Analysis of the Effects of Local Regulations on the Preservation of Water Resources Using the CA-Markov Model

Abstract

The analysis of the local regulation effects is required for sustainable and effective land utilization because land use/land cover (LULC) changes are not only determined by human activity but are also affected by national policy and regulation; however, previous studies for land use/land cover (LULC) have mainly been conducted on the LULC changes using past experience. This study, therefore, analyzed the effects of local regulations aimed at preserving the water quality in South Korea. To this end, changes in LULC were simulated using the CA-Markov model under conditions in which two local regulations, the special countermeasure area (SCA) and total maximum daily load (TMDL), were not applied and examined the differences between the simulated LULC and the actual LULC as of 2018. In addition, the differences in the generation of pollutant loads were driven for Biochemical Oxygen Demand (BOD), Total Nitrogen (TN), and Total Phosphorus (TP) using pollutant unit-load. As a result, without SCA, the agricultural area increased by 379.0 km2, the urban area decreased by 101.8 km2, and the meadow area decreased by 176.0 km2. In addition, without TMDL, the urban area increased by 169.2 km2 and the meadow area decreased to 158.8 km2.Differences in BOD, TN, and TP pollution loads without SCA applications were shown to decrease to 22,710.5 kg·km−2 day−1, 1133.9 kg·km−2 day−1, and 429.8 kg·km−2 day−1, respectively, while BOD, TN, and TP pollution loads without TMDL applications decreased to 14,435.7 kg·km−2 day−1, 2543.6 kg·km−2 day−1, and 368.2 kg·km−2 day−1, respectively. As such, this study presents a methodology for analyzing the effects of local regulations using the CA-Markov model, which can intuitively and efficiently examine the effects of regulations by predicting LULC changes.

The development of inflow discharge for the karian multipurpose reservoir in the pursuit of reservoir management optimization

“…To assess the simulation discharge generation models, a comparison was conducted utilizing correlation, Root Mean Square Error (RMSE), and Absolute Relative Error (ARE) values [19,20]. The correlation coefficient indicates the extent of association in regression analysis with a cause-and-effect relationship, ranging from 1 to -1, where 1 signifies a strong positive correlation, 0 denotes no correlation, and -1 indicates a strong negative correlation.…”

“…The correlation coefficient indicates the extent of association in regression analysis with a cause-and-effect relationship, ranging from 1 to -1, where 1 signifies a strong positive correlation, 0 denotes no correlation, and -1 indicates a strong negative correlation. [20]. Meanwhile, the Root Mean Square Error (RMSE) gauges error by assessing the difference between corresponding values to evaluate data accuracy.…”

The Spatiotemporal Eutrophication Status and Trends in the Paldang Reservoir, Republic of Korea

“…The PDR performs various functions, including flood control, hydroelectric power generation, fishing activities, and recreation, as it coexists with both humans and nature [21]. To protect the water quality of the PDR, in 1998, the government designated the surrounding area as a water source protection zone, enforcing strict water quality management and regulations [22]. These measures aim to protect the water and ecosystem of the PDR and provide safe drinking water for residents of the Seoul metropolitan area.…”