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In the healthcare sector, sense of calling has raised increasing attention for its crucial role in fostering nurses' motivation and dedication to their work. Despite the fact that individuals with a sense of calling are more likely to go beyond their duties, the potential influence of this calling on their innovative behaviour remains largely unexplored. Drawing on work as a calling and self‐determination theories, this study aims to establish a link between a sense of calling and innovative work behaviour in the healthcare sector and investigate the underlying mechanisms and boundary conditions. Questionnaires were distributed through field and online surveys to collect the responses of 350 nurses in China. Structural equation modelling was adopted to test the research hypotheses. The results showed that sense of calling had a positive effect on nurses' innovative work behaviour and the relationship was mediated through meaning of work and employee resilience. Moreover, psychological safety was found to strengthen the positive impact of sense of calling on nurses' innovative work behaviour. Theoretical and practical implications were discussed along with the direction for future research. [ABSTRACT FROM AUTHOR]

In order to achieve sustainable development, low-carbon economic efficiency (LCEE) is particularly important in China. Therefore, this study uses SBM-DEA model to evaluate the LCEE of 30 provinces in China from 2008 to 2017. Based on the uncoordinated coupling model, this study discusses the interaction between China’s provincial LCEE and scientific and technological development level (STDL), and uses the panel VAR model to consider the interactive response relationship between China’s provincial LCEE and STDL. The research shows that the uncoordinated coupling degree (UCCD) between the STDL and LCEE in 30 provinces showed a decreasing trend as a whole during the research period. In terms of spatial distribution, the provinces with UCCD less than 0.5 mainly concentrated in the eastern and southern provinces, gradually spread to the north, and showed positive spatial autocorrelation, with significant spatial accumulation effect. From the perspective of influencing factors, patents, urbanization level, traffic level and financial development have significant positive effects on promoting the coordinated development of STDL and LCEE. From the relationship between them, the STDL has a positive promoting effect on LCEE, but the mechanism of the two is not obvious enough. Therefore, it is necessary to emphasize the coordinated development of low-carbon economy and science and technology, and promote the development of low-carbon economy through scientific innovation.

"The Belt and Road Initiative" (BRI) seeks to attain high‐quality development and sustainability. This study examines the green total factor energy efficiency (GTFEE) of 58 BRI countries from 2005 to 2019 and its influence factors using the Super slacked‐based measurement and Tobit models. The findings indicate that: 1) Singapore and the other seven countries have GTFEEs above 0.9, which is better than other countries; seven out of 58 countries have GTFEEs below 0.5. 2) Due to regional disparities, Southeast Asia, Central, and Eastern Europe have the greatest GTFEE, followed by South Asia, West Asia, and the Commonwealth of Independent States, and the lowest is in Central Asia, China, and Mongolia. 3) Compared to developing economies, developed economies have a higher GTFEE. 4) Between 2005 and 2019, the overall BRI energy efficiency dropped from 0.75 to 0.56. 5) According to Tobit results, for every 1% increase in economic development and energy structure, GTFEE increases by 0.08% and 0.31% points, respectively, and for every 1% increase in trade and land area, GTFEE decreases by 0.04 and 0.05, respectively. Therefore, BRI countries should strengthen international cooperation, develop advanced technologies, and increase the proportion of renewable energy utilization. [ABSTRACT FROM AUTHOR]

The aim of the present study was to assess differences in the conditioning factors and the performance of landslide susceptibility mapping (LSM), employing the SHapley Additive exPlanations (SHAP) model to gain profound insights into the intrinsic decision‐making mechanism of LSM in diverse landforms. Two typical karst erosion landforms were selected as the research areas. Based on 15 conditioning factors, LSMs for the two areas were developed using the Bayesian optimization random forest (RF) and eXtreme Gradient Boosting (XGBoost). The SHAP model was used to explore the landslide formation mechanisms from both global and local perspectives. The results show that the area under the curve (AUC) values of the XGBoost models were 0.791 and 0.761, and the AUC values of the RF models were 0.844 and 0.817, in the two different landform areas, respectively. The RF model's accuracy was higher than that of the XGBoost model in both regions. In the low‐elevation hills area, the primary three conditioning factors were identified as slope, topographic relief and distance from the river. Conversely, in the microrelief and mesorelief low mountain area, the predominant conditioning factors were elevation, distance from the river and distance from the road. Both karst landform areas exhibited a high sensitivity to the distance from the river, indicating its significant interaction with other factors contributing to landslide occurrences. Notably, the RF model demonstrated superior performance compared to the XGBoost model, rendering it a more suitable choice for conducting landslide susceptibility mapping research in karst erosion landform areas. In the present study, a comprehensive explanatory framework based on the RF‐SHAP model was proposed, which enables both global and local interpretation of landslides in various karst landscapes. Such an approach explores the intrinsic decision‐making mechanism of the model, enhancing the transparency and realism of landslide susceptibility prediction results. [ABSTRACT FROM AUTHOR]

For a long time, China 's extensive economic development model has produced a large amount of emissions, which has brought indelible damage to the environment. Green development is of vital importance for China to achieve high-quality development, and it is the core of alleviating environmental problems and promoting sustainable development. How to achieve China 's green development requires us to evaluate the level of green development in China 's provinces and analyze the reasons. In this study, an evaluation index system including undesired output of green development efficiency is constructed, and then the Supe-SBM model is used to assess the green development efficiency of 30 Chinese provinces. This paper also discusses the spatial and temporal differences as well as the factors affecting green development efficiency of green development efficiency among provinces. The findings demonstrate: (1) The green development efficiency in the eastern region is the highest, followed by the western region, while the central region has the lowest, but they all show a downward trend. (2) The spatial characteristics of green development efficiency are remarkable, according to the Global Moran's I index. However, the results of local spatial agglomeration demonstrate "small agglomeration and large dispersion," with the majority of provinces exhibiting L-L agglomeration. (3) Technological Progress, Opening Up, Urbanization Level are positively correlated with the green development efficiency. Industrial Structure, Financial Development, Energy Structure and green development efficiency are significantly negatively correlated, while Environmental Regulation shows no significant impact. [ABSTRACT FROM AUTHOR]

Landslide susceptibility mapping (LSM) enables the prediction of landslide occurrences, thereby offering a scientific foundation for disaster prevention and control. In recent years, numerous studies have been conducted on LSM using machine learning techniques. However, the majority of machine learning models is considered "black box" models due to their lack of transparent explanations. In contrast, the QLattice model serves as a white box model, as it can elucidate the decision‐making mechanism while representing a novel approach to whitening machine learning models. QLattice possesses the capability to automatically select and scale data features. In this study, Fengjie County in China was selected as the research area, with slope units serving as evaluation units. A geospatial database was constructed using 12 conditioning factors, including elevation, slope, and annual average rainfall. LSM models were conducted using both the QLattice and random forest (RF) algorithms. The findings demonstrate that the QLattice model achieved an area under curve value of 0.868, while the RF model attained an area under curve value of 0.849 for the test datasets. These results highlight the superior predictive ability and stability of the QLattice model compared with RF. Furthermore, QLattice can explicate and clarify the change processes of conditioning factors, thereby revealing the internal decision‐making mechanism and causes behind the LSM model's decisions. The innovative QLattice‐based model provides new ideas and methodologies for LSM research. [ABSTRACT FROM AUTHOR]

The article analyzes the comprehensive development levels of the three subsystems of Chongqing's tourism, urbanization and ecological environment from 2000 to 2017, and the temporal evolution characteristics of the coordinated development of the three. The results show that: (1) The comprehensive evaluation index of Chongqing's tourism industry system and urbanization system is on the rise; the comprehensive ecological environment index showed an upward trend before 2008, and fluctuated greatly after 2008. (2) The degree of coupling and coordination of the three systems in Chongqing City generally shows a transformational trend of maladjustment recession-intermediate transition-coordination improvement. In the future, Chongqing should continue to deepen institutional reforms and continue to develop new tourism markets; improve transportation, promote enterprise transformation and upgrading, implement policies for talent introduction; strengthen the construction of environmental protection talents and capital investment, and vigorously develop ecological industries

Scientific descriptions and simulations of the ecological risks in mountainous areas can promote the sustainable use of land resources in these areas and improve the reliability of decision-making for ecological risk management. Taking Chongqing, China, as an example, we constructed a landscape ecological risk (LER) evaluation model based on land use data from 1995 to 2020 and analysed the spatiotemporal evolution characteristics of the LER pattern. Moreover, we coupled the patch-generating land use simulation (PLUS) model and multi-objective programming (MOP) method and input multiple scenarios (inertial development, ID; economic priority development, ED; ecological priority development, PD; and sustainable development, SD) to simulate the ecological risk pattern in 2030. The model coupling the "top-down" and "bottom-up" processes obtained optimal land use patterns in different contexts, and it was used to perform a spatially explicit examination of LER evolutionary trends in different contexts. The results showed that LER evolution in Chongqing has had obvious stage characteristics. The high-risk area decreased significantly under various constraints, including topographic, economic, and other constraints, and the distribution showed a trend of high in the west and low in the east. The LER spatial clustering characteristics were highly coupled with the risk level pattern. The ED scenario presented the most severe risk, the PD scenario presented a moderate risk, and the SD scenario balanced the land demand for economic and ecological development and had a better land use structure and LER compared with the other scenarios. The coupled model proposed in this study helps to obtain the optimal land use structure and mitigate ecological risks, thus providing a scientific basis for future urban development. [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal heterogeneity and complex drivers of PM2.5 concentration variations has important scientific value for sustainable urban development. Taking Beijing-Tianjin-Hebei (BTH) as the research area, and using spatial analysis techniques and wavelet methods to explore the spatiotemporal heterogeneity of variations in PM2.5 concentrations, the research shows that in the past six years (2015–2020), the PM2.5 concentrations in the BTH area have a downward trend, and the mean is 59.41 μg/m3; however, the distribution pattern of PM2.5 pollution has changed very little, and the concentration in the south and southwest is still generally high. The continuous wavelet transform revealed that the PM2.5 concentrations in the study area have a short period of about a week to a half a month and a long period dominated by annual cycle. The effect of a single meteorological factor on PM2.5 concentrations is weak, but this effect has obvious spatial differentiation characteristics from coastal to inland and has a double-sided effect due to different geographical locations. The wavelet transform coherence revealed that dewpoint temperature at 2 m (TED), meridional wind at 10 m (WV) and air temperature at 2 m (TEM) are important single meteorological factors that affect the variation of PM2.5 concentrations. The multiple wavelet coherence reveals that in scenarios where two meteorological factors are combined, the combination of TED-mean wind speed (WS) is the best combination to explain the variation in PM2.5 concentrations (AWC = 0.77, PASC = 41%). In the combination of three meteorological factors, TEM-WV-WS explained the variations of PM2.5 concentrations in the BTH region to the greatest degree (AWC = 0.89, PASC = 45%). Finally, the research shows that the variations of PM2.5 concentrations in the BTH region can be better explained by a combination of 2–3 meteorological factors, among which temperature and wind are the key meteorological factors. This research will provide a new window for the multi-scale variation characteristics and multi-factor control relationship of PM2.5 concentrations in the BTH region and provide a new insight for the prevention and control of air pollution. [ABSTRACT FROM AUTHOR]

In the context of the global Sustainable Development Goals, the study of tourism eco-efficiency (TE) becomes particularly important for the balance between environmental protection and economic development in tourist destinations. This paper improves the measurement method of tourism carbon emissions, uses the Super-SBM model of undesired output to measure China's TE, and then explores the impact of new urbanization (NU) on TE. The results show that TE in China is in dynamic equilibrium in general, the agglomeration characteristics of efficiency changed from high in the east and low in the west to low in the south and high in the north, and developmental differences first increased and then decreased. NU development has a significant one-way positive impact on TE at the national level and in the eastern region. As far as impact, economic urbanization plays a great role, and ecological factors become more and more important. NU has a rapid and long-term impact on TE, and its contribution rate to developed economic regions can reach 35%. This study will provide an important reference for sustainable development of tourism under the trend of urbanization. [ABSTRACT FROM AUTHOR]

Exploring the spatial network structure of tourism flow and its influencing factors is of great significance to the transmission of characteristic culture and the sustainable development of tourism in tourist destinations, especially in backward rural areas. Taking Qiandongnan Miao and Dong Autonomous Prefecture (hereinafter referred to as Qiandongnan Prefecture) as an example, this paper adopts social network analysis and Quadratic Assignment Procedure regression analysis to study the network structural characteristics and influencing factors of tourism flow using online travel blog data. The results show that: (1) There are seasonal changes in tourism flow, but the attractions that tourists pay attention to do not change with the seasons. (2) The tightness of the tourism flow network structure is poor. The core nodes are unevenly distributed, and there are obvious structural holes. (3) The density of the tourism flow network is low. There is a clear core–periphery structure in the network, and the core area has a weak driving effect on the periphery area. There are more cohesive subgroups in the network, but the degree of connectedness between the subgroups varies greatly. (4) Geographical adjacency, transportation accessibility, and tourism resource endowment influence tourism flow network structure. The study found that the influencing factors of tourism flow in rural areas are different from those in urban areas. These results provide useful information for the marketing and development of tourism management departments in rural areas. [ABSTRACT FROM AUTHOR]

The orderly circulation of land can affect the structure of the agricultural industry, improve the level of agricultural industrialization, and realize the sustainable development of agriculture. Located in the inland of southwest China, Chongqing is the core area of China's Three Gorges Reservoir area, with obvious mountain characteristics. The characteristics and influencing factors of land transfer here can guide the reformation of land policy in other rural areas. Therefore, based on the survey data of 1015 mountain farmers in Chongqing, this paper employs a multi-class logistic model to analyze the above issues. The results show the following: (1) The phenomena of "zero rent" and "non-agreement" are widespread, and the spontaneous internal transfer among farmers is the main influencing factor. The decline in land value, the low degree of foreign investment, and the low average level of farmers' understanding of land transfer policies are quite different from the economically developed plains in the east. (2) Different directions of land circulation have different influencing factors. (3) The main factors are the total population of rural households, the proportion of non-agricultural household income, the age of the head of the household, the education level of the head of the household, the degree of land division, and the quality of land grades that affect land transfer and development in mountainous areas. Thus, improving the education level or technological training of farmers, establishing effective market mechanisms, and increasing income from non-agricultural employment can effectively promote land transfer. Moreover, age-oriented land policy is easier to implement. [ABSTRACT FROM AUTHOR]

Landslides are one of the most severe and common geological hazards in the world. The purpose of this research is to establish a coupled landslide warning model based on random forest susceptibility zoning and precipitation. The 1520 landslide events in Fengjie County, Chongqing, China, before 2016 are taken as research cases. We adapt the random forest model to build a landslide susceptibility model. The antecedent effective precipitation model, based on the fractal relationship, is used to calculate the antecedent effective precipitation in the 10 days before the landslide event. Based on different susceptibility zones, the effective precipitation corresponding to different cumulative frequencies is counted as the threshold, and the threshold is adjusted according to the fitted curve. Finally, according to the daily precipitation, the rain warning levels in susceptibility zones are further adjusted, and the final prewarning model of the susceptibility zoning and precipitation coupling is obtained. The results show that the random forest model has good prediction ability for landslide susceptibility zoning, and the precipitation warning model that couples landslide susceptibility, antecedent effective precipitation, and the daily precipitation threshold has high early warning ability. At the same time, it was found that the precipitation warning model coupled with antecedent effective precipitation and the daily precipitation threshold has more accurate precipitation warning ability than the precipitation warning model coupled with the antecedent effective precipitation only; the coupling of the two can complement each other to better characterize the occurrence of landslides triggered by rainfall. The proposed coupled landslide early warning model based on random forest susceptibility and rainfall inducing factors can provide scientific guidance for landslide early warning and prediction, and improve the manageability of landslide risk. [ABSTRACT FROM AUTHOR]

This paper constructed the tourism and eco-environment index system, calculated the coupling and coordination relationship between them in Chongqing, from 2000 to 2017, by comparing 9 combination models; and identified the main obstacles through the obstacle model. The results showed that: (1) The comprehensive weighting method (CWM) has the highest accuracy, the coupling coordination mode (CCDM) is more adaptable; the CWM-CCDM is the most suitable. (2) The coupling degree changed from antagonism to run-in phase. (3) The coupling coordination degree improved annually, is in moderate coordination stage currently. (4) The tourism had greater obstacles; the main obstacles vary with time. [ABSTRACT FROM AUTHOR]

Eliminating poverty is the common mission of all mankind, and it is also an important task faced by many countries. Pro-poor tourism villages are an active attempt by China to use rural tourism to escape poverty. This paper aims to provide theoretical support for consolidating the results of poverty alleviation and achieving comprehensive poverty alleviation and to provide a scientific basis for policy formulation by using GIS spatial analysis to study the spatial distribution characteristics and influencing factors of 22,651 pro-poor tourism villages in China. The findings revealed that the spatial distribution of pro-poor tourism villages is roughly divided by the Hu line. Pro-poor tourism villages show an uneven agglomeration pattern and present a spatial pattern of dense southeast and sparse northwest with six high-density core areas, among which some cities in the southwest are H-H agglomeration areas. Specifically, topography, annual rainfall, endowment of tourism resources, location transportation, and policy orientation are important factors affecting the spatial distribution of pro-poor tourism villages. [ABSTRACT FROM AUTHOR]

Tourism poverty alleviation and ecological environments are closely associated with each other's dissipation structure, which contains various coordinated and noncoordinated coupling states. Based on the perspective of reverse thinking and problem diagnosis, this paper constructs a bridge from uncoordinated pathology to coordinated development. From the perspective of incongruity, the framework model and evaluation index system of tourism poverty alleviation and ecological environments incongruity coupling coordination driving mechanism are constructed. Also, the variation coefficient method is used to calculate the weight of each evaluation index and the coupling relationship and evolution of tourism poverty alleviation and ecological environments in Liupanshui city are analyzed by the noncoordination coupling function. The results suggest the following: (1) During the study period, the poverty alleviation level of tourism in Liupanshui city presents a continuous growth curve. Meanwhile, ecological environment development level depicts rapid growth initially and then slows down and improves further. In this way, it shows different stage characteristics from the tourism poverty alleviation level. (2) The discordant coupling between tourism poverty alleviation and ecological environments in Liupanshui city shows a decreasing curve. So, the noncoordinated development relationship between tourism poverty alleviation and ecological environments is significant. [ABSTRACT FROM AUTHOR]

• The ICGOS-SBM model was constructed with Super-SBM combining five development theories. • Explored the Spatiotemporal evolution characteristics of the YREB's high-quality development via the perspective of efficiency. • An innovative perspective for the measurement of high-quality development level introducing efficiency thinking was provided. • Multi-source data of 108 prefecture-level cities in the Yangtze River Economic Belt were collected and analyzed. High-Quality Development (HQD) can well meet human's growing needs for a better life, and it is an important manifestation of efficient, fair and sustainable development. It is a crucial turning point for China from high-speed development to HQD. A better understanding the HQD from perspective of efficiency is very important for the development of China. Using prefecture-level city panel data of China from 2005 to 2019, this study built a model coupled with innovation, coordination, greenness, openness, sharing, and slacks-based measure (ICGOS-SBM) based on the Super-SBM model of slack variables. By introducing efficiency thinking, this study measured the HQD level of the Yangtze River Economic Belt (YREB, one of driving forces spearheading China's HQD in a new era) from the perspective of development "quality", and explored its spatial and temporal distribution characteristics. The results showed that (a) the temporal HQD levels of the YREB presented an "N", pattern of rising first, then falling, and then rising; (b) the HQD levels exhibited noticeable regional heterogeneity a the different urban scale, and the development trend of the upper of YREB drove that of the middle and then that of the downstream; (c) the HQD levels of the YREB presented different degrees of spatial agglomeration, with an increasing trend over time, and the high-high agglomeration areas were mainly concentrated in the upper of the YREB with better natural endowments; and (d) the spatial HQD trajectory of the YREB mainly moved back and forth in the southwest-northeast direction, which may be due to its unstable development, showing a relatively obvious back-and-forth movement between Changde and Jingzhou. It aims to provide an innovative perspective for the measurement of HQD levels by introducing efficiency thinking. [ABSTRACT FROM AUTHOR]

An evaluation of the relationship between satellite-observed Normalized Difference Vegetation Index (NDVI) data as a proxy for vegetation greenness and water availability (rainfall and soil moisture) can greatly improve our understanding of how vegetation greenness responds to water availability fluctuations. Using Sen and Pearson's correlation methods, we analyzed the spatio-temporal variation of vegetation greenness for both the entire year and the growing season (GS,4-10) in northern China from 1982 to 2006. Although, vegetation greenness and soil moisture during the study period changed significantly for the entire study area, there was no change in rainfall. Linear correlation analysis between NDVI and rainfall revealed higher correlations using data for all seasons. Higher correlations for NDVI and soil moisture were obtained using growing season data. This study highlights how strongly vegetation greenness responds to water availability dynamics, especially in the growing season period. [ABSTRACT FROM AUTHOR]

Chinese agricultural production has grown rapidly over the past two decades. However, expanding large-scale production faces a sharp conflict with the supply of water resources. Meanwhile, to adapt to changes in consumer preferences and protect the environment, both the livestock and crop industries had to input more to achieve a high output of meat and grains and low graywater footprint emission. Using provincial panel data of China from 2008 to 2019, this study adopted a slacked-based model to measure the country's agricultural water use efficiency (AWUE) that considered graywater from crop and livestock production as an unexpected output. Based on the concept of sustainable development, using the graywater footprint as an undesired output included environmental pollution caused by agricultural production as part of the cost and could more accurately measure the water efficiency of current production. We also applied the Tobit model to identify the main factors influencing AWUE. Our results indicated the following. (1) Wealthy provinces produced more graywater than did poor provinces. If the province's gross domestic product climbed, the volume of graywater of livestock would surpass graywater of crops by a greater amount. (2) The AWUE in Southwest and South China fitted a "U" trend, while the remaining five regions showed an inverted U-shaped tendency. (3) To improve the AWUE, it is necessary to increase the crop area of economic crops and expand the scale of the livestock industry; compared with investment in irrigation infrastructure, investment in research and experimental development produces higher marginal benefits in enhancing the AWUE. (4) Environmental regulations inhibit the improvement of the AWUE, while irrigation infrastructure significantly improves the AWUE. • Agricultural water use efficiency (AWUE) in China's 7 regions was analyzed • Super-SBM model was applied for the evaluation of AWUE • Graywater footprints of crops and livestock were shown and compared • Temporal and spatial distribution patterns of AWUE were displayed • Driving forces of AWUE were identified [ABSTRACT FROM AUTHOR]

To understand the effect of submerged macrophytes on P in sediment, P fractions in the surface sediments (0–20 cm) of Potamogeton crispus, Potamogeton maackianus and non-vegetated areas were investigated. In the submerged macrophytes areas, the concentrations of HCl-P, NaOH-P, IP, OP and BD-P were significantly lower than in the non-vegetated area. NH4Cl-P did not differ significantly among areas. In the submerged macrophyte distribution areas, TP was significantly correlated with IP and OP. However, in the non-vegetated area, TP was significantly correlated with NH4Cl-P and OP. In all of the areas sampled, IP was the major phosphorus fraction in the sediments, which consists largely of NAOH-P and HCl-P. The decreasing order of P fractions was: IP > HCl-P > NaOH-P > OP > BD-P > NH4Cl-P. These results show that submerged macrophytes can decrease the concentrations of all P fractions and imply that submerged macrophytes play a key role in the retention of P nutrients. [ABSTRACT FROM PUBLISHER]

An important basis to achieve a sustainable balance between water availability and demand is effectively identifying the factors affecting water resource security and evaluating the effectiveness of existing water resource management measures. To reasonably evaluate water resource security in Guizhou Province, this study combined the water resource security features, selected the indicator system based on the Press–Status–Effect–Response (PSER) framework, and used Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and grey correlation analysis for the province from 2001 to 2015. This allowed us to identify the main driving factors affecting water resource security. The results showed that: (1) Water resource security in Guizhou Province showed an overall trend of improvement from 2001 to 2015 and reached a maximum index of 0.57 in 2015. This amelioration in water security was mainly due to the continuous improvement of the response and effect subgroup as a result of improvements in its existing subgroup factors (policies), such as water consumption per unit of gross domestic product (GDP), the proportion of water conservancy investment, and the proportion of the tertiary industry. Increased water stress due to rapid economic development, such as water supply for the reservoir, and the instability of the status subgroup, were the main factors negatively affecting water resource security. (2) Reduction of water consumption per USD of industrial value added, the control force of water and soil erosion being strengthened, and investment in water resources being increased, are the key factors for achieving water resource security in Guizhou during this period of rapid social and economic development. This indicates that the existing water resource management measures have been improving water resource security. The management measures need to be further improved in the future to protect water resource. [ABSTRACT FROM AUTHOR]