Hydrology and Water Resources in Agriculture and Ecology

Accurate estimation of reference evapotranspiration (ET_r) is important for irrigation planning, water resource management, and preserving agricultural and forest habitats. The widely used Penman–Monteith equation (ASCE-PM) estimates ET_r across various timescales using ground weather station data. However, discrepancies persist between estimated ET_r and measured ET_r obtained from weighing lysimeters (ET_r-lys), particularly in advective environments. This study assessed different machine learning (ML) models in comparison to ASCE-PM for ET_r estimation in highly advective conditions. Various variable combinations, representing both radiation and aerodynamic components, were organized for evaluation. Eleven datasets (DT) were created for the daily timescale, while seven were established for hourly and quarter-hourly timescales. ML models were optimized by a genetic algorithm (GA) and included support vector regression (GA-SVR), random forest (GA-RF), artificial neural networks (GA-ANN), and extreme learning machines (GA-ELM). Meteorological data and direct measurements of well-watered alfalfa grown under reference ET conditions obtained from weighing lysimeters and a nearby weather station in Bushland, Texas (1996–1998), were used for training and testing. Model performance was assessed using metrics such as root mean square error (RMSE), mean absolute error (MAE), mean bias error (MBE), and coefficient of determination (R²). ASCE-PM consistently underestimated alfalfa ET across all timescales (above 7.5 mm/day, 0.6 mm/h, and 0.2 mm/h daily, hourly, and quarter-hourly, respectively). On hourly and quarter-hourly timescales, datasets predominantly composed of radiation components or a blend of radiation and aerodynamic components demonstrated superior performance. Conversely, datasets primarily composed of aerodynamic components exhibited enhanced performance on a daily timescale. Overall, GA-ELM outperformed the other models and was thus recommended for ET_r estimation at all timescales. The findings emphasize the significance of ML models in accurately estimating ET_r across varying temporal resolutions, crucial for effective water management, water resources, and agricultural planning. Full article

Agriculture significantly contributes to the global water footprint (WF) with the animal breeding industry accounting for over 33% of agricultural water consumption. Since 2000, rapid development in animal breeding has intensified the pressure on water resources. Forecasts indicate a projected 70% increase in freshwater usage in the meat industry by 2025 compared to 2000, particularly in developing countries, such as China, yet comprehensive studies regarding China’s animal breeding industry WF remain limited. This study aimed to assess the variations in the green, blue, and gray WF of pork, beef, milk, eggs, and chicken meat across 31 provinces in China from 2000 to 2017. Additionally, a driving force analysis using the Kaya equation and LMDI method was conducted. Findings revealed that the total WF of animal products increased from 1049.67 Gm³ (in 2000) to 1385.05 Gm³ (in 2017) in China, and pork exhibited a significantly higher WF compared to other animal products, contributing 64.49% to China’s total animal product WF. The sharp rise in the green WF demonstrated regional disparities in water consumption efficiency within the animal breeding industry. The increase in the blue WF was associated with rising livestock numbers and China’s efforts to conserve water. The increase in the gray WF indicated that increased consumption of animal products heightened wastewater treatment pressures, particularly in economically developed provinces. The augmentation in China’s animal product WF was primarily influenced by policy and economic effects, with increased agricultural equipment funding and enhanced production efficiency identified as effective strategies for WF reduction. This study suggests that the promotion of technology, combined with scientific policies, can alleviate the pressure on water resources in the animal breeding industry in developing countries. Full article

Aiming at the problem that the existing channel leakage calculation methods generally ignore the dynamic changes of influencing factors, which leads to a large calculation error, this study attempts to utilize the machine learning method to accurately calculate the channel leakage loss under the dynamic changes in the influencing factors. By using the machine learning method to analyze the impact of dynamic changes in the flow rate and soil moisture content over time on the channel leakage loss in the water transmission process and quantify the impact of the selected factors on the leakage loss, a dynamic simulation model of the multi-parameter channel leakage loss was constructed, and a test was carried out in the irrigation area to verify the accuracy of the model. The test results are as follows: the actual leakage loss of the U1 channel is 1094.03 m³, the simulated value of the model is the 1005.24 m³, and the error between the simulated value and the measured value is 8.12%; the total leakage of the U2 channel is 1111.24 m³, the simulated value of the model is 1021.1 m³, and the error between the simulated value and the measured value is 6.31%. The experimental results show that the use of machine learning to construct a dynamic simulation model of channel leakage loss under the comprehensive consideration of the dynamic change in influencing factors over time has a better effect, and the calculation accuracy is high. Full article

Water tunnels are one of the oldest hydro-technologies for extracting water resources and/or transmitting them through water distribution systems. In the past, human societies have used tunneling for various purposes, including development, as a measure to enable underground resource extraction and the construction of transportation networks in challenging landscapes and topographies. The development of hydro-technology potentially involves the construction of tunnels to feed aqueducts, irrigation and waste water systems. Thus, the ability to make and maintain tunnels became an important component in creating lasting and sustainable water systems, which increased water supply and security, minimized construction costs, and reduced environmental impact. Thus, this review asks how, when and why human societies of the past included tunneling for the development of lasting water supply systems. This review presents a comprehensive overview across time and space, covering the history of tunneling in hydro technology from antiquity to the present, and it ponders how past experiences could impact on future hydro-technological projects involving tunneling. A historical review of tunnel systems enhances our understanding of the potential, performance, challenges, and prospects associated with the use of hydro-techniques. In the past, as the different examples in time and space demonstrate, tunneling was often dedicated to solving local problems of supply and disposal. However, across the world, some features were repeated, including the need for carving through the living rock or digging to create tunnels covered with stone slabs. Also, the world-wide use of extensive and costly tunnel systems indicates the high level of investment which human societies are willing to make for securing control over and with its water resources. This study helps us to gather inspiration from proven technologies of the past and more recent knowledge of water tunnel design and construction. As we face global warming and its derivate problems, including problems of water scarcity and flooding, the ability to create and maintain tunnels remains an important technology for the future. Full article

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of an evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources. Full article

The objective of this study was to develop and calibrate a photovoltaic-powered soil moisture sensor (SMS) for irrigation management. Soil moisture readings obtained from the sensor were compared with gravimetric measurements. An automated SMS was used in two trials: (i) okra crop (Abelmoschus esculentus) and (ii) chili pepper (Capsicum frutescens). All sensors were calibrated and automated using an Arduino Mega board with C++. The soil moisture data were subjected to descriptive statistical analysis. The data recorded by the equipment was correlated with the gravimetric method. The determination coefficient (R²), Pearson correlation (r), and root mean square error (RMSE) were adopted as criteria for equipment validation. The results show that our SMS achieved an R² value of 0.70 and an r value of 0.84. Notably, there was a striking similarity observed between SMS and gravimetric data, with RMSE values of 3.95 and 4.01, respectively. The global model developed exhibited highly efficient outcomes with R² (0.98) and r (0.99) values. The applicability of the developed SMS facilitates irrigation management with accuracy and real-time monitoring using digital data. The automation of the SMS emerges as a real-time and precise alternative for performing irrigation at the right moment and in the correct amount, thus avoiding water losses. Full article

This study investigated the hydrological properties of litter in different vegetation cover types, including Eucalyptus sp. plantation, Agroforestry, and Restoration Forest. The research focused on evaluating litter accumulation, composition, water holding capacity, and effective water retention. The results revealed variations in litter accumulation among the stands, and especially Eucalyptus sp., which had a higher proportion of branches compared to leaves. The water holding capacity of the litter differed among the stands. Agroforest and Restoration Forest showed higher litter water capacities than Eucalyptus sp. The composition and decomposition stage of the litter fractions influenced their water retention capabilities, with leaves exhibiting superior water retention. In contrast, branches had lower water absorption due to their hydrophobic nature. Despite these differences, the effective water retention, which indicates the ability of litter to intercept precipitation, was similar among the stands. The findings highlight the importance of considering litter composition and species-specific characteristics in understanding the hydrological functions of litter. This knowledge contributes to effective conservation and management strategies for sustainable land use practices and water resource management. Further research is recommended to expand the study’s scope to include a wider range of forest types and natural field conditions, providing a more comprehensive understanding of litter hydrological functions and their implications for ecosystem processes. Full article

Research on the variation in soil water, heat, and salt in unsaturated zones during the freeze–thaw process has great significance in efficiently utilizing water resources and preventing soil salinization. The freeze–thaw field experiment was carried out with the lysimeter as the test equipment to analyze characteristics of the soil freeze–thaw process, profile water content, main ion content, and salt content of three textured soils with the groundwater table depth of 0.5 m. The results showed that the soil temperature gradient and freezing depth were greater as the average soil particle size increased. The increment of water content at the depth of 0 to 30 cm in sandy loam and loamy sand decreased by 40.20~93.10% and 28.14~65.52% compared with that in sandy soil, and the average increment of salt content at the depth of 0 to 30 cm decreased as the average soil particle size increased during the freeze–thaw period. The average content of Ca²⁺, Na⁺, Cl⁻, and SO₄²⁻ in loamy sand and sandy soil decreased by 4.37~45.50% and 22.60~70.42% compared with that in sandy loam at the end of the freeze–thaw period, and the correlation between soil salt content and water content decreased with the increase in the average soil particle size. The research results can provide a theoretical basis for soil salinization prevention and crop production in shallow groundwater areas. Full article

Spatiotemporal variations in reference evapotranspiration (ET_o) are sensitive to the meteorological data used in its estimation. The sensitivity of the ASCE standardized ET_o equation to meteorological variables from GOES-PRWEB dataset was evaluated for the island of Puerto Rico. Island wide, ET_o is most sensitive to daily mean relative humidity (RH_mean), followed by solar radiation, daily maximum (T_max) and minimum (T_min) air temperatures, and wind speed with average absolute relative sensitivity coefficients (SCs) of 0.98, 0.57, 0.50, 0.27, and 0.12, respectively. The derived SCs guided the prioritization of bias correction of meteorological data for ET_o estimation from two downscaled climate models (CNRM and CESM). The SCs were applied to evaluate how meteorological variables contribute to model errors and projected future changes in ET_o from 1985–2005 to 2040–2060 at irrigated farms in the south. Both models project a 5.6% average increase in annual ET_o due to projected increases in T_max and T_min and a decrease in RH_mean. Despite ET_o being most sensitive to relative changes in RH_mean, the contributions from RH_mean, T_max, and T_min to future changes in ET_o are similar. CESM projects increases in ET_o in March, November, and December, increasing the potential for crop water stress. Study limitations are discussed. Full article

As the saline-alkali paddy area continues to grow, the nutrient (e.g., nitrogen (N) and phosphorus (P)) runoff loss is becoming more serious in the world. The N-fertilizer application affects the nutrient runoff loss risk in paddy. Selecting suitable fertilizer types to reduce nutrient loss is beneficial to agricultural sustainability. However, the effects of N-fertilizer application in saline-alkali paddy are not clear. This study measured the N and P concentration of surface water in saline-alkali paddy, using various N—fertilizer treatments (i.e., urea (U), urea with urease—nitrification inhibitors (UI), organic–inorganic compound fertilizer (OCF), carbon—based slow—release fertilizer (CSF), and no N fertilization (CK)). Based on the structural equation model, both phosphate (PO₄³⁻-P) and total−P (TP) concentrations had a positive influence on total-N (TN) concentration regardless of N−fertilizer types applied. Potential risks of ammonia—N (NH₄⁺—N) and nitrate—N (NO₃⁻—N) runoff losses were reduced in UI treatment, but the TN and TP losses were increased. At the panicle-initiation fertilizer stage, the NO₃⁻−N, TN, and TP concentrations in CSF and OCF treatments were lower than U. The CSF application can control the TP runoff loss risk during the rice-growing season. UI should not be suggested for the control of nutrient runoff loss in saline-alkali paddy. Full article

This study aimed to investigate how sustainable forest management can affect litter hydrological properties. We investigated the net precipitation, litter mass, water-holding capacity, effective water-holding and retention capacity, maximum water retention and water content in unlogged and logged forests over 13 months in the Amazon Forest, where reduced-impact logging is allowed. The mean litter mass was similar for unlogged and logged forests. The litter water-holding capacity was 220% for unlogged and 224% for logged forests, and for fractions followed: unstructured > leaves > seeds > branches for both forests. The effective water-holding capacity was 48.7% and 49.3% for unlogged and logged, respectively, and the effective water retention was 10.3 t·ha⁻¹ for both forests. The effective water retention in the rainy and dry seasons accounted for 12.5 t ha⁻¹ and 7.2 t ha⁻¹ for unlogged and logged, respectively. The maximum water retention was slightly greater for logged forests (16.7 t ha⁻¹) than unlogged (16.3 t ha⁻¹). The litter water content had 40% less water in the dry season than in the rainy in both forests. In general, there were no significant differences in litter storage and hydrological properties between stands. This suggests that reduced-impact logging did not significantly affect the hydrological dynamics of the litter layer in the Amazonian forests studied. Full article

With the intensification of global warming, food production will face serious drought risk. In view of the insufficient applicability of the existing crop drought index, a standardized crop water deficit index (SCWDI) was constructed based on the construction idea of the standardized precipitation evapotranspiration index (SPEI) and the crop water deficit index (CWDI) in this study. On this basis, the spatial and temporal characteristics of spring maize drought in Songnen Plain were explored by the slope trend analysis and Morlet wavelet analysis methods. The results show the following: (1) Compared with the existing drought index, the SCWDI shows obvious advantages in drought monitoring of spring maize. (2) In the whole growth stage of spring maize, the change trend of SCWDI was small in the temporal series (−0.012/10a). Spatially, the drought trend of spring maize was mainly decreasing (−0.14~0/10a). The drought frequency of spring maize in each growth stage was mainly light drought in most regions. (3) The three main drought cycles of spring maize in Songnen Plain were 29 years, 10 years, and 4 years. In the next few years, the drought of spring maize in Songnen Plain was controlled by the first main cycle, and the drought years may increase, which should be prevented. The research was expected to provide technical support for crop drought monitoring and agricultural disaster prevention. Full article

Soil’s physical and hydrological properties influence the proper modeling, planning, and management of water resources and soil conservation. In areas of vertic soils subjected to wetting and drying cycles, the soil–water–atmosphere interaction is complex and understudied at the field scale, especially in dry tropical regions. This work quantifies and analyzes crack development under field conditions in an expansive soil in a semiarid region for both the dry and rainy seasons. Six 1 m² plots in an experimental 2.8 ha watershed were photographed and direct measurements were taken of the soil moisture and crack area, depth and volume once a week and after a rainfall event from July 2019 to June 2020. The rainfall was monitored for the entire period and showed a unimodal distribution from December to May after five months without precipitation. The cracks were first sealed in the plots with a predominance of sand and when the soil moisture was above 23% and had an accumulated precipitation of 102 mm. The other plots sealed their cracks when the soil moisture was above 32% and with an accumulated precipitation in the rainy season above 222 mm. The cracks redeveloped after sealing upon a reduction of 4% in the soil moisture. The depth of the cracks showed a better response to climatic variations (total precipitation, soil moisture and continuous dry and wet days). The higher clay content and the higher plasticity index plots developed more cracks with greater depth and volume. Full article

Various methods have been developed to estimate daily crop coefficients, but their performance varies. In this paper, a comprehensive evaluation was conducted to estimate the crop coefficient of winter wheat in four growth stages based on the observed data of weighing-type lysimeters and the high-precision automatic weather station in the Wudaogou Hydrological Experimental Station from 2018 to 2019. The three methods include the temperature effect method, the cumulative crop coefficient method, and the radiative soil temperature method. Our results suggest that the performance of these methods was different in each individual growth stage. The temperature effect method was better in the emergence-branching (RMSE = 0.06, r = 0.80) and heading-maturity stages (RMSE = 0.16, r = 0.94) because the temperature is suitable for crop growth during most of these two periods. The cumulative crop coefficient method was better in the greening-jointing (RMSE = 0.16, r = 0.88) and heading-maturity stages (RMSE = 0.20, r = 0.91) because this method is closely related to crop growth, which is vigorous during these two stages. The radiative soil temperature method was better in the emergence-branching (RMSE = 0.20, r = 0.35) and branch-overwintering stages (RMSE = 0.25, r = 0.52) as the energy balance can be ensured by the relatively high level of the effective energy during these periods. By comparing the estimation accuracy indices of the three methods, we found that the temperature effect method performed the best during the emergence-branching stage (RMSE = 0.06, MAE = 0.06, r = 0.80, d_IA = 0.88), branch-overwintering stage (RMSE = 0.13, MAE = 0.11, r = 0.44, d_IA = 0.55), and heading-maturity stage (RMSE = 0.16, MAE = 0.13, r = 0.94, d_IA = 0.97), while the cumulative crop coefficient method performed best during the greening-jointing stage (RMSE = 0.16, MAE = 0.13, r = 0.88, d_IA = 0.89). Based on this result, an integrated modelling procedure was proposed by applying the best method in each growth stage, which provides higher simulation precision than any single method. When the best method was adopted in each growth stage, the estimated accuracy of the whole growth process was RMSE = 0.13, MAE = 0.09, r = 0.98, d_IA = 0.99. Full article

Global warming and human activities are complicating the spatial and temporal relationships between basin hydrologic processes and ecosystem quality (EQ), especially in arid and semi-arid regions. Knowledge of the synergy between hydrological processes and ecosystems in arid and semi-arid zones is an effective measure to achieve ecologically sustainable development. In this study, the inland river basin Ulagai River Basin (URB), a typical arid and semi-arid region in Northern China, was used as the study area; based on an improved hydrological model and remote-sensing and in situ measured data, this URB-focused study analyzed the spatial and temporal characteristics of hydrological process factors, such as precipitation, evapotranspiration (ET), surface runoff, lateral flow, groundwater recharge, and EQ and the synergistic relationships between them. It was found that, barring snowmelt, the hydrological process factors such as precipitation, ET, surface runoff, lateral flow, and groundwater recharge had a rising trend in the URB, since the 20th century. The rate of change was higher in the downstream areas when compared with what it was in the upstream and midstream areas. The multi-year average of EQ in the basin is 53.66, which is at a medium level and has an overall improving trend, accounting for 95.14% of the total area, mainly in the upstream, downstream southern, and downstream northern areas of the basin. The change in relationship between the hydrological process factors and EQ was found to have a highly synergistic effect. Temporally, EQ was consistent with the interannual trends of precipitation, surface runoff, lateral flow, and groundwater recharge. The correlation between the hydrological process factors and EQ was found to be higher than 0.7 during the study period. Spatially, the hydrological process factors had a synergistic relationship with EQ from strong to weak upstream, midstream, and downstream, respectively. In addition, ecosystem improvements were accelerated by government initiatives such as the policy of Returning Grazing Land to Grassland Project, which has played an important role in promoting soil and water conservation and EQ. This study provides theoretical support for understanding the relationship between hydrological processes and ecological evolution in arid and semi-arid regions, and it also provides new ideas for related research. Full article

Irrigation water for agriculture in Ningxia during the summer is primarily sourced from the Yellow River self-flow irrigation region. However, the water conveyance system in this region is significantly influenced by hydrodynamic factors, morphological factors, human factors, and the infrastructure used for social purposes, all of which directly impact the irrigation water utilization coefficient. In order to improve the irrigation water utilization coefficient, reduce suspended sediment deposition in the water conveyance channels, and mitigate negative effects on the water supply system, this study implemented a sediment diversion system at the channel head. This is expected to increase water usage efficiency to a certain degree. Using actual data on hydrodynamic factors from the Shizuishan section of the Yellow River in Ningxia, a two-dimensional numerical simulation was performed, and a two-dimensional hydrodynamic model and sediment model of the Shizuishan section of the Yellow River in Ningxia were developed using MIKE 21. The water conveyance method at the channel head was simulated under two different operating conditions. Results indicated that compared to operating condition 1, operating condition 2 had a beneficial effect on diverting and reducing sediment at the fish mouth of the channel head: the sediment accumulation thickness of one day in operating condition 1 was 0.16 m, 0.003 m, 0.15 m, and 0.21 m under actual flow, scenario 1, scenario 2, and scenario 3, respectively; whereas in operating condition 2, the sediment accumulation thickness of one day was 0.11 m, 0.001 m, 0.09 m, and 0.12 m under the same conditions, respectively. Additionally, as the computation period lengthened, the sediment accumulation thickness of operating condition 2 was significantly smaller than that of operating condition 1. In conclusion, operating condition 2 is superior for the design of the channel head in the Yellow River self-flow irrigation region. Full article

Precise assessment of drought and its impact on the natural ecosystem is an arduous task in regions with limited climatic observations due to sparsely distributed in situ stations, especially in the hyper-arid region of Kingdom of Saudi Arabia (KSA). Therefore, this study investigates the application of remote sensing techniques to monitor drought and compare the remote sensing-retrieved drought indices (RSDIs) with the standardized meteorological drought index (Standardized Precipitation Evapotranspiration Index, SPEI) during 2001–2020. The computed RSDIs include Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI), which are derived using multi-temporal Landsat 7 ETM+, Landsat 8 OLI/TIRS satellites, and the Google Earth Engine (GEE) platform. Pearson correlation coefficient (CC) is used to find the extent of agreement between the SPEI and RSDIs. The comparison showed CC values of 0.74, 0.67, 0.57, and 0.47 observed for VHI/SPEI-12, VHI/SPEI-6, VHI/SPEI-3, and VHI/SPEI-1, respectively. Comparatively low agreement was observed between TCI and SPEI with CC values of 0.60, 0.61, 0.42, and 0.37 observed for TCI/SPEI-12, TCI/SPEI-6, TCI/SPEI-3, and TCI/SPEI-1. A lower correlation with CC values of 0.53, 0.45, 0.33 and 0.24 was observed for VCI/SPEI-12, VCI/SPEI-6, VCI/SPEI-3, and VCI/SPEI-1, respectively. Overall, the results suggest that VHI and SPEI are better correlated drought indices and are suitable for drought monitoring in the data-scarce hyper-arid regions. This research will help to improve our understanding of the relationships between meteorological and remote sensing drought indices. Full article

Rainfall is one of the dominating climatic parameters that affect water availability. Trend analysis is of paramount significance to understand the behavior of hydrological and climatic variables over a long timescale. The main aim of the present study was to identify trends and analyze existing linkages between rainfall and streamflow in the Nilwala River Basin (NRB) of Southern Sri Lanka. An investigation of the trends, detection of change points and streamflow alteration, and linkage between rainfall and streamflow were carried out using the Mann–Kendall test, Sen’s slope test, Pettitt’s test, indicators of hydrological alteration (IHA), and Pearson’s correlation test. Selected rainfall-related extreme climatic indices, namely, CDD, CWD, PRCPTOT, R25, and Rx5, were calculated using the RClimdex software. Trend analysis of rainfall data and extreme rainfall indices demonstrated few statistically significant trends at the monthly, seasonal, and annual scales, while streamflow data showed non-significant trends, except for December. Pettitt’s test showed that Dampahala had a higher number of statistically significant change points among the six rainfall stations. The Pearson coefficient correlation showed a strong-to–very-strong positive relationship between rainfall and streamflow. Generally, both rainfall and streamflow showed non-significant trend patterns in the NRB, suggesting that rainfall had a higher impact on streamflow patterns in the basin. The historical trends of extreme climatic indices suggested that the NRB did not experience extreme climates. The results of the present study will provide valuable information for water resource planning, flood and disaster mitigation, agricultural operations planning, and hydropower generation in the NRB. Full article

Water footprint (WF) is a comprehensive summation of the volume of freshwater consumed directly and indirectly in all the steps of the production chain of a product. The water footprint concept has been widely used in agricultural water resources management. Water for irrigation is supplied in Sri Lanka to farmers at no cost, and thus the question is arising, whether the current management strategies the authorities and the farmers follow are appropriate to achieve productive water utilization. Therefore, this study aims at evaluating the water footprint of rice production in an irrigation scheme in the dry zone of Sri Lanka, the Walawe irrigation scheme. Due to the unreliability of the rainfall in the study area paddy cultivation depends entirely on irrigation, thus, the $W{F}_{blue}$, in other terms the volume of water evaporated from the irrigation water supply is considered as the total WF ($W{F}_{tot})$ in this study. Actual crop evapotranspiration (equivalent to $E{T}_{blue}$) was estimated based on the Penman-Monteith (P-M) model integrating effective rainfall, and crop coefficient published in Sri Lankan Irrigation Design Guidelines. The study spanned for three irrigation years from 2018–2021. Actual irrigation water issued to the field was estimated based on the data recorded by the government body responsible for irrigation water management of the area—Mahaweli Authority of Sri Lanka. The total volume of percolated water was computed employing the water balance method while assuming runoff is negligible. Results show that the average annual $W{F}_{blue}$ found to be 2.27 m³/kg, which is higher than global and national $W{F}_{tot}$. As the crop yield in the study area (6.5 ton/ha) is also higher than the global (4.49 ton/ha) and national (3.5 ton/ha) yields, a conclusion was drawn that the irrigation water usage ($CWU{T}_{blue})$ in the area may be significantly higher. It was then noted the higher $CWU{T}_{blue}$ was due to relatively higher evapotranspiration in the area. Thus, it is vital to reduce excess water usage by shifting irrigation practices from flooded irrigation to the System of Rice Intensification (SRI). Full article

With the impacts of climate change and human activities, agricultural drought disaster losses have increased remarkably. Drought disaster risk assessment is a prerequisite for formulating disaster reduction strategies and ensuring food security. However, drought disaster risk is a complex system, and quantitative assessment methods reflecting the risk formation mechanism are still rarely reported. This study presented a chain transmission system structure of drought disaster risk, which meant that drought disaster loss risk R was derived from drought hazard H by the transformation of drought disaster vulnerability V. Based on this point, firstly, a drought hazard curve between drought intensity and drought frequency was established using remote sensing data and the copula function. Then, a crop loss calculation approach under various drought events and drought resistance capacity scenarios was achieved by two-season field experiments and the AquaCrop model. Finally, a loss risk curve cluster of “drought frequency–drought resistance capacity–yield loss rate” was proposed by the composition of the above two quantitative relationships. The results of the case study for summer maize in Bengbu City indicated that the average yield loss rate under 19 droughts occurring during the growth period of maize from 1982 to 2017 was 24.51%. High risk happened in 1988, 1992, 1994, 2001, and 2004, with the largest loss rate in 2001, up to 65.58%. Overall, droughts with a return period less than two years occurred frequently during the growth period of summer maize in Bengbu, though the loss risk was still controllable. In conclusion, the results suggest that the loss risk curve provides a new effective method of drought disaster risk quantitative assessment from a physical mechanism perspective, which lays a scientific foundation for decision-making in risk management. Full article

Land Use/Land Cover (LU/LC) change is among the dominant driving factors that directly influence water balance by transforming hydrological responses. Consequently, a thorough comprehension of its impacts is imperative for sustainable water resource planning and development, notably in developing worlds such as Pakistan, where agriculture is a major livelihood. This research intends to assess the continuing changes in LU/LC and evaluate their probable repercussions on the hydrological regime of the Potohar Plateau. The maximum likelihood classification (MLC) algorithm for land use classification of the high-resolution satellite imageries, the Cellular-Automata Markov Chain Model (CA-MCM) for the projection of LU/LC maps, and the Soil and Water Assessment Tool (SWAT) in tandem with SWAT-CUP for hydrological modeling were employed in this research. The high-resolution climatic dataset (10 × 10 km) was used in SWAT. The LU/LC analysis revealed a continual propagation of agricultural and built-up lands at the detriment of forest and barren land during the last three decades, which is anticipated to continue in the future, too. Hydrological model calibrations and validations were performed on multi-basins, and the performance was evaluated using different statistical coefficients, e.g., the coefficient of determination (R²), Nash–Sutcliffe Efficiency (NSE), Kling–Gupta Efficiency (KGE), and Percent Bias (PBIAS). The results yielded that the model performed very well and demonstrated the model’s robustness in reproducing the flow regime. The water balance study revealed that the anticipated LU/LC changes are projected to decrease the mean annual surface runoff, water yield, and streamflow due to an increase in percolation, lateral flow, sub-surface flow, and evapotranspiration. More significant variations of the water balance components were observed at the sub-basin level, owing to the heterogeneous spatial distribution of LU/LC, than at the basin level. The outcome of this study will provide pragmatic details to legislative bodies to develop land and water management ameliorative strategies to harness hydrological changes sustainably. Full article

Slope farmland is prone to soil erosion, especially in sub/tropical regions. However, our understanding of near-surface hydrology characteristics and their controlled factors in red soil sloping farmland remains limited. Here, we conducted simulated rainfall experiments to assess the impact of rainfall pattern, straw mulching, and soil structure on near-surface hydrological processes of red soil sloping farmland of southern China. Results showed that: (1) short duration-high intensity rain caused greater surface runoff and sediment production than did long duration-low intensity rain, whereas the variation pattern of subsurface flow exhibited the opposite trend; (2) tillage behavior could weaken the surface runoff intensity and promote the development of subsurface flow; (3) straw mulching increased the water infiltration rate and associated subsurface flow production (increased by 1.33~12.71 times), and thus reduced the surface runoff production (reduced by 99.68~100%). These findings highlight the crucial roles of rainfall pattern and straw mulching in regulating the spatial distribution pattern of rainwater and suggest that straw mulching can effectively reduce soil erosion via accelerating water infiltration and subsurface flow form in slope farmland of soil erosion in southern China. Full article

It has long been recognised that the role of soils is critical to the understanding of the way catchments store and release water. This study aimed to gain an understanding of the hydropedological characteristics and flow dynamics of the soils of three mountain catchment areas. Digital soil maps of the hydropedological characteristics of the catchments were interpreted and a conceptual response of these watersheds to precipitation was formed. This conceptual response was then tested with the use of site-specific precipitation and streamflow data. Furthermore, piezometers were installed in soils classified as the interflow hydropedological soil group as well as the saturated responsive hydropedological soil group and water table depth data for the three catchments were analysed. Climatic data indicated that there is a lag time effect in the quantity of precipitation that falls in the catchment and the corresponding rise in streamflow value. This lag time effect coupled with data obtained from the piezometers show that the various hydropedological soil groups play a pivotal role in the flow dynamics. Of importance is the unique influence of different wetland systems on the streamflow dynamics of the catchments. The drying and wetting cycles of individual wetland systems influenced both the baseflow connectivity and the overland flow during wetter periods. They are the key focus in understanding the connectivity between the hydropedological flow paths and the contribution of soil water to the stream networks of the three catchments. Full article

Integrated assessment of the water environment has become widespread in many rivers, lakes, and reservoirs; however, aquatic organisms in freshwater are often overlooked in this process. Zooplankton, as primary consumers, are sensitive and responsive to changes in the water environment. Water and zooplankton samples were collected on-site at Shanxi Reservoir quarterly to determine 12 water environmental indicators and to quantify the abundance of zooplankton of Cladocera, Copepoda and Rotifera by using the ZooScan zooplankton image-scanning analysis system, combined with OLYMPUS BX51 using machine learning recognition classification. The aim was to explore the relationship between water environmental factors and zooplankton through their spatial and temporal heterogeneity. Through principal component analysis, redundancy analysis and cluster analysis, variations in the factors driving zooplankton population growth in different seasons could be identified. At the same time, different taxa of zooplankton can form clusters with related water environmental factors during the abundant water period in summer and the dry water period in winter. Based on long-term monitoring, zooplankton can be used as a comprehensive indicator for water environment and water ecological health evaluation, as well as providing scientific support for regional water resources deployment and management. Full article

Hydrological connectivity directly affects aquatic ecological processes, water environment and wetland ecological security, which is essential to the stability of arid ecosystems. However, the mechanism between hydrological connectivity and water-related environment has not been revealed completely. To address these issues, we use a landscape connectivity approach to assess the connectivity of water patches for analyzing the hydrological connectivity of the Bosten Lake Basin (BLB), as well as its response to human activities and climate change, based on the Joint Research Centre (JRC) global surface water dataset. It shows that the integral index of connectivity (IIC) of the BLB is low (ranging from 0 to 0.2) from 1990 to 2019, with an increasing interannual trend. The connectivity is higher in wet periods and in oases compared with dry periods and high-altitude mountain regions. Correlation and regression analyses indicate that hydrological connectivity has a strong correlation (r > 0.5, p ≤ 0.05) with water area and water level. The interannual and seasonal trends of eight hydrochemical indices in the Bosten Lake have been investigated to systematically elaborate the complex relationships between hydrological connectivity and water quality in the BLB. Results indicated that better hydrological connectivity can improve water quality, and the minimum of pollutants were observed in high hydrological connectivity period, covering approximately 75% of the high-water quality period. These findings could provide scientific support for the water management in the BLB. Full article

Controlled tile drainage (CTD) practices are a promising tool for improving water balance, water quality and increasing crop yield by raising shallow groundwater level and capillary rise due to drainage flow retardation. We tested the effect of CTD on growth and grain yield of spring barley, at a study site in central Bohemia using vegetation indices from unmanned aerial vehicle (UAV) imagery and Sentinel-2 satellite imagery. Tile drainage flow was slowed by fixed water level control structures that increased soil moisture in the surrounding area according to the terrain slope. Vegetation indices based on red-edge spectral bands in combination with near-infrared and red bands were selected, of which the Normalized Red Edge-Red Index (NRERI) showed the closest relationships with shoot biomass parameters (dry biomass, nitrogen concentration and uptake, nitrogen nutrition index) from point sampling at the tillering stage. The CTD sites showed significantly more biomass using NRERI compared to free tile drainage (FTD) sites. In contrast, in the period prior to the implementation of CTD practices, Sentinel-2 satellite imagery did not demonstrate higher biomass based on NRERI at CTD sites compared to FTD sites. The grain yields of spring barley as determined from the yield map also increased due to CTD (by 0.3 t/ha, i.e., by 4%). The positive impact of CTD on biomass development and grain yield of spring barley was confirmed by the increase in soil moisture at depths of 20, 40 and 60 cm compared to FTD. The largest increase in soil water content of 3.5 vol% due to CTD occurred at the depth of 40 cm, which also had a higher degree of saturation of available water capacity and the occurrence of crop water stress was delayed by 14 days compared to FTD. Full article

Nature-Based Solutions for Integrated Water Resources Management (NbS-IWRM) involve natural, or nature-mimicking, processes used to improve water availability in quantity and quality sustainably, reduce the risks of water-related disasters, enhance adaptation to climate change and increase both biodiversity and the social-ecological system’s resilience. United Nations and the European Commission promote their research as a cornerstone in the changeover to the Ecological Transition. In the Sierra Nevada range (Spain) and the Andean Cordillera, there is a paradigmatic and ancestral example of NbS-IWRM known as “careo channels” and “amunas”, respectively. They recharge slope aquifers in mountain areas and consist of an extensive network of channels that infiltrate the runoff water generated during the snow-thawing and rainy season into the upper parts of the slopes. The passage of water through the aquifers in the slope is used to regulate the water resources of the mountain areas and thus ensure the duration of water availability for the downstream local population and generate multiple ecosystem services. This form of water management is known as Water Sowing and Harvesting (WS&H). As shown in this work, it is a living example of a resilience and climate change adaptation tool that can be qualified as a nature-based solution. Full article

Streamflow in semiarid areas, especially in North China, was rapidly decreasing, which made it important to analyze the characteristics and influencing factors of streamflow. Using the hydro-meteorological data series of 1961–2017 in the upper Yongding River Basin (UYRB) (including the Yang River Basin (YRB) and Sanggan River Basin (SRB)), spatio-temporal variation characteristics of air temperature, precipitation, and potential evapotranspiration (E₀) were analyzed. The results showed that precipitation has no significant trend; the temperature showed a significant increase of 0.1–0.5 °C per decade; E₀ showed a significant decrease of approximately −2 mm/10yr (in 18 stations); the estimated rates of streamflow change were −7 and −8 mm/10yr for SRB and YRB. As for spatial distribution, the YRB presented a higher E₀ value than the SRB; the mountain areas had more precipitation than the plain areas. The change points of streamflow occurred in 1982 and 2003. Both the Budyko and the DMC methods were used to evaluate the impacts of climate change and human activities on the mean annual streamflow. In variation stage I (1983~2003), impacts of human activities account for 90.6% and 62.7% of the mean annual streamflow changes in YRB and SRB, respectively. In variation stage II (2004~2017), the percentages were 99.5% and 93.5%, respectively. It is also noted that the first change point in streamflow was indeed at the beginning of China’s land reform, when the farmers could manage their reallocated lands and, therefore, there was an increase in agricultural water consumption. The second change point coincided with “Capital Water Resources Planning”, including water conservation projects and irrigation district construction programs. In general, human activities were mainly responsible for the significant decline in the annual streamflow of UYRB. This paper will provide valuable results for water resources planning and give guidance on the construction of water conservation function areas and ecological environment support areas in the capital. Full article