Water-resources Investigations Research Articles

Microbial community storm dynamics signal sources of "old" stream water.

Accurate characterization of the movement of water through catchments, particularly during precipitation event response, is critical for hydrological efforts such as contaminant transport modeling or prediction of extreme flows. Abiotic hydrogeochemical tracers are commonly used to track sources and ages of surface waters but provide limited details about transit pathways or the spatial dynamics of water storage and release. Alternatively, biotic material in streams is derived from thousands of taxa originating from a variety of environments within watersheds, including groundwater, sediment, and upslope terrestrial environments, and this material can be characterized with genetic sequencing and bioinformatics. We analyzed the stable water isotopes (δ18O and δ2H) and microbiome composition (16S rRNA gene amplicon sequencing) of the Marys River of western Oregon, USA during an early season storm to describe the processes, storage, and flowpaths that shape surface water hydrology. Stable water isotopes (δ18O and δ2H) typified an event response in which stream water is composed largely of 'old' water introduced to the catchment before the storm, a common though not well understood phenomenon. In contrast, microbial biodiversity spiked during the storm, consisting of early- and late-event communities clearly distinguishable from pre-event communities. We applied concentration-discharge (cQ) analysis to individual microbial taxa and found that most Alphaproteobacteria sequences were positively correlated (i.e., were mobilized) with discharge, whereas most sequences from phyla Gammaproteobacteria and Bacteroidota were negatively correlated with discharge (i.e., were diluted). Source predictions using the prokaryote habitat preference database ProkAtlas found that freshwater-associated microbes composed a smaller fraction of the microbial community during the stream rise and a larger fraction during the recession, while soil and biofilm-associated microbes increased during the storm and remained high during recession. This suggests that the "old" water discharged during the storm was likely stored and released from, or passed through, soil- and biofilm-rich environments, demonstrating that this approach adds new, biologically derived tracer information about the hydrologic pathways active during and after this event. Overall, this study demonstrates an approach for integrating information-rich DNA into water resource investigations, incorporating tools from both hydrology and microbiology to demonstrate that microbial DNA is useful not only as an indicator of biodiversity but also functions as an innovative hydrologic tracer.

Surface water monitoring from 1984 to 2021 based on Landsat time-series images and Google Earth Engine

Dynamic monitoring of surface water bodies is essential for understanding global climate change and the impact of human activities on water resources. Satellite remote sensing is characterized by large-scale monitoring, timely updates, and simplicity, and it has become an important means of obtaining the distribution of surface water bodies. This study is based on a long time-series Landsat satellite images and the Google Earth Engine (GEE) platform, focusing on Anhui Province in China, and proposes a method for extracting surface water that combines water indices, Bias-Corrected Fuzzy Clustering Method (BCFCM), and OTSU threshold segmentation. The spatial distribution of surface water in Anhui Province was obtained from 1984 to 2021, and further analysis was conducted on the spatiotemporal characteristics of surface water in each city and three major river basins within the province. The results indicated that the overall accuracy of water extraction in this study was 94.06 %. Surface water in Anhui was most abundant in 1998 and least in 2001, with more distribution in the south than in the north. Northern Anhui is dominated by rivers, while southern Anhui has more lakes. Permanent surface water with an inundation frequency of above 75 % covered approximately 4341 km2, accounting for 32.03 % of the total water, while seasonal water with an inundation frequency between 5 % and 75 % covered about 6661 km2, accounting for 49.15 % of the total water, others were considered temporary surface water. By comparing our results with the global annual surface water released by the Joint Research Centre (JRC), we found that our study performed better in extracting lakes and rivers in terms of completeness, but the extraction results for aquaculture areas were slightly less than the JRC dataset. Overall, the long-term surface water dataset established in this study can effectively supplement the existing datasets and provide important references for regional water resource investigation, management, as well as flood monitoring.

Snow Depth Estimation and Spatial and Temporal Variation Analysis in Tuha Region Based on Multi-Source Data

In the modelling of hydrological processes on a regional scale, remote-sensing snow depth products with a high spatial and temporal resolution are essential for climate change studies and for scientific decision-making by management. The existing snow depth products have low spatial resolution and are mostly applicable to large-scale studies; however, they are insufficiently accurate for the estimation of snow depth on a regional scale, especially in shallow snow areas and mountainous regions. In this study, we coupled SSM/I, SSMIS, and AMSR2 passive microwave brightness temperature data and MODIS, TM, and Landsat 8 OLI fractional snow cover area (fSCA) data, based on Python, with 30 m spatially resolved fractional snow cover area (fSCA) data obtained by the spatio-temporal dynamic warping algorithm to invert the low-resolution passive microwave snow depths, and we developed a spatially downscaled snow depth inversion method suitable for the Turpan–Hami region. However, due to the long data-processing time and the insufficient arithmetical power of the hardware, this study had to set the spatial resolution of the result output to 250 m. As a result, a day-by-day 250 m spatial resolution snow depth dataset for 20 hydrological years (1 August 2000–31 July 2020) was generated, and the accuracy was evaluated using the measured snow depth data from the meteorological stations, with the results of r = 0.836 (p ≤ 0.01), MAE = 1.496 cm, and RMSE = 2.597 cm, which are relatively reliable and more applicable to the Turpan–Hami area. Based on the spatially downscaled snow depth data produced, this study found that the snow in the Turpan–Hami area is mainly distributed in the northern part of Turpan (Bogda Mountain), the northwestern part of Hami (Barkun Autonomous Prefecture), and the central part of the area (North Tianshan Mountain, Barkun Mountain, and Harlik Mountain). The average annual snow depth in the Turpan–Hami area is only 0.89 cm, and the average annual snow depth increases with elevation, in line with the obvious law of vertical progression. The annual mean snow depth in the Turpan–Hami area showed a “fluctuating decreasing” trend with a rate of 0.01 cm·a−1 over the 20 hydrological years in the Turpan–Hami area. Overall, the spatially downscaled snow depth inversion algorithm developed in this study not only solves the problem of coarse spatial resolution of microwave brightness temperature data and the difficulty of obtaining accurate shallow snow depth but also solves the problem of estimating the shallow snow depth on a regional scale, which is of great significance for gaining a further understanding of the snow accumulation information in the Tuha region and for promoting the investigation and management of water resources in arid zones.

Assessing Groundwater Quality for Sustainable Drinking and Irrigation: A GIS-Based Hydro-Chemical and Health Risk Study in Kovilpatti Taluk, Tamil Nadu

The continuous investigation of water resources is essential to assess pollution risks. This study investigated a groundwater assessment in the coastal belt of Tamil Nadu’s Kovilpatti Taluk, Thoothukudi district. Twenty-one groundwater samples were collected during the pre-monsoon and post-monsoon seasons, analyzing water quality parameters, namely pH, EC, Cl−, SO42−, Ca2+, Mg2+, HCO3−, TH, Na2+, and K+. The Water Quality Index (WQI) was computed and it is observed that 5% of pre-monsoon and 9% of post-monsoon samples were unsuitable for drinking. SAR, MHR, RSC, %Na and Kelley’s index were used to determine irrigation suitability. Pre-monsoon shows 29% (MHR) and 71% (RSC) unsuitable, and post-monsoon shows 59% (MHR) and 9% (RSC) unsuitable. Coastal activity, urbanization, and industrialization in Kovilpatti resulted in the degradation of groundwater quality. Solving this coastal issue requires sustainable wastewater treatment and strict industrial discharge guidelines. Spatial distribution plots, Box plots, Gibbs plots, Piper plots, Wilcox plots and Correlation Matrices had similar results to the computed WQI and its physical–chemical parameters. According to the human health risk assessment, the Mooppanpatti, Illuppaiurani, and Vijayapuri regions show high health risks due to the nitrate and fluoride concentration in the groundwater. Kadambu, Melparaipatti, Therkuilandhaikulam, and Vadakku Vandanam have low levels, posing a minimal health risk.

Identification of potential zones on the estimation of direct runoff and soil erosion for an ungauged watershed based on remote sensing and GIS techniques

An investigation of soil and water resources is essential to determine the future scenario of water management and water resources to attain food and water security. The improper management of watersheds results in a huge amount of sediment loss and surface runoff. Therefore, the present study was carried out to estimate the surface runoff and soil erosion using the Soil Conservation Service Curve Number (SCS-CN) method and RUSLE approach, respectively. These have been estimated using geospatial technologies for the ungauged Mandri river watershed from the Kanker district of Chhattisgarh State in India. The runoff potential zones, which are defined by the area's impermeable surfaces for a given quantity of precipitation were identified based on curve numbers at the sub-watershed levels. The land use data were collected from LISS IV images of 2009. The results showed that the average volume of runoff generated throughout the 16 years (2000-2015) was 14.37 million cubic meters (mM3). While average annual soil loss was found to be 17.23 tons/ha/year. Most of the eroded area was found to be around the major stream in a drainage system of Mandri River and on higher slopes of the terrain in the watershed. This study revealed that surface runoff and soil erosion are primary issues, which adversely affected the soil and water resources in this watershed. Therefore, suitable water harvesting sites and structures can be constructed based on the potential runoff zone and severity of soil erosion to conserve the soil and water in the watershed.

A thermodynamics-based versatile evapotranspiration estimation method of minimum data requirement for water resources investigations

A recent, two-parameter version of the thermodynamically derived complementary relationship (CR) of evaporation has been tested on a monthly basis at 124 FLUXNET stations around the globe. Local, station-by-station calibration explained 91% (R2) of the variance in eddy-covariance (EC) obtained latent-heat fluxes with the same Nash-Sutcliffe efficiency (NSE) value. When the dimensionless Priestley-Taylor parameter (α) was expressed as a universal function (f) of the estimated wet-environment air temperature (Tw), station-by-station calibration of the single dimensionless parameter, b (accounting for moisture advection), yielded an R2 value of 87% and NSE of 86%. Global calibration (all stations at once) of the two-parameter CR version yielded R2 = 82% and NSE = 81%, while the single-parameter version produced R2 = 81% and NSE = 79%. With a representative value (between the locally calibrated mode and mean) of b set equal to two, the thus, calibration-free CR still maintained an R2 of 80% and NSE of 78%, which is significantly better than Morton’s calibration-free WREVAP model (i.e., 71% and 55%, respectively). The advantage of the current CR model is that it can be employed in a fully calibration-free mode, similar to WREVAP, yet with available EC measurements or water-balance derived latent-heat fluxes the single [b, when α = f(Tw) is chosen] or two parameters (α and b) of the model can be easily calibrated within the respective 1 – 1.32 and 1 – 10 intervals, for further improved performance.

A Quantitative Approach to the Watershed Governance Prism: The Duero River Basin, Mexico

Advances have been made in water resource investigation due to the implementation of mathematical models, the development of theoretical frameworks, and the evaluation of sustainability indices. Together, they improve and make integrated water resource management more efficient. In this paper, in the study area of the Duero River Basin, located in Michoacan, Mexico, we schematize a series of numerical indices of the Watershed Governance Prism to determine the quantitative status of water governance in a watershed. The results, presented as axes, perspectives, and prisms in the Axis Index, Water Governance Index, and Watershed Governance Prism Index, provide the conclusion that it is possible to establish and evaluate the Watershed Governance Prism Index using our numerical implementation of the Watershed Governance Prism theoretical framework. Thus, it is possible to define a quantitative status and evoke how water governance is being designed and implemented in a watershed.

Evaluation of Terrestrial Water Storage Changes and Major Driving Factors Analysis in Inner Mongolia, China.

Quantitative assessment of the terrestrial water storage (TWS) changes and the major driving factors have been hindered by the lack of direct observations in Inner Mongolia, China. In this study, the spatial and temporal changes of TWS and groundwater storage (GWS) in Inner Mongolia during 2003-2021 were evaluated using the satellite gravity data from the Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow On combined with data from land surface models. The results indicated that Inner Mongolia has experienced a widespread TWS loss of approximately 1.82 mm/yr from 2003-2021, with a more severe depletion rate of 4.15 mm/yr for GWS. Meteorological factors were the driving factors for water storage changes in northeastern and western regions. The abundant precipitation increased TWS in northeast regions at 2.36 mm/yr. Anthropogenic activities (agricultural irrigation and coal mining) were the driving factors for water resource decline in the middle and eastern regions (especially in the agropastoral transitional zone), where the decrease rates were 4.09 mm/yr and 3.69 mm/yr, respectively. In addition, the severities of hydrological drought events were identified based on water storage deficits, with average severity values of 17 mm, 18 mm, 24 mm, and 33 mm for the west, middle, east, and northeast regions, respectively. This study established a basic framework for water resource changes in Inner Mongolia and provided a scientific foundation for further water resources investigation.

Hydrological and water resources investigations of the Mereb-Gash river basin in Eritrea

Introduction. Adaptation and mitigation of climate change and its consequences through effective water resources management, among others, is essential for achieving sustainable development goals. The construction of water infrastructure facilities and the maintenance of existing ones which can be done with up-to-date hydrological information are required. Therefore, this study aims at obtaining unique information and choosing effective tools for stream flow simulations in Mereb-Gash river basin.
 
 Materials and methods. To this end, physically-based semi-distributed and conceptual models are investigated using climate reanalysis datasets and geomorphologic catchment characteristics. Prior to feeding model forcing variables, their statistical and spatial patterns, methods of potential evapotranspiration estimations, and basin drought conditions are studied. Two or more approaches have been employed for each of these tasks.
 
 Results. GIUH-Nash model has the potential to produce acceptable values in most cases irrespective of sources and resolutions of digital elevation models, but it is found to be sensitive to the type of algorithms selected for stream network generations. The continuous simulation models reveal considerable overestimation of most of the precipitation in the reanalysis datasets, which in turn has a significant effect on other variables, such as potential evapotranspiration and thereby leading to a substantial discrepancy between simulated and observed.
 
 Conclusions. Despite the fact that reanalysis dataset has a great advantage over ground-based observations in terms of their simplicity and accessibility, the research results have shown the need for a critical attitude to both sources of initial data. To minimize the uncertainties of mathematical models and thereby to improve modeling capabilities, there is no qualitative alternative to restoring existing as well as new ground-based observation stations.

Water extraction from SAR images based on improved geodesic active contour.

The rapid and accurate acquisition of water body information is of great significance to water resource investigation, flood disaster monitoring, ecological environment protection, and other fields. In this paper, the water boundary is optimized and extracted from single-polarization SAR images based on an improved geodesic active contour model (IMGAC). Firstly, the rough extraction results of the water body were obtained according to the adaptive threshold, and then a narrowband model was established, and the signed pressure force (SPF) function was introduced into the geodesic active contour (GAC) model. Finally, the optimal water boundary was obtained through continuous iteration. Compared with the active contour (AC) model without edge and the traditional GAC model, the results show that the IMGAC model proposed in this paper can reduce the calculation efficiency and improve the accuracy of water boundary detection. The F-measure index was used to evaluate the extraction accuracy of the three methods. IMGAC method had the highest extraction accuracy, which was 96.43%. The kappa coefficient reached 0.929. The F-measure index was 96.20%. Our study can provide a reference for water extraction and water boundary optimization.

Structural breviary about the social construction of scientific water knowledge at Mexico: An approach

The unbridled forces in play that are undermining our social fabric (climate change, pandemics, poverty) erode societies’ capabilities for resilience. Hence there is an urgent need to evaluate the strengths of institutional and community systems in vital areas such as water management. This research analyzed part of the social structure responsible for generating scientific knowledge pertaining to water resources in Mexico, taking into account the organizational patterns pre-established by experts, in order to determine the strengths and weaknesses of the existing structures. We used the social networks approach, which revealed a system permeated by patterns of social centralization that limit knowledge sharing and social cohesion and produce very little innovation within the water resources investigation networks in Mexico. We conclude that it is necessary to expand the training and managing of intellectual capital in various areas of knowledge related to water resources, especially those that are relevant for recuperating environmental sustainability.

Contribution of biostratigraphy to the investigation of water resources. A Case study of the Abiod Formation in the Serj and Fahs areas (Northern Tunisia)

Contribution of biostratigraphy to the investigation of water resources. A Case study of the Abiod Formation in the Serj and Fahs areas (Northern Tunisia)

Surface Water Change Detection via Water Indices and Predictive Modeling Using Remote Sensing Imagery: A Case Study of Nuntasi-Tuzla Lake, Romania

Water body feature extraction using a remote sensing technique represents an important tool in the investigation of water resources and hydrological drought assessment. Nuntasi-Tuzla Lake, a component of the Danube Delta Natural Reserve, is located on the Romanian Black Sea littoral. On account of an event in summer 2020, when the lake surface water decreased significantly, this study aims to identify the variation of the Nuntasi-Tuzla Lake surface water over a long-term period in correlation with human intervention and climate change. To this end, it provides an analysis in the period 1965–2021 via hydrological drought indices and data mining classification. The latter approach is based on several water indices derived from Landsat TM/ETM+/OLI and MODIS full-time series datasets: Normalized Difference Vegetation Index (NDVI), Normalized Difference Vegetation Index (NDVI), Modified NDWI (MNDWI), Weighted Normalized Difference Water Index (WNDWI), and Water Ratio Index (WRI). The experimental results indicate that the proposed classification methods can extract relevant features from waterbodies using remote sensing imagery with a high accuracy. Moreover, the study shows a similarity in the evolution of surface water cover identified with the data mining classification and the drought periods detected in the flow data series for the Nuntasi and Sacele Rivers that supply the Nuntasi-Tuzla Lake. Overall, the results of our investigation show that human intervention and hydrological drought had an extensive impact on the long-term changes in surface water of the Nuntasi-Tuzla Lake.

Lightweight Deep Neural Network Method for Water Body Extraction from High-Resolution Remote Sensing Images with Multisensors.

Rapid and accurate extraction of water bodies from high-spatial-resolution remote sensing images is of great value for water resource management, water quality monitoring and natural disaster emergency response. For traditional water body extraction methods, it is difficult to select image texture and features, the shadows of buildings and other ground objects are in the same spectrum as water bodies, the existing deep convolutional neural network is difficult to train, the consumption of computing resources is large, and the methods cannot meet real-time requirements. In this paper, a water body extraction method based on lightweight MobileNetV2 is proposed and applied to multisensor high-resolution remote sensing images, such as GF-2, WorldView-2 and UAV orthoimages. This method was validated in two typical complex geographical scenes: water bodies for farmland irrigation, which have a broken shape and long and narrow area and are surrounded by many buildings in towns and villages; and water bodies in mountainous areas, which have undulating topography, vegetation coverage and mountain shadows all over. The results were compared with those of the support vector machine, random forest and U-Net models and also verified by generalization tests and the influence of spatial resolution changes. First, the results show that the F1-score and Kappa coefficients of the MobileNetV2 model extracting water bodies from three different high-resolution images were 0.75 and 0.72 for GF-2, 0.86 and 0.85 for Worldview-2 and 0.98 and 0.98 for UAV, respectively, which are higher than those of traditional machine learning models and U-Net. Second, the training time, number of parameters and calculation amount of the MobileNetV2 model were much lower than those of the U-Net model, which greatly improves the water body extraction efficiency. Third, in other more complex surface areas, the MobileNetV2 model still maintained relatively high accuracy of water body extraction. Finally, we tested the effects of multisensor models and found that training with lower and higher spatial resolution images combined can be beneficial, but that using just lower resolution imagery is ineffective. This study provides a reference for the efficient automation of water body classification and extraction under complex geographical environment conditions and can be extended to water resource investigation, management and planning.

Accurate extraction of surface water in complex environment based on Google Earth Engine and Sentinel-2.

To realize the accurate extraction of surface water in complex environment, this study takes Sri Lanka as the study area owing to the complex geography and various types of water bodies. Based on Google Earth engine and Sentinel-2 images, an automatic water extraction model in complex environment(AWECE) was developed. The accuracy of water extraction by AWECE, NDWI, MNDWI and the revised version of multi-spectral water index (MuWI-R) models was evaluated from visual interpretation and quantitative analysis. The results show that the AWECE model could significantly improve the accuracy of water extraction in complex environment, with an overall accuracy of 97.16%, and an extremely low omission error (0.74%) and commission error (2.35%). The AEWCE model could effectively avoid the influence of cloud shadow, mountain shadow and paddy soil on water extraction accuracy. The model can be widely applied in cloudy, mountainous and other areas with complex environments, which has important practical significance for water resources investigation, monitoring and protection.

Investigation and assessment of ecological water resources in the salt marsh area of a salt lake: A case study of West Taijinar Lake in the Qaidam Basin, China

The water ecology of salt marshes plays a crucial role in climate regulation, industrial production, and flood control. Due to a poor understanding of water ecology and the extensive mining of salt resources, concerns are mounting about declining groundwater levels, shrinking salt marshes, and other problems associated with the simple yet extremely fragile water ecosystem of salt marshes in arid salt lake areas. This study assessed the ecological status of water resources in the downstream salt marsh area of West Taijinar Lake in the Qaidam Basin, China (2010-2018). Using data from a field investigation, the water ecosystem was divided into an ecological pressure subsystem, an environmental quality subsystem, and a socio-economic subsystem according to an analytic hierarchy process. Each subsystem was quantitatively assessed using the ecological footprint model, the single-factor index, and available data for the salt marsh area. The results showed that water resources were always in a surplus state during the study period, whose development and utilization had a safe status. Surface water had low plankton diversity with no evidence of eutrophication, but its Cl- and SO42- concentrations were too high for direct industrial water uses. Groundwater quality was classified into class V because of high salt concentrations, which could be considered for industrial use given the demand of industrial production. The socio-economic efficiency of water resources was high, as distinguished by decreased water consumption per 10,000 yuan GDP and excellent flood resistance. In conclusion, the ecological status of water resources was deemed good in the study area and this could help sustain regional development. However, since the water ecology in this area is mainly controlled by annual precipitation, it would be challenging to deal with the uneven distribution of precipitation and flood events and to make full use of them for groundwater recharge. This study provides insight into the impact of salt lake resource exploration on water ecology, and the results can be useful for the rational utilization of water resources in salt marshes in other arid areas.

Generation of a long-term daily gridded precipitation dataset for the Upper Indus Basin (UIB) through temporal Reconstruction, Correction & Informed Regionalization-“ReCIR”

This study attempted to generate a long-term (1961–2010) daily gridded precipitation dataset for the Upper Indus Basin (UIB) with orographic adjustments so as to generate realistic precipitation estimates, enabling hydrological and water resource investigations that can close the water balance, that is difficult, if not impossible to achieve with the currently available precipitation data products for the basin. The procedure includes temporal reconstruction of precipitation series at points where data were not recorded prior to the mid-nineties, followed by a regionalization of the precipitation series to a smaller scale across the basin (0.125 ° × 0.125 °), while introducing adjustments for the orographic effect and changes in glacier storage. The reconstruction process involves interpolation of the precipitation at virtual locations of the current (1995-) dense observational network, followed by corrections for frequency and intensity and adjustments for temporal trends at these virtual locations. The data generated in this way were further validated for temporal and spatial representativeness through evaluation of SWAT-modelled streamflow responses against observed flows across the UIB. The results show that the calibrated SWAT-simulated daily discharge at the basin outlet as well as at different sub-basin outlets, when forcing the model with the reconstructed precipitation of years 1973–1996, is almost identical to that when forcing it with the reference precipitation data (1997–2008). Finally, the spatial distribution pattern of the reconstructed (1961–1996) and reference (1997–2008) precipitation were also found consistent across the UIB, reflecting well the large-scale atmospheric-circulation pattern in the region.

Harmonic Noise-Elimination Method Based on the Synchroextracting Transform for Magnetic-Resonance Sounding Data

Magnetic-resonance sounding (MRS) is a direct, quantitative, accurate, and efficient technology that has been applied in the fields of groundwater detection, regional water-resource investigation, and geological-disaster-risk early warning. However, owing to strong environmental noise, the signal-to-noise ratio (SNR) of data collected by MRS instruments is low; thus, providing reliable results for subsequent hydrological interpretation is difficult. To solve this issue, we propose a method based on the synchroextracting transform (SET) to eliminate harmonic noise from MRS data in an environment with strong noise. Compared with the harmonic modeling cancellation (HMC) and three existing data processing algorithms, the SET can effectively eliminate the harmonic noise in a single record and process multiple types of harmonic noise in stacked data at a time. The calculation amount and time are much lower than those of the HMC algorithm, and the calculation accuracy is similar to that of the HMC algorithm. More importantly, after the harmonics are eliminated by the SET method, the impact on the free induced decay (FID) signal is small, whereas the other three methods severely distort the FID signal. Considering that FID signals may exhibit the characteristics of multiexponential decay and that its Larmor frequency is close to a certain harmonic frequency, we study the applicable scope of the SET. Finally, by processing the results of field-measured data, the validity and practicability of SET are further verified. We also discuss the advantages of the SET method and existing problems to provide future research directions.

Research on Ecological Environmental Protection and Utilization of Water Resource—Investigation and Data Analysis on Ecological Practice of Five Villages in Jiangsu, Jiangxi, Hubei, Hunan and Gansu

Zhang, Y.X., 2020. Research on ecological environmental protection and utilization of water resource—investigation and data analysis on ecological practice of five villages in Jiangsu, Jiangxi, Hubei, Hunan and Gansu. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 522-525. Coconut Creek (Florida), ISSN 0749-0208.Based on the ecology practice condition investigation and data analysis in five villages from five provinces of Jiangsu, Jiangxi, Hubei, Hunan and Gasu, the rural ecological practice and relevant water resource protection regulations implementation present situation were analyzed. In this paper, it was discussed that there was regional differences about water resource protection regulation and the importance of the rural farmers to “green water and green mountains” and “gold and silver mountains”, and the deeper problems of the ineffective transformation from “green water and green mountains” to “gold and silver mountains”. Accordingly, corresponding countermeasure proposal was put forward. To build an ecological civilization, we should lead economic benefits with ecological benefits, turn ecological environmental advantages into advantages in ecological agriculture, ecological industry, ecological tourism and other ecological economies, promote the transformation of green water and green mountains into gold and silver mountains, create a beautiful ecological environment for China's economic development, and create good material conditions for China's residents' income.

Integrated Water Resources Research: Advancements in Understanding to Improve Future Sustainability

Anthropogenic and natural disturbances to freshwater quantity and quality is a greater issue for society than ever before. To successfully restore water resources in impaired watersheds requires understanding the interactions between hydrology, climate, land use, water quality, ecology, social and economic pressures. Current understanding of these interactions is limited primarily by a lack of innovation, investment, and interdisciplinary collaboration. This Special Issue of Water includes 18 articles broadly addressing investigative areas related to experimental study designs and modeling (n = 8), freshwater pollutants of concern (n = 7), and human dimensions of water use and management (n = 3). Results demonstrate the immense, globally transferable value of the experimental watershed approach, the relevance and critical importance of current integrated studies of pollutants of concern, and the imperative to include human sociological and economic processes in water resources investigations. Study results encourage cooperation, trust and innovation, between watershed stakeholders to reach common goals to improve and sustain the resource. The publications in this Special Issue are substantial; however, managers remain insufficiently informed to make best water resource decisions amidst combined influences of land use change, rapid ongoing human population growth, and changing environmental conditions. There is thus, a persistent need for further advancements in integrated and interdisciplinary research to improve scientific understanding, management and future sustainability of water resources.