Evaluating The Impacts Of Environmental Parameters On: Fill & Download for Free

It is better to start with accomplishments. They have already completed 4 major projects.Impact of anthropogenic and natural changes on natural resources and the environment: Co-PI: $321,800 (USDA-NIFA). 2014-2018.An experimental approach to study water quality and water conservation in an agricultural watershed. PI: $20,000 (Office of Research, Prairie View A&M University). 2016Use Landsat and Sentinel satellite images to identify the inundation/flood zones during the extreme rainfall eventsStudy on climate change impacts on agriculture and the evaluation of adaptation measures in Texas. Co-PI: $20,000 (Office of Research, Prairie View A&M University). 2016.Now let’s discuss what they are planning to do in the future. Because this entire group is led by Dr. Ram L. Ray, remember that he does a significant portion of the work, and is leading all of the below.Develop satellite and hydrologic database for the proposed watershed (2001-2020)Estimate daily surface runoff using hydrologic and satellite data, and SWATUse Landsat and Sentinel satellite images to identify the inundation/flood zones during the extreme rainfall eventsUse estimated runoff and flood map to develop a methodological framework for flood managementDeliver Workforce Development Experiences for studentsExpand students’ experiences to increase their knowledge and engagementProvide experiential learning opportunities related to soft skills development and leadership trainingGenerate projected daily climate forcing data using combined Global Circulation Model (GCM) and stochastic downscaling model for three time periods; 2030s, 2055s & 2090sQuantify the impact of climate change on crop water requirement, crop nutrient and soil and water quality for three major crops (Cotton, corn and sorghum) at Brazos River WatershedDevelop a well-equipped farm testbed at the college’s demonstration farm to enhance extension and outreach activities and strengthen research capacity in Natural Resources and Environmental Systems (NRES)Evaluate different adaptation measures (e.g., change in irrigation and nutrient application rates) and relative change in crop water requirement, crop yield and soil and water quality with and without adaptation approachDevelop plant hardiness zone map (PHZM) for three projected time periods and educate and train limited resource, socially disadvantaged farmers, ranchers and other stakeholders on outcomes of the projectDevelop applications to access: a) near real-time data of rainfall, ETo and their related parameters from different weather networks across Texas, b) forecasted weather data, and c) site specific soil hydrologic dataDevelop, test, and validate a mobile web app, IrrigWise, to provide site specific real-time irrigation scheduling data for different crops under urban and agricultural environmentsConduct an outreach program, e.g. training sessions, livestream videos, and seminar presentations, to demonstrate the use of IrrigWise to different stakeholders; in addition, these outreach activities will be through the college web site and other national meetings and scientific publications.Continue collecting, analyzing, and quantifying the long-term spatio-temporal climatic and hydrologic data of different scales of interest.Continue downscaling projections of selected global circulation models (GCM) to different spatial scales of interest using a nonlinear statistical downscaling approach.Continue developing practical recommendations based on the results of the different components of the project.Further educating and training of students, junior scientists, and different stakeholders on the outcomes of the project through multiple outreach venues and different outreach methods.Continue conducting a series of sensitivity analyses, calibration, and validation of an integrated suite of models (a watershed model [SWAT/AnnAGNPS] and a cropping system model [DSSAT], and water allocation model [IManSys/ IrrigWise/ IWET]) that would be used to predict impacts of climate change scenarios selected above on the major hydrological cycle components, extreme climate events (e.g., drought and flooding) at the watershed scale, water availability, crop yield and water use, and water quality.Continue monitoring of soil moisture and nutrient for irrigation and nutrient management.It is a lot, but that’s their plan until around 2023 or 2024.

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I integrate what I read from scientific papers into my research in several ways:I learn new techniques and approaches. For example, I read Quantifying total suspended sediment export from the Burdekin River catchment using the loads regression estimator tool, saw how the authors had used GAMs to estimate sediment loads in a river and realised that I could use the same general approach, with some tweaks, to predict nutrient concentrations in a different river, which I needed to do for a project I was working on. That spurred me to learn how to use R and to learn about GAMs, and eventually resulted in me writing Prediction of sediment, particulate nutrient and dissolved nutrient concentrations in a dry tropical river to provide input to a mechanistic coastal water quality model. Of course, I cited the original paper, along with several others that I subsequently read that took similar or quite different approaches to the same problem.They inspire me to ask new questions. For example, I read Heavy use of equations impedes communication among biologists, in which they found that papers that contained a lot of equations were cited less often, and I wondered cynically whether this applied even to my field of environmental modelling, where most readers should be very comfortable with equations. Investigating this question led to my paper, Can we predict citation counts of environmental modelling papers? Fourteen bibliographic and categorical variables predict less than 30% of the variability in citation counts. (The answer: probably yes, and the type of equation matters).The give me clues about what to look for when I am investigating a problem. For example, when doing the research for my "citation counts" paper, I read Which factors help authors produce the highest impact research? Collaboration, journal and document properties, wherein the authors found that papers with longer abstracts were cited more often. I checked whether this was true for the papers in my own data set and found that yes, it was.They provide a reference point so I can see how my findings fit in with the findings of others. For instance, when writing Modelling and mass balance assessments of nutrient retention in a seasonally-flowing estuary (Swan River Estuary, Western Australia), I used a round-about method to estimate sediment phosphorus release. As a reality-check, I looked through the literature to find what sediment phosphorus release rates other people had measured in other systems. Papers like Is phosphorus retention in autochthonous lake sediments controlled by oxygen or phosphorus? helped to show that my estimate for the Swan River Estuary was reasonable and not unusual.I can combine their findings with my own work to reach new conclusions. For example, when calculating mass balances of nutrients for the Swan River Estuary in the paper above, I needed an estimate of how much nitrogen came into the estuary with groundwater. I wasn't in a position to measure it myself, but without an estimate, I wouldn't have been able to estimate denitrification fluxes. I refered to Interaction between shallow groundwater, saline surface water and nutrient discharge in a seasonal estuary: the Swan-Canning system to find the groundwater flux estimates that I needed to complete my calculations.They challenge me to improve the way I do things. For example, I read Ten iterative steps in development and evaluation of environmental models and saw that I could make my models better if I added a sensitivity analysis step and more clearly separated calibration from validation. It wasn't immediately clear how well the steps applied to my sort of modelling, which was different from the original author's field in that it involves computationally intensive fluid dynamics models and bioheochemical models that usually have many parameters, so I went through some of my own previous modelling work carefully and evaluated it in the light of that paper. I wrote Ten steps applied to development and evaluation of process-based biogeochemical models of estuaries to discuss the results and show others in my field that the ten steps were indeed very relevant to us.They provide evidence that a problem is important and worthy of study. For instance, I referred to Toxicity associated with commonly occurring cyanobacteria in surface waters of the Murray-Darling Basin, Australia when writing Summer flow event induces a cyanobacterial bloom in a seasonal Western Australian estuary. I didn't study the toxicity of the bloom, but the fact that it was the sort of bloom that has impliciations for human and animal health was part of what made it important to understand its causes. It was all the more important because climate change projections made this sort of bloom more likely to occur in future, though it was the first time this species had caused a problem in the Swan River estuary. How did I know it was more likely to occur in future? I had read Progress towards new climate change scenarios for Australia.