Comprehensive study of algal blooms variation in Jiaozhou Bay based on google earth engine and deep learning.

The Jiaozhou Bay ecosystem, a crucial marine ecosystem in China, has been plagued by frequent harmful algal blooms as due to deteriorating water quality and eutrophication. This study analyzed the temporal and spatial changes of harmful algal blooms in Jiaozhou Bay from 2000 to 2022 using the Floating Algae Index (FAI) calculated from MODIS (2000-2022) and Sentinel-2 (2015-2022) satellite image datasets. The calculation results of the image datasets were compared. The frequency of planktonic algal outbreaks was low and constant until 2017, but has increased annually since then. Algae blooms are most common in the summer and primarily concentrated along the bay's coast, middle, and mouth, with obvious seasonal and spatial distribution characteristics. Several factors influencing algal outbreaks were identified, including sea surface temperature, wind speed, air pressure, dissolved oxygen, nitrogen and phosphorus ratios, chemical oxygen demand, and petroleum pollutants. Algal bloom outbreaks in Jiaozhou Bay are expected to remain high in 2023. The findings provide crucial information for water quality management and future algal outbreak prediction and prevention in Jiaozhou Bay.

Quantitative Evaluation and Obstacle Factor Diagnosis of Agricultural Drought Disaster Risk Using Connection Number and Information Entropy.

To promote the application of entropy concepts in uncertainty analysis of water resources complex system, a quantitative evaluation and obstacle factor diagnosis model of agricultural drought disaster risk was proposed using connection number and information entropy. The results applied to Suzhou City showed that the agricultural drought disaster risks in Suzhou during 2007-2017 were all in middle-risk status, while it presented a decreasing trend from 2010. The information entropy values of the difference degree item bI were markedly lower than those of the difference degree b, indicating that bI provided more information in the evaluation process. Furthermore, the status of drought damage sensitivity and drought hazard were improved significantly. Nevertheless, high exposure to drought and weak drought resistance capacity seriously impeded the reduction of risk. Thus, the key to decreasing risk was to maintain the level of damage sensitivity, while the difficulties were to reduce exposure and enhance resistance. In addition, the percentage of the agricultural population, population density, and percentage of effective irrigation area were the main obstacle factors of risk and also the key points of risk control in Suzhou. In short, the results suggest that the evaluation and diagnosis method is effective and conducive to regional drought disaster risk management.

Construction and application of comprehensive drought index based on uncertainty cloud reasoning algorithm.

The establishment of comprehensive drought index is a fundamental task for the analysis of drought hazard system evolution. To fully explore the characteristics of drought variation process, the cloud uncertainty reasoning method was applied to construct comprehensive drought index integrating precipitation with soil moisture indicators. The application results of the proposed drought index in Anhui Province, China revealed that, (1) The overall drought evolution presented significant intensifying trend with the drought occurrence frequency increasing from 32% to 41% from south to north in Anhui Province, and the primary drought type in the northern area was moderate-level drought events and above, while the drought type in the central and southern region was dominated by light-level drought events. (2) Autumn drought was the dominant type from 1960 to 2007 in Anhui Province, with the average drought occurrence frequency of 40%. In addition, the evolution of spring and autumn drought all presented intensifying trends from 1960 to 2007, while the summer and winter drought evolution trends were opposite. (3) The Mann-Kendall trend test results revealed that the drought evolution presented evidently intensifying trend from August 1967 to February 1969, but slight declining trend from May 1974 to August 1978, July 1989 to August 2001 and February 2003 to December 2007, and the mutation of drought evolution occurred in November 1972, February 1978 and August 1998, etc. The above results were basically consistent with the historical statistics, indicating that the proposed comprehensive drought index and its construction framework were reliable, which can be further applied in the related research field of regional drought risk management.

Spatio-Temporal Evolution Analysis of Drought Based on Cloud Transformation Algorithm over Northern Anhui Province.

Drought is one of the most typical and serious natural disasters, which occurs frequently in most of mainland China, and it is crucial to explore the evolution characteristics of drought for developing effective schemes and strategies of drought disaster risk management. Based on the application of Cloud theory in the drought evolution research field, the cloud transformation algorithm, and the conception zooming coupling model was proposed to re-fit the distribution pattern of SPI instead of the Pearson-III distribution. Then the spatio-temporal evolution features of drought were further summarized utilizing the cloud characteristics, average, entropy, and hyper-entropy. Lastly, the application results in Northern Anhui province revealed that the drought condition was the most serious during the period from 1957 to 1970 with the SPI12 index in 49 months being less than -0.5 and 12 months with an extreme drought level. The overall drought intensity varied with the highest certainty level but lowest stability level in winter, but this was opposite in the summer. Moreover, drought hazard would be more significantly intensified along the elevation of latitude in Northern Anhui province. The overall drought hazard in Suzhou and Huaibei were the most serious, which is followed by Bozhou, Bengbu, and Fuyang. Drought intensity in Huainan was the lightest. The exploration results of drought evolution analysis were reasonable and reliable, which would supply an effective decision-making basis for establishing drought risk management strategies.

Early Warning Method for Regional Water Resources Carrying Capacity Based on the Logical Curve and Aggregate Warning Index.

The sustainable utilization of water resources is a significant factor in the development of the national economy and society. Regional water resources carrying capacity (RWRCC) is an appropriate method for evaluating the balance in such utilization. In this paper, we combined time difference correlation analysis and set pair analysis firstly to identify the early warning sign index (EWSI) for RWRCC, and warning limits were determined using a logical curve. Analytic hierarchy process based on the accelerating genetic algorithm (AGA-AHP) method was used to improve the KLR model by determining weights objectively. We took advantage of the new improved model to build the aggregate warning index (AWI). Then, according to the corresponding relationship between EWSI and AWI, the early warning system for regional water resources carrying capacity (EWS-RWRCC) was established, and a case study was carried out in Anhui Province. The results showed there are eight effective EWSI obtained through the early warning analysis process of RWRCC in Anhui Province, among which the repetitive use rate of industrial water and average daily coefficient have a greater impact on AWI. Basically, the EWS-RWRCC can describe RWRCC changes in Anhui Province. From 2006 to 2014, more than half the signal lights in Anhui Province were yellow and orange, which indicated a poor state. It has been proved that the constraints of population, GDP growth and water supply capacity on the utilization of water resources in the future will be further tightened, which should be considered for future monitoring and early warning. The early warning method we used here can be widely applied into other fields; the results will enhance monitoring capacity and scientifically guide regional water resources management.

Regional water resource carrying capacity evaluation based on multi-dimensional precondition cloud and risk matrix coupling model.

Water resource carrying capacity modelling is a fundamental task to explore the interaction mechanism between socio-economic development and water resource carrying system. To reasonably quantify regional water resource carrying capacity, firstly, the water resource carrying system was divided into pressure, support and regulation forces subsystems, then the multi-dimensional precondition cloud algorithm was introduced to quantify the belonging degree of single evaluation index, and the comprehensive belonging degree of each sample was further obtained through risk matrix and index weight, and finally the multi-dimensional precondition cloud and risk matrix coupling model (PCRM) was established to recognize carrying grade and reveal carrying mechanism. The application results of PCRM model indicated that water resource carrying capacity in Anhui province, China presented a slightly improving trend in both provincial and city scales during 2005 to 2015. Meanwhile, evaluation result of PCRM model was more approaching to the average characteristic value of different approaches, which indicated that PCRM coupling model is effectively to explore properties of indexes and subsystems of water resource carrying system, and could be further applied in other system evaluation and regulation research fields in the future.

Estimation of maize evapotraspiration under drought stress - A case study of Huaibei Plain, China.

Given the importance and complexity of crop evapotranspiration estimation under drought stress, an experiment tailored for maize under drought stress was completed using six sets of large-scale weighing lysimeters at the Xinmaqiao Comprehensive Experimental Irrigation and Drainage Station, Anhui Province, China. Our aim was to analyze maize evapotranspiration under different drought conditions. Based on estimates of maize evapotranspiration under no drought stress using the dual crop coefficient approach, we optimized and calibrated basic crop coefficients Kcbini, Kcbmid, Kcbend, and the maximum crop coefficient Kcmax using a genetic algorithm. Measurements of solar radiation at the experimental station were used to derive the empirical parameters a and b from the Angstrom formula through the genetic algorithm, and then evapotranspiration was calculated for the reference crop (ET0). We then estimated the maize evapotranspiration under drought using the dual crop coefficient approach. The results indicated that a slight water deficit during the earlier stage of vegetative growth may stimulate the maize homeostatic mechanism and increase tolerance to drought stress in later growth periods. Maize evapotranspiration significantly decreased if drought stress continued into the elongation stage, and the same degree of drought stress had a greater influence on the middle and later stages of vegetative and reproductive growth. The calibrated results for Kcbini, Kcbmid, Kcbend, and Kcmax were 0.155, 1.218, 0.420 and 1.497 respectively. We calculated the root-mean-square error (RMSE), mean absolute error (MAE), and mean relative error (MRE) of maize evapotranspiration under no drought stress over the full growing season using a dual crop coefficient approach, and the results were 1.33 mm/day, 0.99 mm/day, and 1.30%, respectively, or 18.40%, 17.50%, and 91.11% lower than results using the recommended coefficients. The RMSE, MAE, and MRE results for maize under drought stress during two full growth periods were 1.18 mm/day, 0.98 mm/day, and 13.92%, respectively. These results were higher than maize without drought stress, but better than the estimated results based on FAO-56 recommended values. Therefore, maize evapotranspiration estimation under drought stress using the dual crop coefficient approach and genetic algorithm was reasonable and reliable. This study provides a theoretical basis for developing suitable regional irrigation programs and decreasing losses due to agricultural drought.

Optimal Water Resources Regulation for the Pond Irrigation System Based on Simulation-A Case Study in Jiang-Huai Hilly Regions, China.

Due to the importance and complexity of water resources regulations in the pond irrigation systems of the Jiang-Huai hilly regions, a water allocation simulation model for pond irrigation districts based on system simulation theory was developed in this study. To maximize agricultural irrigation benefits while guaranteeing rural domestic water demand, an optimal water resources regulation model for pond irrigation districts and a simulation-based optimal water resources regulation technology system for the pond irrigation system were developed. Using this system, it was determined that the suitable pond coverage rate (pond capacity per unit area) was 2.92 × 105 m3/km2. Suitable water supply and operational rules for adjusting crop planting structure were also developed the water-saving irrigation method and irrigation system. To guarantee rural domestic water demand, the multi-year average total irrigation water deficit of the study area decreased by 4.66 × 104 m3/km2; the average multi-year water deficit ratio decreased from 20.40% to 1.18%; the average multi-year irrigation benefit increased by 1.11 × 105 RMB (16,128$)/km2; and the average multi-year revenue increased by 6.69%. Both the economic and social benefits were significant. The results of this study provide a theoretical basis and technological support for comprehensive pone governance in the Jiang-Huai hilly regions and promote the establishment of a water allocation scheme and irrigation system for pond irrigation districts, which have practical significance and important application value.

Quantitative Assessment and Diagnosis for Regional Agricultural Drought Resilience Based on Set Pair Analysis and Connection Entropy.

Assessment and diagnosis of regional agricultural drought resilience (RADR) is an important groundwork to identify the shortcomings of regional agriculture to resist drought disasters accurately. In order to quantitatively assess the capacity of regional agriculture system to reduce losses from drought disasters under complex conditions and to identify vulnerability indexes, an assessment and diagnosis model for RADR was established. Firstly, this model used the improved fuzzy analytic hierarchy process to determine the index weights, then proposed an assessment method based on connection number and an improved connection entropy. Furthermore, the set pair potential based on subtraction was used to diagnose the vulnerability indexes. In addition, a practical application had been carried out in the region of the Huaibei Plain in Anhui Province. The evaluation results showed that the RADR in this area from 2005 to 2014 as a whole was in a relatively weak situation. However, the average grade values had decreased from 3.144 to 2.790 during these 10 years and the RADR had an enhanced tendency. Moreover, the possibility of RADR enhancement for six cities in this region decreased from east to west, and the drought emergency condition was the weak link of the RADR in the Huaibei Plain.

Development and interpretation of new sediment rating curve considering the effect of vegetation cover for Asian basins.

Suspended sediment concentration of a river can provide very important perspective on erosion or soil loss of one river basin ecosystem. The changes of land use and land cover, such as deforestation or afforestation, affect sediment yield process of a catchment through changing the hydrological cycle of the area. A sediment rating curve can describe the average relation between discharge and suspended sediment concentration for a certain location. However, the sediment load of a river is likely to be undersimulated from water discharge using least squares regression of log-transformed variables and the sediment rating curve does not consider temporal changes of vegetation cover. The Normalized Difference Vegetation Index (NDVI) can well be used to analyze the status of the vegetation cover well. Thus long time monthly NDVI data was used to detect vegetation change in the past 19 years in this study. Then monthly suspended sediment concentration and discharge from 1988 to 2006 in Laichau station were used to develop one new sediment rating curve and were validated in other Asian basins. The new sediment model can describe the relationship among sediment yield, streamflow, and vegetation cover, which can be the basis for soil conservation and sustainable ecosystem management.

[Effects of combined pollution of lead and benzo[a] pyrene on seed growth of wheat in soils].

Seed germination, root elongation, shoot elongation and ratio of shoot to root of wheat in soils polluted by lead (Pb) and benzo (a)pyrene (B[a] P) with medium-low concentrations were studied to reveal the ecological effects of combined pollution and screen the indicative markers. Results indicated that seed germination was not sensitive to single or combined pollution of Pb or B[a] P. Root elongation was inhibited by single pollution of Pb or B[a]P to different extents. Extensive interactions between Pb and B[a]P occurred to root elongation of wheat, including synergistic-stimulatory effect and antagonistic-inhibitory effect. The joint action was mainly antagonistic. Single pollution of B [a] P had an inhibitory effect on shoot elongation. Under combined pollution conditions, the shoot elongation of wheat correlated well with Pb contents (p < 0.01). B[a] P or the interactions between pollutants had little effect on shoot elongation of wheat. The joint action on shoot elongation was consistently antagonistic. The response pattern of the ratio of shoot to root was similar to the response pattern of shoot elongation. However, the former had better correlation than the latter, indicating it as a more suitable indicative marker for Pb pollution. If lead acetate was employed instead of lead nitrate, longer root elongation, shorter shoot elongation and no effect on ratio of shoot to root were found. Therefore, the forms of Pb salt had significant influence on seed growth of wheat in soils.