Driving forces behind the spatiotemporal heterogeneity of land-use and land-cover change:A case study of the Weihe River Basin,China

The impact of socioeconomic development on land-use and land-cover change(LUCC)in river basins varies spatially and temporally.Exploring the spatiotemporal evolutionary trends and drivers of LUCC under regional disparities is the basis for the sustainable development and management of basins.In this study,the Weihe River Basin(WRB)in China was selected as a typical basin,and the WRB was divided into the upstream of the Weihe River Basin(UWRB),the midstream of the Weihe River Basin(MWRB),the downstream of the Weihe River Basin(DWRB),the Jinghe River Basin(JRB),and the Luohe River Basin(LRB).Based on land-use data(cultivated land,forestland,grassland,built-up land,bare land,and water body)from 1985 to 2020,we analyzed the spatiotemporal heterogeneity of LUCC in the WRB using a land-use transfer matrix and a dynamic change model.The driving forces of LUCC in the WRB in different periods were detected using the GeoDetector,and the selected influencing factors included meteorological factors(precipitation and temperature),natural factors(elevation,slope,soil,and distance to rivers),social factors(distance to national highway,distance to railway,distance to provincial highway,and distance to expressway),and human activity factors(population density and gross domestic product(GDP)).The results indicated that the types and intensities of LUCC conversions showed considerable disparities across different sub-basins,where complex conversions among cultivated land,forestland,and grassland occurred in the LRB,JRB,and UWRB,with higher dynamic change before 2000.The conversion of other land-use types to built-up land was concentrated in the UWRB,MWRB,and DWRB,with substantial increases after 2000.Additionally,the driving effects of the influencing factors on LUCC in each sub-basin also exhibited distinct diversity,with the LRB and JRB being influenced by the meteorological and social factors,and the UWRB,MWRB,and DWRB being driven by human activity factors.Moreover,the interaction of these influencing factors indicated an enhanced effect on LUCC.This study confirmed the spatiotemporal heterogeneity effects of socioeconomic status on LUCC in the WRB under regional differences,contributing to the sustainable development of the whole basin by managing sub-basins according to local conditions.

Quantitative Estimation on Contributions of Climate Changes and Human Activities to Decreasing Runoff in Weihe River Basin, China

Human activities and climate changes are deemed to be two primary driving factors influencing the changes of hydrological processes, and quantitatively separating their influences on runoff changes will be of great significance to regional water resources planning and management. In this study, the impact of climate changes and human activities was initially qualitatively distinguished through a coupled water and energy budgets analysis, and then this effect was further separated by means of a quantitative estimation based on hydrological sensitivity analysis. The results show that: 1) precipitation, wind speed, potential evapotranspiration and runoff have a significantly decreasing trend, while temperature has a remarkably increasing tendency in the Weihe River Basin, China; 2) the major driving factor on runoff decrease in the 1970 s and 1990 s in the basin is climate changes compared with that in the baseline 1960 s, while that in the 1980 s and 2000 s is human activities. Compared with the results based on Variable Infiltration Capacity(VIC) model, the contributions calculated in this study have certain reliability. The results are of great significance to local water resources planning and management.

Application of the InVEST model for assessing water yield and its response to precipitation and land use in the Weihe River Basin, China

With realizing the importance of ecosystem services to society, the efforts to evaluate the ecosystem services have increased. As the largest tributary of the Yellow River, the Weihe River has been endowed with many ecological service functions. Among which, water yield can be a measure of local availability of water and an index for evaluating the conservation function of the region. This study aimed to explore the temporal and spatial variation of water yield and its influencing factors in the Weihe River Basin(WRB), and provide basis for formulating reasonable water resources utilization schemes. Based on the InVEST(integrated valuation of ecosystem services and tradeoffs) model, this study simulated the water yield in the WRB from 1985 to 2019, and discussed the impacts of climatic factors and land use change on water yield by spatial autocorrelation analysis and scenario analysis methods. The results showed that there was a slight increasing trend in water yield in the WRB over the study period with the increasing rate of 4.84 mm/10a and an average depth of 83.14 mm. The main water-producing areas were concentrated along the mainstream of the Weihe River and in the southern basin. Changes in water yield were comprehensively affected by climate and underlying surface factors. Precipitation was the main factor affecting water yield, which was consistent with water yield in time. And there existed significant spatial agglomeration between water yield and precipitation. Land use had little impact on the amount of water yield, but had an impact on its spatial distribution. Water yield was higher in areas with wide distribution of construction land and grassland. Water yield of different land use types were different. Unused land showed the largest water yield capacity, whereas grassland and farmland contributed most to the total water yield. The increasing water yield in the basin indicates an enhanced water supply service function of the ecosystem. These results are of great significance to the water resources management of the WRB.

Spatial-temporal Analysis and Prediction of Precipitation Extremes: A Case Study in the Weihe River Basin, China

Extreme precipitation events bring considerable risks to the natural ecosystem and human life.Investigating the spatial-temporal characteristics of extreme precipitation and predicting it quantitatively are critical for the flood prevention and water resources planning and management.In this study,daily precipitation data(1957–2019)were collected from 24 meteorological stations in the Weihe River Basin(WRB),Northwest China and its surrounding areas.We first analyzed the spatial-temporal change of precipitation extremes in the WRB based on space-time cube(STC),and then predicted precipitation extremes using long short-term memory(LSTM)network,auto-regressive integrated moving average(ARIMA),and hybrid ensemble empirical mode decomposition(EEMD)-LSTM-ARIMA models.The precipitation extremes increased as the spatial variation from northwest to southeast of the WRB.There were two clusters for each extreme precipitation index,which were distributed in the northwestern and southeastern or northern and southern of the WRB.The precipitation extremes in the WRB present a strong clustering pattern.Spatially,the pattern of only high-high cluster and only low-low cluster were primarily located in lower reaches and upper reaches of the WRB,respectively.Hot spots(25.00%–50.00%)were more than cold spots(4.17%–25.00%)in the WRB.Cold spots were mainly concentrated in the northwestern part,while hot spots were mostly located in the eastern and southern parts.For different extreme precipitation indices,the performances of the different models were different.The accuracy ranking was EEMD-LSTM-ARIMA>LSTM>ARIMA in predicting simple daily intensity index(SDII)and consecutive wet days(CWD),while the accuracy ranking was LSTM>EEMD-LSTM-ARIMA>ARIMA in predicting very wet days(R95 P).The hybrid EEMD-LSTM-ARIMA model proposed was generally superior to single models in the prediction of precipitation extremes.

Runoff characteristics and its sensitivity to climate factors in the Weihe River Basin from 2006 to 2018

Exploring the current runoff characteristics after the large-scale implementation of the Grain for Green(GFG)project and investigating its sensitivities to potential drivers are crucial for water resource prediction and management.Based on the measured runoff data of 62 hydrological stations in the Weihe River Basin(WRB)from 2006 to 2018,we analyzed the temporal and spatial runoff characteristics in this study.Correlation analysis was used to investigate the relationships between different runoff indicators and climate-related factors.Additionally,an improved Budyko framework was applied to assess the sensitivities of annual runoff to precipitation,potential evaporation,and other factors.The results showed that the daily runoff flow duration curves(FDCs)of all selected hydrological stations fall in three narrow ranges,with the corresponding mean annual runoff spanning approximately 1.50 orders of magnitude,indicating that the runoff of different hydrological stations in the WRB varied greatly.The trend analysis of runoff under different exceedance frequencies showed that the runoff from the south bank of the Weihe River was more affluent and stable than that from the north bank.The runoff was unevenly distributed throughout the year,mainly in the flood season,accounting for more than 50.00%of the annual runoff.However,the trend of annual runoff change was not obvious in most areas.Correlation analysis showed that rare-frequency runoff events were more susceptible to climate factors.In this study,daily runoff under 10%-20%exceeding frequencies,consecutive maximum daily runoff,and low-runoff variability rate had strong correlations with precipitation,aridity index,and average runoff depth on rainy days.In comparison,daily runoff under 50%-99%exceeding frequencies,consecutive minimum daily runoff,and high-runoff variability rate had weak correlations with all selected impact factors.The sensitivity analysis results suggested that the sensitivity of annual runoff to precipitation was always higher than that to potential evaporation.The runoff about 87.10%of the selected hydrological stations were most sensitive to precipitation changes,and 12.90%were most sensitive to other factors.The spatial pattern of the sensitivity analysis indicated that in relatively humid southern areas,runoff was more sensitive to potential evaporation and other factors,and less sensitive to precipitation.

Drought monitoring and reliability evaluation of the latest TMPA precipitation data in the Weihe River Basin, Northwest China

The high resolution satellite precipitation products bear great potential for large-scale drought monitoring, especially for those regions with sparsely or even without gauge coverage. This study focuses on utilizing the latest Version-7 TRMM Multi-satellite Precipitation Analysis （TMPA 3B42V7） data for drought condition monitoring in the Weihe River Basin （0.135×10^6 km2）. The accuracy of the monthly TMPA 3B42V7 satellite precipitation data was firstly evaluated against the ground rain gauge observations. The statistical characteristics between a short period data series （1998-2013） and a long period data series （1961-2013） were then compared. The TMPA 3B42V7-based SPI （Standardized Precipitation Index） sequences were finally validated and analyzed at various temporal scales for assessing the drought conditions. The results indicate that the monthly TMPA 3B42V7 precipitation is in a high agreement with the rain gauge observations and can accurately capture the temporal and spatial characteristics of rainfall within the Weihe River Basin. The short period data can present the characteristics of long period record, and it is thus acceptable to use the short period data series to estimate the cumulative probability function in the SPI calculation. The TMPA 3B42V7-based SPI matches well with that based on the rain gauge observations at multiple time scales （i.e., 1-, 3-, 6-, 9-, and 12-month） and can give an acceptable temporal distribution of drought conditions. It suggests that the TMPA 3B42V7 precipitation data can be used for monitoring the occurrence of drought in the Weihe River Basin.

The Spatio-temporal Evolution of Ecological Risk and Its Drivers in the Weihe River Basin Landscape from 1990 to 2020

The Weihe River Basin has a significant number of tributaries and a delicate ecological environment.Understanding the spatial and temporal evolution and determinants of landscape ecological risk in the Weihe River Basin(WRB)can improve the scientific protection and development of its watershed ecosystems.This study is based on land use statistics from the WRB for a 30-year period represented by 1990,2000,2010,and 2020.An initial model for the assessment of landscaping ecological hazards was created using the software that was also used to generate the landscape ecological risk index,such as ArcGIS 10.4 and Fragstats 4.2-64.Next,the spatial and temporal evolution of landscape ecological risk in the vicinity of the study area was characterized by the trajectory of the center of gravity migration and the spatial autocorrelation of GeoDa.Finally,Geodetector was used to analyze ecological risk drivers in the landscapes.According to the findings,the high-risk and relatively high-risk regions are steadily expanding,while the low-risk and relatively low-risk areas dominate the ecological risk landscape in the WRB.Within the Weihe River Basin,Xianyang and Xi'an are the areas to which the high-risk centers of gravity are migrating.Positive spatial correlations were found between the landscape ecological hazards in the study area,most prominently in the form of high-high and low-low aggregations.The primary drivers are the interplay between the GDP component,temperature,and elevation as a single factor.

Identification of impacts of climate change and direct human activities on streamflow in Weihe River Basin in Northwest China

Climate change and human activities make major influences on hydrology,which are known to have important impacts on streamflow variation.Therefore,it is critically important to identify how climate change and human activities will impact streamflow variation.Thus,the goal of this study is to identify the impacts of climate change and direct human activities on annual streamflow at four hydrologic stations in the Weihe River basin of China,with the estimation of evaporation based on the Budyko hypothesis.The Mann-Kendall test was employed to detect the break points of the four stations.According to the occurrence time of break points,the data series were divided into two periods:pre-change period(1960-1984)and post-change(1985-2010)period.The parameter of one-parameter Budyko-type model was calibrated with observed data during the pre-change period,with the R^(2) values ranged from 0.95 to 0.97 and the NSE values ranged from 0.80 to 0.94,and the high R^(2) and Nash-Sutcliffe Efficiency coefficient shows the model has good performance.The contribution ratios of climate change impacts on decreasing streamflow were 37%,23%,57%and 43%,and those of the impacts of direct human activities were 63%,77%,43%and 57%for the Linjiacun,Xianyang,Lintong and Huaxian station,respectively.Both the climate change and direct human activities have positive impacts on streamflow decrease at all of the four stations,and the direct human activities are the main factor causing the decrease of annual streamflow.