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Changes in water quality were examined during selected rainfall events in a headwater stream severely damaged by a forest fire on 21–23 February 2021. Seven water quality parameters were analyzed: pH, electrical conductivity, biochemical oxygen demand, chemical oxygen demand, total suspended solids (TSS), total nitrogen, and total phosphorous. First-flush effect and event mean concentration analyses were conducted in spring (dry season) and summer (wet season) immediately after the forest fire. In spring, the non-biodegradable organic matter concentrations increased along with pollutants related to ash-enhanced soil water repellency in water affected by first-flush effects. In summer, TSS and nutrient concentrations increased along with pollutants related to fire-induced soil surface disturbances after a series of rainfall events. First-flush analyses indicated that cumulative pollutant loads were greater in the spring than in the summer due to a higher concentration of forest fire ash in the early storm runoff immediately after the forest fire. The event mean concentrations revealed that pollutant loads were associated with both forest fire ash and storm events in the immediate post-fire period. Therefore, this study indicated that water quality along a headwater stream is affected by short-term effects of large and intense forest fires and rainfall seasonality.

The severity and incidence of flash floods are increasing in forested regions, causing significant harm to residents and the environment. Consequently, accurate estimation of flood peaks is crucial. As conventional physically based prediction models reflect the traits of only a small number of areas, applying them in ungauged catchments is challenging. The interrelationship between catchment characteristics and flood features to estimate flood peaks in ungauged areas remains underexplored, and evaluation standards for the appropriate number of flood events to include during data collection to ensure effective flood peak prediction have not been established. Therefore, we developed a machine-learning predictive model for flood peaks in ungauged areas and determined the minimum number of flood events required for effective prediction. We employed rainfall-runoff data and catchment characteristics for estimating flood peaks. The applicability of the machine learning model for ungauged areas was confirmed by the high predictive performance. Even with the addition of rainfall-runoff data from ungauged areas, the predictive performance did not significantly improve when sufficient flood data were used as input data. This criterion could facilitate the determination of the minimum number of flood events for developing adequate flood peak predictive models.

Continuously increasing demand for freshwater makes many scientists study water yield prediction. In South Korea, of which two-third is covered by forests, understanding the water cycle especially in forests is even more important. Throughfall is penetrated rainfall through the tree canopy and it is the basic source for groundwater recharge which is directly related to the water yield on the catchment scale. Therefore, understanding the throughfall characteristics is essential for sustainable water management. This study is conducted to develop simple throughfall simulation models and estimate prediction uncertainty from developed models by different forest stand characteristics. National Institute of Forest Service (NIFoS) has collected throughfall data for 2 years from 7 different forest stand sites. Rutter model was used for the structure of the simple throughfall simulation model and it had several parameters for simulating. And over a million Monte Carlo experiments and generalized likelihood uncertainty estimation (GLUE) methodology were used for selecting parameters sets of behavioural models from comparing simulated throughfall and observed throughfall. From the range of behaviours in a period, we successfully estimated the prediction uncertainty. We also compared the features of behavioural parameter sets by different forest stand characteristics. We expect developed models can be applied for several forest stands in South Korea with various physical-based hydrological models.

This paper is concerend with tackling the L 1 performance analysis problem of continuous and piecewise continuous nonlinear systems with non-unique solutions by using the involved arguments of set-invariance principles. More precisely, this paper derives a sufficient condition for the L 1 performance of continuous nonlinear systems in terms of the invariant set. However, because this sufficient condition intrinsically involves analytical representations of solutions of the differential equations corresponding to the nonlinear systems, this paper also establishes another sufficient condition for the L 1 performance by introducing the so-called extended invariance domain, in which it is not required to directly solving the nonlinear differential equations. These arguments associated with the L 1 performance analysis is further extended to the case of piecewise continuous nonlinear systems, and we obtain parallel results based on the set-invariance principles used for the continuous nonolinear systems. Finally, numerical examples are provided to demonstrate the effectiveness as well as the applicability of the overall results derived in this paper.

Forests and water are closely related to each other. Thus, forest management is crucial for the sustainable clean water supply. Forest thinning is one of the fundamental forest management practices, as it can change runoff by controlling the density of trees. In this study, the effect of forest thinning on long-term runoff changes was evaluated, based on the long-term rainfall-runoff data of a coniferous plantation forest catchment in Korea. From the double mass curve and Pettitt&rsquo, s test, a statistically significant increase in runoff rates was identified. A simple linear regression model of the double mass curve can successfully quantify the net effect of forest thinning on the runoff increase. Furthermore, it was also confirmed that forest thinning does not significantly increase the risk of flooding. About ten years after forest thinning, crown closure rates of the coniferous plantation forest reached a level similar to the pre-thinning period, and runoff rates returned to the pre-thinning level, due to forest growth. As a result of this study, a proposed direction for Korea&rsquo, s forest policy for water resource management is presented for the future.

The Mongolian pine (Pinus sylvestris var. mongolica) is one of the most common tree species in semiarid and arid areas of China, especially in the sand dunes of the Hulunbeier steppe. This study addresses the morphological and physiological characteristics of the Mongolian pine according to sand dune height. Five sites were chosen with various sand dune heights (P1&ndash, P5). Nine years after planting, tree growth, leaf area, leaf mass per leaf unit area (LMA), diameter at breast height (DBH), tree height, diameter at root collar (DRC), longest shoot length, carbon isotope composition, and intrinsic water use efficiency (iWUE) were measured to explore the responses of Mongolian pine trees to drought. DBH, tree height, DRC, leaf area, leaf length, and longest shoot length significantly decreased with greater sand dune height (p &lt, 0.05). However, the carbon isotope actually increased with dune height (p &lt, 0.05). Conversely, the iWUE of current-year pine needles was significantly higher at measurement points P3 (132.29 &mu, mol CO2 mol &minus, 1 H2O), P4 (132.96 &mu, 1 H2O), and P5 (125.34 &mu, 1 H2O) than at the lower points P1 (95.18 &plusmn, 9.87 &mu, 1 H2O) and P2 (103.10 &plusmn, 11.12 &mu, 1 H2O). Greater sand dune height increases the distance to groundwater, which in this study led to an increase in iWUE in the Mongolian pines, thus these trees appear to adapt to increased sand dune height by increasing their iWUE and decreasing their leaf area. However, prolonged periods characterized by such adaptations can lead to tree death. We expect these findings to be useful when selecting plantation sites for Mongolian pines in semiarid and arid climates.

This study aims to contribute to better understanding the effects of the changes in the parameter values of GroundFilter algorithm(GF), which performs filtering process, and of GridsurfaceCreate algorithm(GC), which creates regular grid, provided in Fusion software on the accuracy of elevation of the final LiDAR-DEM products through comparative analysis. In order to test whether there are significant effects on the accuracy of the final LiDAR-DEM products due to the changes of GF(1, 3, 5, 7, 9) parameter levels and GC(1, 3, 5, 7, 9) parameter levels, two-way ANOVA is conducted based on residuals. The residuals are calculated using the differences between each sample plot`s paired field-measured and DEM-derived elevation values given each individual GF and GC level. After that, Tukey HSD test is conducted as a post hoc test for grouping the levels. As a result of two-way ANOVA test, it is found that the change in the GF levels significantly affects the accuracy of LiDAR-DEM elevations(F-value : 27.340, p

This study was carried out to investigate coefficient and exponent of runoff energy in MUSLE for small forest watershed, Hwachoen watershed in Gangwon-do. For 15 rainfall events, runoff volume, peak discharge and sediment yield were measured and these data were used to calculate coefficient and exponent of runoff energy. The results of this study showed that factors of MUSLE were affected by slope steepness. The coefficient and exponent of runoff energy were validated with coefficient of efficiency of 0.92 and these values were suggested to 0.002 and 0.81 respectively. The comparison of the coefficients and exponents between Hwacheon and other forest watersheds showed that these values would reflect the effect of forest management within watershed.

This study was carried to figure out appropriate method for time of concentration used in the Rational method at design flood estimation. For 6 small forest watershed, time of concentration was obtained from time of concentration formulas including Kirpich Rziha, Kraven (I), Kraven (II) and SCS lag method and the results from these were compared to the results from cross correlation function based on real rainfall runoff events. The results of cross correlation function ranged from 12.9 to 28.8 minutes and the average difference between SCS lag method and cross correlation function was 2.5 minutes. SCS lag method would be feasible to estimate time of concentration in small forest watershed.

This study was carried out to investigate the characteristics of suspended solid concentration in small forest watershed, Hwacheon, Gangwondo. For five rainfall events from July 2013 to August 2013, rainfall, discharge, and suspended solid load has been measured. The results showed that the fist flush effect was observed for suspended solid in each rainfall event, sediment rating curve was obtained with at rising limb and at falling limb, and EMC (event mean concentration) of suspended solid was calculated to 9.4 mg/L. EMC was compared to the values from the watershed that has various land use types and EMC from forest watershed was much lower that from the crop, paddy or low covered forest watershed.

This review was to determine a standard post-fire restoration strategy for use in South Korea according to the magnitude of the damage and the condition of the affected site. The government has strongly enforced reforestation in deforested areas as well as fire prevention and suppression since the 1960s. These efforts have successfully recovered dense even-aged forests over the last five decades. However, high fuel loading and the homogeneous structure have made forests vulnerable to large fires. In recent years, large forest fires have occurred in the eastern coastal region of Korea. Forest fires can significantly influence the economic and social activities of the residents of such affected forest regions. Burned areas may require urgent and long-term restoration strategies, depending on the condition of the affected site. Erosion control is the most important component of an urgent restoration and should be completed before a rainy season to prevent secondary damage such as landslides and sediment runoff in burned areas. Long-term restoration is necessary to renew forest functions such as timber production, water conservation, ecosystem conservation, and recreation for residents. Sound restoration for burned areas is critical for restoring healthy ecological functions of forests and providing economic incentives to local residents.

In South Korea, since small forest catchments are located upstream of most river basins, the baseflow from these catchments is important for a clean water supply to downstream areas. Baseflow recession analysis is widely recognized as a valuable tool for estimating the baseflow component of the stream hydrograph. However, few studies have applied this tool to small forest catchments. So, this study was conducted to assess the applicability of the recession analysis methods proposed in previous studies. The data used were long-term rainfall-runoff data from 1982 to 2011 in the Gwangneung coniferous (GC) and deciduous (GD) forest catchment in Gyeonggi-do, South Korea. For the applicability assessment, six recession constant estimation methods, which were used by previous studies, were selected. The recession constants of the GC and GD catchments were calculated, and applicability assessments were conducted by comparing the recession predictions and baseflow separations. As a result, the recession constants for GC and GD were 0.8480 and 0.9235, respectively. This clear difference may be due to the different forest cover in each area. The correlation regression line, AR(1) model, and the Vogel and Kroll method showed lower error rates and appropriate baseflow indexes compared with other methods.

A new approach to multi-criteria model evaluation is presented. The approach is consistent with the equifinality thesis and is developed within the Generalised Likelihood Uncertainty Estimation (GLUE) framework. The predictions of Monte Carlo realisations of TOPMODEL parameter sets are evaluated using a number of performance measures calibrated for both global (annual) and seasonal (30 day) periods. The seasonal periods were clustered using a Fuzzy C-means algorithm, into 15 types representing different hydrological conditions. The model shows good performance on a classical efficiency measure at the global level, but no model realizations were found that were behavioural over all multi-period clusters and all performance measures, raising questions about what should be considered as an acceptable model performance. Prediction uncertainties can still be calculated by allowing that different clusters require different parameter sets. Variations in parameter distributions between clusters, as well as examination of where observed discharges depart from model prediction bounds, give some indication of model structure deficiencies.

The assimilated carbon stored in terrestrial ecosystems is exported with water movement in both organic and inorganic forms, which are defined as particulate organic carbon (POC), dissolved organic carbon (DOC), and dissolved inorganic carbon (DIC). The transport of terrestrial carbon into streams, rivers and eventually the oceans is an important link in the global carbon cycle (Ludwig et al., 1996; Warnken and Santschi, 2004). The Committee on Flux of Carbon to the Ocean estimated that of the organic carbon entering rivers globally, around 50% is transported to the ocean, 25% is oxidized within the system and 25% stored as POC in the system as sediment (Hope et al. 1994). As compared to the terrestrial carbon sinks (1.9 Gt-C/yr; Prentice et al., 2001), the organic carbon transport from terrestrial ecosystems to oceans is 0.4–0.9 Gt-C/yr (Meybeck, 1982; Hope et al., 1994; Prentice et al., 2001), representing a substantial component of the ecosystem carbon balance.