Study region: China. Study focus: Accurate estimation of potential evapotranspiration (PET) is essential for under -standing climate change. Using ground-based pan evaporation measurements over continental China, the monthly scale PET data during 2000-2017 of ERA5, ERA5-Land, GLDAS-2.1/Noah, and GLEAM V3.8a are evaluated, from the perspectives of their consistency in spatiotemporal variation, and performance measures. Factors controlling the data quality of the four datasets are investigated from the perspective of their PET calculation models and meteorologically input data. New hydrological insights for the region: PETERA5 performs the best in mainland China among four gridded PET datasets with higher correlation coefficients (r) and smaller biases, which can well capture the temporal variation of Epan. The outstanding performance of PETERA5 in China mainly results from the utilization of the Penman-Monteith (P-M) equation which performs the best among several competing formulas for PET computation, as well as its better meteorological inputs for computing PET than other datasets. Although the PETERA5-Land is a replay of the land component of the ERA5 climate reanalysis, it exhibits substantial overestimation of PET values and temporal trends, particularly in coastal areas of Southern China and the eastern side of Northeastern China, mainly caused by the overestimation of its net radiation. The PETGLDAS shows significant overestimation, partly due to its overestimation of wind speed, but mostly due to its modified P-M equation with its parameterization of land surface conditions for computing PETGLDAS. The PETGLEAM underestimated PET generally mainly due to the joint effect of the use of the Priestley-Taylor equation with small P-T parameter alpha, and the underestimation of the net radiation input from ERA-Interim, especially in Northwest and Qinghai Tibet.

Atmospheric water vapor is not only a key element of the global hydrological cycle but also the most abundant greenhouse gas. The phase transition and transportation of water vapor are essential for maintaining global energy balance and regulating hydrological processes. However, due to insufficient meteorological observational data, climate research in Africa faces significant limitations despite its substantial contribution to changes in global precipitable water vapor (PWV). In this study, we used MODIS near-infrared (NIR) PWV products and Berkeley temperature data to depict the spatial–temporal variability in PWV across Africa from 2001 to 2020. The results reveal a significant increasing trend in PWV over Africa, with an increase of 0.0158 cm/year. Nearly 99.96% of Africa shows an increase in PWV, with 88.95% of these areas experiencing statistically significant changes, particularly in central regions of Africa. The increase in PWV is more pronounced in high-value months compared to low-value months. The equatorial region of the Congo Basin exhibits higher PWV, which gradually decreases as latitude increases. Despite significant warming (0.0162 °C/year) in Africa, there is no consistent positive correlation between temperature and water vapor. A positive relationship between PWV and temperature is observed in western Africa, while a negative relationship is noted in eastern and southern Africa on an annual scale. Additionally, an increasing trend in precipitation (4.6669 mm/year) is observed, with a significant positive correlation between PWV and precipitation across most of Africa, although this relationship varies by month. These findings provide valuable insights into the comprehension of the hydrothermal variation in Africa amidst climate warming.

Compound drought-heatwaves (CDHWs) accelerate the warming and drying of soils, triggering soil compound drought-heatwaves (SCDHWs) that jeopardize the health of soil ecosystems. Nevertheless, the behavior of these events worldwide and their responses to climatic warming are underexplored. Here, we show a global escalation in the frequency, duration, peak intensity, and severity of SCDHWs, as well as an increase in affected land area, from 1980 to 2023. The increasing trends, which are particularly prominent since the early 2000 s, and projected to persist throughout this century, are dominated by summertime SCDHWs and enhanced by El Ni & ntilde;o. Intensive soil warming as well as climatologically lower soil temperatures compared to air temperatures lead to localized hotspots of escalating SCDHW severity in northern high latitudes, while prolonged duration causes such hotspots in northern South America. Transformation of natural ecosystems, particularly forests and wetlands, to cropland as well as forest degradation substantially enhance the strength of SCDHWs. Global SCDHWs consistently exhibit higher frequencies, longer durations, greater severities, and faster growth rates than CDHWs in all aspects from 1980 to 2023. They are undergoing a critical transition, with droughts replacing heatwaves as the primary constraint. We emphasize the significant intensification of SCDHWs in northern high latitudes as well as the prolonged duration of SCDHWs in the Southern Hemisphere, posing an underrated threat to achieving carbon neutrality and food security goals.

The potential of satellite soil moisture (SM) in improving hydrological modeling has been addressed in synthetic experiments, but it is less explored in real data cases. Here, we investigate the added value of Soil Moisture and Passive (SMAP) and Advanced Scatterometer (ASCAT) SM data to distributed hydrological modeling with the soil and water assessment tool (SWAT) in a highly human disturbed catchment (126, 486 km2) featuring a network of SM and streamflow observations. The investigation is based on the ensemble Kalman filter (EnKF) considering SM errors from satellite data using the triple collocation. The assimilation of SMAP and ASCAT SM improved the surface (0–10 cm) and rootzone (10–30 cm) SM at >70% and > 50% stations of the basin, respectively. However, the assimilation effects on distributed streamflow simulation of the basin are un-significant and not robust. SM assimilation improved the simulated streamflow at two upstream stations, while it deteriorated the streamflow at the remaining stations. This can be largely attributed to the poor vertical soil water coupling of SWAT, suboptimal model parameters, satellite SM data quality, humid climate, and human disturbance to rainfall-runoff processes. This study offers strong evidence of integrating satellite SM into hydrological modeling in improving SM estimation and provides implications for achieving the added value of remotely sensed SM in streamflow improvement.

Study Region: Endorheic and exorheic basins of the Tibetan Plateau (TP). Study Focus: Reanalysis and satellite precipitation products provide alternatives for regions of sparse ground precipitation observation, but pose a tough task to select a suitable one for the TP. This study conducts a multiscale evaluation of six reanalysis and satellite precipitation products in endorheic and exorheic basins using water balance and extended triple collocation (ETC) methods. The reanalysis precipitation products include ECMWF Re-Analysis version 5 (ERA5-Land), China Meteorological Forcing Dataset (CMFD), Global Land Data Assimilation Systems (GLDAS), and High-resolution Precipitation dataset for the Third Pole region (TPHiPr). The satellite precipitation data include Global Precipitation Measurements (GPM) and Tropical Rainfall Measuring Mission (TRMM) products. New Hydrological Insights for the Region: The precipitation products vary in accuracy from basin to basin, with better performance in exorheic than endorheic basins. Reanalysis-based ERA5-land, TPHiPr, and CMFD perform well in most basins at annual scale, among which TPHiPr performs best at daily scale. At regional scale, GPM performs well in endorheic region, and ERA5-land in exorheic region. While all the products increase significantly in accuracy from basin to regional scale in endorheic region, ERA5-land shows best performance at annual and multi-year scales in the entire region. Our findings provide valuable supports for precipitation product selection in the Tibetan endorheic and exorheic basins.

Lakes are known as sentinels of climate change, but their responses may differ from one to another leading to different strategies in lake protection. It is particularly the case in the Tibetan Plateau (TP) of multiple hydrological processes. We employed the Budyko framework to study Tibetan lakes from two lake-basins of contrasting climates for the period between 1980 and 2022: Taro Co Basin (TCB) in a sub-arid climate, and Ranwu Lake Basin (RLB) in a sub-humid climate. Our results showed that total lake area, surface air temperature, evapotranspiration, and potential evapotranspiration increased in both lake-basins, while precipitation and soil moisture increased in the TCB but decreased in the RLB. In the Budyko space, two basins had contrast hydroclimatic trajectories in terms of aridity and evaporative index. The TCB shifted from wetting to drying trend, while the RLB from drying to wetting in early 2000s. Notably, lake change was generally consistent with the drying/wetting phases in the TCB, but in contrast with that in the RLB, which can be attributed to warming-induced glacier melting. Despite of significant correlation with the large-scale atmospheric oscillations, it turned to be more plausible if lake area changes were substituted with basin's hydroclimatic trajectories. Among the large-scale oscillations, El Niño-Southern Oscillation (ENSO) is the most dominant control of lake trends and their drying/wetting shifts. Our findings offer a valuable insight into lake responses to climate change in the TP and other regions.

The Middle Route Project of South-to-North Water Diversion (SNWD-MRP), a crucial strategic inter-basin water transfer project in China, aims to alleviate water scarcity issues in the central and northern arid regions of China. Drought characteristic changes induced by climate change pose challenges to its operational scheduling and management. In this study, we first use the Standardized Precipitation Index (SPI) to identify drought events in different regions of the SNWD-MRP during historical periods and future periods under the SSP2-4.5 scenario. And then, we investigate the drought change characteristics in the water source region and receiving regions in the SNWD-MRP, and assess the encounter risk of drought events among these regions. The results demonstrate that: (1) The spatial characteristics of droughts are changing. Historically, Hebei faced the most severe drought conditions, while in the future, Danjiangkou will emerge as the area with the highest drought risk across different drought levels (SPI≤-0.5 and SPI≤-1.0). (2) Comparable to the historical period, the risk of drought events with SPI≤-0.5 is anticipated to remain relatively stable in the near future period (2021-2051), and may decrease in the far future (2051-2100) in all regions. (3) The encounter risk of drought events with SPI≤-0.5 in the historical period is higher than that in the future in all encounter situations, while it is higher than that in the historical period for the drought events with SPI≤-1.0. This suggests that the risk of experiencing more severe drought simultaneously in the water resource region and receiving regions may increase in the future.

This study investigates the climatological spatial scales (CSSs) of meteorological droughts in China and the linkages to climate variability. The Global Precipitation Climatology Centre monthly gridded precipitation with a spatial resolution of 25 km x 25 km for 1961-2010 is used. The standardized precipitation index at different timescales (1-, 3-, 6-, 9-, 12-, 24-, 36-, and 48-month) is applied to characterize meteorological droughts. The CSSs of meteorological droughts are calculated using a method considering spatial correlation and anisotropy. The relationships between the CSSs and main monsoons and climate teleconnections in five selected regions are quantified using dynamic spatial panel models. The five regions are South China (SC), the Yangtze River Valley (YRV), North China (NC), Northeast China (NE), and the Tibetan Plateau (TIB). The following results are ob-tained: (1) The CSSs of multi-timescale meteorological droughts in China are determined. The means of the CSSs at various timescales in China are 68.9, 73.8, 71.8, 69.7, 68.8, 65.9, 62.9, and 60.8 x 104 km2, respectively. The CSSs in eastern China generally show a significant decrease with increasing timescale. (2) Significant quantifi-cation relationships (R2 greater than 0.85) suggest that there is not a simple linear relationship between climate anomalies and the CSSs, but rather a complex spatiotemporal interaction including exogenous and endogenous interaction effects. The CSSs not only strongly depend on their neighbors on the same timescale but also significantly depend on the CSSs of neighbors on adjacent timescales. Three monsoon indices (Indian monsoon, East Asian monsoon, and western North Pacific monsoon) have significant impacts on the multi-timescale CSS variations in the five regions, especially for NE, YRV, SC, and TIB, while the El Nin similar to o-Southern Oscillation and Pacific Decadal Oscillation affect mainly SC and YRV. These findings could broaden our understanding of the spatiotemporal relationships of droughts and be useful for drought risk management.

To effectively monitor the spatio–temporal dynamics of the surface water extent (SWE) in Lake Victoria, this study introduced a novel methodology for generating a seamless SWE time series with fine resolution by integrating daily a Moderate-resolution Imaging Spectroradiometer (MODIS) and Landsat imagery. In the proposed methodology, daily normalized difference vegetation index (NDVI) time series data with 30 m resolution were first generated based on the constructed pixel-by-pixel downscaling models between the simultaneously acquired MODIS-NDVI and Landsat-NDVI data. In the compositing process, a Minimum Value Composite (MinVC) algorithm was used to generate monthly minimum NDVI time series, which were then segmented into a seamless SWE time series of the years 2000–2020 with 30 m resolution from the cloud background. A comparison with the existing Landsat-derived JRC (European Joint Research Centre) monthly surface water products and altimetry-derived water level series revealed that the proposed methodology effectively provides reliable descriptions of spatio–temporal SWE dynamics. Over Lake Victoria, the average percentage of valid observations made using the JRC’s products was only about 70% due to persistent cloud cover or linear strips, and the correlation with the water level series was poor (R2 = 0.13). In contrast, our derived results strongly correlated with the water level series (R2 = 0.54) and efficiently outperformed the JRC’s surface water products in terms of both space and time. Using the derived SWE data, the long-term and seasonal characteristics of lake area dynamics were studied. During the past 20 years, a significant changing pattern of an initial decline followed by an increase was found for the annual mean SWE, with the lowest area of 66,386.57 km2 in 2006. A general seasonal variation in the monthly mean lake area was also observed, with the largest SWE obtained during June–August and the smallest SWE observed during September–November. Particularly in the spring of 2006 and the autumn of 2020, Lake Victoria experienced intense episodes of drought and flooding, respectively. These results demonstrate that our proposed methodology is more robust with respect to capturing spatially and temporally continuous SWE data in cloudy conditions, which could also be further extended to other regions for the optimal management of water resources.

Global evapotranspiration products from GLEAM（Global Land Evapotranspiration Amsterdam Model） and MOD 16（MODIS Global Evapotranspiration Project） have been widely validated and applied.However,due to insufficient observational data,there is still a lack of products validation in plateau areas.This study took Lake Ranwu,Yamzho YumCo,Nam Co,Siling Co and Taro Co basins as study area,and applied basin water balance,correlation coefficient,relative error,root mean square error and Kling-Gupta coefficient to verify and evaluate the accuracy of GLEAM and MOD 16 products in the Qinghai-Tibet Plateau.The results demonstrated that GLEAM products were underestimated in Lake Ranwu,Siling Co and Taro Co basins,slightly overestimated in Yamzho YumCo and Nam Co basins,while MOD 16 products were slightly underestimated in Siling Co basin and overestimated in other lake basins.GLEAM and MOD 16 products were overestimated in dry year,and underestimated in wet year in the five lake basins.GLEAM products showed high accuracy in Lake Ranwu,Yamzho YumCo and Siling Co basins,while MOD 16 products had high accuracy in Nam Co and Taro Co basins.In general,the accuracy of GLEAM products was significantly better than that of MOD 16 products in the central and southeastern lake basins of the Qinghai-Tibet Plateau on the annual scale and the multi-year average scale.This results provided an important reference for the selection of evapotranspiration products suitable for the Qinghai-Tibet Plateau.

Study region: East Africa (EA).Study focus: The current poor capability of drought resistance and the high dependence of local residents on agriculture and animal husbandry initiated a comprehensive understanding of soil moisture (SM) droughts in EA. Previous lower-order subspace drought investigations that have neglected the space-time continuity of actual droughts hindered deeper knowledge of droughts. To fill this gap, this study investigated the SM droughts in EA from a space-time joint perspective, focusing on drought spatiotemporal patterns and variations, and climate drivers.New hydrological insights for the region: Based on the space-time joint approach, 582 drought clusters and 226 events over 1979-2014 were identified. Spatially, historical droughts presented a dual-centre pattern in the northwest and southeast; they were characterised by high frequency, long duration, and large severity, driven by the climate forcing of precipitation (Prep) and temperature (Temp). This pattern differed seasonally due to the major control of Prep and the partly strengthening effect of Temp. Temporally, seasonal droughts displayed significant (p < 0.05) increasing/decreasing trends in summer/autumn. Regarding the climate drivers, the partial least squares regression approach was first employed in the space-time continuous drought domain. The innovative method clarified the contribution of different climate elements to SM droughts and recognised the critical climate drivers of Prep, wind speed, and downward radiation. The results provides important implications for drought mechanism exploration and drought prediction.

The Soil Moisture Active Passive (SMAP) mission provides state-of-the-art global soil moisture (SM) datasets. However, seasonal SM biases and their contributing factors have not be systematically reviewed. This study evaluated the biases of SMAP V6 dual channel algorithm (DCA), single channel algorithm H-pol (SCA-H) and V-pol (SCA-V) SM products based on core validation sites data. All algorithms perform better under clear- than cloudy-sky, and in cloudless daytime than nighttime. Consecutive clear-sky benefits SM retrieval, progressively lowering the uncertainty of SM retrievals while at the cost of dry biases. Cloudy-sky deteriorates the quality of SM retrievals, and wet biases increase with the duration time of cloudy-sky. The modified V7 DCA has a major improvement, owning the potential to provide accurate retrievals under cloudy-sky. SMAP SM biases are co-determined by vegetation index, soil temperature and their biases, and a single factor only explains at most 54% variance in SM biases. Generally, SMAP SM bias is negatively correlated with soil temperature and positively correlated with its bias. SM bias correlates positively with vegetation index and its bias for single channel algorithms, and the underestimation of SM increases with vegetation density for DCA. To get a complete picture of SMAP SM biases, a total differential of radiative transfer equation is recommended for decomposing SMAP SM biases. To this end, more validation sites are required covering diverse land cover types and providing continuous data records.

Remote sensing and land surface models promote the understanding of soil moisture dynamics by means of multiple products. These products differ in data sources, algorithms, model structures and forcing datasets, complicating the selection of optimal products, especially in regions with complex land covers. This study compared different products, algorithms and flagging strategies based on in situ observations in Anhui province, China, an intensive agricultural region with diverse landscapes. In general, models outperform remote sensing in terms of valid data coverage, metrics against observations or based on triple collocation analysis, and responsiveness to precipitation. Remote sensing performs poorly in hilly and densely vegetated areas and areas with developed water systems, where the low data volume and poor performance of satellite products (e.g., Soil Moisture Active Passive, SMAP) might constrain the accuracy of data assimilation (e.g., SMAP L4) and downstream products (e.g., Cyclone Global Navigation Satellite System, CYGNSS). Remote sensing has the potential to detect irrigation signals depending on algorithms and products. The single-channel algorithm (SCA) shows a better ability to detect irrigation signals than the Land Parameter Retrieval Model (LPRM). SMAP SCA-H and SCA-V products are the most sensitive to irrigation, whereas the LPRM-based Advanced Microwave Scanning Radiometer 2 (AMSR2) and European Space Agency (ESA) Climate Change Initiative (CCI) passive products cannot reflect irrigation signals. The results offer insight into optimal product selection and algorithm improvement.

Soil salt affects microwave radiometer observations in a similar way to soil moisture (SM). Without consideration of soil salt, the quality of radiometer-based SM products might be impaired. This study explores the magnitude, frequency dependence, seasonal patterns, and influence factors of soil salinity effects based on triple collocation (TC) analyses using X-, C-, and L-band radiometer-based SM products over global cropland. Multiple products corroborate that soil salinity dynamics contributes an uncertainty of 0.005–0.01 cm $^{3}~\cdot $ cm $^{-3}$ to the total SM retrieval error budget, proportional to soil salt concentration, higher at L-band and lower at X-/C-band. Soil salinity effects are stronger in spring and summer when rainfall drives significant soil salinity dynamics. SM retrieval uncertainty increases monotonously with the duration time of nonprecipitating weathers when salt is uplifted onto topsoil and sensed by microwave radiometers. Despite of overall weaker saline effects, X-/C-band products seem to respond earlier than the L-band SM products as soils become salinized, probably due to complicated soil-salt-water dielectric properties and shallower microwave penetration depths. The neglect of loss factor in soil moisture active passive (SMAP) SM retrieval algorithm might also enhance soil salinity effects. These uncertainties are essentially time-varying wet biases, and dynamic soil salinity maps are needed for bias-correcting current L-band and future P-band SM products.

基于集合卡尔曼滤波(EnKF)法,在合理量化模型模拟和径流观测误差、有效处理模型参数演变及过拟合问题的基础上,以淮河上游淮滨水文站以上流域为研究区,构建了基于径流数据同化的SWAT分布式水文模型参数优化方案,就站点实测径流数据同化对模型参数的优化效果进行了评估.结果显示,数据同化过程中,被更新的模型参数集合逐渐收敛并趋于稳定,基于稳定后的参数获得的模拟径流与实测径流过程接近,流域出口径流模拟的纳什效率系数可达0.88,说明基于EnKF法的径流数据同化对SWAT模型参数具有一定的优化估计能力,且采用数据同化方式进行模型参数率定具有一定的可行性.

Understanding the hydrological impacts of land use and land cover (LULC) changes is significant for sustainable water resources management and planning. The Lake Victoria basin (LVB) has experienced extensive forest and grass degradation and agricultural land expansion under rapid socio-economic development and population growth in recent decades. However, the hydrological impacts of LULC changes for the whole LVB is still poorly documented. This study first investigated the LULC changing effects of LVB, focusing on its impacts on the annual and seasonal runoff and the hydrological drought based on a distributed hydrological modeling of the Soil and Water Assessment Tool (SWAT). SWAT model showed comparatively good applicability in seasonal runoff simulation of LVB, with the percent bias (PBIAS) kept within ± 20 % and the coefficient of determination (R2) over 0.6 at ten hydrological stations available over the calibration and validation phases. Generally, the annual runoff obtained a monthly increase of 1.5 mm under collective LULC changes. Moreover, the LULC effects presented considerable seasonal dependence. A largest runoff increase of approximately 4 mm was detected in short rainy season attributed to the combined surface runoff and groundwater increase. Insignificant runoff increase was observed in long rainy and dry seasons under the complementary effects of surface runoff increase and groundwater decrease. Additionally, the hydrological drought was generally aggravated with increased drought frequency and lengthened duration, particularly for the central western and eastern regions with massive conversion of forest to agricultural land. The findings provide importance implication for rational water resources management and drought disaster response for the LVB.

Water processes in the Tienshan Mountains have undergone great changes under the impacts of climate warming and human activities. Here, based on the Budyko framework, we investigated the respective contributions of climate change and human activities to decadal runoff changes (1982-2014) in two contrary watersheds, i.e., the humid Kashi watershed in the Yili River valley and the arid Boertala watershed in the Ebinur Lake basin, in the Tienshan Mountains, where closing the water balance is difficult due to the scarcity of precipitation gauges. To achieve closure of the decadal water balance of the study watersheds, we estimated evapotranspiration from a complementary relationship model and snow/ice melt using the degree-day method with the remote sensing snow cover product. We found that the increase of rainfall (+61.6 mm) and snow/ice melt (+57.3 mm) dominated the increase of runoff (+87.2 mm, from 398.2 mm in 1982-1992 to 485.4 mm in 1993-2014) in the Kashi watershed, contributing 47.1 mm (54.8%) and 43.8 mm (51.0%), respectively, to the increase of runoff. Unlike the Kashi watershed, human activities contributed -13.8 mm (-103.7%) to the runoff (+13.9 mm, from 61.4 mm in 1982-1997 to 75.3 mm in 1998-2014) in the Boertala watershed. Most of the increase in rainfall (+62.5 mm) and snow/ice melt (+13.6 mm) was consumed by the increase of ET (+64.0 mm) instead of runoff. Further analysis showed that most of the increases in snow/ice melt and ET were contributed from the high (>2500 m) and low (<1500 m) elevation regions, respectively. Snowmelt showed a decreasing trend in low elevation regions. Our study highlighted the importance of snow/ice melt and ET in understanding decadal changes in runoff in the Tienshan Mountains.

Abstract. The Tibetan Plateau (TP) plays a vital role in Asian and even global atmospheric circulation, through the interactions between land and atmosphere. It experienced significant climate warming and spatially and temporally variant wetting over the past half century. Because of the importance of land surface status to the interactions, determining the wetting/drying of the TP from individual changes in precipitation (Prep) or temperature is difficult. Soil moisture (SM) is the water synthesis of the surface status. The persistent deficit of SM (SM drought) is more sensitive to climate change than normal SM. This study first explored the climate wetting/drying of the TP from variations in historical SM droughts over 1961–2014, with a focus on spatiotemporal patterns, long-term variations, and climate causes of summer (May–September) SM droughts based on multiple observation and reanalysis data. The results showed comparatively frequent and severe droughts in the central and southern regions, particularly in the semi-arid and sub-humid zones. SM drought exhibited an abrupt and significant (p < 0.05) alleviation in the central TP in the mid-1990s. The prominent drought alleviation indicated a hydro-climate shift to a wetter plateau, not merely steady trends in the literature. We demonstrated that the wetting shift was dominated by Prep over potential evapotranspiration (PET). By contrast, the in-phase trends before and after the shift were predominantly driven by the PET. Furthermore, the Prep dominance was largely attributed to a phase transition of the Atlantic multi-decadal oscillation from cold to warm, accompanied by a weakening westerly since the mid-1990s. The PET control on in-phase trends was realized through multiple climate control of temperature, radiation, and vapor pressure deficit. Regionally, the wetting shift was distinct from semi-arid to sub-humid, and from sub-humid to humid climate. Such spatiotemporal changes may affect the TP’s atmospheric circulation and, subsequently, the Asian monsoon and global circulation, in addition to fragile ecosystems in the TP.

The availability of streamflow records in Africa has been declining since the 1980s due to malfunctioning gauging stations and data collection failures. Africa also has insufficient hydrological information owing to the allocation of few resources to research efforts. Unreliable runoff datasets and large uncertainties in runoff trends due to climate change patterns and human activities are major challenges to water resource management in Africa. Therefore, this study aimed to improve runoff estimates and to assess runoff trend responses to climate change and human activities in Africa during 1981–2016. Using statistical methods, monthly gridded runoff datasets were generated for the period of 1981–2016 from a modified runoff curve number method calibrated with river discharge data from 535 gauging stations. According to the cross-validation results, the constructed runoff datasets comprised the Nash and Sutcliffe coefficients ranging from 0.5 to 1, coefficients of determination ranging from 0.5 to 1 and percent biases between ±25% for a large number of stations up to 73%, 80% and 91% of the 535 gauged catchments used as references. Analysis of runoff trend responses to climate change and human activities revealed that land cover change contributed more (72%) to the observed net runoff change (0.30%•a −1 ) than continental climate changes (28%). These contributions were results of cropland expansion rate of 0.46%•a −1 and a precipitation increase of 0.07%•a −1 . The performance and simplicity of the statistical methods used in this study could be useful for improving runoff estimations in other regions with limited streamflow data data. The results of the current study could be important to natural resource managers and decision makers in terms of raising awareness of climate change adaptation strategies and agricultural land-use policies in Africa.