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57 results for “SWAT”
Effect of spatial input data quality on SWAT modelling in the Porijõgi catchment
<p>The Porijõgi Catchment near Tartu, Estonia is the study area for this research. Four model setups were created using global/regional level data (HWSD soil, CORINE), and local high-resolution spatial data including the new Estonian high-resolution EstSoil-EH soil dataset and the Estonian Topographic Database (ETAK). The study employed statistical criteria to assess SWAT model performance for monthly simulated stream flows from 2007 to 2019.</p> <p>Data deposit in preparation for article:</p> <p>Effect of spatial input data quality on the uncertainty of the<br> SWAT model, submitted 2022</p> <p>Alexander Kmoch, Desalew Meseret Moges, Mahdiyeh Sepehrar, Balaji Narasimhan and Evelyn<br> Uuemaa</p> <p>contact: alexander.kmoch@ut.ee</p>
Updated fruits and vegetable parameters for swat models
<p>Ensuring accurate crop yield simulations in ecohydrological models such as the Soil and Water Assessment Tool (SWAT) is crucial to improve our understanding of agricultural systems and productivity. This, in turn, can facilitate the development of more sustainable agricultural practices. In this study, we focused on validating the crop growth parameters of the SWAT model for 24 table food fruits and vegetables in Iowa, located in the western Corn Belt region of the United States.</p> <p>To estimate these parameters, we used five primary sources: a) existing parameters in the SWAT crop parameter database, b) alternative parameters in the Environmental Policy Integrated Climate (EPIC) and Agricultural Policy/Environmental eXtender (APEX) crop parameter databases, c) literature, d) PHU fraction for scheduling dates, and e) expert communication among modeling team members. Among the 24 crops tested, 15 initial parameter data sets were already available in the SWAT database, and the remaining crop types were added to this plant.dat file.</p>
Figures 1–9. Amphicoma spp. 1-3 in Amphicoma gandhara, a new species of Glaphyridae (Coleoptera: Scarabaeoidea) from Swat District in northern Pakistan
Figures 1–9. Amphicoma spp. 1-3) Amphicoma gandhara, new species, dorsal habitus. 1) Holotypus Ƌ. 2) Paratypus Ƌ#1. 3) Paratypus Ƌ#2. 4-6). Amphicoma gandhara, new species, parameres. 4) Right view. 5) Dorsal. 6) Left. 7-9) Amphicoma schneideri Nikodým, parameres. 7) Right view. 8) Dorsal. 9) Left.
SWAT river water, TN & TP loads to Limfjorden under climate change scenarios (Delta change) + baseline SWAT loads 2009-2018. Paper ". Impacts of climate change on water quality, benthic mussels and suspended mussel culture in a shallow, eutrophic estuary by Maar et al. Heliyon,
<p>SWAT river water, TN & TP loads to Limfjorden under climate change scenarios (Delta change) + baseline SWAT loads 2009-2018 </p>
Hydrometeorological dataset and SWAT simulated outputs of Jaguari basin in the Cantareira reservoirs system
<p>Dataset used in the accepted paper "Hydrologic Impact of Climate Change in the Jaguari River in the Cantareira Reservoir System" (Domingues et al., 2022), from Water. A README.txt file is available within each folder with details of the dataset.</p>
Figure 1-2. Lutziella swatensis n in Description of Lutziella swatensis sp.n. (Trematoda: Dicrocoelidae) from Rattus rattus in Swat, Pakistan
Figure 1-2. Lutziella swatensis n.sp. holotype, Photomicrographs. (1) Lutziella swatensis entire specimen; (2) Embryonated eggs enlarged. Note: Entire specimens were measured in millimeter and the eggs were measured in micrometer.
Figure 1 in Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat
Figure 1. Sampling sites: Charbagh, Odigram, and Landakai of River Swat (Google map, 2017). 2.3. Fish identification
Figure 3 in Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat
Figure 3. Atomic absorption spectrophotometer used for the analysis of heavy metals i.e zinc, lead, chromium and nickel present in the extracted tissues of muscles and gills.
Figure 7 in Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat
Figure 7. Heavy metals concentrations (ppm) in muscle and gills of S. plagiostomus at Odigram, Charbagh, and Landakai site.
Figure 2 in Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat
Figure 2. The collected samples of the Schizothorax plagiostomus species from Charbagh, Odigram and Landakai of River Swat.
Figure 1 in Feeding habit of Brown trout (Salmo trutta fario) in upper parts of river Swat, Pakistan
Figure 1. Percentage of N,W, FO and IRI of various diet components. Table 2. GSI and fullness index of various length groups of brown trout.
Fig. 2 in Daboia russelii (Reptilia: Squamata) in remote parts of Gujjar Village Miandam, Swat, Khyber Pakhtunkhwa, Pakistan
Fig. 2. Collection sites of Daboia russelii in Gujjar village Miandam, Swat, KP, Pakistan. (A) Karoo, 35º3ʹ32ʺN 72º33ʹ11ʺE; (B) Kaalandori, 35º3ʹ31ʺN 72º32ʹ21ʺE; (C) Chhar 35º3ʹ34ʺN 72º33ʹ12ʺE; (D) Doop, 35º3ʹ23ʺN 72º32ʹ58ʺE.
Fig. 1 in Daboia russelii (Reptilia: Squamata) in remote parts of Gujjar Village Miandam, Swat, Khyber Pakhtunkhwa, Pakistan
Fig. 1. Map of Khyber Pakhtunkhwa, red circle shows the study area in the District Swat within the province.
Fig. 3 in Daboia russelii (Reptilia: Squamata) in remote parts of Gujjar Village Miandam, Swat, Khyber Pakhtunkhwa, Pakistan
Fig. 3. Photos of the dead Daboia russelii specimens from Gujjar village Miandam, Swat, KP, Pakistan. (A, B) Dorsal views, (C, D) Fangs, (E) Black spots on ventral side, (F) Anal orifice with tail showing a zip-like structure.
Linked collectors and determiners for: Amphicoma gandhara, a new species of Glaphyridae (Coleoptera: Scarabaeoidea) from Swat District in northern Pakistan.
Natural history specimen data linked to collectors and determiners held within, "Amphicoma gandhara, a new species of Glaphyridae (Coleoptera: Scarabaeoidea) from Swat District in northern Pakistan". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/77690e3f-3f08-490a-b0e8-0bbcac1fa05c">https://bionomia.net/dataset/77690e3f-3f08-490a-b0e8-0bbcac1fa05c</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/77690e3f-3f08-490a-b0e8-0bbcac1fa05c">https://gbif.org/dataset/77690e3f-3f08-490a-b0e8-0bbcac1fa05c</a>. Formatted as a Frictionless Data package.
Training Deep Learning Models to Estimate SWAT Parameters using Streamflow Observations
<p>This folder provides the simulation and observational data</p> <p>Simulation data using SWAT (1000 realz)<br> Train, Val, and Test splits (80/10/10)<br> Observational data for ARW (WY2000-2016)</p>
Simulations for SA and SC of SWAT+ model
<p>This repository contains the simulations run with SWATPlusR to perform the Sensitivity analysis and the Soft calibration for a SWAT+ model constructed for the Upper Tagus River basin.</p> <p> </p> <p>In this repository you will find:</p> <p>The raw simulations for the Sensitivity analysis --> SA_runs.rar</p> <p>The files created when extracting the data from the simulations for the Sensitivity analysis --> var_extract.zip</p> <p> </p> <p>The raw simulations for the Soft calibration:</p> <p>For each iteration, the file that contains the entire output from the 1000 simulations is the ronda_X_lsu.rds</p> <p>The file channels_ordered_all.rds contains the streamflow simulated for the evaluated subbasins for the three soft calibration iterations.</p> <p> </p> <p>More info and the code used to analyse this data can be found in the GitHub repository (https://github.com/alejandrosgz/https://github.com/alejandrosgz/HSJ_SA_SC_SWATPlus)</p> <p> </p>
SWAT+ simulation result used in "Smart renewable electricity portfolios in West Africa"
<p>Shapefiles and simulation results from SWAT+ used for the paper "Smart renewable electricity portfolios in West Africa" by Sterl et al., who used it to infer the interannual variability of river flow seasonality across West Africa.</p>
SWAT-GL Demo Model Martelltal
<p>Here we provide an example model of SWAT-GL in the Martelltal with updated input files and the latest revisions. </p>
SWAT proteomics study
<p>CSV file: Prosessed de-identified proteomics data of a sub-cohort of pateints from the SWAT observational study</p> <p>zip folder: SomaLogic adat file and measurment infomration on the same study</p>
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.