Annual Potential Evapotranspiration Research Articles

Global future potential evapotranspiration signal using Penman-Monteith and Hargreaves-Samani method by latitudes based on CMIP6

This study estimated global potential evapotranspiration (PET) using six climate variables of 14 CMIP6 GCMs at different latitudes of both hemispheres. Hargreaves-Samani (HS) and Penman-Monteith (PM) were used to estimate historical and future PETs. To evaluate the historical reproducibility of the six climate variables of the CMIP6 GCMs, five evaluation indicators were used and compared with the NCEP/NCAR reanalysis data. Based on the evaluation metrics, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to calculate the weights for Multi-Model Ensemble (MME) for each band of latitude. After that, the projected annual and seasonal PETs were estimated for the near (2031–2065) and far (2066–2100) futures. The change rate of PET for five timeframes (Annual, Spring, Summer, Fall, and Winter) was calculated for four socioeconomic shared pathways (SSPs). As a result, the PM's PET and HS's PET for all scenarios showed the highest increased signals at 75.5° ∼ 90° in the northern hemisphere (NH) compared to the other latitudes. Especially, the change in the HS of SSP5–8.5 was increased by 26.4% in NH latitude 45.5° to 60° (NL4) compared to the base period. Furthermore, the changes in PET of PM and HS for December, January, and February (DJF) and September, October, and November (SON), and June, July, and August (JJA) lead to remarkably high increases in both hemispheres, irrespective of the level of the emission scenario, completely ignoring the seasonal water cycle in the historical period (1950–2014).

Changes in climate, vegetation cover and vegetation composition affect runoff generation in the Gulf of Guinea Basin

AbstractAlthough considerable effort has been deployed to understand the impact of climate variability and vegetation change on runoff in major basins across Africa, such studies are scarce in the Gulf of Guinea Basin (GGB). This study combines the Budyko framework and elasticity concept along with geospatial data to fill this research gap in 44 nested sub‐basins in the GGB. Annual rainfall from 1982 to 2021 show significant decreasing and increasing trends in the northern and southern parts of the GGB, respectively. Annual potential evapotranspiration (PET) also shows significant increasing trends with higher magnitudes observed in the northern parts of the GGB. Changing trends in climate variables corroborates with shift to arid and wetter conditions in the north and south, respectively. From 2000 to 2020 vegetation cover estimated using enhanced vegetation index (EVI) shows significant increasing trends in all sub‐basins including those experiencing a decline in annual rainfall. Vegetation composition measured using vegetation continuous fields (VCFs) from 2000 to 2020 show an increase in tree canopy cover (TC), a decline in short vegetation cover and marginal changes in bare ground cover (BG). Elasticity coefficients show that a 10% increase in annual rainfall and PET may lead to a 33% increase and 24% decline in runoff, respectively. On the other hand, a 10% increase in EVI may lead to a 4% decline in runoff while a 10% increase in TC, SV and BG may reduce runoff by 4% and increase runoff by 3% and 2%, respectively. Even though changes are marginal, decomposing vegetation into different parameters using EVI and VCFs may lead to different hydrological effects on runoff which is one of the novelties of this study that may be used for implementing nature‐based solutions. The study also demonstrates that freely available geospatial data together with analytical methods are a promising approach for understanding the impact of climate variability and vegetation change on hydrology in data‐scarce regions.

Hydrometeorological Trends in a Low-Gradient Forested Watershed on the Southeastern Atlantic Coastal Plain in the USA

Hydrology and meteorological data from relatively undisturbed watersheds aid in identifying effects on ecosystem services, tracking hydroclimatic trends, and reducing model uncertainties. Sustainable forest, water, and infrastructure management depends on assessing the impacts of extreme events and land use change on flooding, droughts, and biogeochemical processes. For example, global climate models predict more frequent high-intensity storms and longer dry periods for the southeastern USA. We summarized 17 years (2005–2021) of hydrometeorological data recorded in the 52 km2, third-order Turkey Creek watershed at the Santee Experimental Forest (SEF), Southeastern Coastal Plain, USA. This is a non-tidal headwater system of the Charleston Harbor estuary. The study period included a wide range of weather conditions; annual precipitation (P) and potential evapotranspiration (PET) ranged from 994 mm and 1212 mm in 2007 to 2243 mm and 1063 in 2015, respectively. The annual runoff coefficient (ROC) varied from 0.09 in 2007 (with water table (WT) as deep as 2.4 m below surface) to 0.52 in 2015 (with frequently ponded WT conditions), with an average of 0.22. Although the average P (1470 mm) was 11% higher than the historic 1964–1976 average (1320 mm), no significant (α= 0.05) trend was found in the annual P (p = 0.11), ROC (p = 0.17) or runoff (p = 0.27). Runoff occurred on 76.4% of all days in the study period, exceeding 20 mm/day for 1.25% of all days, mostly due to intense storms in the summer and lower ET demand in the winter. No-flow conditions were common during most of the summer growing season. WT recharge occurred during water-surplus conditions, and storm-event base flow contributed 23–47% of the total runoff as estimated using a hydrograph separation method. Storm-event peak discharge in the Turkey Creek was dominated by shallow subsurface runoff and was correlated with 48 h precipitation totals. Estimated precipitation intensity–duration–frequency and flood frequency relationships were found to be larger than those found by NOAA for the 1893–2002 period (for durations ≥ 3 h), and by USGS regional frequencies (for ≥10-year return intervals), respectively, for the same location. We recommend an integrated analysis of these data together with available water quality data to (1) assess the impacts of rising tides on the hydroperiod and biogeochemical processes in riparian forests of the estuary headwaters, (2) validate rainfall–runoff models including watershed scale models to assess land use and climate change on hydrology and water quality, and (3) inform watershed restoration goals, strategies, and infrastructure design in coastal watersheds.

Examination of the Effects of Climate Change on Türkiye through the Google Earth Engine Platform

The objective of this research is to assess the effects of climate change on Türkiye by utilizing data catalogues provided by the Google Earth Engine (GEE) cloud-computing platform. The utilized data catalogues encompassed precipitation, Land Surface Temperature (LST), EvapoTranspiration (ET), Potential EvapoTranspiration (PET), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Vegetation Condition Index (VCI), and Forest Area Loss (FAL). Data spanning the years 2001-2022 were collected, and analyses were conducted separately for seven geographical regions of Türkiye on both an annual and seasonal basis. Initially, trend analysis techniques were applied to the individual data sets, followed by an examination of correlations among them. Notably, significant decreasing and increasing trends were observed in annual precipitation and LST data in the Eastern Anatolia region, respectively. Furthermore, a significant increasing trend was identified in annual ET data across all regions except Eastern Anatolia. Conversely, significant increasing trends were noted in annual PET data in Eastern Anatolia and the Aegean regions. Additionally, significant increasing trends were discerned in annual NDVI, EVI, and VCI data across all regions. Experiments revealed that the ET exhibited robust correlations with the NDVI (0.77), EVI (0.79) and VCI (0.81). Furthermore, the NDVI demonstrated strong correlations with EVI (0.99) and VCI (0.96).

Evaluation of Hydrometeorological Characteristics in the Northern Ethiopia, Gerado Catchment

In Northern Ethiopia, land degradation, together with population pressure foster soil erosion. Soil erosion in turn escalates surface runoff which is a serious challenge to agricultural production and economic growth in the region. Understanding the characteristics and dynamics of hydrometeorological variables are important elements in water resources development projects. Present study was carried out to evaluate hydrometeorological characteristics in the Northern Ethiopia, Gerado Catchment. Long term meteorological data such as precipitation, temperature and other climatic factors were collected from existing meteorological stations. Thornthwaite empirical equation and thornthwaite soil water balance models were employed in estimating potential and actual evapotranspiration. The first approach used air temperature as an index of energy available for evapotranspiration. Similarly, groundwater recharge of the catchment was computed as a difference of between outflow and change in a water storage. The runoff of the area was calculated based on the rainfall coefficient, annual precipitation and aerial coverage. On the other hand, groundwater potential (GWP) of the area was mapped based on important selected controlling factors. The result indicated that the annual potential and actual evapotranspiration of the catchment was found to be 755 mm/year and 723 mm/year respectively. The actual evapotranspiration was evaluated and weighted based on the dominant soil textures, depth root soil, and the respective land uses. As result, high evapotranspiration was observed in moderate deep rooted cereal crops and sandy loam soil texture which accounted 48.5% influence. But, cereal crops with moderate deep rooted and clay loam type have low AET (42.2%). Because of absence of gauging stations in the catchment, the volume runoff was computed using the runoff coefficient method. Accordingly, surface runoff from the catchment was calculated to be 120,581,841 cubic meter (m3) or 326 mm. Whereas, the groundwater recharge of the area was also found to be 52,208,159.5 cubic meter (141.5mm). Thus, out of the given mean annual precipitation, 27.6% and 12% of the mean annual rainfall lost because of runoff and recharge and the rest (60.4%) due to evapotranspiration. Regarding GWP suitability mapping, lithology, liniment density and geomorphology were found the most essential factors affecting groundwater mapping. The suitable GWP areas were lied within lithology and geomorphology class. Moreover, areas with flat slope and low lineament density are also located in most rich groundwater areas. Furthermore, installation of rain gauges at appropriate areas are essential for all inclusive and consistent data availability.      
 Keywords: Hydro-meteorological, Gerdo Catchment, groundwater recharge, runoff, evapotranspiration, GWP

Spatiotemporal Changes in and Driving Factors of Potential Evapotranspiration in a Hyper-Arid Locale in the Hami Region, China

Potential evapotranspiration (PET) is a crucial variable for implementing adaptation measures to mitigate the potential impacts of climate change on water resources. In the context of global warming, PET is essential for predicting water resource supply and demand, guiding irrigation and water management decisions. However, there is limited understanding of the spatiotemporal changes in PET and its driving factors in the hyper-arid regions of Northwest China. In this study, the Hargreaves model was employed to estimate PET in the Hami region from 1991 to 2020. By combining relevant climate data and partial correlation analysis, we investigated the spatiotemporal distribution patterns of PET within the study area and analyzed the factors influencing these patterns. The results showed the following: (1) From 1991 to 2020, the overall PET in the Hami region demonstrated a tendency to rise. The interannual trend rates of PET for the full year, spring, summer, autumn, and winter were 0.933, 2.744, 0.906, 0.488, and −0.406 mm·a-1, respectively. Despite a decreasing trend in winter PET, the other seasonal PET values and the annual PET values exhibited an increasing trend. (2) The spatial distribution of both annual and seasonal PET showed significant regional heterogeneity, following a consistent pattern marked by lower values in the central part and higher values in the surrounding areas. The southern region tended to have relatively high PET, while the northwestern region experienced comparatively low PET. (3) Partial correlation analysis indicated significant differences in the impact of various climatic factors on PET. The maximum temperature emerged as the dominant factor influencing annual PET variation, while precipitation played a leading role in influencing autumn PET variation. This study underscores the influence of climate change on PET in the Hami region, contributing to an enhanced comprehension of PET variations.

Distinct, direct and climate‐mediated environmental controls on global particulate and mineral‐associated organic carbon storage

AbstractIdentifying controls on soil organic carbon (SOC) storage, and where SOC is most vulnerable to loss, are essential to managing soils for both climate change mitigation and global food security. However, we currently lack a comprehensive understanding of the global drivers of SOC storage, especially with regards to particulate (POC) and mineral‐associated organic carbon (MAOC). To better understand hierarchical controls on POC and MAOC, we applied path analyses to SOC fractions, climate (i.e., mean annual temperature [MAT] and mean annual precipitation minus potential evapotranspiration [MAP‐PET]), carbon (C) input (i.e., net primary production [NPP]), and soil property data synthesized from 72 published studies, along with data we generated from the National Ecological Observatory Network soil pits (n = 901 total observations). To assess the utility of investigating POC and MAOC separately in understanding SOC storage controls, we then compared these results with another path analysis predicting bulk SOC storage. We found that POC storage is negatively related to MAT and soil pH, while MAOC storage is positively related to NPP and MAP‐PET, but negatively related to soil % sand. Our path analysis predicting bulk SOC revealed similar trends but explained less variation in C storage than our POC and MAOC analyses. Given that temperature and pH impose constraints on microbial decomposition, this indicates that POC is primarily controlled by SOC loss processes. In contrast, strong relationships with variables related to plant productivity constraints, moisture, and mineral surface availability for sorption indicate that MAOC is primarily controlled by climate‐driven variations in C inputs to the soil, as well as C stabilization mechanisms. Altogether, these results demonstrate that global POC and MAOC storage are controlled by separate environmental variables, further justifying the need to quantify and model these C fractions separately to assess and forecast the responses of SOC storage to global change.

Impact of Climate Change on the Water Balance of the Akaki Catchment

Climate change has an impact on water resources. Estimations of the variations in water balance under climate change variables are essential for managing and developing the water resource of a catchment. The current investigation evaluated the magnitude of the change in the water balance component of the Akaki catchment, Ethiopia, using the semi-distributed hydrological model, the Soil and Water Assessment Tool (SWAT), with the integration of the Coordinated Regional Downscaling Experiment of Africa under RCP4.5 and 8.5. The SWAT model was developed using spatial and temporal data; it was calibrated (1991–2001) and validated (2002–2004) using SWAT-CUP. The statistical monthly SWAT model performance values of the NSE, PBIAS (%), and R2 showed good agreement between calibration and validation. On an annual basis, projected rainfall is expected to increase by 14.96%, 4.13%, 8.39%, and 10.39% in the 2040s under RCP4.5 and 8.5 and in the 2060s under RCP4.5 and 8.5, respectively, with inconsistent change on a monthly projections basis for each scenario. The projected monthly and yearly temperatures are expected to increase under different climate change scenarios. Annual evapotranspiration and potential evapotranspiration increased under both RCPs, whereas surface runoff, lateral flow, and water yield declined under the climate scenarios of each RCP. Monthly projected water yield showed a non-uniform change in the first 30 years and in the second years under the RCP4.5 and RCP8.5 scenarios. These results show that the catchment is highly vulnerable to hydrological and agricultural drought due to water availability. These research findings provide valuable evidence on the role of climate change in water balance, which will help decision makers to achieve better water resource management.

Water Balance, Climate Classification and Empirical Distribution of the Probability of Rain for the Region of Tangará da Serra – MT

Objective: The present work aimed to describe the Climatological Water Balance (BHC), carry out the Climate Classification (CC) and evaluate the Empirical Probability (EP) of rainfall occurrence for the region of Tangará da Serra – MT.
  
 Theoretical Frame: This study used the following main citations as a theoretical basis: National Water Agency (ANA) and National Institute of Meteorology (INMET), source of climate data; Thornthwaite & Mather (1955) for the climatological water balance methodology; Thornthwaite (1948) and Koppen (1900) for climate classification; and Thom (1966) for the methodology of probability of occurrence and return period of rain.
  
 Method: To carry out the study, a series of 31 years of climate data was used, covering the period from 1989 to 2019, obtained from the National Water Agency (ANA) and the National Institute of Meteorology (INMET). Filling gaps in the data was carried out using the Regional Weighting method, according to the methodology of Mello et al. (2017). The climatological water balance was estimated according to Thornthwaite & Mather (1955). The climate classification was obtained using the methodologies of Thornthwaite (1948) and Koppen (1900). The probability of occurrence and the period of return of rain were achieved using the methods of Thom (1966).
  
 Results and Conclusions: Through studies carried out, it was found that the average annual precipitation in Tangará is 1603 mm and the average annual air temperature is 24.5 °C. The months of May, June, July, August and September present a water deficit, while in the months of December, January, February, March and April there is a water surplus. According to Thornthwaite's methodology, the region has a humid climate, with moderate water deficiency in winter, megathermal and with potential evapotranspiration in the summer less than 48% of the annual potential evapotranspiration, whereas according to Koppen's methodology, the location was classified as megathermal or tropical with drought in the winter. The probability of rainfall less than the maximum average of 47.7 mm is 93.3% and its return time is approximately 15 years.
  
 Implications of the research: This research is classified as of great importance for the purposes of the Department of Agricultural Engineering of the State University of Mato Grosso, Campus of Nova Mutum and Tangará da Serra - MT, as well as for the entire academic and scientific community and interested rural producers. in climatic data, water balance and climate of the studied region.
  
 Originality and value: This study aimed to show the academic and scientific community and rural producers the behavior of climatic variables throughout the year in the municipality of Tangará da Serra – MT, where this information can be used for agricultural planning in the region and also serve as a basis for future studies.

Hydrological Balance in the Vistula Catchment under Future Climates

The hydrological assessment of the Vistula River basin in the near future will be a key element in the development of strategies to adapt agriculture to climate change. The Vistula River basin covers 61% of Poland’s area (190,062 km2) and is mainly used for agricultural production. The aim of this study is to assess the water balance of the Vistula River basin from the perspective of 2050 based on the analysis of two climate scenarios, RCP 4.5 and RCP 8.5, and the three climate models ICHEC-EC-EARTH_KNMI-RACMO22E (A), ICHEC-EC-EARTH_DMI-HIRHAM5 (B), and ICHEC-EC-EARTH_SMHI-RCA4 (C). This paper presents the steps in the development of the SWAT model and the results of the hydrological analysis of the Vistula catchment. Calibration and validation of the model were carried out using the SUFI-2 algorithm in the SWAT-CUP programme for 2013–2018. The data used to calibrate the SWAT model are monthly flow measurements [m3/s] from the measurement station in Tczew, located near the estuary of the Vistula basin to the Baltic Sea. The summary result of the work is the results of modelling the flow of the Vistula River catchment for different climate scenarios in the 2020–2050 perspective. The average annual precipitation for all projections in 2021–2030, 2031–2040, and 2041–2050 will be higher by up to 22% (763 mm) (RCP 8.5.C for 2041–2050) compared to the 2013–2018 simulation years (624 mm). The average annual temperature for most climate projections for 2021–2030 will fall to as low as 8.7 °C (RCP 4.5.B) compared to the 2013–2018 simulation period (9.2 °C). In contrast, for all projections in 2031–2040 and 2041–2050, the average annual temperature will increase to as much as 10.3 °C (RCP 8.5.C). The simulation results for the climate projections (2020–2050) indicate that there are no clear trends of change in the water management of the Vistula River basin for the coming decades. According to scenarios RCP 4.5.A, RCP 8.5.A, and RCP 8.5.B, the annual sums of potential evapotranspiration show a slight downward trend. On the other hand, for the RCP 8.5.C and RCP 4.5.C projections and the climate change scenario RCP 4.5.B, the results obtained show a slight upward trend in the annual sum of potential evapotranspiration. For the overall evapotranspiration and potential evapotranspiration assessment for all climate projections analysed, the annual evapotranspiration total shows a clear increase compared to the 2013–2018 baseline period. The average annual actual evapotranspiration for all projections in 2021–2030, 2031–2040, and 2041–2050 will increase up to 467 mm (RCP 4.5.A—2021–2030) compared to the 2013–2018 simulation period of 401 mm. The average annual potential evapotranspiration for all projections in 2021–2030, 2031–2040, and 2041–2050 will increase up to 755 mm (RCP 8.5.C—2031–2040) compared to the 2013–2018 simulation period—616 mm. The analysis of the total runoff in all climate models for the RCP 4.5 scenario shows that the annual average total runoff tends to decrease. The results of the simulations carried out for the RCP 8.5 scenario, which are generally characterised by an increase in total runoff in subsequent years, are different. When analysing annual total runoff on a regional basis, it appears that for most of the climate projections analysed (except for the RCP 8.5.A scenario), annual runoff will be lower, especially in the lowlands in the central part of the Vistula basin. In regions where the increase in precipitation is greatest in the north-western and southern basins, higher total runoff should be expected. The analysis of the total runoff in all climate models for the RCP 4.5 scenario shows that the annual average total runoff tends to decrease. The results of the simulations carried out for the RCP 8.5 scenario, which are generally characterised by an increase in total runoff in subsequent years, are different. When analysing annual total runoff on a regional basis, it appears that for most of the climate projections analysed (except for the RCP 8.5.A scenario), annual runoff will be lower, especially in the lowlands in the central part of the Vistula basin. In regions where the increase in precipitation is greatest in the north-western and southern basins, higher total runoff should be expected.

A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model

Abstract. As the theoretical upper bound of evapotranspiration (ET) or water use by ecosystems, potential ET (PET) has always been widely used as a variable linking a variety of disciplines, such as climatology, ecology, hydrology, and agronomy. However, substantial uncertainties exist in the current PET methods (e.g., empiric models and single-layer models) and datasets because of unrealistic configurations of land surface and unreasonable parameterizations. Therefore, this study comprehensively considered interspecific differences in various vegetation-related parameters (e.g., plant stomatal resistance and CO2 effects on stomatal resistance) to calibrate and parametrize the Shuttleworth–Wallace (SW) model for forests, shrubland, grassland, and cropland. We derived the parameters using identified daily ET observations with no water stress (i.e., PET) at 96 eddy covariance (EC) sites across the globe. Model validations suggest that the calibrated model could be transferable from known observations to any location. Based on four popular meteorological datasets, relatively realistic canopy height, time-varying land use or land cover, and the leaf area index, we generated a global 5 km ensemble mean monthly PET dataset that includes two components of potential transpiration (PT) and soil evaporation (PE) for the 1982–2015 time period. Using this new dataset, the climatological characteristics of PET partitioning and the spatiotemporal changes in PET, PE, and PT were investigated. The global mean annual PET was 1198.96 mm with PT/PET of 41 % and PE/PET of 59 %, controlled moreover by PT and PE of over 41 % and 59 % of the globe, respectively. Globally, the annual PET and PT significantly (p<0.05) increase by 1.26 and 1.27 mm yr−1 over the last 34 years, followed by a slight decrease in the annual PE. Overall, the annual PET changes over 53 % of the globe could be attributed to PT, and the rest to PE. The new PET dataset may be used by academic communities and various agencies to conduct climatological analyses, hydrological modeling, drought studies, agricultural water management, and biodiversity conservation. The dataset is available at https://doi.org/10.11888/Terre.tpdc.300193 (Sun et al., 2023).

Quantitative Analysis of the Impact of Climate Change and Human Activities on Runoff Variation in Akwa Ibom State, Nigeria

The non-parametric Mann-Kendall (MK) trend test, including the Sen's slope test and Pettitt's test, was used to determine trends, magnitudes, and change points in hydro-meteorological variables from 1972 to 2021. The slope change ratio of accumulative quantity (SCRAQ) method was then used to calculate the relative contributions of climate change and human activities to runoff variation in the Uyo-Itu river basin. Annual rainfall, maximum temperature, minimum temperature, and runoff showed significant increasing trends, whereas annual relative humidity, solar radiation, and potential evapotranspiration showed significant decreasing trends. Between 1992 and 2010, there were abrupt changes in hydro-meteorological variables. However, the runoff shift occurred in 2003. The time period under consideration was divided into two parts: baseline period A and change (impacted) period B. Climate change dominates runoff variation in period B, accounting for 103.6 percent of the variation, while human activities have a negative impact (-3.6%). The results indicate that climate change is the primary driver of runoff variation and that its impact is becoming more severe. Furthermore, the Budyko hypothesis was used to validate the contributions of human activities and climatic changes based on the SCRAQ method. The results showed that the contributions of human activities and climatic changes computed using the SCRAQ method are comparable with those computed using the sensitivity-based method. From this study, it can be concluded that assessing the influence of climate changes and human activities on variations and identifying the major driving forces causing the variations are critical for more efficient water resources management for sustainable economic growth
  

A Comprehensive Assessment of the Hydrological Evolution and Habitat Quality of the Xiangjiang River Basin

Human disturbance and climatic factors alter the hydrological state of rivers in many ways and have a degree of negative impact on the quality of watershed habitats; quantifying the impact of both human disturbance and climatic factors on hydrological change can help improve the quality of watershed habitats. Therefore, in this research, an integrated watershed assessment framework is proposed to analyse the watershed from four perspectives: hydrological situation, environmental flows, drivers, and habitat quality. A meteorological streamflow model based on the Long Short-Term Memory (LSTM) model was employed to analyse the hydrological evolution and quantify the influence of the drivers from the perspective of hydrological and environmental flows. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was then used to evaluate the spatial and temporal evolution of habitat quality in the basin. And, finally, the grey correlation theory was used to reveal the response of habitat quality to hydrological changes. Studies have shown that annual flow and precipitation are increasing in the Xiangjiang River (XJR) basin, while its annual potential evapotranspiration is decreasing significantly. After 1991, the hydrological conditions of the XJR were highly variable, with the combined rate of change of the most Ecologically Relevant Hydrological Indicators, ERHIs-IHA and ERHIs-EFCs, reaching 26.21% and 121.23%, respectively. Climate change and human disturbance are the main drivers of change for both (with contributions of 60% and 71%, respectively). Between 1990 and 2020, the habitat quality in the basin declined over time (from 0.770 to 0.757), with areas of high habitat value located mainly in mountainous areas and habitat degradation being concentrated in urban areas in the middle and lower reaches, gradually evolving towards areas of high habitat value in the periphery. There is a strong correlation between watershed habitat quality and the ERHIs. The results of the study can provide a scientific basis for maintaining regional ecological security and rational allocation of water resources.

Soil color mapping based on Munsell system in the northeast of China

Soil color is the most readily available soil property, soil scientists often use the Munsell system to describe soil color and to quickly understand the physical, chemical, and biological properties of soil through soil color variation. Currently, soil color mapping studies often rely on indirect acquisition of Munsell color data from soil spectral information. As a result, there may be some discrepancies between the mapped colors and the colors perceived by humans. In this study, we collected 880 dry and 827 moist Munsell samples from the Northeast China to test the method developed for soil color mapping. We selected a set of covariates (climate, topography, evapotranspiration, regolith thickness, and remote sensing images) for digital soil color mapping, these covariates were related to soil formation or organic matter accumulation processes. Finally, the dry and moist topsoil color mapping with 30-m resolution was obtained for cropland in Northeast China. These covariates all played positive roles in the soil classification process, among which annual temperature mean (MAT), mean annual precipitation (MAP), land surface temperature (LST), and mean annual potential evapotranspiration (MAPET) had the highest contribution. We summarized the difficulties that usually occur in soil color mapping, and put forward a ‘stepwise classification’ method. According to the three-dimensional attributes of the Munsell system, the measured color data were divided into seven color groups (four dry and three moist color groups). Among all color groups, the highest accuracy of mapping validation was 0.69 and the lowest was 0.58. The kappa coefficient, usually affected by classification bias, was small (0.3). The color differences between measured and predicted colors were found to be 1.21 (dry color) and 1.36 (moist color). Compared to direct classification, the stepwise classification method improved classification accuracy and reduced mapping color differences. Our soil color mapping for two cases of dry and moist corresponded well with spectral color maps. The correlation between soil organic matter (SOM) content and soil color (dry and moist) was analyzed in 807 samples. The darker the soil color was, the higher the SOM content was. In summary, soil color holds the potential to serve as a surrogate for assessing cropland quality, particularly in evaluating SOM.

Spatial and Temporal Evolution Characteristics of Water Conservation in the Three-Rivers Headwater Region and the Driving Factors over the Past 30 Years

The Three-Rivers Headwater Region (TRHR), located in the hinterland of the Tibetan Plateau, serves as the “Water Tower of China”, providing vital water conservation (WC) services. Understanding the variations in WC is crucial for locally tailored efforts to adapt to climate change. This study improves the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) water yield model by integrating long-term time series of vegetation data, emphasizing the role of interannual vegetation variation. This study also analyzes the influences of various factors on WC variations. The results show a significant increase in WC from 1991 to 2020 (1.4 mm/yr, p < 0.05), with 78.17% of the TRHR showing improvement. Precipitation is the primary factor driving the interannual variations in WC. Moreover, distinct interactions play dominant roles in WC across different eco-geographical regions. In the north-central and western areas, the interaction between annual precipitation and potential evapotranspiration has the highest influence. Conversely, the interaction between annual precipitation and vegetation has the greatest impact in the eastern and central-southern areas. This study provides valuable insights into the complex interactions between the land and atmosphere of the TRHR, which are crucial for enhancing the stability of the ecosystem.

The contributions of climate and land use/cover changes to water yield services considering geographic scale

BackgroundWater yield services are critical for maintaining ecological sustainability and regional economies. Climate change and land use/cover change (LUCC) significantly affect regional water yield, but the spatiotemporal variability of water yield services has been overlooked in previous studies. This study aims to explore the relative contributions of climate and land use/cover changes to water yield services at both grid and subwatershed scales. MethodsThis study employed the InVEST model to calculate the water yield in the study area and employed a multi-scenario simulation approach to investigate the impacts of climate change and LUCC on water yield at both grid and subwatershed scales. Furthermore, the contributions of these two types of changes to water yield were quantified. ResultsFirstly, upstream areas experience significantly lower annual average precipitation, temperature, and potential evapotranspiration than downstream areas, with worsening drought severity. Secondly, urbanization led to significant LUCC, with decreases in farmland and grassland and increases in forest, water, building land, and unused land. Thirdly, the spatial heterogeneity of water yield services remains consistent across different scales, but more pronounced spatial clustering is observed at the subwatershed scale. Fourthly, climate change is the primary factor affecting regional water yield services, surpassing the influence of LUCC. Lastly, LUCC significantly impacts water cycling in watersheds, with vegetation coverage being a critical factor affecting water yield. ConclusionThese findings highlight the need to consider the complex relationships between climate change, LUCC, and water yield services at multiple scales in water resource management.

Spatio-Temporal Variations of Climate Variables and Extreme Indices over the Aral Sea Basin during 1960 - 2017

The Aral Sea plays a key role in the socio-economic development of Central Asia. In the past few decades, with the combined effects of global warming and human activities, the ecological environment of the Aral Sea has undergone significant changes, such as the reduction of the basin area and the drop in water levels. In this study uses the observed climate data, combined with remote sensing to systematically analyze the characteristics of changes in climate in the Aral Sea Basin (ASB). We used linear regression, Pearson's correlation and Pettit's test to determine climate change. The main conclusions are as follows. Based on the analysis of the temporal and spatial changes of temperature, precipitation, and potential evapotranspiration in the Aral Sea Basin from 1960 to 2017, it was found that the annual average temperature, precipitation, and potential evapotranspiration increased by 0.32 ℃ decade-1, 0.16 mm decade-1, and 0.04 mm day-1 decade-1, respectively. In addition, the changes of these climatic variables were different in the growing season (April - September) and the non-growing season (October - March). Temperature and potential evapotranspiration increased in both growing and non-growing seasons; however, the precipitation decreased (increased) in the growing (non-growing) season. This means that the climate in the growing season showed a warming and drying trend. HIGHLIGHTS In this study, we present the complex and detailed analysis that we performed by combining temporal and spatial changes in key climate parameters temperature, precipitation and potential evapotranspiration and change of climate extreme indices in the entire Aral Sea Basin and its sub-regions. GRAPHICAL ABSTRACT

Spatio-temporal variations in global surface soil moisture based on multiple datasets: Intercomparison and climate drivers

Accurate soil moisture datasets are essential to understand the impacts of climate change. However, few studies have evaluated the consistency and drivers of long-term trends in soil moisture among different dataset types (satellite, assimilation, reanalysis, and climate model) at the global scale. Here we analyze the spatio-temporal variations of global surface soil moisture and associated climate dynamics over 1980–2020 using multiple soil moisture datasets, i.e., multi-satellite assimilated remote sensing datasets (ESA CCI), simulated soil moisture based on LSMs (GLDAS, GLEAM, CMIP6), and reanalysis (ECMWF ERA5, MERRA2, CRA-Land). Most of these datasets indicate pervasive drying of global surface soil moisture over the last four decades. Prominent soil moisture drying is detected in North America, Europe, northeastern Asia, North Africa, and the Arabian Peninsula. The cross-correlations among the five synthetic soil moisture datasets are the highest between GLEAM and the reanalysis datasets. Using the Aridity Index (AI, the ratio between annual total precipitation and potential evapotranspiration), we find that soil moisture drying is the most intensive in the humid-arid transitional regions with AI ranging 0.8–1.2. Surface soil moisture drying is primarily driven by increases in temperature, followed by ENSO, as indicated by Maximum Covariance Analysis (MCA). However, the significance of the impact of ENSO on soil moisture variability is sensitive to the choice of soil moisture dataset used in the MCA.

Analysis of Trend in Meteorological and Hydrological Time-series using Mann-Kendall and Sen’s Slope Estimator Statistical Test in Akwa Ibom State, Nigeria

The monthly, seasonal, annual, and decadal trends of seven hydro-meteorological variables were analysed for stations in Akwa Ibom State, Nigeria, controlled by the Nigerian Meteorological Agency (NiMet) and the Cross River Basin Development Authority (CRBDA) from 1972 to 2021. At the 5% statistical significance level, the non-parametric Mann-Kendall and Sen's slope estimator techniques were used to detect if there was a positive or negative trend and the magnitude of the trend in hydro-meteorological data. In the present study, there was a significant statistically increasing (positive) trend in mean seasonal and annual rainfall, maximum temperature, minimum temperature, and runoff. However, there was a significant statistically decreasing (negative) trend in average annual relative humidity, solar radiation, and potential evapotranspiration. The magnitudes of the trends were 19.39mm/year, 0.0314oC/year, 0.013oC/year, -0.104%/year, -8.78MJ/m2/year, -1.440mm/year, and 0.028m3/s/year for annual rainfall, maximum temperature, minimum temperature, relative humidity, solar radiation, PET, and runoff, respectively. The rising trends in precipitation, temperature, and runoff in this research area show that this region is subject to climatic variability. The results of the Mann-Kendall and Sen's slope estimator statistical tests revealed the consistency of performance in the detection of the trend for the hydro-meteorological variables.

Detecting the main driving force of runoff change in the Beiluo River Basin, China.

Understanding the evolution of runoff and identifying the main driving force of hydrological cycle changes are essential for water resource management. In this study, the spatial and temporal patterns of climate variables and hydrological factors were explored by applying geostatistical analysis and trend analysis in the Beiluo River Basin (BRB), China, and conversions of land use/cover change (LUCC) were assessed using chord diagrams. Contributions of climate change and human activities to runoff change were quantified employing multiple methods. The results show that annual precipitation and actual evapotranspiration increased significantly during the impact period (2004-2014) (p < 0.05), at rates of 19.3 mm/a and 11 mm/a, respectively, and there was a minor upward trend in annual runoff, at a rate of 0.38 mm/a, while annual potential evapotranspiration decreased slightly at a rate of - 3.3 mm/a. Climate variables were the primary contributor to runoff decrease from 2004 to 2011, with an average contribution of - 79% according to the three methods. Human activities were estimated to account for - 81% of runoff change from 2012 to 2014, which was inextricably linked to the increasing LUCC. The results of this study can provide a theoretical basis for regional water resource management under the influence of climate change and human activities.