Search Results (25)

The increasing demand for food and rapid population growth have made advanced crop monitoring essential for sustainable agriculture. Deep learning models leveraging multispectral satellite imagery, like Sentinel-2, provide valuable solutions. However, transferring these models to diverse regions is challenging due to phenological differences in crop growth stages between training and target areas. This study proposes the Adaptive Month Matching (AMM) method to align the phenological stages of crops between training and target areas for enhanced transfer learning in cropland segmentation. In the AMM method, an optimal Sentinel-2 monthly time series is identified in the training area based on deep learning model performance for major crops common to both areas. A month-matching process then selects the optimal Sentinel-2 time series for the target area by aligning the phenological stages between the training and target areas. In this study, the training area covered part of the Mississippi River Delta, while the target areas included diverse regions across the US and Canada. The evaluation focused on major crops, including corn, soybeans, rice, and double-cropped winter wheat/soybeans. The trained deep learning model was transferred to the target areas, and accuracy metrics were compared across different time series chosen by various phenological alignment methods. The AMM method consistently demonstrated strong performance, particularly in transferring to rice-growing regions, achieving an overall accuracy of 98%. It often matched or exceeded other phenological matching techniques in corn segmentation, with an average overall accuracy across all target areas exceeding 79% for cropland segmentation. Full article

Here, we review the functioning and importance of deltaic coastal systems in the northern and southern Gulf of Mexico and how petroleum activities have impacted these two important systems. The Mississippi and Usumacinta-Grijalva Deltas are areas of high biological productivity and biodiversity that support the two largest fisheries in the Gulf. The north central Gulf receives inflow from the Mississippi river, the largest discharge in North America. The Mississippi Delta covers about 10,000 km². The Usumacinta-Grijalva River is the second highest freshwater input to the Gulf and discharges to the Usumacinta-Grijalva/Laguna de Terminos deltaic complex. These two areas are the largest petroleum producing regions in the Gulf, involving both inshore and offshore production. Petroleum activities impact coastal ecosystems in two important ways. In inshore areas dominated by coastal wetlands, there has been enormous physical disruption of the natural environment that affected hydrology and system functioning. In both inshore and offshore areas, spilled oil and release of high salinity produced water has led to widespread toxic pollution. Documentation of petroleum activity impacts on coastal marine ecosystems is much more advanced in the Mississippi Delta. Here, we describe how petroleum production impacts coastal ecosystems and discuss how restoration and management can restore the functioning of impacted coastal ecosystems. Full article

The Mississippi Delta region has worse population health outcomes, including higher overall cardiovascular and infant mortality rates. Water quality has yet to be considered as a factor in these health disparities. The objective of this paper is to determine overall differences in basic water quality indicators, electrolytes of cardiovascular importance, trace elements, heavy metals, and radioactive ions of groundwater in delta and non-delta counties in states along the Mississippi River. Data were sourced from the major-ions dataset of the U.S. Geological Survey. We used the Wilcoxon rank sum test to determine the difference in water quality parameters. Overall, delta counties had lower total dissolved solids (TDS) (47 and 384 mg/L, p-value < 0.001), calcium (7 and 58 mg/L; p-value < 0.001), magnesium (2 and 22 mg/L; p-value < 0.001), and potassium (1.57 and 1.80 mg/L; p-value < 0.001) and higher sodium (38 mg/L and 22 mg/L; p-value < 0.001) compared to non-delta counties. Overall, there were no statistical differences in trace elements, heavy metals, and radioactive ions across delta versus non-delta counties. These results underscore the need for further epidemiological studies to understand if worse health outcomes in delta counties could be partially explained by these parameters. Full article

The Mississippi River Delta Front (MRDF) is a subaqueous apron of rapidly deposited and weakly consolidated sediment extending from the subaerial portions of the Birdsfoot Delta of the Mississippi River, long characterized by mass-wasting sediment transport. Four (4) depositional environments dominate regionally (an undisturbed topset apron, mudflow gully, mudflow lobe, and prodelta), centering around mudflow distribution initiated by a variety of factors (hurricanes, storms, and fluid pressure). To better understand the spatiotemporal scales of the events as well as the controlling processes, eight cores (5.8–8.0 m long) taken offshore from the South Pass (SP) and the Southwest Pass (SWP) were analyzed for gamma density, grain size, sediment fabric (X-radiography), and geochronology (²¹⁰Pb/¹³⁷Cs radionuclides). Previous work has focused on the deposition of individual passes and has been restricted to <3 m core penetration, limiting its geochronologic completeness. Building on other recent studies, within the mudflow gully and lobe cores, the homogeneous stepped profiles of ²¹⁰Pb activities and the corresponding decreased gamma density indicate the presence of gravity-driven mass failures. ²¹⁰Pb/¹³⁷Cs indicates that gully sedimentary sediment accumulation since 1953 is greater than 580 cm (sediment accumulation rate [SAR] of 12.8 cm/y) in the southwest pass site, and a lower SAR of the South Pass gully sites (2.6 cm/y). This study shows that (1) recent dated mudflow deposits are identifiable in both the SWP and SP; (2) SWP mudflows have return periods of 10.7 y, six times more frequent than at the SP (66.7 y); (3) ²¹⁰Pb inventories display higher levels in the SWP area, with the highest focusing factors in proximal/gully sedimentation, and (4) submarine landslides in both study areas remain important for sediment transport despite the differences in sediment delivery and discharge source proximity. Full article

Crop evapotranspiration (ET_C) water demands are critical decision support information for the sustainable use of water resources for optimum crop productivity. When measurements of ET_C at all locations are not feasible, the prediction of ETC and crop growth from weather and soil–water–crop management data using state-of-the-science cropping system simulations is a viable alternative. This study compared soybean (Glycine max (L.) Merr.) ET_C quantified using the eddy covariance (EC) method against simulations from two models, (i) the CSM-CROPGRO-soybean module within the Decision Support System for Agroecology Transfer (DSSAT) and (ii) CSM-CROPGRO-soybean module within the Root Zone Water Quality Model v2.0 (RZWQM) for a grower’s field in the Mississippi Delta, USA, during 2017, 2018, and 2019 growing seasons. The measured soybean grain yields during the three seasons, respectively, were 4979 kg ha⁻¹, 5157 kg ha⁻¹, and 5665 kg ha⁻¹. The DSSAT and RZWQM simulated yields deviated from the measured yields by −10.8% and 15.4% in 2017, −24.0% and 1.56% in 2018, and −6.22%, and 9.98% in 2019. Simulated daily ET_C values were less than EC estimates by 0.33 mm, 0.29 mm, and 0.23 mm for DSSAT and 0.05 mm, 0.42 mm, and 0.24 mm for RZWQM, respectively, for the three seasons. EC-quantified seasonal values of ET_C were 584 mm, 532 mm, and 566 mm, respectively, for three seasons. Similarly, simulated seasonal ET_C values were less than EC estimates by 40 mm, 31 mm, and 16 mm by DSSAT, and 7 mm, 46 mm, and 29 mm by RZWQM. The results obtained demonstrated that accuracy in the prediction of ETC varied among models and growing seasons. When the magnitude of errors in daily ET_C simulations does not deter its applications in tactical irrigation water management decisions, a higher degree of agreement between measured and simulated ET_C values at a seasonal scale is more promising for strategical irrigation water management planning decision support. Further improvement of the models for more accurate simulations of daily ET_C can help in more confident applications of these models for tactical crop-water management applications. Full article

Sediment deposition in river channels from various topographic conditions has been one of the major contributors to water quality impairment through non-point sources. Soil is one of the key components in sediment loadings, during runoff. Yazoo River Watershed (YRW) is the largest watershed in Mississippi. Topography in the watershed has been classified into two types based on land-use and slope conditions: Delta region with a slope ranging from 0% to 3% and Bluff hills with a slope exceeding 10%. YRW spans over 50,000 km²; the Soil and Water Assessment Tool (SWAT) was used to estimate soil-specific sediment loss in the watershed. Soil predominance was based on spatial coverage; a total of 14 soil types were identified, and the sediment contributed by those soils was quantified. The SWAT model was calibrated and validated for streamflow, sediment, Total Nitrogen (TN), Total Phosphorus (TP), and Crop yield for soybeans. Model performance was evaluated using the Coefficient of determination (R²), Nash and Sutcliffe Efficiency index (NSE), and Mean Absolute Percentage Error (MAPE). The performance was good for streamflow, ranging between 0.34 and 0.83, and 0.33 and 0.81, for both R² and NSE, respectively. Model performance for sediment and nutrient was low-satisfactory as R² and NSE ranged between 0.14 and 0.40, and 0.14 and 0.35, respectively. In the case of crop yield, model performance was satisfactory during calibration and good for validation with an R² of 0.56 and 0.76 and with a MAPE of 11.21% and 10.79%, respectively. Throughout YRW, soil type Smithdale predicted the highest sediment loads with 115.45 tons/ha/year. Sediment loss in agricultural fields with a soybean crop was also analyzed, where soil type Alligator predicted the highest with 8.37 tons/ha/year. Results from this study demonstrate a novel addition to the scientific community in understanding sediment loads based on soil types, which can help stakeholders in decision-making toward soil conservation and improving the environment. Full article

Optimizing irrigation water use efficiency (WUE) is critical to reduce the dependency of irrigated cotton (Gossypium spp.) production on depleting aquifers. Cropping system models can integrate and synthesize data collected through experiments in the past and simulate management changes for enhancing WUE in agriculture. This study evaluated the simulation of cotton growth and evapotranspiration (ET) in a grower’s field using the CSM-CROPGRO-cotton module within the Decision Support System for Agrotechnology Transfer (DSSAT) and APSIM (Agricultural Production Systems simulator)-OzCot during 2017–2018 growing seasons. Crop ET was quantified using the eddy covariance (EC) method. Data collected in 2017 was used in calibrating the models and in 2018 validating. Over two cropping seasons, the simulated seedling emergence, flowering, and maturity dates were varied less than a week from measured for both models. Simulated leaf area index (LAI) varied from measured with the relative root mean squared errors (RRMSE) ranging between 20.6% to 38.7%. Daily ET deviated from EC estimates with root mean square errors (RMSEs) of 1.90 mm and 2.03 mm (RRMSEs of 63.1% and 54.8%) for the DSSAT and 1.95 mm and 2.17 mm (RRMSEs of 64.7% and 58.8%) for APSIM, during 2017 and 2018, respectively. Model performance varied with growing seasons, indicating improving ET simulation processes and long-term calibrations and validations are necessary for adapting the models for decision support in optimizing WUE in cotton cropping systems. Full article

This study characterizes the spatial patterns of the overall and monthly trends in sea surface temperature (SST) and chlorophyll-a (Chl-a) of the Gulf of Mexico (GoM) to investigate the seasonal variations in oceanic climate trends. We also investigate the trends in mesoscale eddies using three parameters to identify ocean-eddy-related energetic features in their area, strength, and intensity. Multidecadal remote-sensing-based observations of monthly SST, Chl-a, and sea surface height are used to detect trends at both basin and grid scales. Prominent warming trends are found in most regions of the GoM in all months, with the largest trends in the northern GoM. Winter cooling trends are also detected along the Texas and Florida coast. The overall summer warming trend (~0.22 °C/decade) is larger than the winter trend (~0.05 °C/decade), suggesting seasonal variations of increase in SST with warming. Chl-a trends and variations are confined on the continental shelf and slope in the northern GoM. The largest increase trends are found near the Mississippi River Delta. No obvious Chl-a trend is detected in the deepwater of the GoM, consistent with previous studies. Small but significant changes are found in eddy characteristics, indicating the eddy activities might be slowly affected by climate change in the GoM. The detailed monthly trends at per-grid scale are valuable for regional resource management, environmental protection, and policy making in the GoM. Full article

This article describes the opinions and perceptions of farmers on water management tools that conserve groundwater and on alternative sources of water for irrigation. The analysis is based on a survey of producers ($N=466$) across the Lower Mississippi River Basin (LMRB) areas of Arkansas, Louisiana, Mississippi, and Missouri. Summary statistics of practice usage across the region and for each state are presented. A Poisson count model is applied to the data to identify factors that influence the number of groundwater-conserving practices employed. The number of irrigated acres, years of farming, annual income level, perception of groundwater problems, and participation in conservation programs have statistically significant association with the number of practices employed. Years of farming experience is the only factor negatively associated with the number of practices employed, while participation in conservation programs has the largest magnitude effect on that number. These results provide evidence that sponsored conservation programs increase the number of conservation practices adopted by farmers. This insight is useful for producer collectives, policy makers, and program managers to design and target of conservation programs across the LMRB. Full article

Coastal areas serve as a vital interface between the land and sea or ocean and host about 40% of the world’s population, providing significant social, economic, and ecological functions. Meanwhile, the sea-level rise caused by climate change, along with coastal erosion and accretion, alters coastal landscapes profoundly, threatening coastal sustainability. For instance, the Mississippi River Delta in Louisiana is one of the most vulnerable coastal areas. It faces severe long-term land loss that has disrupted the regional ecosystem balance during the past few decades. There is an urgent need to understand the land loss mechanism in coastal Louisiana and identify areas prone to land loss in the future. This study modeled the current and predicted the future land loss and identified natural–human variables in the Louisiana Coastal Zone (LCZ) using remote sensing and machine-learning approaches. First, we analyzed the temporal and spatial land loss patterns from 2001 to 2016 in the study area. Second, logistic regression, extreme gradient boosting (XGBoost), and random forest models with 15 human and natural variables were carried out during each five-year and the fifteen-year period to delineate the short- and long-term land loss mechanisms. Finally, we simulated the land-loss probability in 2031 using the optimal model. The results indicate that land loss patterns in different parts change through time at an overall decelerating speed. The oil and gas well density and subsidence rate were the most significant land loss drivers during 2001–2016. The simulation shows that a total area of 180 km² of land has over a 50% probability of turning to water from 2016 to 2031. This research offers valuable information for decision-makers and local communities to prepare for future land cover changes, reduce potential risks, and efficiently manage the land restoration in coastal Louisiana. Full article

The Yazoo–Mississippi Delta is one of the regions within the Lower Mississippi River Basin where substantial irrigation development and consequent groundwater depletion have occurred over the past three decades. To describe this irrigation development, a study was conducted to analyze existing geospatial datasets and to synthesize the results with those of past government surveys. The effort produced a quantitative review characterizing three aspects of irrigation development from 1991 to 2020. First, the expansion of irrigated area was tracked in terms of absolute area and in terms of fraction relative to total land or cropland area. Second, trends in irrigated land cover were traced in terms of irrigated crop mix, irrigated fractions of main crops, and comparisons with non-irrigated land. Third, changes in irrigation systems were examined in terms of water sources, energy sources, and application methods. Original findings of this study for the end of 2020 included moderate positive spatial autocorrelation in the density of irrigated areas; a higher irrigated crop preference for soybean and rice over cotton and corn in highly hydric soils; and 91% and 3% of permitted areas studied being respectively under groundwater withdrawal permits exclusively and under surface water diversion permits exclusively. By compiling such information, this paper can serve as a convenient reference on the recent history and status of irrigation development in the Yazoo–Mississippi Delta. Full article

The State of Louisiana is leading an integrated wetland restoration and flood risk reduction program in the Mississippi River Delta. East of New Orleans, Biloxi Marsh, a ~1700 km² peninsula jutting 60 km north toward the State of Mississippi is one of few Delta wetland tracts well positioned to dissipate hurricane surge and waves threatening the city’s newly rebuilt hurricane flood defenses. Both its location on the eastern margin of the Delta, and its genesis as the geologic core of the shallow water St. Bernard/Terre aux Boeuf sub-delta, which was the primary Mississippi outlet for almost 2000 years, make Biloxi Marsh attractive for restoration, now that the Mississippi River Gulf Outlet deep-draft ship channel has been dammed, and 50 years of impacts from construction and operation have abated. Now, the cascade of ecosystem damage it caused can be reversed or offset by restoration projects that leverage natural recovery and increased access to suspended sediment from the Mississippi River. Biloxi Marsh is (1) geologically stable, (2) benefiting from increased input of river sediment, and (3) could be restored to sustainability earlier and for a longer period than most of the rest of the submerging Mississippi Delta. The focus of this review is on the Biloxi Marsh, but it also provides a template for regional studies, including analysis of 2D and 3D seismic and other energy industry data to explore why existing marshes that look similar on the ground or from the air may respond to restoration measures with different levels of success. Properties of inherent durability and resilience can be exploited in restoration project selection, sequencing and expenditure. Issues encountered and investigative methods applied in the Biloxi Marsh are likely to resonate across initiatives now contemplated to sustain valuable river deltas worldwide. Full article

Introducing alternative cultivars with enhanced water use efficiencies can help alleviate pressure on groundwater for crop irrigations in Mississippi (MS) Delta. A two-year field study was conducted in 2019–2020 to compare the water use efficiencies (WUE) of recently released and pre-released soybean {Glycine max (L.) Merr.} cultivars in maturity group (MG) III (‘P37A78’, ‘LG03-4561-14’), IV (‘Dyna-gro 4516x’, ‘DS25-1, DT97-4290’), and V (‘S12-1362’, ‘S14-16306’) in the MS Delta. The experimental design was a split-plot with cultivar as the first factor and the second factor was water variant irrigation (IR) and no irrigation (RF, rainfed), replicated three times. The MG IV cultivar Dyna-gro 4516x recorded the highest grain yield and WUE: grain yields were 4.58 Mg ha⁻¹ and 3.89 Mg ha⁻¹ under IR and RF, respectively in 2019, and 4.74 Mg ha⁻¹ and 4.35 Mg ha⁻¹ in 2020. The WUE were 7.2 and 6.9 kg ha⁻¹ mm⁻¹, respectively, in 2019 under IR and RF, and 13.4 and 16.9 kg ha⁻¹ mm⁻¹ in 2020. The data reveals that ‘Dyna-gro 4516x’ (MG IV), ‘LG03-4561-14’ (MG III), and ‘P37A78’ (MG III) are best adapted to the early soybean production system (ESPS) in MS Delta region for sustainable production for conserving water resources. Full article

Global elevation datasets such as the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) are the best available terrain data in many parts of the world. Consequently, SRTM is widely used for understanding the risk of coastal inundation due to climate change-induced sea level rise. However, SRTM elevations are prone to error, giving rise to uncertainty in the quality of the inundation projections. This study investigated the error propagation model for the Shatt al-Arab River region (SARR) to understand the impact of DEM error on an inundation model in this sensitive, low-lying coastal region. The analysis involved three stages. First, a multiple regression model, parameterized from the Mississippi River delta region, was used to generate an expected DEM error surface for the SARR. This surface was subtracted from the SRTM DEM for the SARR to adjust it. Second, residuals from this model were simulated for the SARR. Modelled residuals were subtracted from the adjusted SRTM to produce 50 DEM realizations capturing potential elevation variation. Third, the DEM realizations were each used in a geospatial “bathtub” inundation model to estimate flooding area in the region given 1 m of sea level rise. Across all realizations, the area predicted to flood covered about 50% of the entire region, while predicted flooding using the raw SRTM covered only about 28%, indicating substantial underprediction of the affected area when error was not accounted for. This study can be an applicable approach within such environments worldwide. Full article

The United States is one of the top rice exporters in the world, but warming temperatures and other climate trends may affect grain yield and quality. The use of crop models as decision support tools for a climate impact assessment would be beneficial, but suitability of models for representative growing conditions need to be verified. Therefore, the ability of CERES-Rice and ORYZA crop models to predict rice yield and growing season duration in the Mississippi Delta region was assessed for two widely-grown varieties using a 34-year database. CERES-Rice simulated growth duration more accurately than ORYZA as a result of the latter model’s use of lower cardinal temperatures. An increase in base and optimal temperatures improved ORYZA accuracy and reduced systematic error (e.g., correlation coefficient increased by 0.03–0.27 and root mean square error decreased by 0.3–1.9 days). Both models subsequently showed acceptable skill in reproducing the growing season duration and had similar performance for predicting rice yield for most locations and years. CERES-Rice predictions were more sensitive to years with lower solar radiation, but neither model accurately mimicked negative impacts of very warm or cold temperatures. Both models were shown to reproduce 50% percentile yield trends of more than 100 varieties in the region for the 34-year period when calibrated with two representative cultivars. These results suggest that both models are suitable for exploring the general response of multiple rice cultivars in the Mississippi Delta region for decision support studies involving the current climate. The response of rice growth and development to cold injury and high temperature stress, and variation in cultivar sensitivity, should be further developed and tested for improved decision making tools. Full article