Daily water temperature, dissolved oxygen (DO) profiles, and ice and snow covers (where applicable) were simulated for 27 types of small lakes (up to 10 km² surface area) at 209 locations in the contiguous United States under past climate (observed from 1961 to 1979) and for projected doubled atmospheric carbon dioxide (2×CO₂) climate conditions. A verified, process‐oriented, dynamic, and one‐dimensional year‐round lake water quality model (MINLAKE96) was applied to simulate water temperature and DO profiles continuously in daily time steps over a 19‐yr simulation period. This regional lake model has no geographic constraints on the model's physical and chemical processes, but the climate forcing is a function of geographic location. Model calibration parameters and initial conditions are correlated to lake geometry, trophic state, and location. The 2×CO₂ climate scenario is projected to increase lake surface temperatures by up to 5.2°C when the climate scenario projects an increase of mean annual air temperature up to 6.7°C. The 2×CO₂ climate scenario is projected to increase the duration of seasonal summer stratification by up to 67 d, to shorten ice cover by up to 90 d, and to reduce the maximum ice thickness by up to 0.44 m. Under a 2×CO₂ climate scenario, lake anoxia during the period of ice cover is projected to shorten so that fish winterkill can be avoided, but the periods of hypolimnetic summer anoxia are projected to lengthen. These projected changes will have many significant effects on ecological conditions and aquatic habitats in lakes in the contiguous United States.

The time of concentration $\left(T_c\right)$ for a watershed is a widely used time parameter to estimate peak discharges in hydrologic designs. In this study, $T_c$ is estimated for 96 Texas watersheds using five empirical equations: Williams, Kirpich, Johnstone–Cross, Haktanir–Sezen, and Simas–Hawkins methods. The drainage areas of watersheds studied are approximately $0.88–440.3{\mathrm{km}}^2$ . Watershed parameters used to estimate $T_c$ were developed by researchers at three institutions using three different methods: the automated method using digital elevation models and geographic information system software, the manual method with watershed delineation, and the manual method without watershed delineation. $T_c$ estimated from five empirical equations using three sets of watershed parameters is compared and analyzed. $T_c$ estimated using watershed parameters developed by the three methods is qualitatively similar and has average relative differences ranging from 6.4 to $-16.9\%$ . Differences between manual and automatic-based watershed characteristics are considered minor sources of error in relation to other uncertainties inherent in time parameter estimation. Average relative differences of $T_c$ estimated using different empirical equations with the same set of watershed parameters range from $-38$ to 207% (absolute average differences range from $-3.0$ to $2.8\mathrm{h}$ ) and are much larger than differences estimated using three sets of watershed parameters. Kirpich and Haktanir–Sezen methods provide reliable estimates of mean values of $T_c$ variations.

Various problems such as urban flood inundation and water shortage occurred in China during the rapid urbanization in the last several decades. An urban water management program called Sponge City (SPC) is put forward in China in 2014 in order to relieve the flood inundation and water shortage situation. The SPC program implements not only the concept and practices of low impact development but also various comprehensive urban water management strategies. The SPC development promotes water security, water environmental protection, and water ecological restoration. The background information and general principles of the SPC program are introduced in this paper as well as the experience and achievement obtained in developing SPC so far. Sixteen cities have been selected by Chinese government as SPC’s pilot cities in March, 2015. The Chinese government will provide special subsidy and financial support for the development of SPC in the next three years. The geographic, hydrologic, economical characteristics of the sixteen cities vary from each other, therefore, the SPC plan and implementation will be different in 16 cities. A new investment and financial supporting mode based on public-private partnership concept is employed to handle the SPC construction and operation cost. Chinese central and local government agencies and engineers are exploring various innovative methods to handle the problems caused by rapid urbanization as well as seek sustainable financial support and investment approaches for urban infrastructure construction related to SPC development.

The rational method for peak discharge ($Q_p$ ) estimation was introduced in the 1880s. Although the rational method is considered simplistic, it remains an effective method for estimating peak discharge for small watersheds. The runoff coefficient ($C$ ) is a key parameter for the rational method and can be estimated in various ways. Literature-based $C$ values ($C_{\mathrm{lit}}$ ) are listed for different land-use/land cover (two words, no hyphen) (LULC) conditions in various design manuals and textbooks; however, these $C_{\mathrm{lit}}$ values were developed with little basis on observed rainfall and runoff data. In this paper, $C_{\mathrm{lit}}$ values were derived for 90 watersheds in Texas by using LULC data for 1992 and 2001; the $C_{\mathrm{lit}}$ values derived from the two data sets were essentially the same. Also for this study, volumetric runoff coefficients ($C_v$ ) were estimated by using observed rainfall and runoff depths from more than 1,600 events observed in the watersheds. Watershed-median and watershed-average $C_v$ values were computed, and both are consistent with data from the National Urban Runoff Program. In addition, $C_v$ values were estimated by using rank-ordered pairs of rainfall and runoff depths (i.e., frequency matching). As anticipated, $C$ values derived by all three methods (literature based, event totals, and frequency matching) consistently had larger values for developed watersheds than for undeveloped watersheds. Two regression equations of $C_v$ versus percent impervious area were developed and combined into a single equation that can be used to rapidly estimate $C_v$ values for similar Texas watersheds.

An urban rainfall-runoff water quality model was developed to simulate total suspend solids (TSS) using the stormwater management model (SWMM) for a 3.8 ha university campus in Beijing (approximately 76.5% impervious), and calibrated and validated against data from two observed rainfall events (221.2 and 16.6 mm rainfall). Model performance is satisfactory (Nash–Sutcliffe model efficiency 0.8 and 0.72 for flow and 0.74 and 0.51 for TSS concentration, respectively). A series of sensitivity model runs were conducted using the calibrated SWMM to study the influences of rainfall characteristics (rainfall hyetographs, depths and durations) and surface flooding on the TSS concentration in outlet runoff of the catchment. The Pilgrim and Cordery rainfall distribution defines a first-quartile storm (the most severe) and results in the highest peak discharge and TSS concentration at the outlet but the lowest outlet TSS load because of the highest TSS flood loss (32.3%). The simulated TSS pollutograph resulting from the Keifer and Chu rainfall distribution (with r = 0.5) is almost identical to that resulting from the alternating block rainfall distribution. Under the same rainfall hyetograph, simulated peak discharge and outlet TSS load are positively correlated (R² = 0.95) to the rainfall depth as a function of the return period.

Heavy metals from urban stormwater runoff are important sources of surface water pollutants. Sand, zeolite, sandy loam, and quartz-sand were separately mixed with lignin to form four bioretention media mixes for experimental study using synthetic stormwater runoff. The average removal efficiencies of four heavy metals (Cu, Zn, Cd, and Pb) by the four media mixes were all better than 97% at the optimum pH of 6.05 (ranging from 6 to 8) and the seven-day rainfall-event interval. The influence of the influent concentration and the rainfall-event interval on the removal efficiency of heavy metals by the four media mixes was not significant, but the variation of the removal efficiencies at the four-day rainfall-event interval was large. Under acidic conditions, there was a certain heavy metal dissolution in the four reactors, but the effect on the removal efficiency was minor. Heavy metals were present in the media mainly in the form of the residual fraction (>50%). The accumulation of Cu, Zn, and Cd in the surface planting-soil layer (same humus and sandy-loam mixture for all reactors) was significantly larger than the accumulation at deeper depths but not for Pb. Overall, the heavy metal removal efficiencies by the four media mixes were not significantly different, and the choice of the planting-soil layer can become the control factor of heavy metal removal.