MODELING THE HYDROLOGY AND NITRATE LOADING OF SIX COASTAL PLAIN WATERSHEDS WITH DIFFERING LAND USE, TOPOGRAPHY, AND CHANNEL NETWORK CHARACTERISTICS

Rapid changes in land use and land cover pattern have exerted an irreversible change on different natural resources, and water resources in particular, throughout the world. Khambhat City, located in the Western coastal plain of India, is witnessing a rapid expansion of human settlements, as well as agricultural and industrial activities. This development has led to a massive increase in groundwater use (the only source of potable water in the area), brought about significant changes to land management practices (e.g., increased fertilizer use), and resulted in much greater amounts of household and industrial waste. To better understand the impacts of this development on the local groundwater, this study investigated the relationship between groundwater quality change and land use change over the 2001–2011 period; a time during which rapid development occurred. Water quality measurements from 66 groundwater sampling wells were analyzed for the years 2001 and 2011, and two water quality indicators (NO3− and Cl− concentration) were mapped and correlated against the changes in land use. Our results indicated that the groundwater quality has deteriorated, with both nitrate (NO3−) and chloride (Cl−) levels being elevated significantly. Contour maps of NO3− and Cl− were compared with the land use maps for 2001 and 2011, respectively, to identify the impact of land use changes on water quality. Zonal statistics suggested that conversion from barren land to agricultural land had the most significant negative impact on water quality, demonstrating a positive correlation with accelerated levels of both NO3− and Cl−. The amount of influence of the different land use categories on NO3− increase was, in order, agriculture > bare land > lake > marshland > built-up > river. Whereas, for higher concentration of Cl− in the groundwater, the order of influence of the different land use categories was marshland > built-up > agriculture > bare land > lake > river. This study will help policy planners and decision makers to understand the trend of groundwater development and hence to take timely mitigation measures for its sustainable management.

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Evaluating SWAT Model Performance for Runoff, Percolation, and Sediment Loss Estimation in Low-Gradient Watersheds of the Atlantic Coastal Plain

Hydrology ◽

10.3390/hydrology7020021 ◽

2020 ◽

Vol 7 (2) ◽

pp. 21 ◽

Cited By ~ 2

Author(s):

Kerry L. Mapes ◽

Narcisa G. Pricope

Keyword(s):

Land Use ◽

Coastal Plain ◽

The United States ◽

Assessment Tools ◽

Shallow Aquifer ◽

Reanalysis Dataset ◽

Hydrologic Processes ◽

Sediment Loss ◽

Model Predictions ◽

Hydrologic Regimes

With predicted alterations in climate and land use, managing water resources is of the utmost importance, especially in areas such as the United States (U.S.) Coastal Plain where extensive connections exist between surface and groundwater systems. These changes create the need for models that effectively assess shifting hydrologic regimes and, in that context, we examine the performance of the Soil and Water Assessment Tool (SWAT) in a low-gradient, shallow-aquifer-dominated watershed of the U.S. Coastal Plain using a gridded reanalysis dataset. We evaluate accuracy, uncertainty, and parameter sensitivity by comparing observed and predicted streamflow at two gaging stations and assess model predictions for yearly average runoff (SURQ), percolation (PERC), and sediment loss (SYLD). Streamflow performance was acceptable during calibration (NSE = 0.67 and 0.60) and very good during validation (NSE = 0.84 and 0.91). Model predictions for SURQ, PERC, and SYLD coincided with expected ranges for this region. Parameters related to shallow aquifer properties or groundwater were highly sensitive, which indicates the need for continued study of spatial and temporal variability within the sub-surface components of these hydrologic systems. Our findings highlight the applicability of this reanalysis dataset for modeling hydrologic processes in poorly gaged watersheds and adds to the body of research that seeks to develop effective assessment tools for shallow-aquifer-dominated systems. Our methodology can effectively assist watershed managers in establishing baseline rates of hydrologic processes as is crucial with future predicted shifts in hydrologic regimes due to land-use alteration and climate change.

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