Development of a Distributed Artificial Neural Network for Hydrologic Modeling

Hydrological models are used to represent the rainfall-runoff and pollutant transport mechanisms within watersheds. Accurate representation of these dynamic and complex natural processes within a watershed is an important step in managing and protecting a watershed Artificial neural network (ANN) models are often used in hydrologic modeling. Typical ANN models are trained to use lumped data. However, watershed characteristics used as inputs in hydrological modeling are spatially and often temporally dynamic. Therefore, a lumped model does not have the ability to represent changes in spatial dynamics of a watershed. Therefore, the purpose of this study was to develop and test a distributed ANN model for simulating the rainfall-runoff process in the L\u27Anguille River Watershed located in Eastern Arkansas. The watershed was divided into nine sub-basins to account for the spatial dynamics of flow within the watershed Inputs for the model were rainfall, average temperature, antecedent flow and curve number. Output was runoff collected from gage-stations at Colt and Palestine representing two of the sub-basins. Daily SCS curve numbers were developed and adjusted for crop planting and harvesting dates and crop rotation practices in each sub-basin. The model had nine layers with one neuron each to represent the nine sub-basins. The layers were connected so that if one sub-basin spatially flowed into another, its output would be an input for the downstream sub-basin. The model performed well, showing R2 values of 0.93 and 0.98 and Nash-Sutcliffe Efficiency values of 0.92 and 0.97 for the validation and test datasets

Development and application of quantitative methods for ecosystem services

Ecosystem services are benefits that people receive from the environment. Despite recent exponential increases in ecosystem service research, the ecosystem service framework has made little impact on policy and land management decisions, especially in the United States. Two of the main limitations for a lack of ecosystem service considerations in both policy and land management decisions are a need for more advanced quantification methods and the lack of engagement of key stakeholders who are responsible for making land management decisions. This research seeks to address these two limitations by testing and improving quantification methods of ecosystem services and by evaluating agricultural managers\u27 understanding and perceptions of ecosystem services. The main objectives of this research were to (1) test an existing ecosystem service evaluation method in the Upper Mississippi River Basin under current conditions and future climate change, (2) improve understanding of influences of aquatic genetic resource provisioning using the SWAT model, (3) improve quantification methods for climate regulation ecosystem services using the DayCent model; and (4) evaluate Indiana agricultural producers\u27 and conservationists\u27 perceptions of ecosystem services in order to identify the best ways to improve inclusion of the ecosystem service considerations in making agricultural management decisions. For the first objective, previously developed quantification methods for freshwater provision, food provision, erosion regulation, and flood regulation were applied to a large 2-digit HUC watershed in the U.S. (the Upper Mississippi River Basin). The results show that these methods were able to capture tradeoffs between existing ecosystem services, specifically freshwater provision and food provision, in this watershed. Climate change and variability may have considerable impact on ecosystem services in this river basin. For the second objective of this research a Soil and Water Assessment Tool (SWAT) model was developed to evaluate the possible drivers of an observed change in fish regime the Wabash River that occurred around the 1990\u27s. The results indicated that changing agricultural practices combined with increasing precipitation may have influenced the observed fish regime change. This link between agricultural management decisions and an historical fish regime change in the Wabash River can improve understanding of the link between management decisions and aquatic genetic resource provisioning. The third objective of this research applied a multi-objective genetic algorithm optimization tool (AMALGAM) to improve the performance of the DayCent model and then proposed a quantification method for climate regulation using DayCent. Although the DayCent calibration method was able to improve the performance of the model at the calibration plots for both yield and N2O flux, the N2O flux simulation of the validation plots were not improved due to the influence of two plots with high N2O emissions. This work suggests that although a multi-objective function can be used to calibrate DayCent, the method may work best within a treatment, even if the plots are all at the same location. The climate regulation index that was developed under Objective 3 was able to capture the ability of a local, terrestrial ecosystem to regulate climate. For the last objective, surveys were conducted of Indiana farmers and conservationists, and interviews were held with Indiana farmers. The results indicated that Indiana farmers and conservationists understand ecosystem services, even if they do not use the terminology. It also shows that the existing conservation framework can be utilized to implement ecosystem service based management. By understanding the perceptions of these key stakeholders, the ecosystem service framework can be better implemented in developing management and policy strategies

Development of a distributed artificial neural network for hydrologic modeling

Development of a distributed artificial neural network for hydrologic modelin

Dynamics of Trophoblast Differentiation in Peri-Implantation–Stage Human Embryos

Single-cell RNA sequencing of cells from cultured human blastocysts has enabled us to define the transcriptomic landscape of placental trophoblast (TB) that surrounds the epiblast and associated embryonic tissues during the enigmatic day 8 (D8) to D12 peri-implantation period before the villous placenta forms. We analyzed the transcriptomes of 3 early placental cell types, cytoTB (CTB), syncytioTB (STB), and migratoryTB (MTB), picked manually from cultured embryos dissociated with trypsin and were able to follow sublineages that emerged from proliferating CTB at the periphery of the conceptus. A unique form of CTB with some features of STB was detectable at D8, while mature STB was at its zenith at D10. A form of MTB with a mixed MTB/CTB phenotype arose around D10. By D12, STB generation was in decline, CTB had entered a new phase of proliferation, and mature MTB cells had begun to move from the main body of the conceptus. Notably, the MTB transcriptome at D12 indicated enrichment of transcripts associated with IFN signaling, migration, and invasion and upregulation of HLA-C, HLA-E, and HLA-G. The STB, which is distinct from the STB of later villous STB, had a phenotype consistent with intense protein export and placental hormone production, as well as migration and invasion. The studies show that TB associated with human embryos is in rapid developmental flux during periimplantation period when it must invade, signal robustly to the mother to ensure that the pregnancy continues, and make first contact with the maternal immune system

Quality of life in patients with mild cognitive impairment

Background: Quality of life (QoL) is affected in patients with dementia, but it is not clear whether it is already disturbed in more initial phases of cognitive decline, like Mild Cognitive Impairment (MCI). Aim: Compare the QoL in MCI patients with controls without cognitive impairment, and ascertain whether there are differences in the reports of QoL made by the subjects and by their informants. Methods: Two hundred participants were enrolled, divided into MCI patients (n¼50), MCI informants (n¼50), recruited from a memory clinic and a dementia outpatient clinic, and controls (n¼50) and controls informants (n¼50), recruited in a family practice clinic. QoL was assessed with the QoL in Alzheimer disease (QOL-AD) scale. Results: The total scores of the QOL-AD questionnaire were 32.1 6.9 for MCI patients self-report, 27.2 6.7 for MCI patients in the opinion of their informants, 35.3 4.9 for controls self-report and 35.6 4.9 for controls in the opinion of their informants. MCI patients had lower QOL-AD scores than controls. The QoL reported by patients with MCI was more favorable than the opinion of their informants. Conclusion: The QoL is affected at early stages of cognitive decline. The QoL reported by patients with MCI is better than the opinion of their informants, similarly to what is known in Alzheimer’s disease patients. QoL appears to be an important domain to be evaluated in aging studies

Multiple models guide strategies for agricultural nutrient reductions

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/1/fee1472_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/2/fee1472-sup-0008-WebTable7.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/3/fee1472-sup-0004-WebTable3.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/4/fee1472.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/5/fee1472-sup-0006-WebTable5.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/6/fee1472-sup-0002-WebTable1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/7/fee1472-sup-0005-WebTable4.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/8/fee1472-sup-0007-WebTable6.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/9/fee1472-sup-0003-WebTable2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/10/fee1472-sup-0001-WebFig1.pd

Using a Multi-Institutional Ensemble of Watershed Models to Assess Agricultural Conservation Effectiveness in a Future Climate

This study investigates the combined impacts of climate change and agricultural conservation on the magnitude and uncertainty of nutrient loadings in the Maumee River Watershed, the second-largest watershed of the Laurentian Great Lakes. Two scenarios — baseline agricultural management and increased agricultural conservation — were assessed using an ensemble of five Soil and Water Assessment Tools driven by six climate models. The increased conservation scenario included raising conservation adoption rates from a baseline of existing conservation practices to feasible rates in the near future based on farmer surveys. This increased adoption of winter cover crops on 6%–10% to 60% of cultivated cropland; subsurface placement of phosphorus fertilizers on 35%–60% to 68% of cultivated cropland; and buffer strips intercepting runoff from 29%–34% to 50% of cultivated cropland. Increased conservation resulted in statistically significant (p ≤ 0.05) reductions in annual loads of total phosphorus (41%), dissolved reactive phosphorus (18%), and total nitrogen (14%) under the highest emission climate scenario (RCP 8.5). While nutrient loads decreased with increased conservation relative to baseline management for all watershed models, different conclusions on the true effectiveness of conservation under climate change may be drawn if only one watershed model was used.publishedVersio