Changes In Water Resources Research Articles

WATER RESOURCES MODELING UNDER CLIMATE CHANGE

Modeling of changes in water resources in the Chirchik river basin in the past, present, and futurehas been carried out. Changes in river basin flow dynamics showed an increase in the proportion of precipitation frequency change by 2030 (2020–2039), 3050 (2040–2069) and 2070 under two IPCC scenarios (RCP4.5 and RCP8.5). Although there is a tendency to increase water flow in the Chirchik River basin under climate change scenarios, it was found that due to the uneven distribution of water resources in the future, the available water may not be sufficient based on the needs of water users in the basin.

Analysis of the Water Resource Carrying Capacity in Guyuan City

To assess the water resource carrying capacity of Guyuan City, an analysis was conducted using the load index method, principal component analysis, and ecological water footprint method. A comprehensive analysis was carried out using these three methods to evaluate the current state of water resource carrying capacity in Guyuan City. The results indicate that the water resource carrying capacity in Guyuan City is mainly influenced by economic development factors, water supply–demand balance factors, and natural factors. During the period from 2002 to 2016, the water resource carrying capacity fluctuated in response to changes in the total water resources. However, from 2016 to 2021, it exhibited an increasing trend due to improvements in water resource utilization efficiency and effective water conservation measures. However, the water resource carrying capacity remains at a relatively low level, and it has consistently been in an overloaded state, with the development and utilization of water resources approaching their limits. Water scarcity in Guyuan City is a pressing concern, characterized by severe limitations on its potential for development and utilization. The persistent supply–demand imbalance is anticipated to impede the region’s pursuit of high-quality economic development in the foreseeable future.

The impact of human activities on blue-green water resources and quantification of water resource scarcity in the Yangtze River Basin

Under the influence of climate change and human activities, water scarcity and uneven spatial distribution have become critical factors constraining societal development and threatening ecological security. Accurately assessing changes in blue and green water resources (BW and GW) caused by human activities can reveal the actual situation of water scarcity. However, previous research often overlooked the calibration of GW and human water usage, and it rarely delved into the primary human factors leading to water scarcity and potential impact mechanisms. Therefore, based on the PCR-GLOBWB model that considers human impacts, and with reasonable calibration of B/GW and human water usage, hydrological processes were simulated under both human-influenced and natural conditions. A comprehensive assessment of the impact of human activities on BW and GW was conducted. The results show that: (1) BW and GW exhibit a spatial pattern of increasing from northwest to southeast in the basin. From 1961 to 2020, the proportion of BW showed an upward trend, while GW was decreasing; (2) The impact of human activities on changes in water resources is mainly concentrated in the midstream and dowmstream of the basin. Due to human influences, the green water flow (GWF) increased by 3–24.4 mm, and the BW volume increased by 67.2–146.4 mm. However, the green water storage (GWS) decreased by 5.6–75.4 mm; (3) The impact of human activities on blue water scarcity (BWscarcity) is significantly greater than green water scarcity (GWscarcity). The worsening of GWscarcity does not exceed 0.2, while areas where BW reaches significant deterioration (BWscarcity > 1.5) account for 1.3 %, 9.8 %, and 17 % of the upstream, midstream and downstream, respectively. (4) Irrigation activities are the main factor causing water resource scarcity. In the future, it is important to reasonably develop the potential for GW utilization and optimize BW management measures to address water resource crises.

Improvement of the Soil and Water Assessment Tool Model and Its Application in a Typical Glacial Runoff Watershed: A Case Study of the Qarqan River Basin, China

The composition of runoff in the basins located in the arid region of Northwest China is complex. How to better simulate and analyze the hydrological process and runoff situation of the basin through hydrological models is the key to the effective management of the regional water resources. This study focused on the Qarqan River Basin in Xinjiang, which is a typical river originating from glaciers and crucial for maintaining the oasis ecology in the downstream Tarim River. Based on the original SWAT model, a SWAT-Gla model containing a new glacier module was constructed according to the characteristics of the basin. After simulating, parameter calibration, and verification of the models, it was found that during the calibration period (1975–2009) and verification period (2010–2019), the R2, NSE, and PBIAS results of the SWAT-Gla model were much better than the original SWAT model. Moreover, SWAT-Gla could also simulate the runoff much better, especially in the peak and recession parts of the hydrograph compared with the original SWAT model. It was found that SWAT-Gla could better describe the runoff process in the basin where glacier recharge was the main component of runoff. Further, the analysis revealed that over the past 50 years, glacier and snowmelt water contributed to approximately 80% of the total basin recharge, which predominantly occurred from March to September. The volume of glacier meltwater exhibited a strong correlation with temperature, with both demonstrating an upward trend. The simulation found that in terms of groundwater, the groundwater recharge in the Qarqan River was relatively stable, stabilizing at 13% over the past 30 years, and groundwater recharge was mainly distributed in spring and summer, accounting for about 95% in total. Overall, we observed an increasing trend in the replenishment of glacial meltwater in both the surface runoff and groundwater in the basin. Therefore, it is essential to pay more attention to the future changes in water resources in the basin to ensure the sustainable development of water resources.

Analysis of Changes in Rainfall Concentration over East Africa

Understanding the spatial and temporal distribution of precipitation is important in agriculture, water management resources, and flood disaster management. The present study analyzed the changes in rainfall concentration over East Africa (EA). Three matrices—the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP)—were used to examine the changes in rainfall during 1981–2021. The changes in spatial variance annually and during two seasons, namely, “long rains” (March to May [MAM]) and “short rain” (October to December [OND]), were estimated using an empirical orthogonal function (EOF). The study employed the robust statistical metrics of the Theil–Sen estimator to detect the magnitude of change and modified Mann–Kendall (MMK) to examine possible changes in rainfall concentration. The localized variation of the power series within the series for PCI, PCD, and PCP variability was performed using the continuous wavelet transform. The findings showed that the concentration of rainfall patterns of EA occurred in four months of the total months in a year over most parts, with the western sides experiencing uniform rainfall events throughout the year. The EOF analysis revealed a homogeneous negative pattern during the MAM season over the whole region for PCD, PCI, and PCP for the first mode, which signified reduced rainfall events. Moreover, the MMK analysis showed evidence of declining trends in the PCD annually and during the MAM season, while the opposite tendency was noted for the OND season where an upward trend in the PCD was observed. Interestingly, areas adjacent to Lake Victoria in Uganda and Lake Tanganyika in Tanzania showed increasing trends in the PCD for annual and seasonal time scales. The analysis to characterize the rainfall cycle and possible return period, considering the indices of PCD, PCI, and PCP, showed higher variability during the year 2000, while much variability was presented in the PCP for the annual period. During the MAM and OND seasons, a 1-year band as a dominant period of variability was observed in all the indices. Overall, the findings of the present study are crucial in detecting the observed changes in rainfall concentration for avoiding the loss of life and property, as well as for coping with potential changes in water resources.

Spatial and temporal downscaling schemes to reconstruct high-resolution GRACE data: A case study in the Tarim River Basin, Northwest China

Climate change and excessive exploitation of water resources exert pressure on groundwater supply and the ecosystem in drylands. Although The Gravity Recovery and Climate Experiment (GRACE) satellites has demonstrated the feasibility of quantifying global groundwater storage variations, monitoring regional-scale groundwater has been challenging due to the coarse resolution of GRACE. Previous GRACE downscaling studies focused on develop new algorithms based on the perspective of pixel spatial correlation to improve resolution, which cannot better capture the temporal evolution of GRACE data effectively. In this study, we employ the semi-supervised variational autoencoder (SSVAER) algorithm and the multi-scale geographically weighted regression (MGWR) model to establish two different downscaling schemes: pixel temporal continuity downscaling and pixel spatial correlation downscaling. These schemes achieve spatial resolution downscaling of GRACE-derived groundwater storage anomalies (GWSA) from 0.5° to 0.1°. Additionally, the applicability of the PCR-GLOBWB model in drylands is verified. Furtherly, the spatiotemporal distribution patterns of GWSA are analyzed. The results show that (1) Both the temporal and spatial downscaling methods produced consistent results, with data correlations ranged from 0.94 to 0.98 observed in over 80 % of the range before and after downscaling; (2) The groundwater storage change rate in the northern Tarim River Basin (TRB) is 25 times greater than the model results, while in other regions, the average deviation is 2.6 times; (3) The two schemes enhance the correlation (0.27) between GWSA and groundwater level anomaly (GWLA) to 0.59 and 0.52, respectively, with a three-month lag in GWSA relative to GWLA. The temporal downscaling approach exhibited higher CC and lower RMSE, outperforming the spatial downscaling approach. The high-resolution results in this study can well complement groundwater level prediction efforts in arid regions and provide quantitative information for local water resource management.

Forecasting and meta-features estimation of wastewater and climate change impacts in coastal region using manifold learning

South Asia's coastlines are the most densely inhabited and economically active ecosystems have already begun to shift due to climate change. Over the past century, climate change has contributed to a gradual and considerable rise in sea level, which has eroded shorelines and increased storm-related coastal flooding. The differences in estuary water quality over time, both seasonally and annually, have been efficiently controlled by changes in stream flow. Assessment requires digitized analytical platforms to lower the risk of catastrophes associated with climate change in coastal towns. To predict future changes in an area's vulnerability and waste planning decisions, a prospective investigation requires qualitative and quantitative scenarios. The paper concentrates on the development of a forecasting platform to evaluate the climate change and waste water impacts on the south coastal region of India. Due to the enhancement of Digitization, a multi-model ensemble combined with manifold learning is implemented on the multi-case models influencing the uncertainty probability rate of 23% and can be ignored with desired precaution on the coastal environmental. Because Manifold Learning Analysis results cannot be utilized directly in wastewater management studies because of their inherent biases, a statistical bias correction and meta-feature estimation have been implemented. Within the climate-hydrology modeling chain, the results demonstrate a wide range of expected changes in water resources in some places. Experimental statistics reveal that the forecasted rate of 91.45% will be the better choice to reduce the uncertainty of climatic change and wastewater management.

Study on Evaluation of Order Degree of Water Resources Coupling System Considering Time Series Characteristics—Take Jiangxi Province as an Example

In recent years, the order evaluation method of a coupled system based on synergetics has been successfully applied in the field of water resources evaluation and management. The evaluation of system order degree needs to comprehensively consider the simple giant system entropy of multiple order parameters. At this stage, the calculation of simple giant system entropy ignores the time series characteristics of order parameters, which makes the evaluation results of system order degree deviate from the actual changes of the system. Therefore, considering the time factor in the entropy calculation of a simple giant system, this paper proposes a synergetic order evaluation method considering the characteristics of time series. Then, taking Jiangxi Province as the research object, an example of a comprehensive evaluation of the order degree of the water resources coupling system is carried out. The relevant experimental results show that: The evaluation results of the synergetic order degree method considering the characteristics of time series presented in this paper are closer to the actual evolution situation of the system than the evaluation results without considering the characteristics of the time series, and maintaining high consistency with the actual evolution situation; the order degree of the water resources subsystem is greatly affected by the changes of water resources; and the entropy change of the water resources coupling system in Jiangxi Province is greatly affected by the entropy change of the water resources subsystem. The research result enhances the universality of the application of the synergetic order evaluation method in the related fields of a comprehensive evaluation of water resources systems and has a certain practical significance.

Monitoring Lake Level Changes in Bosten Lake from 2003-2021 based on Multi-source Satellite Altimetry Data

The investigation of freshwater lake water resource changes in arid regions is crucial for understanding the evolution of regional lake dynamics under climate change, given their value and limited availability. This study aims to overcome the limitations of traditional water level monitoring methods and address the practical need for monitoring water level changes in Lake Bosten, located in the arid and semi-arid regions of China. To this end, we employed ICESat, ICESat-2, and CryoSat-2 altimetry data, as well as Landsat 8-OLI optical remote sensing data, to obtain the water level information for Bosten Lake from 2003 to 2022. We analyzed the temporal variation of the lake level and discussed the response of the lake level to climate and human activities in the context of temperature, precipitation data, and human water use. The water level of Lake Bosten exhibited a decreasing and then increasing trend, with three rising and three falling intervals, respectively. The intra-year variation of the lake water level exhibited bimodal characteristics, and the fluctuation range of water level during abundant water periods was greater than that during dry periods. Finally, we correlated the extracted lake water level with the measured water level at the hydrological station and found a significant positive linear correlation between the observed water level of Bosten Lake based on satellite altimetry and the measured water level at the hydrological station, with an overall correlation coefficient of 0.896 and 0.934 (P < 0.01), indicating high accuracy of the water level results obtained in this study. The dynamics of Lake Bosten are influenced by a combination of climate change, hydrological elements, and human activities, with a relatively weak relationship between climate change and lake volume and a strong influence of human activities. Multi-source altimetry satellites provide a powerful tool for monitoring lake water levels over a long time scale, which is critical for studying lake water level changes and their response to climate and the environment.

Coupling Simulation and Prediction of Sustainable Utilization of Water Resources in an Arid Inland River Basin under Climate Change

The arid endorheic basin of northwest China is characterized by rich land resources, water shortage, and a fragile ecological environment. The establishment of a credible coupling model of groundwater and surface water based on multi-source observation data is an effective means to study the change in basin water cycles and the sustainable utilization of water resources in the past and future. Based on the latest understanding of hydrogeological conditions, hydrology and water resource utilization data in the middle reaches of the Heihe River Basin (HRB), this paper constructs an up-to-date coupling model of surface water and groundwater to study the water balance change of the basin. The water resources data series under historical replay and CMIP5 climate model prediction are constructed to predict future changes in water resources. The study shows that, under the joint influence of natural conditions and human activities, the average annual recharge of groundwater in the study area from 1990 to 2020 is 17.98 × 108 m3/a, the average annual discharge is 18.62 × 108 m3/a, and the difference between recharge and discharge is −0.64 × 108 m3/a. The total groundwater storage is −19.99 × 108 m3, of which the groundwater storage from 1990 to 2001 was −17.52 × 108 m3 and from 2002 to 2020 was −2.47 × 108 m3. Abundant water from 2002 to 2020 in the basin significantly improved the loss of groundwater storage. Under the prediction of historical reappearance and the CMIP5 CNRM-CM5 model RCP4.5 and RCP8.5 pathways, the groundwater level of the Heihe River–Liyuanhe River inclined plain falls first because the HRB has just experienced a wet season and then rises according to future climate change. The groundwater level of the inclined plain east of the Heihe River and Yanchi basin decreases continuously because of the change in water cycle caused by human activities. The erosion accumulation plain is located in the groundwater discharge zone, and the water level is basically stable. Under the conditions of water resource development and utilization, the runoff of Zhengyixia hydrological station cannot meet the requirements of the “97 Water Dividing Plan” of the State Council in most years in the future, and the ecological and production water in the lower reaches of HRB cannot be effectively guaranteed. With the implementation of water-saving irrigation under the RCP4.5 and RCP8.5 scenarios, the runoff of Zhengyixia can meet the “97 Water Diversion Plan”. It is suggested to further improve the level of agricultural water savings in the middle reaches of the HRB and control the reasonable scale of cultivated land in order to reduce water consumption in the middle reaches of the HRB and implement sustainable utilization of water resources in the HRB.

Groundwater Level Trend Analysis and Prediction in the Upper Crocodile Sub-Basin, South Africa

Disasters related to climate change regarding water resources are on the rise in terms of scale and severity. Therefore, predicting groundwater levels (GWLs) is a crucial means to aid adaptive capacity towards disasters related to climate change in water resources. In this study, a Gradient Boosting (GB) regression modelling approach for GWL prediction as a function of rainfall and antecedent GWL is used. A correlation analysis carried out from 2011 to 2020 demonstrated that monthly GWLs can be predicted by antecedent GWLs and rainfall. The study also sought to understand the long-term effects of climate events on groundwater levels over the study area through a Mann–Kendall (MK) trend analysis. A total of 50% of the groundwater stations revealed declining trends, while 25% had no trends and the other 25% showed an increasing trend. Again, the correlation analysis results were used in justifying the trends. The GB predictive model performed satisfactorily for all groundwater stations, with the MSE values ranging from 0.03 to 0.304 and the MAE varying from 0.12 to 0.496 in the validation period. The R2 ranged from 0.795 to 0.902 for the overall period. Therefore, based on projected rainfall and antecedent groundwater levels, future GWLs can be predicted using the GB model derived in this study.

A decade-long study on the effect of furrow and subsurface drip irrigation using unconventional water on soil salinity and the growth of pistachio trees

Furrow irrigation is the most common method of irrigating pistachio orchards in Iran. Water use efficiency using this method of irrigation is close to 35%. Ten years ago, a subsurface drip irrigation (SDI) project was initiated with highly saline and alkaline water for the first time in Iran at the Feyzabad pistachio research station, at 34̊ 54ʹ 15ʺ N, 58̊ 45ʹ 37ʺ E, located in the northeast of Iran, at an altitude of 850 meters from the sea. The water salinity and sodium adsorption ratio were 11.5 dS m-1 and 15.5 at the beginning of the project, and they reached 16.25 dS m-1 and 17.7 in 2021. The amount of SDI water consumption in the first year of the project (2012) was 1640 m3 ha-1 yr-1, and as the trees aged, water consumption reached 3000 m3 ha-1 in 2022. The amount of water utilized for furrow irrigation was about 6912 m3 ha-1 in 2022. Salt entering the soil through irrigation water differed by about 41 t ha-1 in 2022 between the two methods. After ten years of project implementation, the root development layer was more than 100 cm and less than 50 cm, respectively, for SDI and furrow. The trend of soil salinity has changed from 2012 to 2022: it went from 34.7 dS m-1 in 2012 to 110 dS m-1 in 2018, and then decreased to 65 dS m-1 in 2022 in the surface layer of the SDI method. In contrast, salinity increased almost twofold within the root development layer (60-140 cm) in the SDI. In the last two years (2021 and 2022), the height, crown width, trunk circumference, and yield of the pistachio trees were not significantly different between the two irrigation methods. However, there was a significant difference in the irrigation treatments during the two last years (2021 and 2022) in the annual growth, the average number of flower buds in the branch, and the average number of flower buds abscised. The branch vegetative growth in 2022 had decreased by almost 50% compared to 2021 in both methods. The results showed that the lowest annual growth was achieved in the SDI in 2022. Overall, the efficiency of water consumption in the SDI and furrow was equal to 0.09 and 0.06 kg m3, respectively. SDI net income was 1284 $ higher after expenses were deducted from 2012 to 2022. Therefore, due to severe climate change and excessive salinity increase in soil and water resources, a well-managed SDI can provide a more sustainable production method for salt-affected soils for pistachio orchards by reducing water consumption and salt entry into the soil.

Rise in Mid-Tropospheric Temperature Trend (MSU/AMSU 1978–2022) over the Tibet and Eastern Himalayas

The high-altitude Hindu Kush-Himalayan region (HKH, average ~5 km from msl) and the adjacent Indo-Gangetic plains (IG plains, ~0–250 m msl), due to their geographical location and complex topography, are reported to be highly sensitive to climatic changes. Recent studies show that the impacts of climate change and associated changes in water resources (glacial/snow melt water and rainfall) in this region are multifaceted, thereby affecting ecosystems, agriculture, industries, and inhabitants. In this study, 45 years of Microwave Sounding Unit/Advanced Microwave Sounding Unit (MSU/AMSU)-derived mid-tropospheric temperature (TMT, 3–7 km altitude) and lower tropospheric temperature (TLT, 0–3 km altitude) data from the Remote Sensing Systems (RSS Version 4.0) were utilized to analyze the overall changes in tropospheric temperature in terms of annual/monthly trends and anomalies. The current study shows that the mid-tropospheric temperature (0–3 km altitude over the HKH region) has already alarmingly increased (statistically significant) in Tibet, the western Himalayas, and the eastern Himalayas by 1.49 °K, 1.30 °K, and 1.35 °K, respectively, over the last 45 years (1978–2022). As compared to a previous report (TMT trend for 30 years, 1979–2008), the present study of TMT trends for 45 years (1978–2022) exhibits a rise in percent change in the trend component in the high-altitude regions of Tibet, the western Himalayas, and the eastern Himalayas by approximately 310%, 80%, and 170%, respectively. In contrast, the same for adjacent plains (the western and eastern IG plains) shows a negligible or much lower percent change (0% and 40%, respectively) over the last 14 years. Similarly, dust source regions in Africa, Arabia, the Middle East, Iran, and Pakistan show only a 130% change in warming trends over the past 14 years. In the monthly breakup, the ‘November to March’ period usually shows a higher TMT trend (with peaks in December, February, and March) compared to the rest of the months, except in the western Himalayas, where the peak is observed in May, which can be attributed to the peak dust storm activity (March to May). Snow cover over the HKH region, where the growing season is known to be from September to February, is also reported to show the highest snow cover in February (with the peak in January, February, or March), which coincides with the warmest period in terms of anomaly and trend observed in the long-term mid-tropospheric temperature data (1978–2022). Thus, the current study highlights that the statistically significant and positive TMT warming trend (95% CI) and its observed acceleration over the high-altitude region (since 2008) can be attributed to being one of the major factors causing an acceleration in the rate of melting of snow cover and glaciers, particularly in Tibet and the Eastern Himalayas.

Superstructure optimization models for regional coal industry development considering water resources constraints—A case study of Ordos, China

Optimizing the industrial structure is an important way to address resource constraints, achieve sustainable development. In this study, a planning method that combines the superstructure modeling concept and the mathematical method of mixed integer programming is proposed to investigate the optimized results of the coal industry under given constrained water resources, with 4 major coal application industries and 14 coal technology categories are considered. The results indicate that an increase in available water resources is associated with an increased local utilization rate of coal. Under the Water Rights Replacement Scenario, the local utilization rate of coal reaches 24.9%. Changes in available water resources significantly impact the coal chemical industry. In addition, significant reduction by 25% in carbon dioxide emissions requires 70 percent reduction in IDCL and CTO production. The policy implications for the development of the coal industry are also provided in the end.

Spatio-temporal dynamics of water storage across Northwest China over the past four decades

Study regionThe Northwest inland basins of China (NWC). Study focusTerrestrial water resources, especially groundwater resources, are the main source of water for human activities and for maintaining the stability of the ecological environment in NWC. Excessive consumption of water resources will seriously affect the sustainable utilization of water resources and ecological security in this region. Therefore, it is urgent to clarify the long-term changes in water storage in this area in order to handle the pressure of future water resources and the natural environment. Using GRACE satellite datasets and global hydrological models (GHMs) products, this study analyzed spatiotemporal variations in terrestrial water storage anomalies (TWSA), groundwater storage anomalies (GWSA), soil moisture, snow water equivalent, and canopy interception combined anomalies (SSCA) in NWC through the application of the water balance, trend decomposition, and empirical orthogonal decomposition methods. Furthermore, the driving factors of water storage change and feasible water resource management strategies were discussed. New hydrological insights for the regionTWSA in the NWC has experienced a continuous decline over the past nearly 40 years, while SSCA has shown a weak increasing trend (0.03 cm yr-1). Since the availability of glacial retreat data (2003–2016), glacial water storage in the NWC has decreased by 0.09 cm per year, while TWSA, SSCA, and GWSA have changed at rates of − 0.25, 0.02, and − 0.18 cm yr-1, respectively. The North Tianshan Rivers Basin has become one of the areas with the most severe groundwater depletion in China. 2005–2010 was a turning period in the changes of TWSA, followed by widespread water loss across the NWC. Glacier and snow melt are the most important factors for the decline of TWSA in the Tianshan mountains area, and over-exploitation of groundwater by human activities is a secondary factor. For other regions, Groundwater losses remain the most significant contributor to TWSA losses. The massive loss of water storage in the Tianshan Mountains area, especially the accelerated retreat of glaciers, will affect the stable water supply to the middle and lower reaches of the oasis region, perhaps leading to increased groundwater extraction, which will threaten regional water security and sustainable development. Developing a water-saving society and implementing inter-basin water transfer are feasible ways to alleviate the water resource crisis. Conducting a comprehensive analysis of all inland rivers in China helps to facilitate horizontal comparisons between various basins, thereby providing more comprehensive insights of water storage fluctuations. The data on water storage changes, extending back to 1980, provide a longer-term perspective on water resource changes in the region, which can contribute to enhancing water resource security and ecological environmental protection.

Analyzing and mapping agricultural waste recycling research: An integrative review for conceptual framework and future directions

There is a growing interest in the management and disposal of agricultural waste. In our century, problems such as climate change and depletion of natural water resources due to population growth are causing major economic problems. Addressing these problems offers great opportunities for developing a circular economy that uses innovative technologies and profitable business practices to address agricultural waste recycling. This article aims to shed new light on topics neglected in the literature by analyzing agricultural waste and waste recycling. For this purpose, the dataset obtained from the literature was thoroughly and comprehensively studied using the bibliometric text mining technique. This article also has shown which agricultural wastes are the subject of recycling work and entrepreneurship and has identified changes in research and studies on agricultural wastes that have been the subject of twenty years. This research aims to increase the importance and awareness of the most commonly used topics or terms in waste recycling, the contribution of the circular economy, and the recycling of agricultural waste. The research found that activities such as composting, lignocellulosic biomass, biodiesel and biodiesel production, biogas and biogas production, biohydrogen production, and methane production are increasingly important in the processing and recycling of these wastes, with agro-industrial wastes (fruit, vegetable, and plant wastes) standing out.

Spatiotemporal dynamics of blue and green water resources in a mountainous watershed: A case study of the Wujiang River Basin, China

Study regionWujiang River Basin, China. Study focusBlue and green water play key roles in water management and sustainable development in the Wujiang River Basin. It is essential to conduct a comprehensive study on the availability of blue and green water resources due to the uneven distribution of water resources in the basin. In this study, the monthly, seasonal, and interannual variations in blue and green water resources were analyzed during 1985–2014, and the changes in blue and green water resources were predicted for the period 2015–2100 based on the 5 Coupled Model Intercomparison Project Phase 6 (CMIP6). New hydrological insights for the regionFrom 1985–2014, blue water resources were dominant in the Wujiang River basin, accounting for 53.6% of the total water resources. Blue water resources exhibited an increasing trend, while green water resources exhibited a decreasing trend. Precipitation exhibited a much more significant impact on blue water resources than on green water resources. The spatial distribution of blue and green water resources in the basin is uneven, where the blue water resource with an annual average of 629.5 mm, indicating an increase followed by a decreasing trend from upstream to downstream. The green water resources had an annual average of 544.7 mm, with a decrease followed by an increasing trend from upstream to downstream. Delta and multi-model ensemble (MME) can effectively reduce the uncertainties associated with CMIP6 model output. Annual precipitation and mean annual temperature increase from 2015 to 2100 in SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5. Compared to the baseline period, blue water resources show the highest growth in the recent (2015–2040) and intermediate (2041–2070) periods in SSP1–2.6, i.e., by 4.9% and 13.7%, respectively. In the final period (2071–2100), blue water resources exhibit the highest growth in SSP5–8.5, i.e., by 21.5%. The future projections indicated that the uneven spatial distribution of blue water resources in the basin will persist. This study improves our understanding of the blue and green water resources in the Wujiang River Basin under climate change scenarios and can provide valuable insights for integrated water resources management in the Wujiang River Basin.

Adaptation of cotton production to climate change by sowing date optimization and precision resource management

Sowing date optimization is used to achieve a high crop yield and efficient resource utilization, and it is an important strategy for the adaptation of crop production to climate change. However, there is still little field evidence on the coupling effect of multiple environmental resources on cotton and its response to climate change under sowing date management. In this study, the changes in light, temperature, and water resources under different cotton sowing dates were monitored in 2021 (when an extreme rainfall occurred) and 2022. Ridge regression and structural equation models were used to analyze the responses of cotton biomass and yield formation under different sowing dates over two years to the availability and use efficiency of multiple resources, and a strategy for adapting cotton production to climate was discussed. The interaction between sowing date and climate change had significant effects on cotton yield components, as did light, temperature, and water resource use efficiency. The extreme rainstorm in 2021 reduced seed cotton yield by 52.75 % at most, and the yield reduction was alleviated through sowing date management. Growth degree day (GDD), photosynthetically active radiation (PAR), and soil water consumption (SWC) accumulation had positive coupling effects on cotton biomass formation, and the magnitude of their effects decreased. The PAR and GDD at squaring stage and SWC at flowering and boll development stage affected aboveground biomass and thus seed cotton yield. The heat use efficiency (HUE) and water use efficiency (WUE) had a positive coupling effect on seed cotton yield. Improving HUE and WUE through precise management of temperature and light resources during squaring stage and water resources during flowering and boll development stage may promote efficient production and high yields of cotton under climate change. This study portrays climate-smart agriculture and has important reference value for adapting cotton production to climate change.

An Integrated Approach for Analyzing the Morphological Evolution of the Lower Reaches of the Minjiang River Based on Long-Term Remote Sensing Data

Understanding the evolution of river morphology is crucial for comprehending changes in water resources and implementing development projects along rivers. This study proposes an integrated approach utilizing remote sensing image data combined with deep learning and visual interpretation algorithms to analyze continuous-type changes in river morphology. This research focuses on the lower reaches of the Minjiang River in China and comprehensively analyzes the river’s morphological evolution from 1986 to 2021. The results show that the proposed method of river water identification in this study demonstrates high accuracy and effectiveness, with an F1 score and Kappa coefficient greater than 0.96 and 0.91, respectively. The morphology of the river channel remains stable in the upstream and estuarine sections of the study region while undergoing substantial alterations in the middle section. Additionally, this study also identifies several factors that significantly impact the evolution of river morphology, including reservoir construction, river sediment mining, river training measures, geological conditions, and large flood events. The findings of this study can provide some insights into the management and conservation of water resources.

Integrated water resources trend assessments: State of the science, challenges, and opportunities for advancement

AbstractWater is vital to human life and healthy ecosystems. Here we outline the current state of national‐scale water resources trend assessments, identify key gaps, and suggest advancements to better address critical issues related to changes in water resources that may threaten human development or the environment. Questions like, “Do we have less suitable drinking water now than we had 20 years ago?” or “Are flood events more common now than they were in the past?” prompted improvements in data, trend estimation methods, and modeling frameworks to track changes in, and better understand how land use and climate influence four water resources domains: surface and groundwater quantity and quality. However, continued advancement in trend assessments to better address issues related to changes in water availability is needed. Areas of need include more timely and efficient delivery of water resources trend results and improved capacity to estimate trends at unmonitored locations. Additional integration pieces include increased understanding of groundwater–surface water interactions, incorporation of both quantity and quality trends into water availability estimates, and the refinement of trend metrics to account for the competing needs of society and ecological integrity. Coupled with improved driver attribution studies, these components will better inform current and future water resources management.