**1. Introduction**

The Lower Rio Grande Valley (LRGV) region has undergone sudden hydrologic change due to urbanization. This abrupt change has produced a decline in water quality in the primary waterways of the region. The Laguna Madre is an estuarine wetland system along the Gulf of Mexico that receives freshwater from the LRGV [1]. This watershed is known for its recreational activities and is currently threatened by the inflows of main drainage pathways that carry significant levels of contaminants. According to the Texas Commission on Environmental Quality (TCEQ) 2020 Integrated Report [2], two water segments from the Lower Laguna Madre are considered impaired due to high levels of bacteria and low dissolved oxygen. The watershed is comprised of three waterways, Hidalgo/Willacy Main Drain (HWMD), Raymondville Drain (RVD), and International

Ernest, A.; Oubeidillah, A.; Johnstone, J.; Chavez, I.R.S.; Fuller, C. Development of a Cyberinfrastructure for Assessment of the Lower Rio Grande Valley North and Central Watersheds Characteristics. *Sustainability* **2021**, *13*, 11186. https://doi.org/10.3390/ su132011186

**Citation:** Navarro, L.; Mahmoud, A.;

Academic Editors: Julian Scott Yeomans and Mariia Kozlova

Received: 25 July 2021 Accepted: 26 September 2021 Published: 11 October 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Boundary & Water Commission North Floodway (IBWCNF), that provide freshwater inflows to the Lower Laguna Madre. Prior to this study, these waterways had not been characterized. Watershed characterization can enable proper identification of potential sources of pollution to help reduce water impairments to the Laguna Madre and preserve the ecosystem.

One of the emerging tools for watershed characterization is cyberinfrastructure that can assist in both data collection and decision-making processes within the watershed. Cyberinfrastructure supports the process of accessing data via an extensive network and provides updated water quality data for further research. The introduction of a cyberinfrastructure can provide an efficient data collection to well demonstrate the watershed characteristics. In one study, cyberinfrastructure not only utilized widespread data but also allowed researchers to analyze large amounts of data over time at different locations [3–5]. This platform offers a rapid generation of new relationships between wide inventories of data. Cyberinfrastructure secures data and delivers interpreted information via a sequence of web services and portals in forms that are universally coherent by distinct stakeholders [6]. Further, it serves as the center for a variety of data from distinct sources, such as non-point and point source and watershed delineation characteristics. Cyberinfrastructure and the watershed delineation are crucial for the watershed characterization since together they will help identify sources of pollution data within the drainage area.

An ample watershed delineation is key for a successful watershed characterization. A watershed delineation is developed by using elevation data and computing several elevation-based files that represent the overall drainage area as well as the hydrological characteristics of a watershed [7]. Each watershed can be divided into sub-watersheds to produce a more detailed drainage structure. The Geographical Information systems (GIS) platform has facilitated the development of hydrological analysis, such as drainage areas based on elevation data. In 2010, a watershed GIS-based applications study performed a hydrological analysis which showed positive outcomes regarding GIS-applications for watershed management and water quality by providing a full overview of watershed characteristics, such as land cover [8]. Hydraulic and hydrological modelling as well as water resource management commonly require investigation of landscape and hydrological features, such as terrain slope, drainage networks, drainage divides, and catchment boundaries [9]. Additionally, high resolution in data resources is important to obtain accurate results in watershed drainage areas [10]. When the land slope is very flat and has few contours, it is challenging for the acquisition of topographic maps. Light Detection and Ranging (LIDAR) is a high-resolution digital elevation model (DEM) that is an ideal source for the type of topography characterized in low elevation areas [11]. Although the terrain in the LRGV is flat, the complex hydrologic features make the process difficult and challenging with even high-resolution DEM. Hence, a previous study focused on enhancing streamlines and watershed boundaries derived from a high-resolution DEM for future hydrologic modeling and flood forecasting [12]. To determine accurate stream networks, an effective method of eliminating pits or depressions is the stream burning algorithm. This algorithm often identifies river channels or lakes that are not recorded in the DEM, avoiding serious errors in the streaming [3,4]. A stream-burning algorithm can enhance the replication of streams' positions by using raster representation of a vector stream network to trench known hydrological features into a DEM, resulting in a comprehensive watershed delineation [4,13,14]. In addition, delineation of watersheds will not only serve to determine drainage boundaries but to distinguish existing sources of nonpoint sources (NPS) and point sources (PS) pollution.

Part of watershed characterization is to identify potential sources of pollution within the watershed. Pollutant sources have been divided into two different classifications: NPS and PS; with this distinction, it becomes easier to study, analyze, understand, and propose actions to mitigate the pollutant load. NPS pollutants are difficult to identify because they cannot be tracked and usually come from several land uses. The major contributor of NPS pollution is stormwater runoff originated by rainfall [15] and other forms of water

flow through several different land uses. They ultimately discharge to lakes, canals, and coastal waters. This runoff carries significant levels of pollution caused by fertilizers, oil, grease, sediments, bacteria, and nutrients [16]. NPS pollutants contained a significant amount of nutrients, such as nitrogen and phosphorus [17]. There has been increasing emphasis on tackling NPS pollution from agricultural land for the presence of high nutrient contamination [18]. Currently, urbanization has led to increased water transfers from agriculture to urban uses [1,19]. These changes are altering the nature, location, and scope of wastewater loadings into the river. Urban runoff has caused negative results on water quality due to high bacteria and low dissolved oxygen (DO) levels [15]. Recent reports indicated that more than 40% of all impaired waters were affected solely by NPS pollutants, while only 10% of impairments were caused by PS pollutant discharges alone [20].

Unlike NPS pollutants, PS pollutants can be identified because they come from only one source. However, they still present a problem when addressing the pollution issues in primary waterways. To establish the proper actions to reduce or stop the pollutant load into waterbodies, it is necessary to identify the source of the pollutant. PS pollution identification is a challenging task because of the uncertainties and nonlinearity in the transport process of pollutants [21]. The typical way to identify PS pollution requires obtaining prior information of the pollution source, gaining complex information about pollution such as incidents regarding flow simulation dimensions, tabulating the number of PS pollutants involved, and evaluating the pollutant release process [22]. Determining potential sources is the first step in acting toward reducing the effects of water quality problems. Unlike NPS, PSs can be identified because they come from only one source. However, they still present a problem when addressing the pollution issues in primary waterways. To establish the proper actions to reduce or stop the pollutant load into waterbodies, it is necessary to identify the source of the pollutant. PS identification is a challenging task because of the uncertainties and nonlinearity in the transport process of pollutants [21]. The typical way to identify a PS requires obtaining prior information of the pollution source, gaining complex information about pollution such as incidents regarding flow simulation dimensions, tabulating the number of PS involved, and evaluating the pollutant release process [22]. Determining potential sources is the first step in acting toward reducing the effects of water quality problems.

Almost 70% of all rivers and streams in the United States are unassessed. In the State of Texas, 88% of all rivers and streams are unassessed. In the United States, 53% of the assessed water bodies were considered impaired due to high levels of *E. coli* and fecal coliform [23]. In addition, fecal coliform bacteria and other pathogens present in stormwater discharges threaten public health and have been responsible for numerous beach closings in the region [24]. Some studies have found that both livestock and manure management can potentially be agricultural sources of fecal indicator bacteria in watersheds [25]. Moreover, estuaries have faced eutrophication because of increased inputs of nutrients, such as nitrogen and phosphorus. This phenomenon is now considered to be a worldwide issue [26–28]. Ammonia can enter the aquatic environment via direct means of municipal effluent discharge and excretion of nitrogenous wastes from animals. It may also contaminate certain areas through indirect means such as nitrogen fixation, air deposition, and runoff from agricultural lands [29]. Improper wastewater management practices in this under-served region have caused severe water quality problems, and sections of the river have experienced poor water quality with regard to dissolved oxygen, bacteria, and algae [30].

The Laguna Madre is identified as an impaired waterbody due to the presence of high concentrations of bacteria and low dissolved oxygen [2]. The Lower Laguna Madre receives freshwater inflows from three waterways located in the north and central part of the LRGV. The three waterways are HWMD, RVD and IBWCNF, which are not fully characterized due to insufficient data. The aim of this paper is to provide a comprehensive characterization of the north and central watersheds to analyze pollution sources. A cyberinfrastructure database was developed to facilitate navigating through distinct information

to obtain potential sources of pollution. Watershed delineation was developed using as GIS platform to determine the watersheds' drainage areas. Quantifying this information will support the identification of which of the three watersheds contribute the most to water impairments in the Lower Laguna Madre by assessing each watershed independently. The watershed characterization has been shown to support stakeholders in the region for optimal watershed management and enhance their decision-making process.
