Atmosphere

Research

22 pages, 11105 KiB

Open AccessArticle

Effects of Effective Precipitation and Accumulated Temperature on the Terrestrial EVI (Enhanced Vegetation Index) in the Yellow River Basin, China

by Huiliang Wang, Linpo He, Jun Yin, Zhilei Yu, Simin Liu and Denghua Yan

Atmosphere 2022, 13(10), 1555; https://doi.org/10.3390/atmos13101555 - 23 Sep 2022

Cited by 8 | Viewed by 2139

Abstract

To identify the vegetation dynamics and relationship with the hydrothermal conditions in the Yellow River basin (YRB), the spatial–temporal variations of EVI, effective precipitation (Epr), accumulated temperature (At), and their relationships were obtained based on the MODIS EVI data and meteorological data from [...] Read more.

To identify the vegetation dynamics and relationship with the hydrothermal conditions in the Yellow River basin (YRB), the spatial–temporal variations of EVI, effective precipitation (Epr), accumulated temperature (At), and their relationships were obtained based on the MODIS EVI data and meteorological data from the YRB during 2001–2020. The results indicate that EVI trends increased during 2001 to 2020, especially in the farmland, forestland, and grassland ecosystems. Epr and At have also increased over the last 20 years. Epr mostly increased faster in the grassland, and water bodies and wetland ecosystems. At mostly increased faster in the water bodies and wetland, desert, and forest ecosystems. Affected by Epr and At, the correlation between the EVI and hydrothermal conditions varied under different hydrothermal conditions. Compared to the At, the Epr was the restrictive factor for the EVI variations in the terrestrial ecosystem in the YRB. In addition, the dynamical thresholds of the EVI, Epr, and At were confirmed. This study can improve the understanding of vegetation variations and their response to regional climate change, which is critical for ecological conservation and the high-quality development of the YRB. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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16 pages, 3923 KiB

Open AccessArticle

Influence of Karst Reservoir Capacity on Flood in Lijiang Basin Based on Modified HEC-HMS through Soil Moisture Accounting Loss

by Junfeng Dai, Saeed Rad, Jingxuan Xu, Zupeng Wan, Zitao Li, Linyan Pan and Asfandyar Shahab

Atmosphere 2022, 13(10), 1544; https://doi.org/10.3390/atmos13101544 - 21 Sep 2022

Cited by 4 | Viewed by 3638

Abstract

The objective of this work was to modify the HEC-HMS flood prediction for the karstic watershed of the Lijiang River, South China, through the quantitative inclusion into the model of the available reservoir capacity of karst (ARCK) as a case study. Due to [...] Read more.

The objective of this work was to modify the HEC-HMS flood prediction for the karstic watershed of the Lijiang River, South China, through the quantitative inclusion into the model of the available reservoir capacity of karst (ARCK) as a case study. Due to the complexities caused by hidden drainage networks in karst hydrology, as a new approach, soil moisture accounting loss was used to reflect the ARCK in flood forecasting. The soil moisture loss was analyzed against daily rainfall runoff data across 1.5 years by using an artificial neural network via phyton programming. Through the correlations found among the amounts of soil moisture and river flow fluctuations in response to precipitation and its intervals, coefficients were introduced to the model for output modifications. ARCK analysis revealed that while heavy rainfalls with longer intervals (i.e., 174 mm/2d after 112 days of the dry season) may not cause considerable changes in the river flow magnitude (0.1–0.64 higher owing to high ARCK), relatively small rainfalls with higher frequency (i.e., 83 mm/4d during the wet season) can cause drastic raise of river flow (10–20 times greater at different stations) due to lower ARCK. Soil moisture accounting loss coefficients did enhance the model’s simulated hydrographs accuracy (NSE) up to 16% on average as compared to the initial forecasting via real data. However, the modifications were valid for flood events within a few years from the soil moisture observation period. Our result suggested that the inclusion of ARCK in modeling through soil moisture accounting loss can lead to increased prediction accuracy through consistent monitoring. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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17 pages, 6316 KiB

Open AccessArticle

Characteristics of Propagation of Meteorological to Hydrological Drought for Lake Baiyangdian in a Changing Environment

by Shan He, Enze Zhang, Junjun Huo and Mingzhi Yang

Atmosphere 2022, 13(9), 1531; https://doi.org/10.3390/atmos13091531 - 19 Sep 2022

Cited by 6 | Viewed by 2113

Abstract

The analysis of drought propagation has garnered mounting attention in the changing global environment. The current studies tend to focus on the propagation characteristics from meteorological to hydrological drought in rivers. Lakes, despite being a key component of watershed ecosystems, have received little [...] Read more.

The analysis of drought propagation has garnered mounting attention in the changing global environment. The current studies tend to focus on the propagation characteristics from meteorological to hydrological drought in rivers. Lakes, despite being a key component of watershed ecosystems, have received little attention to their response to meteorological and hydrological droughts. To this end, here, we investigated the characteristics of propagation from meteorological to hydrological drought for a lake in a changing environment. To determine the drought propagation time from meteorological to hydrological drought, we analyzed correlations between the standardized precipitation index (SPI), standardized runoff index (SRI), and standardized water level index (SWI). Lake Baiyangdian in China served as the case study. The results showed that meteorological droughts occur at high frequency but are short in duration, indicating that not every meteorological drought will necessarily lead to a hydrological drought. By contrast, lake hydrological droughts have low frequency and long duration and feature more severe consequences. Comparing drought characteristics before and after a changing environment, we found a reduced frequency of the SPI, SRI, and SWI, yet their duration was prolonged. For the SWI especially, these results were even more pronounced, which suggests the changing environment enabled further intensification of the lake hydrological drought. In addition, more time was needed for a meteorological drought to transition into a lake hydrological drought after a changing environment. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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20 pages, 2826 KiB

Open AccessArticle

Closing the Feedback of Evapotranspiration on the Atmospheric Evaporation Demand Based on a Complementary Relationship

by Tongtong Li, Dengfeng Liu, Songjun Han, Guanghui Ming, Jingjing Fan, Xianmeng Meng and Qiang Huang

Atmosphere 2022, 13(9), 1431; https://doi.org/10.3390/atmos13091431 - 4 Sep 2022

Cited by 4 | Viewed by 1641

Abstract

Evapotranspiration is the important feedback of the catchment into the atmosphere. However, in catchment hydrological modeling, the feedback of evaporation into the atmosphere is not closed and potential evaporation is always a meteorological forcing which is not dependent on the actual evaporation. A [...] Read more.

Evapotranspiration is the important feedback of the catchment into the atmosphere. However, in catchment hydrological modeling, the feedback of evaporation into the atmosphere is not closed and potential evaporation is always a meteorological forcing which is not dependent on the actual evaporation. A modeling framework to close the feedback of evapotranspiration into the atmosphere (FCEA) based on the evapotranspiration complementary relationship was proposed in the catchment hydrological modeling, and the effect of land-use changes on the runoff and evapotranspiration in the upper reach of Han River of China was investigated in the FCEA. Brutsaert uses the boundary condition analysis method to propose a nonlinear complementary relationship based on polynomial formula (B2015 function), which was applied in the study area, and the parameters were calibrated based on the catchment water balance of 1972–1990 and validated in 1991–2017. The actual evapotranspiration (AET) in the study area was estimated based on the complementary model in the upper reach of Han River. The SWAT model was used to simulate the catchment hydrological processes in the study area from 1972 to 2017. The evapotranspiration in the upper reach of Han River was studied in four scenarios to realize the feedback of evapotranspiration to the atmosphere and analyze the impact of the evapotranspiration feedback to the change of runoff in the basin. The results showed that the annual runoff in the upper reach of the Han River will increase, and the annual actual evapotranspiration will decrease in the long-term simulations in Scenarios 1 and 4. In Scenarios 2 and 3, with the increase of woodland, the annual runoff will decrease due to the feedback to the atmosphere, and annual actual evapotranspiration will increase, which is related to the increase in ecological water demand caused by the increase in woodland. Converting grassland into farmland will increase the runoff of the watershed. It is important to improve the land-use planning policy in the Han River Basin in order to realize the sustainable development of the river basin. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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19 pages, 4854 KiB

Open AccessArticle

Attribution Analysis of Runoff Change in the Upper Reaches of the Kaidu River Basin Based on a Modified Budyko Framework

by Guosen Shi and Bing Gao

Atmosphere 2022, 13(9), 1385; https://doi.org/10.3390/atmos13091385 - 29 Aug 2022

Cited by 3 | Viewed by 1737

Abstract

The Kaidu River plays an important role in the water development and utilization in the Tarim River basin in northwestern China. In this study, we used a modified Budyko framework, which considered the snowmelt to analyze and attribute the runoff change in the [...] Read more.

The Kaidu River plays an important role in the water development and utilization in the Tarim River basin in northwestern China. In this study, we used a modified Budyko framework, which considered the snowmelt to analyze and attribute the runoff change in the upper Kaidu River basin based on the observations during the period of 1960–2010. The time series was divided into two periods: 1960–1995 and 1996–2010. The contribution rate of runoff change between these two periods and the elasticity coefficient of runoff were estimated to quantify the effect of climatic variables and landscape changes on runoff alteration. The results show that the increase in precipitation was the major cause of increase in runoff, whose contribution accounted for 81.42%. The contribution rate of the landscape change was lower than that of the precipitation change, accounting for 9.07%. The elasticity coefficient of runoff to precipitation was 1.24, and the elasticity coefficient of runoff to the landscape was −0.74. Compared with the original Budyko framework, without considering the snowmelt, the contribution rates of precipitation and potential evaporation to runoff change would decrease after considering the snowmelt in the modified Budyko framework, while the contribution rate of landscape would increase. The increased snow ratio would cause more fluctuations in the runoff. This study provides a valuable reference for the water resources management in the upper Kaidu River basin and deepens our understanding of the response of runoff to climate change in snowmelt-affected regions. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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23 pages, 6707 KiB

Open AccessArticle

Spatio-Temporal Variation of Precipitation and Evaporation on the Tibetan Plateau and Their Influence on Regional Drought

by Yuanzhi Tang, Junjun Huo, Dejun Zhu, Tailai Gao and Xiaoxuan Jiang

Atmosphere 2022, 13(8), 1323; https://doi.org/10.3390/atmos13081323 - 19 Aug 2022

Cited by 1 | Viewed by 2359

Abstract

The Tibetan Plateau (TP) is an important water source in Asia, and precipitation and evaporation patterns at different geographical and temporal scales play a significant role in managing water resource distribution. Based on quality control data from 87 meteorological stations, this study analyzed [...] Read more.

The Tibetan Plateau (TP) is an important water source in Asia, and precipitation and evaporation patterns at different geographical and temporal scales play a significant role in managing water resource distribution. Based on quality control data from 87 meteorological stations, this study analyzed the spatial and temporal evolution patterns of precipitation and pan evaporation (Epan) on the TP in 1966–2016 using the Mann–Kendall test, the moving t-test, wavelet analysis, Sen’s slope method, and correlation analysis. The results revealed that the average mean temperature in the TP area increased by about 2.1 °C during the study period, and precipitation steadily increased at an average rate of 8.2 mm/10a, with summer and autumn precipitation making up about 80% of the year. In contrast, Epan showed an overall decreasing trend at a decline rate of 20.8 mm/10a, with spring and summer Epan values making up about 67% of the year. The time series of the precipitation and Epan within the TP region clearly exhibit nonstationary features. Precipitation is more concentrated in the southeast than in the northwest, while Epan is mostly concentrated in the southwest and northeast of the plateau around the Qaidam Basin. The “evaporation paradox” phenomenon was common in the TP region for about 40 years (1960s–1990s) and gradually faded in the 21st century. In addition, we introduced a standardized precipitation evaporation index (SPEI) to investigate the differences and relationships between precipitation and Epan time series over the past 50 years. The findings indicate that the southern Qinghai was dominated by an arid trend, while the central and southeast TP remained wet. Droughts and floods coexist in the eastern Qinghai and southern Tibet areas with high population concentrations, and the risk of both is rising as the inhomogeneity of precipitation distribution in the TP region will increase in the future. This study can be used as a reference for managing water resources and predicting regional drought and flood risk. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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17 pages, 14301 KiB

Open AccessArticle

Spatiotemporal Variation of Snow Cover and Its Response to Climate Change in the Source Region of the Yangtze River, China

by Mengqi Shi, Zhe Yuan, Xiaofeng Hong and Simin Liu

Atmosphere 2022, 13(8), 1161; https://doi.org/10.3390/atmos13081161 - 22 Jul 2022

Cited by 6 | Viewed by 1978

Abstract

In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data [...] Read more.

In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data in the source region of Yangtze River (SRYR) from 2000 to 2019, the snow phenology variables such as the snow cover day (SCD), snow onset date (SOD), snow end date (SED), and snow duration day (SDD) were extracted separately for each hydrological year, and the vertical distribution of snow cover area (SCA) in the SRYR was analyzed by combining with the digital elevation model (DEM). In addition, we also combined climate factors and land cover types to further explore the spatiotemporal variation characteristics of snow phenology in response to different influencing factors, in order to reveal the spatiotemporal variation patterns of snow cover in the SRYR. The results showed that: (1) The SCA in the SRYR has a more obvious vertical distribution, with the maximum SCA reaching 61.58% at high elevation, while at low elevation, the SCA is mostly below 20%. The distribution of SCD in the study area showed a significant exponential correlation with DEM (R² = 0.87). (2) The area of SOD in the SRYR showed an advanced trend of about 63.37%, while the area of SED showed a delayed trend of about 69.59%, and the area which showed significant trends is 4.29% and 4.36%, respectively. Therefore, the trends of both SOD and SED showed insignificant changes. (3) Temperature change is the main factor affecting the change of snow cover in the SRYR. Among them, 90.9% of the regions showed a significant positive correlation between temperature and SCD, while precipitation showed a significant negative correlation with SCD in about 75.3% of the total area of SRYR. Under the stable snow area (SCD > 60), the land cover type is glacial or permanent snow about 1.5 × 10³ km², which covers almost the entire glacial or permanent snow of the SRYR. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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25 pages, 4108 KiB

Open AccessArticle

Non-Stationary Hydrological Regimes Due to Climate Change: The Impact of Future Precipitation in the Spillway Design of a Reservoir, Case Study: Sube y Baja Dam, in Ecuador

by Jorge Enrique Herbozo, Luis Eduardo Muñoz, María José Guerra, Veronica Minaya, Patricia Haro, Veronica Carrillo, Carla Manciati and Lenin Campozano

Atmosphere 2022, 13(5), 828; https://doi.org/10.3390/atmos13050828 - 18 May 2022

Cited by 4 | Viewed by 3660

Abstract

Changes in flood loads and reservoir levels, produced by climate change (CC), represent an increasing concern for dam safety managers and downstream populations, highlighting the need to define adaptation strategies based on the dam failure risk management framework. Currently, thousands of dams worldwide, [...] Read more.

Changes in flood loads and reservoir levels, produced by climate change (CC), represent an increasing concern for dam safety managers and downstream populations, highlighting the need to define adaptation strategies based on the dam failure risk management framework. Currently, thousands of dams worldwide, varying in use, age, and maintenance, may represent a threat to downstream cities in the case of structural failure. Several studies relate the failure of dams to several issues in the spillway, which may be even more vulnerable in CC conditions. This study provides a review of dam safety threats due to CC and approaches for the design/redesign of the spillway to cope with CC. A general four-stage methodology is proposed: data gathering and hydro-climatic, hydrological, and hydraulic analyses. Afterward, this methodology is applied to the spillway design for the Sube y Baja dam in Ecuador. The Probable Maximum Precipitation (PMP) increases around 20% considering CC under the Representative Concentration Pathway 8.5. Such an increment derived a 25% increase in the spillway maximum flow. These results show that the non-stationary hydrological regimes related to CC require a revision of engineering design criteria for hydraulic structures in general, and call for a consensus on design variables under CC. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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13 pages, 4435 KiB

Open AccessArticle

ConvLSTM Network-Based Rainfall Nowcasting Method with Combined Reflectance and Radar-Retrieved Wind Field as Inputs

by Wan Liu, Yongqiang Wang, Deyu Zhong, Shuai Xie and Jijun Xu

Atmosphere 2022, 13(3), 411; https://doi.org/10.3390/atmos13030411 - 3 Mar 2022

Cited by 11 | Viewed by 3296

Abstract

Strong convection nowcasting has been gaining importance in regional security, economic development, and water resource management. Rainfall nowcasting with strong timeliness needs to effectively forecast the intensity of rainfall in a local region in the short term. The forecast performance of traditional methods [...] Read more.

Strong convection nowcasting has been gaining importance in regional security, economic development, and water resource management. Rainfall nowcasting with strong timeliness needs to effectively forecast the intensity of rainfall in a local region in the short term. The forecast performance of traditional methods is limited. In this paper, a rainfall nowcasting model based on the Convolutional Long Short-Term Memory (ConvLSTM) is proposed. Combined reflectance (CR) and the retrieved wind field are selected as the key factors for prediction. The model considers the influence of water vapor content, transport, and change on rainfall by measuring CR and the retrieved wind field. Forecast results are compared to different models and different input data schemes. The analysis shows that the CSI scores of this method can reach about 0.8, which is 28% higher than that of the optical flow method. The ConvLSTM structure with spatial analysis and time memory can greatly enhance the predictive ability of the model, and the addition of wind field data also improves the forecasting performance of the model. Therefore, the idea of forecasting rainfall on the basis of water vapor content and water vapor transport is practical and effective, and the accuracy of a forecast can be improved by using ConvLSTM network to extract spatiotemporal features. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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19 pages, 6297 KiB

Open AccessArticle

Spatiotemporal Characteristics of Droughts and Their Propagation during the Past 67 Years in Northern Thailand

by Baoxu Zhao, Dawen Yang, Shuyu Yang and Jerasorn Santisirisomboon

Atmosphere 2022, 13(2), 277; https://doi.org/10.3390/atmos13020277 - 7 Feb 2022

Cited by 6 | Viewed by 1953

Abstract

Droughts grow concurrently in space and time; however, their spatiotemporal propagation is still not fully studied. In this study, drought propagation and spatiotemporal characteristics were studied in northern, northeastern, and central Thailand (NNCT). The NNCT is an important agricultural exporter worldwide, and droughts [...] Read more.

Droughts grow concurrently in space and time; however, their spatiotemporal propagation is still not fully studied. In this study, drought propagation and spatiotemporal characteristics were studied in northern, northeastern, and central Thailand (NNCT). The NNCT is an important agricultural exporter worldwide, and droughts here can lead to considerable pressure on the food supply. This study investigated meteorological drought and soil drought in northern Thailand and identified 70 meteorological drought events and 44 soil drought events over 1948–2014. Severe droughts (droughts with long trivariate return periods) mainly occurred after 1975 and were centered in northern and northeastern Thailand. Meteorological drought and soil drought that occurred during 1979–1980 had the longest trivariate return periods of 157 years and 179 years, respectively. The drought centers were mainly located in the Chao Phraya River basin and the Mun River basin. The mean propagation ratios of all drought parameters (duration, area, severity) were lower than 1, indicating that the underlying surface can serve as a buffer to alleviate water deficits. Most of the probability distribution coefficients and all drought propagation ratios of the three drought parameters were found to change significantly based on a moving-window method, indicating that the drought parameters and propagation from meteorological drought to soil drought were non-stationary. Significant increasing trends were detected in mean values of most drought parameters, ranging from 2.4%/decade to 16.6%/decade. Significant decreasing trends were detected in coefficients of skewness (Cs) of all drought parameters and coefficients of variation (Cv) of most drought parameters, ranging from −3.3 to −12.4%/decade, and from −5.5 to −19.4%/decade, respectively. The propagation ratios of all drought parameters showed significant increasing trends, indicating that the function of the underlying surface as a buffer has become weaker. The drought propagation ratios were found to be positively related to two climate indices, the phase index (PI) and the climate seasonality index (CSI). These findings will help to develop a better understanding and management of water resources in Thailand. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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17 pages, 4008 KiB

Open AccessArticle

Compounding Effects of Fluvial Flooding and Storm Tides on Coastal Flooding Risk in the Coastal-Estuarine Region of Southeastern China

by Weiwei Lu, Lihua Tang, Dawen Yang, Heng Wu and Zhiwu Liu

Atmosphere 2022, 13(2), 238; https://doi.org/10.3390/atmos13020238 - 30 Jan 2022

Cited by 10 | Viewed by 2869

Abstract

In coastal areas of southeastern China, multiple flood drivers such as river flow, precipitation and coastal water level can lead to compound flooding which is often much greater than flooding simulated by one flood driver in isolation. Bivariate probability distributions accounting for compound [...] Read more.

In coastal areas of southeastern China, multiple flood drivers such as river flow, precipitation and coastal water level can lead to compound flooding which is often much greater than flooding simulated by one flood driver in isolation. Bivariate probability distributions accounting for compound flooding from river discharge and sea level were constructed based on MvCAT (Multivariate Copula Analysis Toolbox) combined with goodness of fit tests in 15 coastal-estuarine regions of Southeastern China. Flood typing-based bivariate probability distributions considering multiple flood-generating mechanisms were also built. Our results indicated that the performance of flood typing-based bivariate distribution was not significantly better than the bivariate probability distribution in coastal-estuarine regions based on the Mann–Whitney U test; the compounding effects of river discharge and sea level had limited impact on bivariate return periods, but had greater impact on coastal flooding risk in terms of design values. Ignoring compounding effects of river discharge and sea level leads to significant underestimation of design values. The results suggest that the compounding effect of river discharge and sea level should be considered when calculating design values in coastal flood risk assessment. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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20 pages, 5118 KiB

Open AccessArticle

Investigation of the Long-Term Trends in the Streamflow Due to Climate Change and Urbanization for a Great Lakes Watershed

by Elizabeth Philip, Ramesh P. Rudra, Pradeep K. Goel and Syed I. Ahmed

Atmosphere 2022, 13(2), 225; https://doi.org/10.3390/atmos13020225 - 29 Jan 2022

Cited by 4 | Viewed by 3203

Abstract

Climate change and rapid urbanization could possibly increase the vulnerability of the Great Lakes Basin, Canada, which is the largest surface freshwater system in the world. This study explores the joint impact of climate change and land-use changes on the hydrology of a [...] Read more.

Climate change and rapid urbanization could possibly increase the vulnerability of the Great Lakes Basin, Canada, which is the largest surface freshwater system in the world. This study explores the joint impact of climate change and land-use changes on the hydrology of a rapidly urbanizing Credit River watershed which lets out into Lake Ontario 25 km southwest of downtown Toronto, Ontario (ON), Canada; we began by classifying the watershed into urban and rural sections. A non-parametric Mann–Kendall test and the Sen slope estimator served to detect and describe the annual-, seasonal-, and monthly-scale trends in the climate variables (temperature, precipitation, and evapotranspiration), as well as the streamflow characteristics (median annual streamflow, baseflow, Runoff Coefficients (RC), Flow Duration Curve (FDC), Center of Volume (COV), and Peak Over Threshold (POT)) since 1916 for four rural and urban sub-watersheds. The temperature, precipitation and evapotranspiration (1950–2019) showed significant increasing trends for different months and seasons. Furthermore, the results indicated that the median annual streamflow, 7-day annual minimum flow, and days above normal are increasing; meanwhile, the annual maximum streamflow is decreasing. A total of 230 datasets were tested for their trends; of these, 80% and 20% increasing and decreasing trends were obtained, respectively. Of the total, significant trends (<0.05%) of 32% and 2% increasing and decreasing, respectively, were observed. The results of the FDC analysis indicated a decline in the annual and winter 10:90 exceedance ratio over the years for the rural and urban sub-watershed gauges. The BFI results show that the BFI of the rural areas was, on average, 18% higher than that of the urban areas. In addition, the RC also showed the influence of land-use and population changes on the watershed hydrology, as the RC for the urban gauge area was 19.3% higher than that for the rural area gauge. However, the difference in the RC was the lowest (5.8%) in the summer. Overall, the findings from this study highlight the annual, seasonal, and monthly changes in the temperature, precipitation, evapotranspiration, and streamflow in the watershed under study. Based on the available monitored data, it was difficult to quantify the changes in the streamflow over the decade which were attributable to population growth and land-cover use and management changes due to municipal official planning in the watershed. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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18 pages, 39113 KiB

Open AccessArticle

The Intraseasonal Variations of the Leading Mode of Summer Precipitation Anomalies in Meiyu Area of East Asia

by Zikang Jia, Zhihai Zheng, Guolin Feng and Mingjun Tong

Atmosphere 2022, 13(2), 217; https://doi.org/10.3390/atmos13020217 - 28 Jan 2022

Cited by 2 | Viewed by 2440

Abstract

The intraseasonal variations of summer precipitation anomalies in the Meiyu area of East Asia are analyzed by applying a combined empirical orthogonal function (CEOF) of the latest meteorological reanalysis data ERA5 of European Center for Medium-Range Weather Forecasts for the period from 1991 [...] Read more.

The intraseasonal variations of summer precipitation anomalies in the Meiyu area of East Asia are analyzed by applying a combined empirical orthogonal function (CEOF) of the latest meteorological reanalysis data ERA5 of European Center for Medium-Range Weather Forecasts for the period from 1991 to 2020, and the circulation structures and sources of variability of CEOF are also investigated. The first mode of the intraseasonal variations shows an in-phase pattern over the Meiyu area in June, July, and August, accounting for 22.2% of the total variance in the intraseasonal variations of summer precipitation anomalies. The positive (negative) CEOF1 is accompanied by the negative (positive) East Asia/Pacific pattern, including strong westerly wind anomalies in the upper troposphere and southwest monsoon in the lower troposphere, and the Western Pacific Subtropical High extending westward and its ridge line slightly south. The positive CEOF1 is preceded by decay of El Niño episodes, including the abnormal warm sea surface temperature anomalies (SSTAs) in the equatorial Central-Eastern Pacific in spring and warm SSTAs in the equatorial Indian Ocean in summer. The second mode shows an opposite precipitation anomaly in June and July, and the distribution in August is not significant. The corresponding geopotential height circulation of positive CEOF2 shows the large negative anomaly in the region north of 40° N and a positive anomaly over Japan in June, whereas the pattern reverses in July. At the same time, there is a radical reversion from abnormal eastly to westly wind in the upper troposphere. The structure of CEOF2 is somewhat induced by local SSTAs over the Northern Indian Ocean and South China Sea. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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21 pages, 5644 KiB

Open AccessArticle

Future Changes in High and Low Flows under the Impacts of Climate and Land Use Changes in the Jiulong River Basin of Southeast China

by Shuyu Yang, Dawen Yang, Baoxu Zhao, Teng Ma, Weiwei Lu and Jerasorn Santisirisomboon

Atmosphere 2022, 13(2), 150; https://doi.org/10.3390/atmos13020150 - 18 Jan 2022

Cited by 11 | Viewed by 2809

Abstract

Climate change and human activities have profoundly affected the world with extreme precipitation, heat waves, water scarcity, frequent floods and intense droughts. It is acknowledged that climate change will persist and perhaps intensify in the future, and it is thus meaningful to explore [...] Read more.

Climate change and human activities have profoundly affected the world with extreme precipitation, heat waves, water scarcity, frequent floods and intense droughts. It is acknowledged that climate change will persist and perhaps intensify in the future, and it is thus meaningful to explore the quantitative impacts of these changes on hydrological regimes. The Jiulong River basin serves as an important watershed on the southeast coast of China. However, future hydrological changes under the combined impacts of climate change and land use change have been barely investigated. In this study, the climate outputs from five general circulation models (GCMs) under the Coupled Model Intercomparison Project Phase 6 (CMIP6) were corrected and spatially downscaled by a statistical downscaling method combining quantile mapping and machine learning. The future high-resolution land use maps were projected by the CA–Markov model with land use changes from the Land-Use Harmonization 2 (LUH2) as constraints. The future dynamic vegetation process was projected by the Biome-GBC model, and then, the future hydrological process under four representative concentration pathways and shared socioeconomic pathways (RCP–SSP) combined scenarios was simulated by a distributed hydrological model. Based on the copula method, the flood frequency and corresponding return periods were derived. The results demonstrated that future precipitation and air temperature would continue to rise, and future land use changes would have different developing pathways determined by the designs in various SSP–RCPs. Under the combined impacts of climate and land use change, the total available water resources will increase due to increasing precipitation, and the high flow and low flow will both increase at three stations under the four SSP–RCPs. The annual 1-day maximum discharge is projected to increase by 67–133% in the last decade of the 21st century, and the annual 7-day minimum discharge is projected to increase by 19–39%. The flood frequency analysis showed that the Jiulong River basin would face more frequent floods in the future. By the end of the 21st century, the station-average frequency of a historical 100-year flood will increase by 122% under the most optimistic scenario (SSP126) and increase by 213% under the scenario of greatest regional rivalry (SSP370). We demonstrated that climate change would be the major cause for the increase in future high flows and that land use change would dominate future changes in low flows. Finally, we recommend integrated and sustainable water management systems to tackle future challenges in this coastal basin. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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22 pages, 6315 KiB

Open AccessArticle

Quantifying the Impact of Future Climate Change on Runoff in the Amur River Basin Using a Distributed Hydrological Model and CMIP6 GCM Projections

by Ke Wen, Bing Gao and Mingliang Li

Atmosphere 2021, 12(12), 1560; https://doi.org/10.3390/atmos12121560 - 26 Nov 2021

Cited by 14 | Viewed by 2824

Abstract

The Amur River is one of the top ten longest rivers in the world, and its hydrological response to future climate change has been rarely investigated. In this study, the outputs of four GCMs in the Coupled Model Intercomparison Project Phase 6 (CMIP6) [...] Read more.

The Amur River is one of the top ten longest rivers in the world, and its hydrological response to future climate change has been rarely investigated. In this study, the outputs of four GCMs in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were corrected and downscaled to drive a distributed hydrological model. Then, the spatial variations of runoff changes under the future climate conditions in the Amur River Basin were quantified. The results suggest that runoffs will tend to increase in the future period (2021–2070) compared with the baseline period (1961–2010), particularly in August and September. Differences were also found among different GCMs and scenarios. The ensemble mean of the GCMs suggests that the basin-averaged annual precipitation will increase by 14.6% and 15.2% under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. The increase in the annual runoff under the SSP2-4.5 scenario (22.5%) is projected to be larger than that under the SSP5-8.5 scenario (19.2%) at the lower reach of the main channel. Future climate changes also tend to enhance the flood peak and flood volume. The findings of this study bring new understandings of the hydrological response to future climate changes and are helpful for water resource management in Eurasia. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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19 pages, 16720 KiB

Open AccessArticle

Spatio-Temporal Variations in the Temperature and Precipitation Extremes in Yangtze River Basin, China during 1961–2020

by Zhe Yuan, Jun Yin, Mengru Wei and Yong Yuan

Atmosphere 2021, 12(11), 1423; https://doi.org/10.3390/atmos12111423 - 28 Oct 2021

Cited by 14 | Viewed by 2858

Abstract

Based on daily maximum temperature (Tmax), minimum temperature (Tmin), and precipitation of the Yangtze River Basin (YRB) from 1961 to 2020, we employed the trend analysis method and correlation analysis method to analyze spatiotemporal variations in 10 extreme indices and their associations with [...] Read more.

Based on daily maximum temperature (Tmax), minimum temperature (Tmin), and precipitation of the Yangtze River Basin (YRB) from 1961 to 2020, we employed the trend analysis method and correlation analysis method to analyze spatiotemporal variations in 10 extreme indices and their associations with atmospheric and oceanic circulations. Results indicated that maximum Tmax (TXx), maximum Tmin (TNx), and minimum Tmin (TNn) all increased significantly, at rates of 0.19 °C, 0.19 °C, and 0.37 °C per decade, respectively, whereas minimum Tmax (TXn) did not show any significant trend. The diurnal temperature range (DTR) decreased by 0.09 °C per decade as minimum temperatures increased faster than maximum temperatures. TNx and TNn increased significantly in the majority of the YRB, but TXn showed no significant increases. TXn increased significantly in the upper reaches of the Yangtze River. The DTR increased significantly in the Jinsha River Basin and the lower reaches of the Yangtze River. Rx1day (maximum 1-day precipitation), SDII (Simple daily intensity index) and R99p (extremely wet-day precipitation) increased significantly, at rates of 1.12 mm, 0.09 mm, and 5.87 mm per decade, respectively, but the trends of Rx5day (maximum 5-day precipitation) and PRCPTOT (total wet-day precipitation) were not significant. However, the trends of precipitation extreme indices were not statistically significant in most of the YRB. In the future, maximum temperature and minimum temperature might increase while DTR might decrease. But, the trends of precipitation extremes in the future were ambiguous. Nearly all the extreme indices were related to the variability of Atlantic multidecadal oscillation (AMO) in the YRB. In addition, the correlations between extreme temperature indices and AMO are higher than that of extreme precipitation indices. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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13 pages, 2330 KiB

Open AccessArticle

Impacts of Climate Change on Blue and Green Water Resources in the Middle and Upper Yarlung Zangbo River, China

by Junjun Huo, Xing Qu, Dejun Zhu, Zhe Yuan and Yuanzhi Tang

Atmosphere 2021, 12(10), 1280; https://doi.org/10.3390/atmos12101280 - 30 Sep 2021

Cited by 5 | Viewed by 2320

Abstract

The Yarlung Zangbo River is the largest river on the Tibetan Plateau and a major international river in South Asia. Changes in the blue and green water resources in its basin are of great importance to the surrounding local and Asian regions in [...] Read more.

The Yarlung Zangbo River is the largest river on the Tibetan Plateau and a major international river in South Asia. Changes in the blue and green water resources in its basin are of great importance to the surrounding local and Asian regions in the context of global warming. This research used the Soil and Water Assessment Tool model to estimate blue and green flows (BWF and GWF) and analyze the spatial-temporal distribution characteristics under different hypothetical climate change scenarios. The results show that (1) the multi-year average BWF in the middle and upper reaches of the Yarlung Zangbo River Basin is 176.2 mm, the GWF is 213.1 mm, and the difference between precipitation and total water resources is only 5.4 mm; (2) both BWF and GWF in this basin showed a slightly increasing trend from 1980 to 2010, but the distribution of subbasins from upstream to downstream is decreasing; and (3) GWF has a positive correlation with both precipitation and temperature, but BWF only increases with precipitation and decreases with increasing temperature. Moreover, the change in blue and green water resources is more sensitive to the changes in precipitation than to changes in the temperature. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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15 pages, 2924 KiB

Open AccessArticle

Characteristics of Agricultural Droughts and Spatial Stratified Heterogeneity and Dependence of Dominant Factors in Inner Mongolia Autonomous Region, China

by Simin Yang, Quan Quan, Weijia Liang and Tiejun Liu

Atmosphere 2021, 12(10), 1249; https://doi.org/10.3390/atmos12101249 - 26 Sep 2021

Cited by 3 | Viewed by 2008

Abstract

Droughts have significantly damaged the environment of the Inner Mongolia Autonomous Region, China. In this study, the region was divided into two subregions. Soil moisture was used as the basic parameter to analyze the characteristics of agricultural droughts. Based on a geographical detector, [...] Read more.

Droughts have significantly damaged the environment of the Inner Mongolia Autonomous Region, China. In this study, the region was divided into two subregions. Soil moisture was used as the basic parameter to analyze the characteristics of agricultural droughts. Based on a geographical detector, the spatial stratified heterogeneity in different seasons was discussed. Moreover, the copula joint functions of characteristics and dominant factors of agricultural droughts were constructed. Based on the Soil Moisture Anomaly Percentage Index (SMAPI), the results demonstrate that the climate tendency rate of droughts in the summer and in spring in Subregion I shows an increasing trend, while it decreases in the autumn and winter. In Subregion II, the climate tendency rate of droughts in different seasons has no significant change. Through geographical detection, the single factor detection illustrates that temperature and Precipitation Conversion Efficiency (PCE) show the highest explanatory power in different subregions. The interactive detection also demonstrates the explanatory powers of the combination of the PCE and temperature, respectively. The t-copula function describes the correlation coefficients of the SMAPI with the PCE and temperature, with the optimal tail dependence. In short, agricultural droughts are most significantly affected by temperature and the PCE, and their balance has a significant impact on agricultural droughts. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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15 pages, 2921 KiB

Open AccessArticle

Early-Warning Signals of Drought-Flood State Transition over the Dongting Lake Basin Based on the Critical Slowing Down Theory

by Hao Wu, Wei Hou, Dongdong Zuo, Pengcheng Yan and Yuxing Zeng

Atmosphere 2021, 12(8), 1082; https://doi.org/10.3390/atmos12081082 - 23 Aug 2021

Cited by 6 | Viewed by 2482

Abstract

In this study, the standardized precipitation index (SPI) data in Hunan Province from 1961 to 2020 is adopted. Based on the critical slowing down theory, the moving t-test is firstly used to determine the time of drought-flood state transition in the Dongting [...] Read more.

In this study, the standardized precipitation index (SPI) data in Hunan Province from 1961 to 2020 is adopted. Based on the critical slowing down theory, the moving t-test is firstly used to determine the time of drought-flood state transition in the Dongting Lake basin. Afterwards, by means of the variance and autocorrelation coefficient that characterize the phenomenon of critical slowing down, the early-warning signals indicating the drought-flood state in the Dongting Lake basin are explored. The results show that an obvious drought-to-flood (flood-to-drought) event occurred around 1993 (2003) in the Dongting Lake basin in recent 60 years. The critical slowing down phenomena of the increases in the variance and autocorrelation coefficient, which are detected 5–10 years in advance, can be considered as early-warning signals indicating the drought-flood state transition. Through the studies on the drought-flood state and related early-warning signals for the Dongting Lake basin, the reliabilities of the variance and autocorrelation coefficient-based early-warning signals for abrupt changes are demonstrated. It is expected that the wide application of this method could provide important scientific and technological support for disaster prevention and mitigation in the Dongting Lake basin, and even in the middle and lower reaches of the Yangtze River. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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16 pages, 13222 KiB

Open AccessArticle

Research on Monthly Precipitation Prediction Based on the Least Square Support Vector Machine with Multi-Factor Integration

by Jingchun Lei, Quan Quan, Pingzhi Li and Denghua Yan

Atmosphere 2021, 12(8), 1076; https://doi.org/10.3390/atmos12081076 - 21 Aug 2021

Cited by 5 | Viewed by 2303

Abstract

Accurate precipitation prediction is of great significance for regional flood control and disaster mitigation. This study introduced a prediction model based on the least square support vector machine (LSSVM) optimized by the genetic algorithm (GA). The model was used to estimate the precipitation [...] Read more.

Accurate precipitation prediction is of great significance for regional flood control and disaster mitigation. This study introduced a prediction model based on the least square support vector machine (LSSVM) optimized by the genetic algorithm (GA). The model was used to estimate the precipitation of each meteorological station over the source region of the Yellow River (SRYE) in China for 12 months. The Ensemble empirical mode decomposition (EEMD) method was used to select meteorological factors and realize precipitation prediction, without dependence on historical data as a training set. The prediction results were compared with each other, according to the determination coefficient (R²), mean absolute errors (MAE), and root mean square error (RMSE). The results show that sea surface temperature (SST) in the Niño 1 + 2 region exerts the largest influence on accuracy of the prediction model for precipitation in the SRYE (

R_{SST}^{2} =

0.856,

{RMSE}_{SST} =

19.648,

{MAE}_{SST} =

14.363). It is followed by the potential energy of gravity waves (Ep) and temperature (T) that have similar effects on precipitation prediction. The prediction accuracy is sensitive to altitude influences and accurate prediction results are easily obtained at high altitudes. This model provides a new and reliable research method for precipitation prediction in regions without historical data. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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20 pages, 9141 KiB

Open AccessArticle

Comparison of CMIP5 and CMIP6 Multi-Model Ensemble for Precipitation Downscaling Results and Observational Data: The Case of Hanjiang River Basin

by Dong Wang, Jiahong Liu, Weiwei Shao, Chao Mei, Xin Su and Hao Wang

Atmosphere 2021, 12(7), 867; https://doi.org/10.3390/atmos12070867 - 3 Jul 2021

Cited by 29 | Viewed by 6008

Abstract

Evaluating global climate model (GCM) outputs is essential for accurately simulating future hydrological cycles using hydrological models. The GCM multi-model ensemble (MME) precipitation simulations of the Climate Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6, respectively) were spatially and temporally downscaled [...] Read more.

Evaluating global climate model (GCM) outputs is essential for accurately simulating future hydrological cycles using hydrological models. The GCM multi-model ensemble (MME) precipitation simulations of the Climate Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6, respectively) were spatially and temporally downscaled according to a multi-site statistical downscaling method for the Hanjiang River Basin (HRB), China. Downscaled precipitation accuracy was assessed using data collected from 14 meteorological stations in the HRB. The spatial performances, temporal performances, and seasonal variations of the downscaled CMIP5-MME and CMIP6-MME were evaluated and compared with observed data from 1970–2005. We found that the multi-site downscaling method accurately downscaled the CMIP5-MME and CMIP6-MME precipitation simulations. The downscaled precipitation of CMIP5-MME and CMIP6-MME captured the spatial pattern, temporal pattern, and seasonal variations; however, precipitation was slightly overestimated in the western and central HRB and precipitation was underestimated in the eastern HRB. The precipitation simulation ability of the downscaled CMIP6-MME relative to the downscaled CMIP5-MME improved because of reduced biases. The downscaled CMIP6-MME better simulated precipitation for most stations compared to the downscaled CMIP5-MME in all seasons except for summer. Both the downscaled CMIP5-MME and CMIP6-MME exhibit poor performance in simulating rainy days in the HRB. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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14 pages, 1634 KiB

Open AccessArticle

Study on the Response of Different Soybean Varieties to Water Management in Northwest China Based on a Model Approach

by Yunxuan Zhang, Sien Li, Mousong Wu, Danni Yang and Chunyu Wang

Atmosphere 2021, 12(7), 824; https://doi.org/10.3390/atmos12070824 - 27 Jun 2021

Cited by 3 | Viewed by 2247

Abstract

Soybean is one of the major crops that is widely cultivated in Northwest China due to its high nutritional and economic value. However, drought has recently become an important factor restricting the growth of soybeans in the arid region of Northwest China and [...] Read more.

Soybean is one of the major crops that is widely cultivated in Northwest China due to its high nutritional and economic value. However, drought has recently become an important factor restricting the growth of soybeans in the arid region of Northwest China and the selection of drought-resistant soybean is of importance for cooperating with drought and improving yield. In this study, three-year soybean field experiments were conducted to test the effects of different water treatments on the soil moisture status and the yield of two varieties of soybeans (Longhuang1 (LH1), Longahuang3 (LH3)). Based on the field data, the soil water content, biomass, LAI, and yield were calibrated and evaluated using the soil-crop system model WHCNS (soil Water Heat Carbon Nitrogen Simulator). The results showed that the nRMSE, NSE, IA, and R² of the soil water content from two types of soybean, i.e., LH1 (LH3) were 10.98% (9.79%), 0.86 (0.90), 0.96 (0.97), 0.87 (0.90), respectively. The nRMSE, NSE, IA and R² of the yield of LH1 (LH3) were 19.12% (4.41%), 0.87 (0.99), 0.97 (1.00), 0.98 (0.99), respectively. Scenario simulations of yield and other indicators in two soybean varieties under different irrigation schedules in different hydrological years showed that the maximum yield and II of LH3 are lower than those of LH1, but the higher yield and II of LH1 comes from a larger irrigation amount. Appropriately reducing the number of irrigations in the branching period will not reduce crop yield and may oppositely lead to a small increase in yield and income; reducing the number of irrigations at the end of grouting has no significant impact on yield and income. Full article

(This article belongs to the Special Issue Hydrological Responses under Climate Changes)

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