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Climate change could add a variety of uncertainties to hydrological processes and water resources. Very limited efforts have been devoted to applying the US-EPA (Environmental Protection Agency)'s Hydrologic and Water Quality System (HAWQS) model for predicting climate change impacts on hydrological processes at the basin scale. Here, we applied the model to project the next 50 years' (from 2021 to 2070) hydrological processes at the Yazoo River basin in Mississippi, USA. Simulations showed that over the next 50 years, there are no significant trends in monthly precipitation, ET, runoff and discharge; only 2% of the annual precipitation percolated into the deep aquifer; and dry seasons become dryer and wet seasons become wetter. These findings provide very useful information to stakeholders for water resource management. Our study further suggests that the HAWQS model is a user-friendly and time-saving tool for basin-scale hydrological modelling. [ABSTRACT FROM AUTHOR]

Classification of remotely sensed imagery for reliable land use and land cover (LULC) remains a challenge in areas where spectrally similar LULC features occur. For example, bare soils of harvested crop fields in agricultural watersheds exhibit spectral characteristics similar to high-intensity developed regions and impede an accurate classification. The goal of this study is to improve the accuracy of LULC classification of satellite imagery for the Big Sunflower River Watershed, Mississippi using ancillary data, multiple classification methods, and a post-classification correction (PCC). To determine the best approach, the methodology was applied to Landsat 8 Operational Land Imager (OLI) imagery during the growing season and post-harvest. Imagery for the growing season was acquired on 25 August 2015, and post-harvest was acquired on 7 January 2018. Three classification methods were applied: maximum likelihood (ML), support vector machine (SVM), and random forest (RF). LULC imagery was classified as open water, woody wetlands, harvested crop, rangeland, cultivated crop, high-intensity developed, and mid-low intensity developed areas. Ancillary data such as normalized difference vegetation index (NDVI), thematic maps of urban areas, river networks, transportation networks, high-resolution National Agriculture Imagery Program (NAIP) imagery, Google Earth time-series data, and phenology were used to determine the training dataset. Initially none of the three classification methods performed adequately. Hence, a post-classification correction (PCC) was implemented by masking and applying a majority filter using thematic maps of urban areas. Once PCC was implemented, the accuracies from each of the classification methods increased significantly with the SVM classification method performing best in both the growing season and post-harvest with an overall classification accuracy of 93.5% with a Kappa statistic of 0.88 in the post-harvest imagery and an overall classification accuracy of 84% with a Kappa statistic of 0.789 in the imagery from the growing season. It was found that SVM was the best classification method while PCC is an effective strategy to implement when dealing with spectrally similar LULC features. The use of SVM together with PCC increased the reliability of the information extracted. Strategies from this study can help to evaluate the LULC in agricultural and other watersheds. [ABSTRACT FROM AUTHOR]

Impact of Best Management Practices (BMPs) can be evaluated using hydrologic and water quality models. Although numerous models with diverse function, capability and degree of complexity are available, suitable model for each watershed should be determined. The Soil and Water Assessment Tool (SWAT) and Hydrologic Simulation Program-Fortran (HSPF) models were applied to the Big Sunflower River Watershed (BSRW) and their performances in simulating hydrology and water quality were evaluated. Both the models simulated streamflow, sediment, and nutrient concentrations with model efficiency greater than 50%. The SWAT model simulated streamflow and sediment concentration more accurately than HSPF whereas, for total nitrogen (TN) and total phosphorous (TP) concentrations, the HSPF model simulated equally good as SWAT. Models evaluated effect of two BMPs: vegetative filter strip (VFS) and tailwater recovery pond (TRP) in reduction of streamflow, sediment, TN, and TP concentrations. Average reduction of streamflow due to the implementation of both BMPs in SWAT and HSPF were less than 1% but average reduction of sediment concentration by VFS in SWAT was 26% and in HSPF was 38%. Average reduction of sediment concentration by TRP in SWAT and HSPF were 21% and 30% respectively. VFS reduced TN concentration by 51% in SWAT and by 25% in HSPF, while average reduction of TN concentration by TRP in SWAT and HSPF were 7% and 2% respectively. Similarly, average reduction of TP concentration by VFS in SWAT and HSPF were 56% and 31% respectively and that by TRP in SWAT and HSPF were 2% and 1% respectively. Differences in simulation results based on application of two models were mainly attributed by the modelling mechanism and equations used. The results from this study will provide a broader idea to other modellers and end-users in selecting appropriate model according to their need and type of watershed. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) provides important information for hydrological studies, including estimating plant water requirements which can be derived from remote sensing data or simulated using hydrological models. In this study, ET derived from the Moderate Resolution Imaging Spectrometer (MODIS) was compared with ET simulated by the calibrated and validated Soil and Water Assessment Tool (SWAT) model for the Big Sunflower River watershed (BSRW) in Mississippi. The comparisons were made based on 8-day, 1-month, seasonal, and annual timescales. The coefficients of variation (COVs) for the 8-day, 1-month, seasonal, and annual ET simulated by SWAT were 0.42, 0.40, 0.32, and 0.04, respectively, whereas the COVs for the ET derived from MODIS were 0.06, 0.12, 0.08, and 0.01 for the respective time scales. Lower COVs for the ET derived from MODIS indicated lower sensitivity to crop growth in the field. SWAT-simulated ET was the highest during crop growing season and lowest during dormant season, but MODIS-derived ET did not vary considerably according to crop growing or harvesting seasons. As MODIS-derived ET accounts for only climatic conditions and vegetation cover, SWAT-simulated ET is recommended for the short-term estimation of crop water requirements because it accounts for climatic, land use, soil, and slope conditions. [ABSTRACT FROM AUTHOR]

Over the last several decades, increased groundwater usage by agriculture with a consequence of groundwater resource depletion has motivated the discussion of sustainability of groundwater resource. In this study, to investigate the impacts of agricultural best management practices (BMPs) on groundwater level, two kinds of conservation practices and five scenarios of tail water recovery pond and crop rotation were simulated by various groundwater recharge and pumping plans in Soil and Water Assessment Tool (SWAT) and MODFLOW models in an agriculture watershed in Mississippi, U.S.. The calibrated and validated ground water model indicated coefficient of determination (R2) of 0.81 and Nash–Sutcliffe model efficiency coefficient (NSE) of 0.79 respectively. The results from this study showed that the groundwater recharge changed with irrigation plans and surface hydrological impact of management practices. In addition, it determined that tail water recovery pond could help mitigate groundwater depletion. The groundwater recharge due to continuous corn crop scenario was 7% higher in average than that of the continuous soybean. Non-growing season groundwater recharge may be critical for groundwater recovery. The average groundwater level was increased continuous corn scenario by 15%, continuous soybean by 13%, and corn-soybean by 14% as compare to the baseline scenario with rice planted. Results of this study can be helpful for planning on how various BMPs impact on groundwater. [ABSTRACT FROM AUTHOR]

The effect of cover crop (CC) on soil water balance and agricultural production is closely related to rainfall amount and distribution in rainfed cropping systems. This study used the root zone water quality model, RZWQM2, calibrated and validated with 4‐yr field measurements to predict the effect of planting a winter wheat (Triticum aestivum L.) CC in a no‐till rainfed corn (Zea mays L.)–soybean (Glycine max L.) rotation on soil water balance, crop yield, and grain water‐use efficiency (WUE) in northeast Mississippi. Seasonal rainfall for 80 consecutive years (1938–2017) was classified as 'wet,' 'normal,' and 'dry' years using frequency analysis, and the data sets matched chronologically to wheat, corn, and soybean growth periods were used as an input parameter in RZWQM2 simulations. During autumn and spring (early October to early April), the CC reduced deep drainage by 69 (11%), 53 (15%), and 51 mm (21%) in wet, normal, and dry years, respectively. Averaged across 40 yr, the CC decreased surface evaporation by 64 (32%) and 38 mm (24%) for corn and soybean growth periods, respectively. Wheat CC also improved soil water storage in early crop growth period during April–June in any of the three rainfall patterns. Regardless of rainfall patterns, the increase in WUE can be attributed to a decrease in evapotranspiration during cash crop period without sacrificing cash crop yield in the CC system. Introducing CC into cropping systems is beneficial to reduce annual deep drainage and evaporation while maintaining higher crop yields under different rainfall patterns. [ABSTRACT FROM AUTHOR]

• Application of US-EPA's HAWQS model in the Yazoo River basin, Mississippi. • Forest land reduces evapotranspiration (ET) and increases water yield (WYLD) over a long-range. • No temporal trend of ET under the past and future 50 years climate conditions. • Very significant increasing trend of ET was observed in recent 20 years from 1997 to 2017. • Findings could change the traditional views on how forests and crops affect ET and WYLD. Forest lands are sometimes thought to increase evapotranspiration (ET) and decrease water yield (WYLD) more than those of croplands, especially in the semi-arid subtropical and tropical regions. Using the US-EPA (Environmental Protection Agency)'s Hydrologic and Water Quality System (HAWQS) model along with Mann Kendall statistics (τ) and Kolmogorov-Smirnov test, I compared ET and WLYD between a cropland and a forest land in a humid subtropical region – Yazoo River basin (YRB), Mississippi, USA – under the changing climate. Results show that no temporal trend of ET was found over the past 50-year (1966 to 2015) and future 50-year (2021 to 2070) climate conditions, but a significant increasing trend (τ = 0.403, p < 0.01) of ET was observed in the recent 20 years (1997 to 2017) in both the crop and forest lands. The simulation further reveals that the annual average air temperature over the past and future 50 years was about 1 °C cooler in the forest land than in the cropland. During the past 50 years, there was 10.8% more water lost from ET in the cropland (656 mm/year) than in the forest land (592 mm/year), while there was 17.3% less WYLD in the cropland (711 mm/year) than in the forest land (834 mm/year). Similar results were also obtained for the future 50 years, i.e., there were 42.0% more ET and 20.7% less WYLD in the cropland than in the forest land. Results show that over a long-range, the forest land reduced ET and increased WYLD as compared to those of the cropland in the YRB (a humid subtropical region). These new insights change the traditional views on how forests and crops affect ET and WYLD in the humid subtropical regions around the world and provide useful information to farmers and foresters for effective water resource management [ABSTRACT FROM AUTHOR]

Summary: Low flow selections are essential to water resource management, water supply planning, and watershed ecosystem restoration. In this study, a new approach, namely the frequent-low (FL) approach (or frequent-low index), was developed based on the minimum frequent-low flow or level used in minimum flows and/or levels program in northeast Florida, USA. This FL approach was then compared to the conventional 7Q10 approach for low flow selections prior to its applications, using the USGS flow data from the freshwater environment (Big Sunflower River, Mississippi) as well as from the estuarine environment (St. Johns River, Florida). Unlike the FL approach that is associated with the biological and ecological impacts, the 7Q10 approach could lead to the selections of extremely low flows (e.g., near-zero flows) that may hinder its use for establishing criteria to prevent streams from significant harm to biological and ecological communities. Additionally, the 7Q10 approach could not be used when the period of data records is less than 10years by definition while this may not the case for the FL approach. Results from both approaches showed that the low flows from the Big Sunflower River and the St. Johns River decreased as time elapsed, demonstrating that these two rivers have become drier during the last several decades with a potential of salted water intrusion to the St. Johns River. Results from the FL approach further revealed that the recurrence probability of low flow increased while the recurrence interval of low flow decreased as time elapsed in both rivers, indicating that low flows occurred more frequent in these rivers as time elapsed. This report suggests that the FL approach, developed in this study, is a useful alternative for low flow selections in addition to the 7Q10 approach. [ABSTRACT FROM AUTHOR]

Climate-driven hydrological models rarely incorporate intermittent rivers and ephemeral streams (IRES) due to monitoring difficulties and their perceived minor effect on river networks. Worldwide, IRES represent approximately 50% of river networks and up to 60% of annual flow and are recognized as conduits and processors of organic matter (OM). Climate induced changes in precipitation and discharge (Q) may impact OM fluxes from IRES. We assessed storm-driven source and flux of total suspended solids (TSS) and OM from small IRES in Mississippi, USA. We used linear Pearson correlations to evaluate relationships between water and storm characteristics (e.g., discharge). Stepwise regression was used to predict change in flux. Dissolved OM was derived from saturated flow through soil whereas particulate OM was derived from channel extension during storms. A power log relationship between Q and materials flux indicated that Q was the driver for flux. A 5% increase in Q within IRES may result in flux increase of 2% TSS and 1.7–2.8% OM. Climate change projections of increased storm intensity over a shorter water year will increase channel extension and soil water transfer resulting in higher material flux to downstream reaches. Climate-driven hydrological models of OM flux should incorporate IRES. [ABSTRACT FROM AUTHOR]

Many agricultural production regions in the world have been experiencing groundwater resource depletion, which threatens water and food security if mitigation practices are not developed and implemented. To understand how changing land use and irrigation schedule impact groundwater, a coupled SWAT-MODFLOW model was applied to determine groundwater depletion mitigation strategy in a humid region, the Big Sunflower River Watershed (BSRW) in Mississippi, USA. It was found that converting grasslands to forests contributed to reducing groundwater declining. Simulated results indicated that the watershed lost 749, 586, and 381 mm yr−1 of water through surface runoff in the wet, normal and dry years, respectively. The amount of groundwater that moved into the vadose zone to help satisfy crop water demand ranged from 700 to 750 mm yr−1. Precipitation increased the groundwater recharge during the rainy season from fall to spring. Annual recharge rate was only 34–50 mm. Groundwater level dropped 0.2–0.5 m in crop irrigation seasons (May to August). Land use dataset showed 81 % of the area is cropland, with soybean, corn, rice, and cotton accounting for 64 % of the total cropland area in BSRW. The planted area of corn and soybean significantly increased while the area of cotton area was tremendously reduced. Corn, soybean, and rice consumed approximately 96 % of the total amount of groundwater irrigation. This study indicated that irrigation scheduling based on plant water demand could save 47 % of groundwater currently used by conventional irrigation. The improved irrigation schedule could reduce groundwater decline by 0.01–2.05 m across the watershed, and mitigate the declines by 1.35–2.05 m in the depression cone in the central east part of the watershed. The results can assist with planning land and water use and developing sustainable groundwater management practices focused on locations of high groundwater withdrawals in other regions around the world. • Coupled SWAT-MODFLOW model determined groundwater depletion mitigation strategy. • Land use change from grasslands to forests contributed to reduce groundwater level declining. • Groundwater level dropped 0.2–0.5 m in crop irrigation seasons (May to August). • Annual groundwater recharge was 34–50 mm during the rainy season from fall to spring. • Irrigation scheduling based on plant water demand saved 47 % groundwater, reduced groundwater level decline by 0.01–2.05 m. [ABSTRACT FROM AUTHOR]

Assessment of surface water quality in the Mississippi Delta is essential to quantify the eutrophication of the Gulf of Mexico. This study estimated the characteristics and variations of surface water quality at three study sites in the Big Sunflower River Watershed (BSRW) within the Mississippi Delta using Kruskal-Wallis, Dunn, Mann-Kendall, and Pettitt tests. In general, contents of some water quality constituents such as nitrate-nitrogen (NO3 − N) and total phosphorus (TP) in the BSRW varied from site to site each year, whereas variations of other constituents such as pH and dissolved oxygen (DO) each year were basically not significant. The highest median concentrations were found in spring for NO3 − N and total nitrogen (TN); in summer for specific conductance (SC), Na, and Cl; and in winter for DO. Mann-Kendall trend analysis revealed that there was an increasing annual trend at Leland but a decreasing annual trend at Merigold for NO3 − N concentrations even though such changes were very small, whereas there was no annual trend for TP at any of the three study sites. Pettitt's test further identified that the NO3 − N concentrations had an abrupt increase in February 2009 at the median value of 0.44 mg L−1 in Leland and an abrupt decrease in June 2012 at the median value of 3.65 mg L−1 in Merigold. A very good linear correlation existed between total dissolved solid (TDS) and magnesium (Mg) in the BSRW, which could be used to estimate TDS from Mg concentrations for this watershed when the data for TDS are absent. [ABSTRACT FROM AUTHOR]

• A GIS method to simulate LULC change based on past LULC data. • Increased cropland resulted in higher sediment concentration, TN, and TP yields. • Different crop species contributed on TN, and TP yields. • Agricultural LULC change impacts on downstream stream quality. Land use and land cover (LULC) change impacts on hydrology and water quality are of critical importance in regions where water quality is degraded. One such location is the Mississippi Delta in the United States, where widespread agriculture across the landscape is a major contributing source to sediment- and nutrient-heavy runoff. To address how the landscape has changed in the recent past and consider how it may continue to change in the future, we analyzed the temporal and spatial variability of the LULC changes (e.g. forest, cropland, corn and soybean) in the Big Sunflower River Watershed. We applied these LULC changes in the Soil and Water Assessment Tool (SWAT) model to demonstrate the impacts on stream discharge, total suspended sediments (TSS) concentrations, total nitrogen (TN), and total phosphorus (TP) yields. Model performance was considered satisfactory to good (R2 = 0.46–0.88, NSE = 0.34–0.64) for all simulated water quantity and water quality parameters. TSS concentrations increased 1.9%, while TN and TP yields increased by 12.7%, and 10.2%, respectively as the area of the cropland increased. Stream discharge was unchanged. Moreover, TN yield increased as the percentage of land occupied by cornfields increased while TP yield increased as the percentage of land occupied by soybean increased, due to differences in crop management practices such as fertilization and tillage. [ABSTRACT FROM AUTHOR]

Knowledge of soybean yield constraints under rainfed conditions on major soil types in East Central Mississippi would assist growers in the region to effectively utilize the benefits of water/irrigation management. The objectives of this study were to use the Agricultural Policy/Environmental eXtender (APEX) agro-ecosystem model to simulate rainfed soybean grain yield (GY) for nine major soils during 14 years (2002–2015) and then to evaluate selected model inputs/outputs in relation to irrigation management that may decrease difference in simulated GY among the different soils. Values for GY ranged broadly from 2.24 to 6.14 Mg ha −1 across soils and years, giving a maximum yield difference of 3.90 Mg ha −1 . For the average GY of nine soils, the range was from 3.52 to 5.42 Mg ha −1 over 14 years. Averaged across 14 years, GY ranged from 3.66 to 4.90 Mg ha −1 across the nine soils and was affected by difference in soil texture (clay and sand percentages) and soil available water content (AWC). Simulations revealed relatively high water stress during the R4, R5 and R6 stages of plant development (early- to mid-fruit development), suggesting great potential to enhance soybean yield if some irrigation is provided during these critical water stress periods; whereas, the potential was accordingly less in the normal and wet years. Results indicated installing irrigation on Griffith, Sumter or Demopolis soils would have a large impact through increased crop productivity and yield stability. [ABSTRACT FROM AUTHOR]

• Generated seasonal Land use and land cover (LULC) change data layers. • Performed accuracy assessment of those data layers. • Simulated the LULC data layers in the Soil and Water Assessment Tool (SWAT) model. • Analyzed the effects of LULC variation on hydrology and water quality. Land use and land cover (LULC) change is critical to hydrologic study as it affects surface runoff, sediment yield, and nutrient load from watersheds. Change in LULC is a continuous process in agricultural watersheds as per the growing and harvesting seasons. In this study, monthly LULC data layers were generated for the Big Sunflower River Watershed (BSRW), Mississippi by classifying cloud free Landsat images from 2014 to 2018 and combining them according to the season in order to obtain dominant LULC data layers for spring, summer, and fall. About 60 % of the total land area in summer was cultivated land, whereas only 20 and 5 % of the total land area were cultivated land during fall and spring, respectively. The rest of the total land area was constantly covered with urban, forest, and water for the three seasons. The overall accuracy and kappa coefficient ranging from of 87 % to 92 % and 0.8 to 0.90 was obtained during accuracy assessment of the seasonal LULC data layers. This suggested that the seasonal data layers can reasonably be used in the Soil and Water Assessment Tool (SWAT) to analyze the effects of LULC data variation on hydrology and water quality of BSRW. SWAT was calibrated and validated for streamflow, sediment yield, and nutrient concentration using the summer LULC data layer and those parameters were applied to the models using the spring and fall LULC data layers. SWAT output for runoff, sediment yield, and nutrient load was found to be very sensitive to the change in LULC data layers. The average amount of runoff and sediment yield was higher during the summer while total nitrogen and total phosphorous yields were higher during the fall and spring, respectively. Agricultural operations are usually conducted during the summer and fields are mostly barren during the spring and fall. The use of seasonal LULC data layers is very beneficial to the scientific community as they can better explain the seasonal variation in hydrology and water quality as compared to the annual cropland data layer that is available for a single season of a year. [ABSTRACT FROM AUTHOR]

This research was conducted to develop relationships among evapotranspiration (ET), percolation (PERC), groundwater discharge to the stream (GWQ), and water table fluctuations through a modeling approach. The Soil and Water Assessment Tool (SWAT) hydrologic and crop models were applied in the Big Sunflower River watershed (BSRW; 7660 km(2) ) within the Yazoo River Basin of the Lower Mississippi River alluvial plain. Results of this study showed good to very good model performances with the coefficient of determination (R(2) ) and Nash-Sutcliffe efficiency (NSE) index from 0.4 to 0.9, respectively, during both hydrologic and crop model calibration and validation. An empirical relationship between ET, PERC, GWQ, and water table fluctuations was able to predict 64% of the water table variation of the alluvial plain in this study. Thematic maps were developed to identify areas with overuse of groundwater, which can help watershed managers to develop water resource programs., (© 2013, National Ground Water Association.)

Elevated phosphorus (P) in surface waters can cause eutrophication of aquatic ecosystems and can impair water for drinking, industry, agriculture, and recreation. Currently, no effort has been devoted to estimating real-time variation and load of total P (TP) in surface waters due to the lack of suitable and/or cost-effective wireless sensors. However, when considering human health, drinking water supply, and rapidly developing events such as algal blooms, the availability of timely P information is very critical. In this study, we developed a new approach in the form of a dynamic data driven application system (DDDAS) for monitoring the real-time variation and load of TP in surface water. This DDDAS consisted of the following three major components: (1) a User Control that interacts with Schedule Run to implement the DDDAS with starting and ending times; (2) a Schedule Run that activates the Hydstra model; and (3) a Hydstra model that downloads the real-time data from a US Geological Survey (USGS) website that is updated every 15 min with data from USGS monitoring stations, predicts real-time variation and load of TP, graphs the variables in real-time on a computer screen, and sends email alerts when the TP exceeds a certain value. The DDDAS was applied to monitor real-time variation and load of TP for 30 days in Deer Creek, a stream located east of Leland, Mississippi, USA. Results showed that the TP concentrations in the stream ranged from 0.24 to 0.48 mg L(-1) with an average of 0.30 mg L(-1) for a 30-day monitoring period, whereas the cumulative load of TP from the stream was about 2.8 kg for the same monitoring period. Our study suggests that the DDDAS developed in this study was useful for estimating the real-time variation and load of TP in surface water ecosystems., (Published by Elsevier Ltd.)