Both TRMM products combined with ERA-Interim temperature were found suitable for daily runoff modelling with NSE >0.835 and R2 >0.872.

scholarly journals Assessing climate and land-use change impacts on streamflow in a mountainous catchment

2018 ◽  
Vol 11 (2) ◽  
pp. 503-513 ◽  
Author(s):  
Qiang Liu ◽  
Liqiao Liang ◽  
Yanpeng Cai ◽  
Xuan Wang ◽  
Chunhui Li
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Field Capacity ◽  
Soil Parameters ◽  
Area Index ◽  
Mountainous Catchment ◽  
Vegetation Height ◽  
Streamflow Response ◽  
Model Efficiency ◽  
Surrounding Areas

AbstractIt is essential to assess streamflow response to climate and land-use change in catchment basins that serve cities and their surrounding areas. This study used the Distributed Hydrology Soil Vegetation Model (DHSVM) to simulate streamflow under different climate and land-use change scenarios in the Dashi River catchment, China. The most sensitive soil parameters were maximum infiltration, porosity, field capacity, and wilting point, while the most sensitive vegetation parameters were leaf area index (LAI) and vegetation height. The suitability of the DHSVM model was aligned with Nash–Sutcliffe model efficiency coefficients (NSE) greater than 0.41 and 0.84 at daily and monthly scales, respectively. Streamflow increased/decreased with increasing/decreasing precipitation, while it decreased with increasing air temperature. Furthermore, streamflow decreased with the increase in forestland due to higher water consumption, especially during summer. Results from this study could help us to better understand streamflow response to changes in climate and land use.

scholarly journals The Global Long-term Microwave Vegetation Optical Depth Climate Archive VODCA

2019 ◽  
Author(s):  
Leander Moesinger ◽  
Wouter Dorigo ◽  
Richard de Jeu ◽  
Robin van der Schalie ◽  
Tracy Scanlon ◽  
...  
Keyword(s):  
Optical Depth ◽  
Cumulative Distribution ◽  
Strong Increase ◽  
Data Sets ◽  
Area Index ◽  
North Asia ◽  
Multiple Data Sets ◽  
Spatio Temporal ◽  
Microwave Sensors

Abstract. Since the late 1970s, spaceborne microwave sensors have been providing measurements of radiation emitted by the Earth's surface. From these measurements it is possible to derive vegetation optical depth (VOD), a model-based indicator related to vegetation density and its relative water content. Because of its high temporal resolution and long availability, VOD can be used to monitor short- to long-term changes in vegetation. However, studying long-term VOD dynamics is generally hampered by the relatively short time span covered by the individual microwave sensors. This can potentially be overcome by merging multiple VOD products into a single climate data record. But, combining multiple sensors into a single product is challenging as systematic differences between input products, e.g. biases, different temporal and spatial resolutions and coverage, need to be overcome. Here, we present a new series of long-term VOD products, which combine multiple VOD data sets derived from several sensors (SSM/I, TMI, AMSR-E, Windsat, and AMSR-2) using the Land Parameter Retrieval Model. We produce separate VOD products for microwave observations in different spectral bands, namely Ku-band (period 1987–2017), X-band (1997–2018), and C-band (2002–2018). In this way, our multi-band VOD products preserve the unique characteristics of each frequency with respect to the structural elements of the canopy. Our approach to merge the single-sensor VOD products is similar to the one of the ESA CCI Soil Moisture products (Liu et al., 2012; Dorigo et al., 2017): First, the data sets are co-calibrated via cumulative distribution function matching using AMSR-E as scaling reference. We apply a new matching technique that scales outliers more robustly than ordinary piece-wise linear interpolation. Second, we aggregate the data sets by taking the arithmetic mean between temporally overlapping observations of the scaled data, generating a VOD Climate Archive (VODCA). The characteristics of VODCA are assessed for self-consistency and against other products: spatio-temporal patterns and anomalies of the merged products show consistency between frequencies and both with observations of Leaf Area Index derived from the MODIS instrument as well as Vegetation Continuous Fields from AVHRR instruments. Trend analysis shows that since 1987 there has been a decline in VOD in the tropics and in large parts parts of east-central and north Asia along with a strong increase in India, large parts of Australia, south Africa, southeastern China and central north America. Using an autocorrelation analysis, we show that the merging of the multiple data sets successfully reduces the random error compared to the input data sets. In summary, VODCA shows vast potential for monitoring spatio-temporal ecosystem behaviour complementary to existing long-term vegetation products from optical remote sensing. The VODCA products (Moesinger et al., 2019) are open access and available under Attribution 4.0 International at https://doi.org/10.5281/zenodo.2575599.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Climate drivers of plague epidemiology in British India, 1898–1949

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200538
Author(s):  
Warren S. D. Tennant ◽  
Mike J. Tildesley ◽  
Simon E. F. Spencer ◽  
Matt J. Keeling
Keyword(s):  
Predictive Models ◽  
Control Measures ◽  
Climate Data ◽  
British India ◽  
Middle Income ◽  
Middle Income Countries ◽  
Complex Interactions ◽  
The World ◽  
Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

scholarly journals Sensitivity and Performance Analyses of the Distributed Hydrology–Soil–Vegetation Model Using Geomorphons for Landform Mapping

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2032
Author(s):  
Pâmela A. Melo ◽  
Lívia A. Alvarenga ◽  
Javier Tomasella ◽  
Carlos R. Mello ◽  
Minella A. Martins ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Overland Flow ◽  
Hydrological Model ◽  
Model Performance ◽  
Soil Parameters ◽  
Vegetation Model ◽  
Landform Classification ◽  
Physically Based ◽  
And Performance ◽  
Streamflow Simulation

Landform classification is important for representing soil physical properties varying continuously across the landscape and for understanding many hydrological processes in watersheds. Considering it, this study aims to use a geomorphology map (Geomorphons) as an input to a physically based hydrological model (Distributed Hydrology Soil Vegetation Model (DHSVM)) in a mountainous headwater watershed. A sensitivity analysis of five soil parameters was evaluated for streamflow simulation in each Geomorphons feature. As infiltration and saturation excess overland flow are important mechanisms for streamflow generation in complex terrain watersheds, the model’s input soil parameters were most sensitive in the “slope”, “hollow”, and “valley” features. Thus, the simulated streamflow was compared with observed data for calibration and validation. The model performance was satisfactory and equivalent to previous simulations in the same watershed using pedological survey and moisture zone maps. Therefore, the results from this study indicate that a geomorphologically based map is applicable and representative for spatially distributing hydrological parameters in the DHSVM.

scholarly journals Tracking Changes on Soil Structure and Organic Carbon Sequestration after 30 Years of Different Tillage and Management Practices

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 291
Author(s):  
Ramón Bienes ◽  
Maria Jose Marques ◽  
Blanca Sastre ◽  
Andrés García-Díaz ◽  
Iris Esparza ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Organic Carbon ◽  
Management Practices ◽  
Management Strategies ◽  
Triticum Aestivum L ◽  
Field Trials ◽  
Conventional Tillage ◽  
Soil Parameters ◽  
Wilting Point

Long-term field trials are essential for monitoring the effects of sustainable land management strategies for adaptation and mitigation to climate change. The influence of more than thirty years of different management is analyzed on extensive crops under three tillage systems, conventional tillage (CT), minimum tillage (MT), and no-tillage (NT), and with two crop rotations, monoculture winter-wheat (Triticum aestivum L.) and wheat-vetch (Triticum aestivum L.-Vicia sativa L.), widely present in the center of Spain. The soil under NT experienced the largest change in organic carbon (SOC) sequestration, macroaggregate stability, and bulk density. In the MT and NT treatments, SOC content was still increasing after 32 years, being 26.5 and 32.2 Mg ha−1, respectively, compared to 20.8 Mg ha−1 in CT. The SOC stratification (ratio of SOC at the topsoil/SOC at the layer underneath), an indicator of soil conservation, increased with decreasing tillage intensity (2.32, 1.36, and 1.01 for NT, MT, and CT respectively). Tillage intensity affected the majority of soil parameters, except the water stable aggregates, infiltration, and porosity. The NT treatment increased available water, but only in monocropping. More water was retained at the permanent wilting point in NT treatments, which can be a disadvantage in dry periods of these edaphoclimatic conditions.

Seabird bycatch vulnerability in pelagic longline fisheries based on modelling of a long-term dataset

2021 ◽  
pp. 1-16
Author(s):  
CAN ZHOU ◽  
NIGEL BROTHERS
Keyword(s):  
Capture Event ◽  
Retrieval Rate ◽  
Competitive Environments ◽  
Global Concern ◽  
Competitive Species ◽  
Spatio Temporal ◽  
Longline Fisheries ◽  
Pelagic Longline

Summary The incidental mortality of seabirds in fisheries remains a serious global concern. Obtaining unbiased and accurate estimates of bycatch rates is a priority for seabird bycatch mitigation and demographic research. For measuring the capture risk of seabird interactions in fisheries, the rate of carcass retrieval from hauled gear is commonly used. However, reliability can be limited by a lack of direct capture observations and the substantial pre-haul bycatch losses known to occur, meaning incidence of seabird bycatch is underestimated. To solve this problem, a new measure (bycatch vulnerability) that links an observed interaction directly to the underlying capture event is proposed to represent the capture risk of fishery interactions by seabirds. The new measure is not affected by subsequent bycatch loss. To illustrate how to estimate and analyse bycatch vulnerability, a case study based on a long-term dataset of seabird interactions and capture confirmation is provided. Bayesian modelling and hypothesis testing were conducted to identify important bycatch risk factors. Competition was found to play a central role in determining seabird bycatch vulnerability. More competitive environments were riskier for seabirds, and larger and thus more competitive species were more at risk than smaller sized and less competitive species. Species foraging behaviour also played a role. On the other hand, no additional effect of physical oceanic condition and spatio-temporal factors on bycatch vulnerability was detected. Bycatch vulnerability is recommended as a replacement for the commonly used bycatch rate or carcass retrieval rate to measure the capture risk of an interaction. Combined with a normalized contact rate, bycatch vulnerability offers an unbiased estimate of seabird bycatch rate in pelagic longline fisheries.

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