A novel spatial optimization approach for the cost-effectiveness improvement of LID practices based on SWMM-FTC.

Due to the increasingly frequent occurrence of urban waterlogging, the spatial optimization of low impact development (LID) practices has been commonly used to detain and reduce storm water runoff in the most cost-effective way. In this study, the flow transmission chain (FTC) was proposed to replace the routing portion of the Storm Water Management Model (SWMM) and was combined with the runoff component of the SWMM to simulate LID practices (SWMM-FTC). In the SWMM-FTC, the third Evolution Step of Generalized Differential Evolution (GDE3) was employed to optimize the LID layout design. The results showed that the relative error between the modified SWMM-FTC and the calibrated SWMM was less than 0.25% under various LID scenarios, and the computational efficiency of the SWMM-FTC was improved by 19.3 times. Moreover, the GDE3 outperformed the commonly used non-dominated sorting genetic algorithm (NSGA-II), the strength Pareto evolutionary algorithm (SPEA2), and the multi-objective shuffled frog leaping algorithm (MOSFLA) due to its ability to find the most cost-effective solution. The LID layout obtained from the SWMM-FTC with the GDE3 saved $210-1067 to achieve a 1% reduction in storm water runoff. This result demonstrates that the SWMM-FTC with the GDE3 can achieve higher environmental benefits than comparable models, providing better guidance for managers and stakeholders.

Flood Risk Assessment and Regionalization from Past and Future Perspectives at Basin Scale.

Flooding is a major natural disaster that has brought tremendous losses to mankind throughout the ages. Even so, floods can be controlled by appropriate measures to minimize loss and damage. Flood risk assessment is an essential analytic step in preventing floods and reducing losses. Identifying previous flood risk and predicting future features are conducive to understanding the changing patterns and laws of flood risk. Taking the Dongjiang River basin as a study case, we assessed and regionalized flood risk in 1990, 2000, and 2010 from the past perspective and explored dynamic expansion during 1990-2010. Then, we projected land-use type, population, and gross domestic product in 2030 and 2050 and finally assessed and regionalized the risk from a future perspective. Results show that areas with very high risk accounted for 14.98-18.08% during 1990-2010; approximately 13.90% areas of the basin transformed from lower-level risk to higher-level risk whereas 9.07% fell from a higher level to a lower level during the period. For the future scenario, areas with very high and high risk in 2030 and 2050 are expected to account for 21.55% and 24.84%, respectively. Generally, our study can better identify changes in flood risk at a spatial scale and reveal the dynamic evolution rule, which provides a synthetical means of flood prevention and reduction, flood insurance, urban planning, and water resource management in the future under global climate change, especially for developing or high-speed urbanization regions.

Climate and landuse change enhance spatio-temporal variability of Dongjiang river flow and ammonia nitrogen.

The adverse impacts of climate and landuse change are threatening the availability of water quantity and its quality, yet there are limited understandings in the response of water availability to changing environment at different spatio-temporal scales. Aimed at quantifying the individual and superimposed effects of climate and landuse change on streamflow and ammonia nitrogen (NH3-N) load in the Dongjiang River Basin (DRB), we dynamically simulated the historical (1981-2010) and future (2030-2070) variation of runoff depth and NH3-N load coupling multiple regional climate model and landuse data. The increase in runoff depth (avg. +233.9 mm) due to climate change was about 33 times greater than that caused by landuse change (avg. -7.2 mm). Especially in the downstream of DRB (Hong Kong, Shenzhen and Dongguan cities, etc.), the maximum rise of runoff depth under climate change was near twice compared with baseline period, indicating the dominant control of climate change on runoff. Also there existed higher coefficient of variation (Cv) value of runoff in the dry season of downstream DRB, contributing potential great fluctuation in runoff. Besides, the variation of NH3-N load was jointly influenced by climate and landuse change, revealing an offset or amplification effect. Moreover, the variability of NH3-N load (Cv value as the metric) increased from 2030, reached a maximum in 2050, following decreased to 2070. The spatial distribution of NH3-N load, in general, presented a downward trend and concentrated near the water body, while the monthly average NH3-N load showed distinct peaks in spring and late summer temporally. Overall, the results highlight the significance of investigating the water availability under changing environment and more adaptive strategies should be proposed for better basin water management.

Effects of different cropping systems on ammonia nitrogen load in a typical agricultural watershed of South China.

The excessive application of agricultural irrigation water and chemical fertilizer has increased crop yields to help meet the demand for food, but it has also led to major water environment problem, i.e. non-point source (NPS) pollution, which needs to be addressed to achieve sustainable development targets. Although numerous studies have focused on the control and reduction of agricultural NPS pollution from the perspective of irrigation and fertilizer, the effects of different cropping systems on NPS pollution (ammonia nitrogen (NH3-N)) in the Dongjiang River Basin (DRB) were seldom assessed. Specifically, variation in the NH3-N load was simulated and analyzed at the annual and semi-annual scales under ten different cropping systems using the Soil and Water Assessment Tool (SWAT) model, which was calibrated and validated with satisfactory statistical index values in the DRB. The results indicated that the NH3-N load decreased, distinctly increased, slightly decreased when sweet potato, peanut, and rice were planted, respectively. Compared with mono-cropping, crop rotation could reduce the NH3-N load, and the planting sequence of crops could affect the NH3-N load to a certain extent. Planting peanuts in spring would dramatically increase NH3-N load. To evaluate NH3-N pollution, a critical threshold of NH3-N emission (5.1 kg·ha-1·year-1) was proposed. Meeting the NH3-N emission threshold cannot be achieved by altering the cropping system alone; additional measures are needed to reduce agricultural NPS pollution. This study facilitates the development of cropping systems and provides relevant information to aid the sustainable development of agriculture in the DRB.

Applicability of two satellite-based precipitation products for assessing rainfall erosivity in China.

Soil erosion has become one of the most serious environmental problems worldwide, and rainfall is considered a crucial factor in water erosion. Rainfall erosivity is defined as the ability of precipitation to trigger soil erosion. The accurate assessment of rainfall erosivity is essential before taking appropriate measures to stop or slow down water erosion. In this study, we calculated the rainfall erosivity in China using the Xie model and two satellite-based precipitation products (SPPs). Gauge-based data from 2417 stations in China were used for a comparison of the results. We also proposed a procedure to assess the performance of the two SPPs using four statistical metrics and provided recommendations for different sub-regions at different time scales. The results showed that the annual rainfall erosivity based on the IMERG-F and TMPA 3B42-V7 products and the in situ gauge stations were 2014, 1954, and 2138 MJ·mm/(hm2·h·yr), respectively. The spatial correlation between IMERG-F and situ gauge stations is 0.944 and that between the TMPA 3B42-V7 product and situ gauge stations is 0.909. The variation trends of the two were highly similar to those of the gauge-based rainfall erosivity at all time scales. The TMPA 3B42-V7 product is recommended for estimating rainfall erosivity in Haihe River Basin and Huaihe River Basin at monthly scale, in Haihe River Basin and China at seasonal scale, in the Haihe River Basin, Huaihe River Basin, Yellow River Basin at annual scale; while the IMERG-F is recommended for the remaining regions except Continental Basins at the three time scales. Generally, the IMERG-F has broader applicability than the TMPA 3B42-V7 product for estimating rainfall erosivity in China. The results of this study provide a reference for selecting suitable SPPs for rainfall erosivity estimates.

Response of non-point source pollution to landscape pattern: case study in mountain-rural region, China.

Landscape patterns have a substantial effect on non-point source (NPS) pollution in watersheds. Facilitating sustainable development of mountain-rural areas is a major priority for China. Knowledge of the impacts of various landscapes on water quality in these areas is critical to meeting environmental goals. This study applied the Soil and Water Assessment Tool (SWAT) to create a hydrologic and water quality model of the study watershed; then, the relationship between water quality and landscape patterns was investigated using multiple linear regression and redundancy analysis. The results show that the western sub-basins had higher nitrogen pollution loads, and the total nitrogen concentration reached a maximum value of 3.91 mg/L; the eastern sub-basins had a higher pollution load of phosphorous featured by maximum total phosphorous concentration of 2.15 mg/L. The water quality of the entire watershed in all scenarios tended to deteriorate over time. Landscape metrics accounted for 81.7% of the total variation in pollutant indicators. The percentage of forest landscape was negatively correlated with NPS pollution, while other types of landscape showed a positive correlation. The patch density, landscape shape index, and largest patch index of urban and agricultural lands were negatively correlated with pollutant concentrations. Upland landscapes contributed more pollutants than paddy fields. Some measures, e.g., returning grassland and farmland to forest in steep regions and replacing upland crops with paddy fields, were recommended for mitigating NPS pollution in the study watershed.

Severe drought events inducing large decrease of net primary productivity in mainland China during 1982-2015.

The analysis of the impact of drought events on terrestrial net primary productivity (NPP) is significant to understand the effects of droughts on regional/global carbon cycling. During the past three decades, terrestrial ecosystems in mainland China have been frequently impacted by drought events. However, quantitative analyses of the variation of NPP induced by droughts are still not enough. Therefore, this study explored the response of NPP to drought events from 1982 to 2015 based on the standardized evapotranspiration deficit index (SEDI) and an NPP dataset obtained from the Carnegie-Ames-Stanford Approach model. We first identified drought events and analyzed the characteristics of drought events using a three-dimensional clustering algorithm. Subsequently, we determined the NPP variations in the drought-affected areas during the droughts and explored the correlation between the NPP variation and the drought characteristics. The results showed that 152 persistent drought events lasting at least 3 months were identified. Most events had durations between 3 and 5 months, and 19 events lasted >9 months. A negative NPP was detected in >60% of the drought-affected areas during long-term (>6 months) and severe (>4 × 106 km2 month) drought events and the total NPP showed a clear decrease during these events. In general, strong drought events reduced the total NPP by >30 TgC in the Northern Region, South Region, Southwest Region, and Northeast Region. The substantial decrease was mainly caused by the NPP anomaly from April to September. The NPP responses to drought events exhibited differences due to different drought characteristics. Although a high proportion of the drought-affected areas experienced a decrease in NPP during most short-term (<5 months) and less severe droughts (<2 × 106 km2 month), the total NPP did not exhibit a large change during these events.

Monitoring hydrological drought using long-term satellite-based precipitation data.

Long-term (over 30a) satellite-based quantitative rainfall estimate (SRE) products provide an ideal data source for hydrological drought monitoring. This study mainly explores the suitability of the two long-term SREs, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and the Climate Hazards Group (CHG) Infrared Precipitation with Stations (CHIRPS), for hydrological drought monitoring. A hydrological drought index called the standardized streamflow index (SSI) was used as an example and the Grid-based Xinanjiang (GXAJ) hydrological model was used for streamflow generation of the SREs. A middle size basin in the humid region of south China was selected as case study. The obtained results show that both SREs present acceptable performances for hydrological modeling, and CHIRPS outperformed PERSIANN-CDR. SSIs calculated by the SRE simulations generally fit well with the trend of observation-based on SSI but apparent deviations in drought intensity were also found. In contrast to hydrological modeling, performance of the SRE-based SSI showed almost no change after model recalibration. Both SREs generally present acceptable classification accuracy but tended to underestimate the levels of drought types. Both SREs accurately captured the beginning, end, and duration of this drought event; however, several deviations were found in severity and intensity estimation of the drought event. In general, both SREs are suitable for hydrological drought monitoring. Although the CHIRPS generally presented better performance, the PERSIANN-CDR is still adequate for hydrological drought monitoring.

Response of net primary production to land use and land cover change in mainland China since the late 1980s.

Land use and land cover patterns in mainland China have substantially changed in the recent decades under the economic reform policies of the government. The terrestrial carbon cycle, particularly the net primary productivity (NPP), has been substantially changed on both local and national scales. With the growing concern over the effects of the terrestrial carbon cycle on global climate changes, the impacts of land use and cover change (LUCC) on NPP need to be understood. In this study, variations in NPP caused by LUCC (e.g., urbanization and conversion of other land use to forest and grassland) in mainland China from the late 1980s to 2015 were evaluated based on land cover datasets and NPPs simulated from the Carnegie-Ames-Stanford Approach model. The results indicate that the national total losses in NPP attributed to urbanization reached 1.695 TgC between the late 1980s and 2015. A large proportion (63.02%) of the total losses was due to the transformation from cropland to urban land. Urban expansion decreased the monthly and total NPPs over southern China, which includes the South China Region, Southwest China Region, and the middle and lower regions of the Yangtze River. However, the total NPP increased in the majority of urbanized areas in Northern China, including the Huang-Huai-Hai Region, Inner Mongolia Region (MGR), Gan-Xin Region (GXR), and Northeast China Region; monthly NPP in GXR and MGR increased throughout the year. By contrast, the conversion to grassland or forestland increased the monthly and total NPPs of Northern China, suggesting that returning to forestland and grassland could increase the carbon sequestration capacity of terrestrial ecosystems in mainland China. Among the sub-regions, the Loess Plateau Region contributed the largest increase in NPP, which was prompted by the conversion to grassland and forestland.

Integrating the social, hydrological and ecological dimensions of freshwater health: The Freshwater Health Index.

Degradation of freshwater ecosystems and the services they provide is a primary cause of increasing water insecurity, raising the need for integrated solutions to freshwater management. While methods for characterizing the multi-faceted challenges of managing freshwater ecosystems abound, they tend to emphasize either social or ecological dimensions and fall short of being truly integrative. This paper suggests that management for sustainability of freshwater systems needs to consider the linkages between human water uses, freshwater ecosystems and governance. We present a conceptualization of freshwater resources as part of an integrated social-ecological system and propose a set of corresponding indicators to monitor freshwater ecosystem health and to highlight priorities for management. We demonstrate an application of this new framework -the Freshwater Health Index (FHI) - in the Dongjiang River Basin in southern China, where stakeholders are addressing multiple and conflicting freshwater demands. By combining empirical and modeled datasets with surveys to gauge stakeholders' preferences and elicit expert information about governance mechanisms, the FHI helps stakeholders understand the status of freshwater ecosystems in their basin, how ecosystems are being manipulated to enhance or decrease water-related services, and how well the existing water resource management regime is equipped to govern these dynamics over time. This framework helps to operationalize a truly integrated approach to water resource management by recognizing the interplay between governance, stakeholders, freshwater ecosystems and the services they provide.

Does drought in China show a significant decreasing trend from 1961 to 2009?

In recent decades, the occurrence and severity of drought in China has had devastating impact on social and economic development. The increase in drought has been attributed to global warming. We used the high-accuracy self-calibrating Palmer Drought Severity Index (scPDSI) to investigate the variation in drought in China between 1961 and 2009 using the Mann-Kendall (MK), continuous wavelet transform (CWT) and the rotated empirical orthogonal function (REOF) methods. We also analyzed the relationship between the rotated principal component time series (RPCs) and 74 circulation indices. The results revealed that: 1) all of China experienced a significant wet trend at annual and seasonal scale; an abrupt change in the drought pattern occurred around 1970 with a 2-8-year significant period; 2) eight major sub-climate regions were identified: Northwest China, Northeast-Inner Mongolia Plateau, Greater Khingan Range area, Northern Tibetan Plateau, Southern Tibetan Plateau, Central China, Huang-Huai-Hai Plain and Southeast China. Of these regions, the Southern Tibetan Plateau experienced a significant wet trend, but the Northeast-Inner Mongolia Plateau and Northern Tibetan Plateau became significantly drier. Using either annual or seasonal scales, Northwest China became significantly wetter and Central China became more arid. In addition, the period of each sub-climate region shared a significant 2-8-year band; 3) the polar vortex exhibited dominant patterns that affected most areas of China. The Pacific Decadal Oscillation had a significant influence on drought evolution, especially for Northwest China and the Huang-Huai-Hai plain. Additionally, the El Niño-Southern Oscillation also affected drought evolution, and the Central China was impacted by the Indian Ocean Dipole.