As the population living near natural waters increases, there is an increased global interest in water security and the impacts of development on water resource quantity and quality. Urban developments (e.g., construction of roads, buildings, and parking lots) alter watershed characteristics such as land-use and land-cover (LULC) and total impervious area. Changes in LULC ultimately impact water resources and the ecology of the streams and, therefore, such changes are of a great concern not only to watershed managers but also to all levels of stakeholders in areas around these features [1
In recent decades, many studies have demonstrated the impacts of watershed development on streams, deepening our understanding of fluvial geomorphology, river channel dynamics, and sediment transport [4
]. Urbanizing watersheds often have a larger total sediment yield compared with unurbanized and fully developed watersheds, even for watersheds with small and widely scattered areas of exposed soil [6
]. Hillslope erosion is largely responsible for the increased sediment supply during the construction or urbanizing phase [7
]. For urbanized watersheds, hillslope sediment supply is decreased, but bankfull flows are increased due to imperviousness as a result of the reduction in infiltration rates [1
]. This results in bank erosion, as the urban stream attempts to adjust itself to receive larger discharge [8
]. Imperviousness leads to a reduction in infiltration rates and increase in runoff [1
]. Studies by Wolman and Schick [6
], Leopold [7
] and Paul and Meyer [8
] all emphasize the importance of land development on suspended sediment yield in urban areas. While the total sediment load decreases in urban areas, the suspended load often increases [9
Precipitation is a key factor for surface erosion and driving suspended sediment transport through waterways for a given watershed [10
]. Surface erosion within a watershed is often intensified by a combination of rain events with high intensity and substantial LULC changes towards development [13
]. Additionally, storm water in a developed area may transport considerable amounts of nutrients and suspended sediment [12
]. The suspended sediment concentration is closely correlated with water quality [18
] and is, therefore, factored into stormwater regulation as it is of great concern to watershed managers and residents. Although changes in precipitation may alter the suspended sediment concentration within the stream, the relationship between the two is difficult to establish. Sediment discharge is not solely dependent on precipitation and usually varies nonlinearly during an event [18
]. Further, different rain patterns generate completely different patterns of surface erosion [20
], resulting in alteration in the sediment yield delivered downstream. For example, in a study of rivers fed by runoff from the Himalaya mountains using over a decade of data [21
], it was reported that only two out of eight peaks of suspended sediment discharges coincided with peaks in precipitation. The other six peaks coincided with moderate–low rain. This suggests that other control factors such as substantial erosions within the streams and banks, a potentially significant source of suspended sediment, may be responsible for the peaks [22
Land-cover type significantly influences suspended sediment yield [25
]. Exposure of soil to stormwater runoff is the principal consequence of land use on sediment yield in a developing watershed [7
]. Land development and watershed surface alterations have the potential to substantially alter suspended sediment yield in streams [15
]. Despite numerous studies on the effects of land-cover types on water resources, the relationship between land development and suspended sediment is not fully understood. For instance, land-use changes in a watershed may cause an increase in sediment yield, while a similar change in another watershed may decrease the yield [30
]. Variations in sediment yield are assumed to be related to watershed physiography [32
] and the system of sediment delivery in the watershed [33
]. Schilling [34
] reported that for a case study in Iowa, changing the LULC of a watershed from agriculture to native prairie did not cause significant change in sediment yield due to an increase in channel erosion. In this case, a substantial amount of the eroded sediment may originate from within a river’s channels and banks [1
]. Local changes in a watershed such as urban construction, dams, new patterns of agriculture, mining, and tree felling can alter the erosion and deposition regime [25
]. Sediment yield in a small watershed (<103 km2
) is more sensitive to LULC change [35
]. In larger watersheds, the eroded sediment is more likely to settle in the basin before reaching the outlet [35
]. These factors highlight the need for individual case studies of watersheds to quantify the effects of urban development on sediment yield.
Remote sensing techniques and satellite imagery are useful tools for assessing Earth’s surface features, providing valuable information for water resource analysis [37
]. Landsat satellite images provide the world’s longest continuous Earth surface data and have been used extensively for land type classification and surface change detection. Landsat images continue to play an important role in many water resource applications, such as the classification of isolated wetlands in Cuyahoga County, Ohio [38
There are few studies on land type changes and their effects on sediment yield for the Cuyahoga Watershed. One study [39
] analyzed trapped sediment behind the Gorge Dam on the Cuyahoga River and concluded that from 1926 to 1978, sediment yield had doubled due to urbanization in the watershed. The study also showed that there was no substantial increase in total sediment yield until 2004 and then an increase from 2004 to 2008 and in 2011. To the best of the authors’ knowledge, there is currently no model for predicting suspended sediment yield within the Cuyahoga River. Suspended sediment transport modeling is traditionally based on an understanding of the hydraulics of particle transport [40
]. Advancements in computational power over recent decades, however, has resulted in the creation of innovative techniques for estimating sediment load such as machine learning algorithms that can estimate suspended sediment yield without solving the governing hydraulic equations [42
]. In addition to these methods, empirical models such as the Soil Water Assessment Tool (SWAT), which is based on the Universal Soil Loss Equation (USLE) [44
], and physically based models such as the Water Erosion Prediction Project (WEPP) model [46
] have also been used. However, most of these existing models require either substantial amounts of data or training in order to properly utilize them. There is no known study which utilizes limited historical satellite image and precipitation data to create a simplified Multiple Linear Regression (MLR) model for predicting suspended sediment yield.
In contrast to existing models for estimating suspended sediment yield, this study introduces a new framework for suspended sediment yield estimation by combining remote sensing techniques with limited historical data to establish and quantify the combined effect of land development and precipitation on suspended sediment yield in the Cuyahoga Watershed. This unique approach simplifies the process of suspended sediment yield estimation by taking advantage of readily available historical satellite image and precipitation data. The period of 1991–2011 was chosen for this study because it contains continuous satellite image data for the Cuyahoga Watershed. A major advantage of this simplified statistical method for modeling suspended sediment yield is that this framework can be easily replicated in other watersheds, particularly with the growing availability of satellite and precipitation data. The outcome of this research provides decision makers with a means for assessing the impacts of future development and climate alteration on stream total suspended solids (TSS) for a given watershed, as well as implications for stream stability, fluvial infrastructure stainability, and flood management.
2. Study Area
The study area for this research is the Cuyahoga River watershed in northeast Ohio (Figure 1
). The watershed area is 2105 km2
—of which, 51% is covered by forest, shrub, grassland, pasture, cultivated crops and wetlands, and 46% is classified as developed land based on National Land Cover Database 2011 [48
], following two decades of substantial development. The average terrain slope for the whole watershed is 3.8%, with an elevation change from 160 to 395 m [48
]. The relatively steep slopes of the Cuyahoga River banks and its tributaries’ banks cause frequent river bank failures in the watershed [49
]. The watershed is U-shaped, with its origins in northeast Ohio. It flows southwards to Cuyahoga Falls, where it redirects northward towards Cleveland and finally empties into Lake Erie. Compared with the western segment, the eastern segment is less urbanized, with more wetlands and more channelized tributaries. The degree of development within the watershed increases from Summit County toward Lake Erie, reaching peak industrial development in the Cleveland area [50
]. The soil of the watershed ranges from organic to clay, silt and sand, with an estimated average sediment yield of 5 to 100 tons per acre per year [49
]. There are five major dams along the main stem of the Cuyahoga River and several smaller dams on many of its tributaries.
Land-use and land-cover characteristics along with precipitation are some of the most important factors influencing the suspended sediment yield in a watershed. The relation between those variables is site specific and important for watershed managers, as it provides them with a tool to predict potential impacts to water quality and also evaluate possible implications for stream stability, dam and flood management, and in-stream and near-stream infrastructure life.
This study aimed to develop a framework for establishing the relation between land developments, mean annual precipitation, and mean annual suspended sediment yield in Cuyahoga River, OH by combining remote sensing techniques with limited data. To do that, remote sensing techniques were employed to classify land cover of the Cuyahoga watershed from 1991 to 2011 with historical satellite imagery. Then, a statistical model was developed to find the relation between measured mean annual precipitation, land development and measured mean annual suspended sediment yield. The geospatial imagery analysis showed that nearly all the urbanization within the Cuyahoga watershed between 1991 and 2011 occurred within the first decade. This rapid urbanization, however, did not directly result in an increase in suspended sediment yield within the Cuyahoga River. It is, therefore, possible that within the period of study, urbanization was not the most dominant geomorphic driver for suspended sediment yield. This study also found that within the Cuyahoga watershed, precipitation was more correlated to the suspended sediment yield than the rate of urbanization. This is demonstrated by the similarity in trends between mean annual precipitation and mean annual suspended sediment yield. It is worth noting, however, that the highest mean annual precipitation measurement did not coincide with the years with the highest mean annual suspended sediment yield, an additional indication that there may be some other factors influencing suspended sediment yield. This finding is consistent with findings from previous studies such as Wulf [21
Using an MLR model, this research predicted the suspended sediment yield from 2001 to 2011 moderately well. Given the limited amount of data used in developing the model, this result is acceptable and can be improved with additional data. The study has produced a tool for estimating the potential changes in suspended sediment yield in the Cuyahoga River resulting from alterations in the land-use and land-cover as well as climatic effects on this watershed. The outcome of this research can provide decision makers with a measure for assessing the impacts of future development and climate alteration on Total Suspended Solids (TSS), and ultimately water quality in the watershed and may have implications for stream stability, dam and flood management as well as infrastructure life. With the increasing availability of satellite and precipitation data, this method has the potential to be a viable alternative to other data-intensive and sophisticated models for predicting suspended sediment yield especially for watersheds with limited data.
Overall, the performance of the model presented in this study was acceptable, as demonstrated by an estimated R-squared value of 0.7 based on the comparison between predicted and observed mean annual suspended sediment yield. However, it is important to note that typical with regression-based studies, this model has some uncertainty which was investigated and discussed. Based on the uncertainty analysis, there is a 63% chance that the observed suspended sediment of the Cuyahoga River falls within the 95% confidence interval of this model. Some of the uncertainty around the model’s predictions is due to the size of dataset used to develop the model. Further, there are inherent uncertainties with data, such as suspended sediment yield measurements in general, which may impact the performance of any suspended sediment yield model.