Search Results (134)

With the swift progression of the High-Standard Farmland Construction Program in China and worldwide, many dryland wheat fields can be irrigated once during the wheat growth stage (one-off irrigation). However, the combined strategies of one-off irrigation, tillage, and N management for augmenting wheat grain yield and quality are still undeveloped in drought regions. Two-site split–split field experiments were conducted to study the impacts of irrigation, tillage, and N management and their combined effects on grain yield; the contents of protein and protein components; processing quality; and the characteristics of N accumulation and translocation in wheat from a typical dryland wheat production area in China from 2020 to 2022. The irrigation practices (I0, zero irrigation and I1, one-off irrigation), tillage methods (RT, rotary tillage; PT, plowing; and SS, subsoiling) and N management (N0, N120, N180, and N240) were applied to the main plots, subplots and sub-subplots, respectively. The experimental sites, experimental years, irrigation practices, tillage methods, and N management methods and their interaction significantly affected the yield, quality, and plant N characteristics of wheat in most cases. Compared to zero irrigation, one-off irrigation significantly increased the plant N accumulation, enhancing grain yield by 33.7% while decreasing the contents of total protein, albumin, globulin, gliadin, and glutenin by 4.4%, 6.4%, 8.0%, 12.2%, and 10.0%, respectively. It also decreased the wet gluten content, stability time, sedimentation value, extensibility by 4.1%, 10.7%, 9.7%, and 5.5%, respectively, averaged across sites and years. Subsoiling simultaneously enhanced the aforementioned indicators compared to rotary tillage and plowing in most sites and years. With the increase in N rates, wheat yield firstly increased and then decreased under zero irrigation combined with rotary tillage, while it gradually increased when one-off irrigation was combined with subsoiling; however, the contents of total protein and protein components and the quality tended to increase firstly and then stabilize regardless of irrigation practices and tillage methods. The correlations of yield and quality indicators with plant N characteristics were negative when using distinct irrigation practices and tillage methods, while they were positive under varying N management. The decrease in wheat quality induced by one-off irrigation could be alleviated by optimizing N management. I1STN180 exhibited higher yield, plant N accumulation and translocation, and better quality in most cases; thus, all metrics of wheat quality were significantly increased, with a yield enhancement of 50.3% compared to I0RTN180. Therefore, one-off irrigation with subsoiling and an N rate of 180 kg ha⁻¹ is an optimal strategy for high yield, high protein, and high quality in dryland wheat production systems where one-off irrigation is assured. Full article

Drought impacts agricultural production and regional sustainable development. Accordingly, timely and accurate drought monitoring is essential for ensuring food security in rain-fed agricultural regions. Alternating drought and flood events frequently occur in the Heilongjiang River Basin, the largest grain-producing area in Far East Asia. However, spatiotemporal variability in drought is not well understood, in part owing to the limitations of the traditional Temperature Vegetation Dryness Index (TVDI). In this study, an Improved Temperature Vegetation Dryness Index (ITVDI) was developed by incorporating Digital Elevation Model data to correct land surface temperatures and introducing a constraint line method to replace the traditional linear regression for fitting dry–wet boundaries. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) normalized vegetation index and land surface temperature products, the Heilongjiang River Basin, a cross-border basin between China, Mongolia, and Russia, exhibited pronounced spatiotemporal variability in drought conditions of the growing season from 2001 to 2023. Drought severity demonstrated clear geographical zonation, with a higher intensity in the western region and lower intensity in the eastern region. The Mongolian Plateau and grasslands were identified as drought hotspots. The Far East Asia forest belt was relatively humid, with an overall lower drought risk. The central region exhibited variation in drought characteristics. From the perspective of cross-national differences, the drought severity distribution in Northeast China and Inner Mongolia exhibits marked spatial heterogeneity. In Mongolia, regional drought levels exhibited a notable trend toward homogenization, with a higher proportion of extreme drought than in other areas. The overall drought risk in the Russian part of the basin was relatively low. A trend analysis indicated a general pattern of drought alleviation in western regions and intensification in eastern areas. Most regions showed relatively stable patterns, with few areas exhibiting significant changes, mainly surrounding cities such as Qiqihar, Daqing, Harbin, Changchun, and Amur Oblast. Regions with aggravation accounted for 52.29% of the total study area, while regions showing slight alleviation account for 35.58%. This study provides a scientific basis and data infrastructure for drought monitoring in transboundary watersheds and for ensuring agricultural production security. Full article

In recent years, under the influence of climate change and human activities, droughts and floods have occurred frequently in the Yangtze River Basin (YRB), seriously threatening socioeconomic development and ecological security. The topography and climate of the YRB are complex, so it is crucial to develop appropriate drought and flood policies based on the drought and flood characteristics of different sub-basins. This study calculated the water storage deficit index (WSDI) based on the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GFO) mascon model, extended WSDI to the bidirectional monitoring of droughts and floods in the YRB, and verified the reliability of WSDI in monitoring hydrological events through historical documented events. Combined with the wavelet method, it revealed the heterogeneity of climate responses in the three sub-basins of the upper, middle, and lower reaches. The results showed the following. (1) Compared and verified with the Standardized Precipitation Evapotranspiration Index (SPEI), self-calibrating Palmer Drought Severity Index (scPDSI), and documented events, WSDI overcame the limitations of traditional indices and had higher reliability. A total of 21 drought events and 18 flood events were identified in the three sub-basins, with the lowest frequency of drought and flood events in the upper reaches. (2) Most areas of the YRB showed different degrees of wetting on the monthly and seasonal scales, and the slowest trend of wetting was in the lower reaches of the YRB. (3) The degree of influence of teleconnection factors in the upper, middle, and lower reaches of the YRB had gradually increased over time, and, in particular, El Niño Southern Oscillation (ENSO) had a significant impact on the droughts and floods. This study provided a new basis for the early warning of droughts and floods in different sub-basins of the YRB. Full article

With climate warming, the global precipitation patterns have undergone significant changes, which will profoundly impact flood–drought disaster regimes and socioeconomic development in key regions of human activity worldwide. The convergence zone of the Indian Ocean monsoon and Pacific monsoon in China covers most of the middle and lower reaches of the Yangtze River (MLRYR), which is located in the transitional area of the second and third steps of China’s terrain. Changes in precipitation patterns in this region will significantly impact flood and drought control in the MLRYR, as well as the socioeconomic development of the MLRYR Economic Belt. In this study, Huaihua area in China was selected as the study area to study the characteristics of regional precipitation change, and to analyze the evolution in the trends in annual precipitation, extreme precipitation events, and their spatiotemporal distribution, so as to provide a reference for the study of precipitation change patterns in the intersection zone. This study utilizes precipitation data from meteorological stations and the China Meteorological Forcing Dataset (CMFD) reanalysis data for the period 1979–2023 in Huaihua region. The spatiotemporal variation in precipitation in the study area was analyzed by using linear regression, the Mann–Kendall trend test, the moving average method, the Mann–Kendall–Sneyers test, wavelet analysis, and R/S analysis. The results demonstrate the following: (1) The annual precipitation in the study area is on the rise as a whole, the climate tendency rate is 9 mm/10 a, and the precipitation fluctuates greatly, showing an alternating change of “dry–wet–dry–wet”. (2) Wavelet analysis reveals that there are 28-year, 9-year, and 4-year main cycles in annual precipitation, and the precipitation patterns at different timescales are different. (3) The results of R/S analysis show that the future precipitation trend will continue to increase, with a strong long-term memory. (4) Extreme precipitation events generally show an upward trend, indicating that their intensity and frequency have increased. (5) Spatial distribution analysis shows that the precipitation in the study area is mainly concentrated in the northeast and south of Jingzhou and Tongdao, and the precipitation level in the west is lower. The comprehensive analysis shows that the annual precipitation in the study area is on the rise and has a certain periodic precipitation law. The spatial distribution is greatly affected by other factors and the distribution is uneven. Extreme precipitation events show an increasing trend, which may lead to increased flood risk in the region and downstream areas. In the future, it is necessary to strengthen countermeasures to reduce the impact of changes in precipitation patterns on local and downstream economic and social activities. Full article

Based on the long-term daily historical rainfall data, this study analyzes the seasonal differences in extreme rainfall in the monsoon region with frequent extreme rainfall in China over the past 40 years. From the detailed analysis of extreme rainfall indicators, the spatial and temporal variation in extreme rainfall indicators in the monsoon region of China from 1980 to 2020 is explored. Through Mann–Kendall test and multi-index spatial and temporal analysis, the spatial and temporal evolution law and seasonal differentiation characteristics of extreme precipitation events are revealed. The results show the following: (1) The precipitation change presents a dipole pattern of southeast–northeast enhancement, northwest–central attenuation. (2) The precipitation intensity showed the spatial heterogeneity of latitude differentiation of “strong in summer and weak in winter, strong in south and weak in north”, and generally attenuated in winter after reaching the peak in summer. (3) There were significant dry and wet differences between continuous drought days (CDDs) and wet days (CWDs), reflecting the characteristics of “dry in winter and wet in summer”, and the seasonal differentiation of cumulative precipitation (PRCPTOT) was significant. (4) The extreme precipitation threshold is strengthened in winter, and the frequency shows the characteristics of “high in winter and spring, low in summer and autumn”. Studies have shown that extreme precipitation in the monsoon region of China has seasonal redistribution characteristics, which may aggravate the challenge of water resources management. It is necessary to further analyze its driving factors in combination with a dynamic climate mechanism. Full article

This study evaluates the performance of CMIP6 models in simulating drought characteristics in the Mekong region, including drought duration, intensity, and severity, using the SPI and SPEI indices. The results show that CMIP6 models are capable of accurately reproducing past drought conditions, with a high agreement between model data and actual data from ERA5. This study projects that future droughts will become more prolonged and severe which could lead to long-term agricultural and hydrological droughts tending to increase. In the SSP585 scenario, drought intensity will increase sharply in the southern and central regions by the end of the century. The SSP245 and SSP585 climate scenarios have distinct differences in drought trends, with SSP245 showing a strong drought trend, while SSP585 indicates a potential increase in precipitation. The SPEI indices show a clear improvement in wet conditions, with the highest drought variability in zone 2 and stable trends across scenarios. Ecosystems influence drought impacts and management needs. These results highlight the importance of accurately assessing drought characteristics to develop effective water resource and agricultural management measures, especially in the context of climate change. However, this study also points out some limitations, including the imperfect accuracy in future projections and the use of only SPI and SPEI indices without combining them with other indices which may reduce the comprehensiveness of drought impact assessment. This requires future studies to improve and expand to overcome the above limitations, thereby enhancing the reliability of drought forecasts and water resource management strategies. Full article

Quantifying extreme weather events (EWEs) and understanding their impacts on vegetation phenology is crucial for assessing ecosystem stability under climate change. This study systematically investigated the ecosystem growing season length (GL) response to four types of EWEs—extreme heat, extreme cold, extreme wetness (surplus precipitation), and extreme drought (lack of precipitation). The EWE extremity thresholds were found statistically using detrended long time series (2000–2022) ERA5 meteorological data through z-score transformation. The analysis was based on a grassland ecosystem in the Mongolian Plateau (MP) from 2000 to 2022. Using solar-induced chlorophyll fluorescence data and event coincidence analysis, we evaluated the probability of GL anomalies coinciding with EWEs and assessed the vegetation sensitivity to climate variability. The analysis showed that 83.7% of negative and 87.4% of positive GL anomalies were associated with one or more EWEs, with extreme wetness (27.0%) and extreme heat (25.4%) contributing the most. These findings highlight the dominant role of EWEs in shaping phenological shifts. Negative GL anomalies were more strongly linked to EWEs, particularly in arid and cold regions where extreme drought and cold shortened the growing season. Conversely, extreme heat and wetness had a greater influence in warmer and wetter areas, driving both the lengthening and shortening of GL. Furthermore, background hydrothermal conditions modulated the vegetation sensitivity, with warmer regions being more susceptible to heat stress and drier regions more vulnerable to drought. These findings emphasize the importance of regional weather variability and climate characteristics in shaping vegetation phenology and provide new insights into how weather extremes impact ecosystem stability in semi-arid and arid regions. Future research should explore extreme weather events and the role of human activities to enhance predictions of vegetation–climate interactions in grassland ecosystems of the MP. Full article

On intensive dairy farms, good decision making regarding application of fertilisers and irrigation requires an understanding of soil moisture conditions. Targeted fertiliser application not only contributes to high nutrient use efficiency but reduces the potential for leaching of nutrients and controls emissions from farms. This calls for the development of an improved farm management decision support system focussed on precision agriculture solutions for sustainable agriculture. Knowledge of soil moisture at high resolution at the farm scale can help develop such solutions while at the same time reducing the risk of soil compaction by machinery and/or animals, especially under wet conditions. The objective of this study is to examine and compare two intensive dairy farms, with similar average annual rainfall but contrasting soil (but similar drainage) and topographic characteristics, for their resilience towards extreme conditions (e.g., saturation or drought). Soil moisture thresholds for optimal conditions and corresponding farm area proportions were calculated, identifying areas for targeted farm management. This study addresses the knowledge gap of including high-resolution satellite derived soil moisture as a variable in designing farm management systems targeted towards precision agriculture. Farm 1 was situated in a drumlin belt, whereas Farm 2 had lowland terrain, representing major land cover categories in Ireland. The results showed that Farm 2 was more resilient towards extreme conditions and that the variable topography and soil heterogeneity act as a buffer in regulating moisture regimes on the farm, preventing movement towards the extremes. Across the years, Farm 1 showed less variability in optimal farm area proportions and could be managed better than Farm 2 in terms of overall productivity and resilience towards extreme weather conditions such as droughts, even in a drought year. This study showed that along with variations in soil type, topographic features also dictate water movement and therefore soil moisture regimes on farms. Full article

Water utilities use a significant amount of electrical energy due to the rising demand for wastewater treatment driven by environmental and economic reasons. The growing demand for energy, rising energy costs, and the drive toward achieving net-zero emissions require a sustainable energy future for the water industry. This can be achieved by integrating onsite renewable energy sources (RESs), energy storage, demand management, and participation in demand response (DR) programs. This paper analyzes the energy profile and load flexibility of water utilities using a data-driven approach to reduce energy costs by leveraging RESs for regional water utilities. It also assesses the potential for DR participation across different types of water utilities, considering peak-load shifting and battery storage installations. Given the increasing frequency of extreme weather events, such as bushfires, heatwaves, droughts, and prolonged cold and wet season floods, regional water industries in Australia serve as a relevant case study of sectors already impacted by these challenges. First, the data characteristics across the water and energy components of regional water industries are analyzed. Next, barriers and challenges in data acquisition and processing in water industries are identified and recommendations are made for improving data coordination (interoperability) to enable the use of a single platform for identifying DR opportunities. Finally, the energy profile and load flexibility of regional water industries are examined to evaluate onsite generation and battery storage options for participating in DR operations. Operational data from four regional sites across two regional Australian water utilities are used in this study. Full article

Drought is one of the most widespread natural disasters globally, and its spatiotemporal distribution is profoundly influenced by the El Niño-Southern Oscillation (ENSO). As a typical humid coastal basin, the Jiaojiang River Basin in southeastern China frequently experiences hydrological extremes such as dry spells during flood seasons. This study focuses on the Jiaojiang River Basin, aiming to investigate the response mechanisms of drought evolution to ENSO in coastal regions. This study employs 10-day scale data from 1991 to 2020 to investigate the drought mechanisms driven by ENSO through a comprehensive framework that combines standardized indices with climate–drought correlation analysis. The results indicate that the Comprehensive Drought Index (CDI), integrating the advantages of the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI), effectively reflects the basin’s combined meteorological and hydrological wet-dry characteristics. A strong response relationship exists between drought indices in the Jiaojiang River Basin and ENSO events. Drought characteristics in the basin vary significantly during different ENSO phases. The findings can provide theoretical support for the construction of resilient regional water resource systems, and the research framework holds reference value for sustainable development practices in similar coastal regions globally. Full article

The scanning curve of the soil–water characteristic curve (SWCC) represents the intermediate paths followed by soil as it transitions between the initial drying and main wetting cycles. The alternating occurrence of climatic conditions, such as rainfall and evaporation in different regions globally, provides a valuable framework for understanding how these dynamics influence the scanning curve. Monitoring the scanning curve can provide valuable insights for managing water resources and mitigating the impacts of drought, contributing to environmental sustainability by enabling more precise agricultural practices, promoting water conservation, and supporting the resilience of ecosystems in the face of climate change. It enhances sustainability by enabling data-driven designs that minimize resource use, reduce environmental impact, and increase the resilience of slopes to natural hazards like landslides and flooding. Available studies to determine the scanning curve of SWCC are limited and mostly conducted in the laboratory. This study aims to determine the real-time measurement of the scanning curve of SWCC for unsaturated soil. The research focuses on assessing the hysteresis behavior of residual soil slope from old alluvium through a combination of field instrumentation and laboratory testing. The pore size distribution was derived from the initial drying and main wetting SWCC. Field monitoring (scanning curve) indicates measurable deviations from the experimental results, including a 10% lower saturated water content and a 25% lower air-entry value. This study demonstrates the potential for field-based determination of scanning curves. It highlights their role in improving the prediction of the hydraulic behavior of residual slopes during varying climatic conditions. Full article

Evapotranspiration (ET) plays a crucial role in the surface water cycle and energy balance, and accurate ET estimation is essential for study in various domains, including agricultural irrigation, drought monitoring, and water resource management. Remote sensing (RS) technology presents an efficient approach for estimating ET at regional scales; however, existing RS retrieval algorithms for ET are intricate and necessitate a multitude of parameters. The land surface temperature–vegetation index (LST-VI) space method and statistical regression by machine learning (ML) offer the benefits of simplicity and straightforward implementation. This study endeavors to identify the optimal long-term sequence LST-VI space method and ML for ET estimation under conditions of limited observed variables, (LST, VI, and near-surface air temperature). A comparative analysis of their performance is undertaken using ground-based flux observations and MOD16 ET data. The findings can be summarized as follows: (1) Long-term remote sensing data can furnish a more comprehensive background field for the LST-VI space, achieving superior fitting accuracy for wet and dry edges, thereby enabling precise ET estimation with the following metrics: correlation coefficient (r) = 0.68, root mean square error (RMSE) = 0.76 mm/d, mean absolute error (MAE) = 0.49 mm/d, and mean bias error (MBE) = −0.14 mm. (2) ML generally produces more accurate ET estimates, with the Random Forest Regressor (RFR) demonstrating the highest accuracy: r = 0.79, RMSE = 0.61 mm/d, MAE = 0.42 mm/d, and MBE = −0.02 mm. (3) Both ET estimates derived from the LST-VI space and ML exhibit spatial distribution characteristics comparable to those of MOD16 ET data, further attesting to the efficacy of these two algorithms. Nevertheless, when compared to MOD16 data, both approaches exhibit varying degrees of underestimation. The results of this study can contribute to water resource management and offer a fresh perspective on remote sensing estimation methods for ET. Full article

Drought presents significant challenges in arid regions, influencing local climate and environmental dynamics. While the large-scale climatic phenomena in Xinjiang, northwest China, are well-documented, the finer-scale climatic variability in subregions such as the Ili River Valley (IRV) remains insufficiently studied. This knowledge gap impedes effective regional planning and environmental management in this ecologically sensitive area. In this study, we analyze the spatiotemporal evolution of drought in the IRV from 1961 to 2023, using data from ten meteorological stations. The SPEI drought index, along with Sen’s trend analysis, the Mann–Kendall test, the cumulative departure method, and wavelet analysis, were employed to assess drought patterns. Results show a significant drying trend in the IRV, starting in 1995, with frequent drought events from 2018 onwards, and no notable transition year observed from wet to dry conditions. The overall drought rate was −0.09 per decade, indicating milder drought severity in the IRV compared to broader Xinjiang. Seasonally, the IRV experiences drier summers and wetter winters compared to regional averages, with negligible changes in autumn and milder drought conditions in spring. Abrupt changes in the drying seasons occurred later in the IRV than in Xinjiang, with delays of 21 years for summer, and over 17 and 35 years for spring and autumn, respectively, indicating a lagged response. Spatially, the western plains are more prone to aridification than the central and eastern mountainous regions. The study also reveals significant differences in drought cycles, which are longer than those in Xinjiang, with distinct wet–dry phases observed across multiple time scales and seasons, emphasizing the complexity of drought variability in the IRV. In conclusion, the valley exhibits unique drought characteristics, including milder intensity, pronounced seasonal variation, spatial heterogeneity, and notable resilience to climate change. These findings underscore the need for region-specific drought management strategies, as broader approaches may not be effective at the subregional scale. Full article

Amid global climate change, recurrent drought events pose significant challenges to regional water resource management and the sustainability of socio-economic growth. Thus, understanding drought characteristics and regional development patterns is essential for effective drought monitoring, prediction, and the creation of robust adaptation strategies. Most prior research has analyzed drought events independently in spatial and temporal dimensions, often overlooking their dynamic nature. In this study, we employ a three-dimensional methodology that accounts for spatiotemporal continuity to identify and extract meteorological drought events based on a 3-month standardized precipitation evapotranspiration index (SPEI3). Measured by the SPEI3 index, the incidence of drought increased in the middle part of the basin, especially in some parts of Sichuan and Yunnan province, and the frequency of drought events decreased in the upper reaches. We evaluate drought events within the Yangtze River basin from 1980 to 2016 by examining five variables: chronology, extent, severity, duration, and epicenter locations. The results show that a total of 97 persisting drought events lasting at least 3 months have been identified in Yangtze River basin. Most events have a duration between 4 and 7 months. The findings indicate that while the number of drought events in the Yangtze River basin has remained unchanged, the intensity, duration, and severity of these events have shown a slight increase from 1980 to 2016. The drought events gradually moved from the western and southeastern parts of the basin to the central region. The most severe drought event occurred between January 2011 and October 2011, with a duration of 10 months and an affected area of 0.94 million km², impacting over fifty percent of the basin. Changes in wetness and dryness in the Yangtze River basin are closely related to El Niño/Southern Oscillation (ENSO) events, with a positive correlation between the intensity of cold events and the probability of extreme drought. This study enhances our understanding of the dynamics and evolution of drought events in the Yangtze River basin, providing crucial insights for better managing water resources and developing effective adaptation strategies. Full article

Drought has become an important factor affecting the environment and socio-economic sustainable development in northern China due to climate change. This study utilized the Standardized Precipitation Index (SPI) as a drought metric to investigate the correlation between drought characteristics and different grades of precipitation and rain days. The analysis was based on a long-term time series of precipitation data obtained from 116 meteorological stations located in Inner Mongolia, spanning 1960 to 2019. To achieve the objectives of the current research, the daily precipitation was categorized into four grades based on the “24-h Precipitation Classification Standard”, and the frequency of rain days for each grade was determined. Subsequently, the SPI was calculated for 1 and 12 months, enabling the identification of drought events. The results revealed pronounced spatiotemporal regional variations and complexities in the dry–wet climatic patterns of Inner Mongolia, with significant decreases in precipitation emerging as the primary driver of drought occurrences. Approximately 6% of the entire study period experienced short-term drought, while long-term drought periods ranged from 23% to 38%. Regarding multi-year trends, precipitation exhibited a weak increasing trend, while rain days exhibited a weak decreasing trend. Drought exhibited an alleviating trend, with 92% of stations displaying coefficients > 0 for SPI_Month and over 62% of stations displaying coefficients > 0 for SPI_Year. At the monthly scale, drought was most correlated with light rainfall trends and least correlated with moderate rainfall trends. At the annual scale, drought was relatively highly correlated with moderate and heavy rainfall distributions but poorly correlated with light rainfall. The results suggested that achieving the precise monitoring and mitigation of drought disasters in Inner Mongolia in the future will require a combined analysis of indicators, including agricultural drought, hydrological drought, and socio-economic drought. Such an approach will enable a comprehensive analysis of drought characteristics under different underlying surface conditions in Inner Mongolia. Full article