Performances of Remote Sensing Monitoring Indices of Agricultural Drought in Growing Season of Typical Dry Year in Northeast China

During dry seasons or years, the runoff processes from small rivers influence the safety of riverside groundwater source fields. Water source exploitation has a considerable effect on river runoff. In this study, the riverside source field of the Liuan River in the Linquan County, Anhui Province, was analyzed. The effect of mining on the ecological flow of the river under river runoff conditions in different typical dry years was quantified. This was undertaken using numerical simulations of the groundwater flow to provide guidance for the establishment of mining schemes for riverside source fields. In 95% of typical dry years, the water supply of small rivers is insufficient. The improved 7Q10 method used to calculate the ecological flow in different dry years revealed that mining water had little effect on the ecological flow. However, during the pumping process, the groundwater level of the water source area decreased greatly. The establishment of riverside source fields can aid in reducing excessive development and use of deep groundwater. The planning, construction, and implementation of the “Divert water from the Yangtze River to the Huaihe River” project can effectively reduce the economic losses that have occurred due to severe drought in the local area.

Numerous drought indices have been developed and applied to monitor the severity of drought. It has been demonstrated that the evaluation of the indices is very important for further utilization of remotely sensed and meteorological information. The objective of this article is to investigate and compare the different methods derived from satellite/meteorological data for drought monitoring during the typical dry year (2006) in mid-eastern China. The compared six drought indices include the vegetation condition index (VCI), percent of average seasonal greenness (PASG), temperature condition index (TCI), vegetation supply water index (VSWI), percentage of precipitation anomalies (PPA) and standardized precipitation index (SPI). These indices are calculated based on different data sources including reflective data, thermal data, the combination of reflective and thermal data and meteorological data. The correlation matrix and regression relationships among the integrals under all drought indices, the integral under the relative air humidity (RAH) curve and cumulative rainfall at the location of 11 agro-meteorological stations for 2006 were calculated. Spatial comparison analysis among the drought indices reveals that all the indices have certain coincidence in the detected regional-scale distribution of drought especially those derived from the same data set, while obviously local-scale distribution differences were found among the different groups of indices. Compared to curves of the reflective and thermal indices, the overall trend of VSWI series has better consistence with the PPA curve. Based on correlation and regression analysis, it is demonstrated that VSWI can better reflect both the amount of precipitation and the severity of drought due to lack of rainfall. Furthermore, land surface temperature (LST) contributes more to the result of hybrid index (VSWI) than reflective information. There is logarithmic relationship between integral of VSWI and cumulative precipitation, while obvious linear correlations were found between integral under VSWI curve and integral under the RAH/TCI/PASG curves. According to the filed observation of droughts from agro-meteorological stations in the study area, it can be concluded that any single index is not sufficient to precisely depicting drought characteristics. The combined use of different indices at the same time or indices which integrate various sources of information may obtain more consistent results with the actual situation.

Establishing and assessing the Integrated Surface Drought Index (ISDI) for agricultural drought monitoring in mid-eastern China

Plastic film mulching (PM) has been widely used to improve maize (Zea mays L.) yields and water use efficiency (WUE) in Northeast China, but the effects of PM in a changing climate characterized by highly variable precipitation are not well understood. Six site-year field experiments were conducted in the dry and rainy years to investigate the effects of PM on maize growth, grain yield, and WUE in Northeast China. Compared to crops grown without PM treatment (control, CK), PM significantly increased the grain yield by 15-26% in the dry years, but no significant yield increase was observed in the rainy years. Yield increase in the dry years was mainly due to a large increase in dry matter accumulation pre-silking compared to the CK, which resulted from a greater dry matter accumulation rate due to the higher topsoil temperature and water content. As a result, the WUE of the crops that underwent PM (3.27 kg m-3) treatment was also increased by around 16% compared to the CK, although the overall evapotranspiration was similar between the two treatments. In the rainy years, due to frequent precipitation and scant sunshine, the topsoil temperature and water content in the field that received PM treatment was improved only at some stages and failed to cause higher dry matter accumulation, except at the 8th leaf stage. Consequently, the grain yield and WUE were not improved by PM in the rainy years. In addition, we found that PM caused leaf senescence at the late growth stage in both dry and rainy years. Therefore, in practice, PM should be applied cautiously, especially when in-season precipitation is taken into account.

Drought is a complex natural phenomenon. To effectively characterize the spatial extent and intensity of the phenomenon, multiple drought-related factors, such as precipitation, vegetation growth condition, and land surface temperature, should be considered comprehensively. However, the capability of each of these factors in drought monitoring varies with seasonal time. Thus, in formulating a drought index, different weights should be assigned to these factors at different time periods. This study proposes a novel remote sensing index, the Integrated Drought Condition Index (IDCI), for short-term drought monitoring. The index sets different weights for each month of the growing season into three components, i.e., precipitation, vegetation growth condition, and land surface temperature, based on the principle component analysis. To assess IDCI performance, the spatial drought conditions of the IDCI maps during the growing season in a typical dry year and individual month of August from 2003 to 2012 were compared with in situ drought indices in Northern China. Correlation analyses were performed between the IDCI and different timescale Standardized Precipitation Evapotranspiration Index values, and the year-to-year IDCI variations were compared with in situ drought indices. The results of the comparison and correlation analysis confirmed the effectiveness of IDCI in characterizing drought conditions and patterns.

In view of the problems that have not been solved or studied in the previous studies of cascade Energy Storage Operation Chart (ESOC), based on a brief description of the composition, principle, drawing methods, and simulation methods of ESOC, the following innovative work has been done in this paper. Firstly, considering the inconsistency of inflow frequency of upstream and downstream watershed in selecting the typical dry years, a novel optimization model for selecting the overall inflow process considering the integrity of watershed was proposed, which aimed at minimizing the sum of squares of inflow frequency differences. Secondly, aiming at the influence of output coefficients (including number and values) on the results of ESOC, this paper proposed a new method to construct the initial solution of output coefficients and established an optimization model of output coefficients based on progressive optimality algorithms. Thirdly, to the optimization of ESOC with multi-year regulating reservoir, a discrete optimization model of drawdown level was constructed based on the idea of ergodic optimization. On these bases, taking the seven reservoirs in the Yalong River basin of China as an example, the typical dry years considering the inflow frequency inconsistency, the optimal output coefficients of ESOC and the optimal end-of-year drawdown level of a multi-year regulating reservoir (Lianghekou) were obtained, and compared with the previous research results, the ESOC optimized in this paper can increase the total power generation of the cascade system by 9% under the condition that the guaranteed rate did not change much. Furthermore, the difference of the optimal end-of-year drawdown levels between the cascade joint operation and single reservoir operation was discussed for the Lianghekou reservoir at the end of the case study. The obtained results were of great significance for guiding the actual operation of cascade reservoirs.

Poyang Lake is the largest wintering habitat for migratory birds in Asia. In the last decade, the lake has experienced an early-occurring and prolonged dry season that has deteriorated the lake’s ecological status. To tackle this issue, the Chinese government has proposed the construction of the Poyang Lake Hydraulic Project (PLHP) to regulate water flow to the lake. However, its impact on migratory bird habitats is unknown. In this study, we simulated the habitat suitability for migratory birds in Poyang Lake during wet and dry years, with and without the presence/operation of the hydraulic project. A two-dimensional hydrodynamic model was used to simulate the water conditions for each case. Matter-element theory, 3S technology and ecological knowledge were combined to develop a matter-element-based habitat suitability model in a geographic information system (GIS)-based platform. We assessed and compared the habitat suitability in four scenarios: (1) Wet year without the hydraulic project, (2) wet year with the hydraulic project, (3) dry year without the hydraulic project, and (4) dry year with the hydraulic project. The results showed that the operation of the hydraulic project can effectively alleviate the water shortage issue in the wetland and increase the area of habitats suitable for migratory birds in typical dry years. However, it can reduce the area of suitable habitats in the northern provincial nature reserve of the lake. In addition, a reasonable management of the lake’s fishing activities can also increase habitat suitability and promote balanced patterns between human activities and migratory bird habitats.

Droughts are recognized as a natural disaster that is caused by the extreme and continuous shortage of precipitation. Drought indices assist in a number of tasks, including their early warning and monitoring by computing severity levels and proclaiming the start and end of droughts. Various drought indices were formulated for the forecasting and prediction of spatiotemporal drought characteristics using various hydrological variables, such as precipitation, evapotranspiration, runoff and soil moisture content. Due to anthropogenic global warming and the increase of temperature, evapotranspiration-based drought indices have become an interest in recent years in drought assessment. This paper attempts to provide more information on drought indices which incorporates Evapotranspiration. The study used Standardized Precipitation Evapotranspiration Index (SPEI), based on evapotranspiration to understand the drought variability at various time scales. This study adopted the Hargreaves model to calculate Potential Evapotranspiration. The SPEI index can also be used to study the wet and dry periods including Evapotranspiration along with precipitation. The study used SPEI to understand the dry and wet years over an urban semi-arid region, Hyderabad, capital and the biggest city of the southern Indian state of Telangana for the years 1965–2015. The years 1965, 1966, 1972, 1973, 1985, 1993 and 2012 were noted as dry years with SPEI values −1.35, −1.06, −1.43, −1.31, −1.05, −1.22 and −1.51 sequentially and year 2006 as the severe wet year with an SPEI value +1.65. The characterization of dry and wet years as demonstrated in the present study will enhance better urban water resources management.KeywordsDroughtSPEIEvapotranspirationHyderabad

The algal blooms in the Middle and Lower reaches of the Hanjiang River (MLHR) have become a great aquatic eco-environmental problem over recent years. The planned implementation of the Water Diversion Project from the Three Gorges Reservoir to the Hanjiang River (WDP-TH) would influence the growth and propagation of diatoms and the development of algal blooms. In this paper, a dynamic model of diatom growth is developed that considers factors such as light exposure, water temperature, total phosphorus, and flow velocity. The effects of the WDP-TH on algal density and blooms in the MLHR were predicted for a typical median year, a typical dry year, and an extremely dry year. The results showed that following the water recharge in a typical median year, the propagation of diatoms in the MLHR was significantly promoted because of an increase in total phosphorus concentration. However, following the water recharge in typical dry and extremely dry years, increased flow rate and improved hydrodynamic conditions significantly inhibited diatom growth and accelerated the transport process. The results of the hypothetical simulation showed that after the initiation of the WDP-TH, inhibition effects of improved hydrodynamic force on algae were more apparent than promotion effects of increased total phosphorus concentration in the MLHR.

In the context of global climate change, the increasing frequency, scale, and intensity of droughts severely threaten food security of China. We established two drought indices (crop evapotranspiration-effective preci-pitation index (CEEP) and water deficit index (WDI)) based on meteorological parameters and crop growth-related data during growing season. The performance of those two indices was compared with that of four widely used ones, i.e., percentage of precipitation anomaly (PA), moisture index (MI), standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI). We further used the six indices to analyze the characteristics of typical drought events in the winter wheat region of North China and the spring maize region of Northeast China, as well as the spatiotemporal variations of droughts from 1979 to 2018. The results showed that CEEP and WDI effectively captured crop water scarcity and drought characteristics, and WDI was identified as the optimal drought index in more than one-third of provinces, mainly concentrated in Northeast and North China. In terms of temporal variation, based on the WDI, there was no significant trend of drought events in the winter wheat region in North China and the spring maize region in Northeast China. In terms of spatial variation, the performance of the drought indices differed. In the winter wheat zone of North China, PA, MI, and SPI detected more wetting characteristics, while SPEI, CEEP, and WDI detected more drying characteristics. In the spring maize zone of Northeast China, the indices performed more consistency, with wetting trends observed in Suihua, Daqing, and Hegang while drying trends in western part of Jilin and Liaoning, southern Liaoning, western Heilongjiang, and southern Sanjiang Plain. WDI was suitable for crop water deficit analysis in Northeast and North China and could accurately reflect the spatial distribution of drying or wetting trends, which would provide support for water resource management and decision-making in agricultural production.

A variety of drought indices have been constructed to monitor agricultural drought using ground‐based observations and satellite data. The drought indices focus on diverse aspects of agricultural drought and may have diverse applicability in different regions. We calculated seven popular drought indices and evaluated their performances on monitoring agricultural drought in the main agricultural regions of China (i.e., Northeast China, the North China Plain, the middle‐and‐lower reaches of the Yangtze River, and the Sichuan Basin). The independent assessment data used here included three aspects: soil moisture, vegetation photosynthesis (i.e., sun‐induced chlorophyll fluorescence, SIF), and crop yield. Results show that drought indices with one‐month time scale are more sensitive to topsoil moisture than drought indices with longer time scales. Drought indices based on regular meteorological data (DImet) and synthesized drought indices (DIsyn) show better performances on capturing drought impacts on the SIF than other drought indices. DIsyn is more appropriate for predicting drought impact on crop yield than other drought indices. In addition, drought impact on vegetation photosynthesis and crop yield is lessened in humid or irrigated regions. Our study sheds light on agricultural drought researches in the future.

Study on runoff variations and responses can lay a foundation for flood control, water allocation and integrated river basin management. This study applied the Soil and Water Assessment Tool model to simulate the effects of land use on annual and monthly runoff in the Middle and Upstream Reaches of Taoerhe River basin, Northeast China, under the wet, average and dry climate conditions through scenario analysis. The results showed that from the early 1970s to 2000, land use change with an increase in farmland (17.0%) and decreases in forest (10.6%), grassland (4.6%) and water body (3.1%) caused increases in annual and monthly runoff. This effect was more distinct in the wet season or in the wet year, suggesting that land use change from the early 1970s to 2000 may increase the flood potential in the wet season. Increases in precipitation and air temperature from the average to wet year led to annual and monthly (March and from June to December) runoff increases, while a decrease in precipitation and an increase in air temperature from the average to dry year induced decreases in annual and monthly (all months except March) runoff, and moreover, these effects were more remarkable in the wet season than those in the dry season. Due to the integrated effects of changing land use and climate conditions, the annual runoff increased (decreased) by 70.1 mm (25.2 mm) or 197.4% (71.0%) from the average to wet (dry) year. In conclusion, climate conditions, especially precipitation, played an important role in runoff variations while land use change was secondary over the study area, and furthermore, the effects of changes in land use and/or climate conditions on monthly runoff were larger in the wet season. Copyright © 2012 John Wiley & Sons, Ltd.

Drought is one of the main natural disasters affecting economic development and food security. Drought monitoring and identification are the premise of disaster risk management, and the drought index is the main means of monitoring and identifying drought. The paper proposes a new drought index, the agricultural crop drought index (ACDI), which is suitable for rainfed agriculture in arid areas. ACDI calculates water deficit from precipitation and evapotranspiration and considers the weight of crop growth stage. The weight of growth stage and water deficit constitute the weighted data series. The fitting distribution is optimized by Kolmogorov–Smirnov test, and the data are standardized to obtain ACDI. The weight of growth stage is determined by the multiple correlation coefficient between meteorological factors and grain yield. A large weight is equivalent to a large coefficient, large coefficient means that meteorological factors in this growth stage will have a greater impact on grain yield, so the water deficit in this growth stage should play a more important role in defining drought index to better identify agricultural drought from the perspective of crops. Finally, Qiqihar, a semiarid area in Northeast China, is selected as the research area for the case study. Comparing ACDI with standard precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI) and crop water deficit index (CWDI), the standard deviation of ACDI is larger, which indicates that the difference between index values is larger and it is relatively good in distinguishing the degree of drought. In addition, the correlation coefficient between ACDI and climate grain yield passed the test with a significance level of 0.05, while the other three indexes did not pass the test, which shows that the relationship between ACDI and grain yield is higher than the other three drought indexes. For arid areas, grain yield can reflect the impact of drought. Therefore, ACDI looks more promising to identify agricultural drought from the perspective of crops. ACDI provides a reference for monitoring agricultural drought from the perspective of crop growth stage, and enriches the drought index theory.

Drought is a multidisciplinary concept that can have major impacts on ecological, agricultural, and socio-economic spheres. The accurate monitoring and information of spatio-temporal distribution of agricultural drought are effective means of reducing the farmers’ losses. The space-based technology is proven to provide the detail of land information, which helps to quantify different natural resources and even severity of climate extremes. The biophysical parameters such as precipitation, temperature, soil, and vegetation significantly influence drought monitoring in the regions. An artificial Neural Network (ANN) model based on the integration of Precipitation Condition Index (PCI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Soil Condition Index (SCI) derived from multi-source remote sensing satellite imagery was applied for assessment and prediction of drought. The study was implemented in Sangli, Maharashtra, India from the period 2003–2016 to assess the efficiency of the ANN model for near real-time drought monitoring. In our research, the investigation results for 2006, 2011, and 2016 (a typical dry year) were accurately explored using the ANN model. The multiyear ANN model results were also checked with the actual drought intensity of government records and observation. The proposed system demonstrated 92% accuracy and matched the trend with the ground base stations, hence the ANN model demonstrates the potential of using as drought monitoring indicator capturing both meteorological and agricultural drought information. The output of the study can be utilized for contingency planning by state and local governments.

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