Analysing the Potential Impact of Climate Change on the Hydrological Regime of the Upper Benue River Basin (North Cameroon)

In this study, we analyse the climate variability in the Upper Benue basin and assess its potential impact on the hydrology regime under two different greenhouse gas emission scenarios. The hydrological regime of the basin is more vulnerable to climate variability, especially precipitation and temperature. Observed hydroclimatic data (1950-2015) was analysed using a statistical approach. The potential impact of future climate change on the hydrological regime is quantified using the GR2M model and two climate models: HadGEM2-ES and MIROC5 from CMIP5 under RCP 4.5 and RCP 8.5 greenhouse gas emission scenarios. The main result shows that precipitation varies significantly according to the geographical location and time in the Upper Benue basin. The trend analysis of climatic parameters shows a decrease in annual average precipitation across the study area at a rate of -0.568 mm/year which represents about 37 mm/year over the time 1950-2015 compared to the 1961-1990 reference period. An increase of 0.7°C in mean temperature and 14% of PET are also observed according to the same reference period. The two climate models predict a warming of the basin of about 2°C for both RCP 4.5 and 8.5 scenarios and an increase in precipitation between 1% and 10% between 2015 and 2100. Similarly, the average annual flow is projected to increase by about +2% to +10% in the future for both RCP 4.5 and 8.5 scenarios between 2015 and 2100. Therefore, it is primordial to develop adaptation and mitigation measures to manage efficiently the availability of water resources.

Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis

Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.

Effect of sand-fixing vegetation on the hydrological regulation function of sand dunes and its practical significance

Soil water content is a key controlling factor for vegetation restoration in sand dunes.The deep seepage and lateral migration of water in dunes affect the recharge process of deep soil water and groundwater in sand dune ecosystems.To determine the influence of vegetation on the hydrological regulation function of sand dunes,we examined the deep seepage and lateral migration of dune water with different vegetation coverages during the growing season in the Horqin Sandy Land,China.The results showed that the deep seepage and lateral migration of water decreased with the increase in vegetation coverage on the dunes.The accumulated deep seepage water of mobile dunes(vegetation coverage<5%)and dunes with vegetation coverage of 18.03%,27.12%,and 50.65%accounted for 56.53%,51.82%,18.98%,and 0.26%,respectively,of the rainfall in the same period.The accumulated lateral migration of water in these dunes accounted for 12.39%,6.33%,2.23%,and 7.61%of the rainfall in the same period.The direction and position of the dune slope affected the soil water deep seepage and lateral migration process.The amounts of deep seepage and lateral migration of water on the windward slope were lower than those on the leeward slope.The amounts of deep seepage and lateral migration of water showed a decreasing trend from the bottom to the middle and to the top of the dune slope.According to the above results,during the construction of sand-control projects in sandy regions,we suggest that a certain area of mobile dunes(>13.75%)should be retained as a water resource reservoir to maintain the water balance of artificial fixed dune ecosystems.These findings provide reliable evidence for the accurate assessment of water resources within the sand dune ecosystem and guide the construction of desertification control projects.

Initiatives to clarify mechanisms of hydrological evolution in human-influenced Yellow River Basin

Significant changes in water cycle elements/processes have created serious challenges to regional sustainability and high-quality development in the Yellow River Basin in China.It is necessary to investigate the impacts of climate change and human activities on hydrological evolution and disaster risk from a holistic perspective of the basin.This study developed initiatives to clarify the mechanisms of hydrological evolution in the human-influenced Yellow River Basin.The proposed research method includes:(1)a tool to simulate multiple factors and a multi-scale water cycle using a grid-based spatiotemporal coupling approach,and(2)a new algorithm to separate the responses of the water cycle to climate change and human impacts,and de-couple the eco-environmental effects using artificial intelligence techniques.With this research framework,key breakthroughs are expected to be made in the understanding of the impacts of land cover change on the water cycle and blue/green water redirection.The outcomes of this research project are expected to provide theoretical support for ecological protection and water governance in the basin.

Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

Hydrological Processes in a Small Research Watershed under Forest Coverage in the Coast of Chiapas, Mexico

In the hydrological watershed, some natural processes take place in which the interaction of water, soil, climate and vegetation favors the capture of water. The present study aimed to evaluate preliminary information regarding the hydrological response and the water balance in a small research watershed with tropical forest cover (15°01'44''N and 92°13'55''W, 471 m, 2.3 has). Events of precipitation, direct runoff, infiltration rate and baseflow were performed. The amount, duration and intensity of rainfall events were recorded with the use of a pluviograph. Surface runoff was quantified with an established gauging station, an H-type gauging device and a horizontal mechanical gauging limnograph. Runoff base flow was measured at the gauging station using the volume-time method. Infiltration was measured using a triple ring infiltrometer, taking two measurements in the upper part and two in the lower part of the microbasin. Evapotranspiration was measured with the amount of rainfall entering and runoff leaving the watershed. In the study period, annual rainfall of 4417.6 mm distributed over 181 events were recorded;about 70% of the storms showed lower intensities at 20 mm·h-1. The total runoff was 345.8 mm caused by half of the rainfall events, which represents 7.8% of the total rain;77% of runoff events showed lower sheets of 5 mm and an average specific rate of 20.7 L·s-1·ha-1 with a maximum of 113.6 L·s-1·ha-1. Three runoff events were greater than 20.1 mm and caused the 22.5% of the total runoff depth in the study period showing the equilibrium conditions in the hydrological response of the forest. Water outputs like baseflow was 669.5 mm. In this way, 90% of the rainfall is infiltrated every year in the micro-watershed, which shows the importance of the plant cover in the hydrological regulation and the groundwater recharge.

Intensity Estimation of Extreme Meteorological and Hydrological Factors Induced by Tropical Cyclones Affecting Hong Kong

Hong Kong is often affected by tropical cyclones.The Hong Kong observatory issues warning signals based on the impact of tropical cyclones on the region.The joint frequency analysis of tropical cyclones in Hong Kong can provide a scientific basis for disaster reduction and prevention and post-disaster reconstruction of tropical cyclones.First,the maximum hourly mean wind speed(W),warning signal duration(D),maximum sea level(L),and total rainfall(R)of each tropical cyclone that affected Hong Kong from 1985 to 2019 are selected and fitted using the Gumbel,Weibull,Pearson type 3,and lognormal distributions.Then,bivariate copula functions,such as the Clayton,Frank,Gumbel-Hougaard,and Gaussian copulas,are applied to construct the joint probability models of W,D,L,and R,respectively.The joint return periods of W and D and those of L and R are defined as the meteorological and hydrological intensities of tropical cyclones,respectively.The results show that the joint return periods are good indicators of the comprehensive effect of the meteorological and hydrological intensities of tropical cyclones.No necessary correlation between meteorological and hydrological intensities of tropical cyclones exists.The meteorological and hydrological intensities of tropical cyclones show an upward trend in recent years.

Anthropogenic activity,hydrological regime,and light level jointly influence temporal patterns in biosonar activity of the Yangtze finless porpoise at the junction of the Yangtze River and Poyang Lake,China

Under increasing anthropogenic pressure,species with a previously contiguous distribution across their ranges have been reduced to small fragmented populations.The critically endangered Yangtze finless porpoise(Neophocaena asiaeorientalis asiaeorientalis),once commonly observed in the Yangtze River-Poyang Lake junction,is now rarely seen in the river-lake corridor.In this study,static passive acoustic monitoring techniques were used to detect the biosonar activities of the Yangtze finless porpoise in this unique corridor.Generalized linear models were used to examine the correlation between these activities and anthropogenic impacts from the COVID-19 pandemic lockdown and boat navigation,as well as environmental variables,including hydrological conditions and light levels.Over approximately three consecutive years of monitoring(2020–2022),porpoise biosonar was detected during 93%of logged days,indicating the key role of the corridor for finless porpoise conservation.In addition,porpoise clicks were recorded in 3.80%of minutes,while feeding correlated buzzes were detected in 1.23%of minutes,suggesting the potential existence of localized,small-scale migration.Furthermore,both anthropogenic and environmental variables were significantly correlated with the diel,lunar,monthly,seasonal,and annual variations in porpoise biosonar activities.During the pandemic lockdown period,porpoise sonar detection showed a significant increase.Furthermore,a significant negative correlation was identified between the detection of porpoise click trains and buzzes and boat traffic intensity.In addition to water level and flux,daylight and moonlight exhibited significant correlations with porpoise biosonar activities,with markedly higher detections at night and quarter moon periods.Ensuring the spatiotemporal reduction of anthropogenic activities,implementing vessel speed restrictions(e.g.,during porpoise migration and feeding),and maintaining local natural hydrological regimes are critical factors for sustaining porpoise population viability.

Dimensioning Urban Drainage Systems in Housing Subdivisions in the Amazon Using Different Hydrological Models

Hydrological studies for sizing urban drainage systems in the Amazon have often been neglected and little investigated for rainwater projects. This research evaluated alternative hydrological models used in sizing urban drainage network projects in subdivisions with subsidized houses in the Amazonian region in Brazil. Statistical tests of these models were performed for both original and alternative scenarios. The methodological steps we conducted as follows: 1) evaluate the dimensioning of infrastructure project networks, considering two case studies contemplated by the Calha Norte Program (CNP) in the state of Amapá;2) test the statistical significance of the dimensioning of network diameters (α < 0.05), considering a) benchmark project (MD or M1) approved by the Ministry of Defense;b) determination of concentration time (Ct) and rainfall intensity-duration-frequency (IDF) relationships, as well as estimating diameters using alternative models. The results indicated a significant influence on the diameters of the projected rainfall networks (p < 0.05), suggesting that alternative models predicted more unfavorable flow peaks than the original model. We conclude that the benchmarking model underestimated the diameter of the project compared to alternative models, which means the optimized Ct parameter significantly impacts dimensioning estimates in rainwater projects in these Amazonian municipalities. This suggests that underestimated parameters in MD may cause inefficiency in the stormwater system projects in future similar scenarios.

Artificial Intelligence Technique in Hydrological Forecasts Supporting for Water Resources Management of a Large River Basin in Vietnam

Hydrological forecasting plays an important role in water resource management, supporting socio-economic development and managing water-related risks in river basins. There are many flow forecasting techniques that have been developed several centuries ago, ranging from physical models, physics-based models, conceptual models, and data-driven models. Recently, Artificial Intelligence (AI) has become an advanced technique applied as an effective data-driven model in hydrological forecasting. The main advantage of these models is that they give results with compatible accuracy, and require short computation time, thus increasing forecasting time and reducing human and financial effort. This study evaluates the applicability of machine learning and deep learning in Hanoi water level forecasting where it is controlled for flood management and water supply in the Red River Delta, Vietnam. Accordingly, SANN (machine learning algorithm) and LSTM (deep learning algorithm) were tested and compared with a Physics-Based Model (PBM) for the Red River Delta. The results show that SANN and LSTM give high accuracy. The R-squared coefficient is greater than 0.8, the mean squared error (MSE) is less than 20 cm, the correlation coefficient of the forecast hydrology is greater than 0.9 and the level of assurance of the forecast plan ranges from 80% to 90% in both cases. In addition, the calculation time is much reduced compared to the requirement of PBM, which is its limitation in hydrological forecasting for large river basins such as the Red River in Vietnam. Therefore, SANN and LSTM are expected to help increase lead time, thereby supporting water resource management for sustainable development and management of water-related risks in the Red River Delta.

Hydrological Process Factors Analysis of Heihe River Mountain Basin Based on GIS

Hydrological process factors are a reflection of the physical mechanism of basin hydrology,which can provide important basis for the use and protection of water resources.Taking Heihe River Mountain Basin as the study area,the hydrological simulation was made based on SWAT-GIS integrated model platform.The calculation methods of hydrological process factors using SWAT model were described based on the simulation results of runoff from 1990 to 2000.Hydrological process factors in the study area were analyzed by using GIS technology.The spatial and temporal characteristics of precipitation,runoff,infiltration,evapotranspiration and snowmelt in the basin were calculated and analyzed.

Spatial distribution characteristics and mechanism of nonhydrological time-variable gravity in China's Mainland

The purpose of this study is to explore nonhydrological mass transfer in China's Mainland.For this purpose,gravity recovery and climate experiment(GRACE)data were obtained to study the spatial distribution of time variant gravity signals in China's Mainland.Then,from auxiliary hydrological data processed according to the current hydrological model,a new more comprehensive hydrological model of China's Mainland was constructed.Finally,the time variant signals of this new hydrological model were removed from the time variant gravity field computed from GRACE data,thus obtaining a description of the nonhydrological mass transfer of China's Mainland.The physical sources and mechanisms of the resulting mass transfer are then discussed.The improved,more realistic,hydrological model used here was created by selecting the hydrological components with the best correlations in existing hydrological models,by use of correlation calculation,analysis,and comparison.This improved model includes water in soils and deeper strata,in the vegetation canopy,in lakes,snow,and glaciers,and in other water components(mainly reservoir storage,swamps,and rivers).The spatial distribution of the transfer signals due to nonhydrological mass in China's Mainland was obtained by subtracting the combined hydrological model from the GRACE time-variable gravity field.The results show that the nonhydrological signals in China's Mainland collected in GRACE data were mainly positive signals,and were distributed in the Bohai Rim and the northern and eastern parts of the Tibetan Plateau.The above nonhydrological mass transfer signals have been studied further and are discussed.The results show that the nonhydrological mass migration signals in the Bohai Rim region originate primarily from sea level change and marine sediment accumulation.The mass accumulation from Indian plate collision in the Tibetan Plateau appears to be the main reason for the increase in the residual gravity field in that region.

Hydrological assessment of TRMM rainfall data over Yangtze River Basin

High-quality rainfall information is critical for accurate simulation of runoff and water cycle processes on the land surface. In situ monitoring of rainfall has a very limited utility at the regional and global scale because of the high temporal and spatial variability of rainfall. As a step toward overcoming this problem, microwave remote sensing observations can be used to retrieve the temporal and spatial rainfall coverage because of their global availability and frequency of measurement. This paper addresses the question of whether remote sensing rainfall estimates over a catchment can be used for water balance computations in the distributed hydrological model. The TRMM 3B42V6 rainfall product was introduced into the hydrological cycle simulation of the Yangtze River Basin in South China. A tool was developed to interpolate the rain gauge observations at the same temporal and spatial resolution as the TRMM data and then evaluate the precision of TRMM 3B42V6 data from 1998 to 2006. It shows that the TRMM 3B42V6 rainfall product was reliable and had good precision in application to the Yangtze River Basin. The TRMM 3B42V6 data slightly overestimated rainfall during the wet season and underestimated rainfall during the dry season in the Yangtze River Basin. Results suggest that the TRMM 3B42V6 rainfall product can be used as an alternative data source for large-scale distributed hydrological models.

Runoff separation and eco-hydrological function in the typical landscape zones combining hydrochemical and isotopic tracers:a review

The study on the coupling relationship and hydrology mechanism between ecosystem and hydrological process in a basin has recently become the international research frontier in hydrology.Runoff separation is still an important subject and possibly cutting edge process in hydrology.This paper summarizes the progress of national and international research,and comments on the advantages and disadvantages of recent,diverse base flow separation methods.This paper also presents research on hydrological process and eco-hydrological function in different landscape zones,combining isotopic technology with hydrochemical methods.Based on the runoff separation of different water bodies,this paper probes into the coupling relationship and hydrology mechanism between ecosystem pattern and eco-hydrological process,and makes analysis on water conservation,regulation and storage mechanism,and eco-hydrological function in different landscape zones.This report also examines future trends in research on hydrological process and eco-hydrological function in mountainous areas.

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological impact

Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

Modelling Hydrological Consequences of Climate Change—Progress and Challenges

The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.

Simulations of a Hydrological Model as Coupled to a Regional Climate Model

Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltration, is constructed and incorporated into the land surface scheme BATS. Via the coupled-model (i.e., a regional climate model) simulations, the following major conclusions are obtained: the simulation of surface hydrology is sensitive to the inclusion of heterogeneities in precipitation and infiltration; the runoff ratio is increased after considering the infiltration heterogeneity, a result which is more consistent with the observations of surface moisture balance over humid areas; the introduction of the parameterization of infiltration heterogeneity can have a greater influence on the regional hydro-climatology than the precipitation heterogeneity; and the consideration of the impermeable fraction for the region reveals some features that are closer to the trend of aridification over northern China.

Hydrological response to climate change and human activities:A case study of Taihu Basin,China

Climate change and human activities have changed a number of characteristics of river flow in the Taihu Basin.Based on long-term time series of hydrological data from 1986 to 2015,we analyzed variability in precipitation,water stage,water diversion from the Yangtze River,and net inflow into Taihu Lake with the Mann-Kendall test.The non-stationary relationship between precipitation and water stage was first analyzed for the Taihu Basin and the Wuchengxiyu(WCXY)sub-region.The optimized regional and urban regulation schemes were explored to tackle high water stage problems through the hydrodynamic model.The results showed the following:(1)The highest,lowest,and average Taihu Lake water stages of all months had increasing trends.The total net inflow into Taihu Lake from the Huxi(HX)sub-region and the Wangting Sluice increased significantly.(2)The Taihu Lake water stage decreased much more slowly after 2002;it was steadier and higher after 2002.After the construction of Wuxi urban flood control projects,the average water stage of the inner city was 0.16e0.40 m lower than that of suburbs in the flood season,leading to the transfer of flooding in inner cities to suburbs and increasing inflow from HX into Taihu Lake.(3)The regional optimized schemes were more satisfactory in not increasing the inner city flood control burden,thereby decreasing the average water stage by 0.04e0.13 m,and the highest water stage by 0.04e0.09 m for Taihu Lake and the sub-region in the flood season.Future flood control research should set the basin as the basic unit.Decreasing diversion and drainage lines along the Yangtze River can take an active role in flood control.

Effect of Hydrological Connectivity on Soil Carbon Storage in the Yellow River Delta Wetlands of China

Hydrological connectivity has significant effects on the functions of estuarine wetland ecosystem.This study aimed to examine the dynamics of hydrological connectivity and its impact on soil carbon pool in the Yellow River Delta,China.We calculated the hydrological connectivity based on the hydraulic resistance and graph theory,and measured soil total carbon and organic carbon under four different hydrological connectivity gradients(Ⅰ0‒0.03,Ⅱ0.03‒0.06,Ⅲ0.06‒0.12,Ⅳ0.12‒0.39).The results showed that hydrological connectivity increased in the north shore of the Yellow River and the south tidal flat from 2007 to 2018,which concentrated in the mainstream of the Yellow River and the tidal creek.High hydrological connectivity was maintained in the wetland restoration area.The soil total carbon storage and organic carbon storage significantly increased with increasing hydrological connectivity fromⅠtoⅢgradient and decreased inⅣgradient.The highest soil total carbon storage of 0‒30 cm depth was 5172.34 g/m^(2),and organic carbon storage 2764.31 g/m^(2)inⅢgradient.The hydrological connectivity changed with temporal and spatial change during 2007‒2018 and had a noticeable impact on soil carbon storage in the Yellow River Delta.The results indicated that appropriate hydrological connectivity,i.e.0.08,could effectively promote soil carbon storage.

Revegetation with artificial plants improves topsoil hydrological properties but intensifies deep-soil drying in northern Loess Plateau,China

Knowledge about the effects of vegetation types on soil properties and on water dynamics in the soil profile is critical for revegetation strategies in water-scarce regions, especially the choice of vegetation type and human management measures. We focused on the analysis of the effects of vegetation type on soil hydrological properties and soil moisture variation in the 0–400 cm soil layer based on a long-term（2004―2016） experimental data in the northern Loess Plateau region, China. Soil bulk density（BD）, saturated soil hydraulic conductivity（Ks）, field capacity（FC） and soil organic carbon（SOC） in 2016, as well as the volumetric soil moisture content during 2004–2016, were measured in four vegetation types, i.e., shrubland（korshinsk peashrub）, artificial grassland（alfalfa）, fallow land and cropland（millet or potato）. Compared with cropland, revegetation with peashrub and alfalfa significantly decreased BD and increased Ks, FC, and SOC in the 0–40 cm soil layer, and fallow land significantly increased FC and SOC in the 0–10 cm soil layer. Soil water storage（SWS） significantly declined in shrubland and grassland in the 40–400 cm soil layer, causing severe soil drought in the deep soil layers. The study suggested that converting cropland to grassland（alfalfa） and shrubland（peashrub） improved soil-hydrological properties, but worsened water conditions in the deep soil profile. However, natural restoration did not intensify deep-soil drying. The results imply that natural restoration could be better than revegetation with peashrub and alfalfa in terms of good soil hydrological processes in the semi-arid Loess Plateau region.