Assessment of Variations in Runoff Due to Landcover Changes Using the SWAT Model in an Urban River in Dublin, Ireland

Investigating the impact of land cover change in hydrological modelling is essential for water resources management. This paper investigates the importance of landcover change in the development of a physically-based hydrological model called SWAT. The study area considered is the Dodder River basin located in southern Dublin, Ireland. Runoff at the basin outlet was simulated using SWAT for 1993–2019 using five landcover maps obtained for 1990, 2000, 2006, 2012 and 2018. Results indicate that, in general, the SWAT model-simulated runoff for a chosen time-period are closer to the real-world observations when the landcover data used for simulation was collated as close to the time-period for which the simulations were performed. For 23 (20) years (from 27 years period) the monthly mean (maximum) runoff for the Dodder River generated by the SWAT model had the least error when the nearby landcover data were used. This study indicates the necessity of considering dynamic and time-varying landcover data during the development of hydrological modelling for runoff simulation. Furthermore, two composite quantile functions were generated by using a kappa distribution for monthly mean runoff and GEV distribution for monthly maximum runoff, based on model simulations obtained using different landcover data corresponding to different time-period. Modelling landcover change patterns and development of projected landcover in the future for river basins in Ireland needs to be integrated with SWAT to simulate future runoff.

The Influence of Landcover and Climate Change on the Hydrology of the Minjiang River Watershed

Changes in the climate and landcover are the two most important factors that influence terrestrial hydrological systems. Today, watershed-scale hydrological models are widely used to estimate the individual impacts of changes in the climate and landcover on watershed hydrology. The Minjiang river watershed is an ecologically and economically important, humid, subtropical watershed, located in south-eastern China. Several studies are available on the impacts of recent climate change on the watershed; however, no efforts have been made to separate the individual contributions of climate and landcover changes. This study is an attempt to separate the individual impacts of recent (1989–2018) climate and landcover changes on some of the important hydrological components of the watershed, and highlight the most influential changes in climate parameters and landcover classes. A calibrated soil and water assessment tool (SWAT) was employed for the study. The outcomes revealed that, during the study period, water yield decreased by 6.76%, while evapotranspiration, surface runoff and sediment yield increased by 1.08%, 24.11% and 33.85% respectively. The relative contribution of climate change to landcover change for the decrease in the water yield was 95%, while its contribution to the increases in evapotranspiration, surface runoff and sediment yield was 56%, 77% and 51%, respectively. The changes in climate parameters that were most likely responsible for changes in ET were increasing solar radiation and temperature and decreasing wind speed, those for changes in the water yield were decreasing autumn precipitation and increasing solar radiation and temperature, those for the increase in surface runoff were increasing summer and one-day maximum precipitation, while those for the increasing sediment yield were increasing winter and one-day maximum precipitation. Similarly, an increase in the croplands at the expense of needle-leaved forests was the landcover change that was most likely responsible for a decrease in the water yield and an increase in ET and sediment yield, while an increase in the amount of urban land at the expense of broadleaved forests and wetlands was the landcover change that was most likely responsible for increasing surface runoff. The findings of the study can provide support for improving management and protection of the watershed in the context of landcover and climate change.

Analysis of Wetland Landcover Change in Great Lakes Urban Areas Using Self-Organizing Maps

Wetland loss and subsequent reduction of wetland ecosystem services in the Great Lakes region has been driven, in part, by changing landcover and increasing urbanization. With landcover change data, digital elevation models (DEM), and self-organizing maps (SOM), this study explores changing landcover and the flood mitigation attributes of wetland areas over a 15-year period in Toronto and Chicago. The results of this analysis show that (1) in the city of Toronto SOM clusters, the landcover change correlations with wetland volume and wetland area range between −0.1 to −0.5, indicating that a more intense landcover change tends to be correlated with small shallow wetlands, (2) in the city of Chicago SOM clusters, the landcover change correlations with wetland area range between −0.1 to −0.7, the landcover change correlations with wetland volume per area range between −0.1 to 0.8, and the landcover change correlations with elevation range between −0.2 to −0.6, indicating that more intense landcover change tends to be correlated with spatially small wetlands that have a relatively high water-storage capacity per area and are located at lower elevations. In both cities, the smallest SOM clusters represent wetland areas where increased landcover change is correlated with wetland areas that have high flood mitigation potential. This study aims to offer a new perspective on changing urban landscapes and urban wetland ecosystem services in Toronto and Chicago.

Prediction of Sediment Yield Using the Algoritma Lavenberg-Marquardt

Erosion and sediment that occurs in the basin is very important to be studied scientifically.Forcasting of sediment yield in a basins area is important to used to evaluate the land-use/landcover change, soil erosion hazard, planning, water quality, water resources in river, and to determine the extent of the damage that occurred in the basins. The algoritmh lavenberg-marquardt can be used to forcest the total of sediment yield the basin area. Artificial neural networks using feedforward multilayer percePsron with three learning algorithms namely Levenberg-Marquardt. The number of neurons of the hidden layer is three to sixteen, while in the output layer only one neuron because only one output target. The root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2 ), and coefficient of efficiency (CE). The performance value in the training process, R2, and CE (0.98 and 0.98). As well as for the testing process, R2 and CE (0.98 and 0.97). Based on the performance statistics value, LM is very suitable and accurate for to forcesting by modeling the non-linear complex behavior of sediment yield responses to water discharge, intensity of rainfall, and water depth in the river.

A Phytolith Supported Biosphere-Hydrosphere Predictive Model for Southern Ethiopia: Insights into Paleoenvironmental Changes and Human Landscape Preferences since the Last Glacial Maximum

During the past 25 ka, southern Ethiopia has undergone tremendous climatic changes, from dry and relatively cold during the Last Glacial Maximum (LGM, 25–18 ka) to the African Humid Period (AHP, 15–5 ka), and back to present-day dry conditions. As a contribution to better understand the effects of climate change on vegetation and lakes, we here present a new Predictive Vegetation Model that is linked with a Lake Balance Model and available vegetation-proxy records from southern Ethiopia including a new phytolith record from the Chew Bahir basin. We constructed a detailed paleo-landcover map of southern Ethiopia during the LGM, AHP (with and without influence of the Congo Air Boundary) and the modern-day potential natural landcover. Compared to today, we observe a 15–20% reduction in moisture availability during the LGM with widespread open landscapes and only few remaining forest refugia. We identify 25–40% increased moisture availability during the AHP with prevailing forests in the mid-altitudes and indications that modern anthropogenic landcover change has affected the water balance. In comparison with existing archaeological records, we find that human occupations tend to correspond with open landscapes during the late Pleistocene and Holocene in southern Ethiopia.

Urban Sprawl Analysis using GIS Application of Bhagur City

The word “Urban Sprawl” means growth is more than the normal and the criteria that makes it different from urban growth is this excessive nature. Cities grow continuously and planned growth is achieved when there is a right balance between urban growth and urbanization. But when growth is above normal its pressure on the region and the city will face major new challenges. Urban sprawl is unrestricted growth in many urban housing areas, business development and roads in large parts of the world, without worrying about urban planning. Urban Sprawl are of three types i.e., linear growth, cluster growth and leapfrog growth. This paper inspect the use of Remote Sensing and GIS in mapping of urban sprawl (1990-2021) and landuse/ landcover change detection to detect changes that has been taken place between these periods in Bhagur city. The paper helps to study the software such as ArcGIS, used to classify between built up and agricultural land using temporal signatures obtained from satellite images. To numerically understand the growth pattern Shannon’s entropy is used. Shannon’s entropy is used as an index to quantify the degree of dispersion or concentration of built-up areas. Entropy approach shows concentration growth pattern in Bhagur city. Keywords: Urban Sprawl, GIS, Remote sensing, Land use/ Land cover, Shannon’s entropy.

Estimates of energy partitioning, evapotranspiration, and net ecosystem exchange of CO2 for an urban lawn and a tallgrass prairie in the Denver metropolitan area under contrasting conditions

Lawns as a landcover change substantially alter evapotranspiration, CO2, and energy exchanges and are of rising importance considering their spatial extent. We contrast eddy covariance (EC) flux measurements collected in the Denver, Colorado, USA metropolitan area in 2011 and 2012 over a lawn and a xeric tallgrass prairie. Close linkages between seasonal vegetation development, energy fluxes, and net ecosystem exchange (NEE) of CO2 were found. Irrigation of the lawn modified energy and CO2 fluxes and greatly contributed to differences observed between sites. Due to greater water inputs (precipitation + irrigation) at the lawn in this semi-arid climate, energy partitioning at the lawn was dominated by latent heat (LE) flux. As a result, evapotranspiration (ET) of the lawn was more than double that of tallgrass prairie (2011: 639(±17) mm vs. 302(±9) mm; 2012: 584(±15) mm vs. 265(±7) mm). NEE for the lawn was characterized by a longer growing season, higher daily net uptake of CO2, and growing season NEE that was also more than twice that of the prairie (2011: −173(±23) g C m−2 vs. -81(±10) g C m−2; 2012: −73(±22) g C m−2 vs. -21(±8) g C m−2). During the drought year (2012), temperature and water stress greatly influenced the direction and magnitude of CO2 flux at both sites. The results suggest that lawns in Denver can function as carbon sinks and conditionally contribute to the mitigation of carbon emissions - directly by CO2 uptake and indirectly through effects of evaporative cooling on microclimate and energy use.