Improve Water Resources Management Research Articles

A Review of Fluid Flow Applications and Hydraulic Performance of Sustainable Drip Irrigation to Improve Water Resource Management

Fluid flow applications to improve water resource management towards sustainable irrigation are one of the main targets of engineers nowadays, especially with global climate change. The performance assessment of the irrigation system is an important area of research to improve water resource management. Through drip irrigation systems, this review evaluated the application uniformity of water and nutrients to sustain agricultural production and protect the environment’s natural resources. To achieve these goals, the adequate use of nutrients and water must be emphasized by utilizing sufficient water and nutrient management approaches, including a drip irrigation system that supplies the inputs immediately to the crop’s root zone. The process operating pressure and the drip line length are the two most crucial aspects that affect the uniformity of the water and nutrient distribution in fields. Inconsistent or inadequate applications of fertilizers and water in the fields contribute to the incorrect supply of useful water and nutrients in the soil profile along the drip line length resulting in a significant decrease in crop yields and poor product quality. The main cause behind the operating pressures in a “micro-irrigation system” is the inadequate distribution of fertilizers and water in the fields. Therefore, the effects of such non-uniform distribution must be carefully quantified and studied to understand the reasons behind soil degradation and groundwater contamination, which occurs due to excess nutrient leaching from the crop’s root zone. Data on the distribution and movement of water and nutrients in the soil is essential for designing efficient fertilization systems. Drip irrigation can reduce water exposure and input costs, making agribusiness more resilient, profitable, and successful. This paper discusses the uniformity of the nutrients and water application for crops grown in various agro-climatic regions. In addition, an effort was made to compare the findings’ quality of various commonly used methods of water and nutrient application under different climatic conditions.

Research and innovation in agricultural water management for a water‐secure world

AbstractThere is increased awareness that the current food system is unsustainable and that transformative research, development and innovation in agricultural water management (AWM) are needed to transform water and food systems under climate change. We provide an overview of research efforts, challenges, opportunities and innovations to improve water resource management and sustainability, especially in the agricultural sector. We highlight how sustainable AWM is central to balancing the needs of a growing population and increasing food demand under increasing water insecurity and scarcity, with environmental and socio‐economic outcomes. Innovative technologies are being developed to optimize water use and productivity through sustainable irrigation technologies, irrigation modernization and smart water management. However, these innovations still need to fully address equity, inequality and social justice concerning access to water, infrastructure and the delayed technological advances in the global South. This requires adopting transdisciplinary approaches, as espoused by the water–energy–food (WEF) nexus, to better anticipate and balance trade‐offs, optimize synergies and mitigate risks of maladaptation. Through such transdisciplinary approaches, AWM innovations could better consider local socio‐economic, governance, institutional and technological constraints, thus allowing for more contextualized and relevant innovations that can be scaled.

Investigating the effectiveness of Landsat-8 OLI and Sentinel-2 MSI satellite data in monitoring the effects of drought on surface water resources in the Western Cape Province, South Africa

Drought frequency and magnitude are increasing, posing significant risks to surface water bodies, particularly in arid and semi-arid regions. Leveraging on moderate resolution satellite data, such as Landsat-8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI), offers unique opportunities for monitoring surface water availability and drought impacts. In this study, we assessed the extent to which Landsat-8 OLI and Sentinel-2 MSI satellite data can be used to characterise and monitor the impacts of drought on water resources in the Western Cape, South Africa. Multispectral indices including Normalised Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Normalised Difference Water Index (NDWI), Modified Normalised Difference Water Index (MNDWI), and the Land Surface Water Index (LSWI+5) were computed to determine the most suitable method for surface water detection and drought monitoring. Sentinel-2-derived NDVI emerged as the most suitable index for mapping surface waterbodies, demonstrating an overall accuracy of 77.27%. However, LSWI+5 exhibited limitations, misclassifying built-up and mountainous areas as surface waterbodies. SPI, VCI, and WRSI effectively identified drought periods and correlated well with climate data, revealing low rainfall and high evapotranspiration rates during the 2016–2018 drought period. These findings provide valuable insights into surface water variability and the impacts of drought on water resources. Overall, our study underscores the feasibility of utilizing moderate resolution datasets to assess drought impacts on surface water resources, enabling improved water resource management, drought detection, and preparedness efforts in resource limited environments.

Calibration of volumetric soil moisture using Landsat-8 and Sentinel-2 satellite imagery by Google Earth Engine

Water scarcity for agriculture is increasingly evident due to climatic alterations and inadequate management of this resource. Therefore, developing digital models that help improve water resource management to provide solutions to agronomic problems in northern Mexico is necessary. In this context, the objective of the present research is to calibrate the Optical Trapezoid (OPTRAM) and Thermal-Optical Trapezoid (TOTRAM) models to estimate the volumetric soil moisture at different depths through vegetation indices derived from Landsat-8 and Sentinel-2 satellite images using Google Earth Engine (GEE). Agricultural areas under gravity irrigation and rainfed runoff in the Comarca Lagunera, the lower part of the Hydrological Region No. 36 of the Nazas and Aguanaval rivers were selected for in-situ measurements. The OPTRAM and TOTRAM normalized moisture content (W) estimates were compared with in-situ volumetric soil moisture (Ɵ) data. Results indicate that the predictions of OPTRAM errors using Sentinel-2 images showed RMSE between 0.033 to 0.043 cm3 cm-3 and R2 between 0.66 to 0.75, whereas Landsat-8 errors showed RSME from 0.036 to from 0.036 to 0.057 cm3 cm-3 and R2 between 0.70 to 0.81. On the other hand, TOTRAM errors showed RMSE between 0.045 to 0.053 cm3 cm-3 and R2 between 0.62 to 0.85 through calibrations. This study made it possible to evaluate the most accurate combinations of the pixel distributions of each model and vegetation indices for the estimation of volumetric soil moisture within the different phenological stages of the crops.

A New Dialectical Model of Water Security under Climate Change

Although Integrated Water Resources Management (IWRM) is widely accepted as the state-of-the-art rational model for improving water governance, its evaluations under climate change at national and global scales indicate that progress made in water security and ecosystem preservation is slow. The paper identifies the relationship between Humans and Nature as the main reason for that and generates a novel social component to improve Water Resources Management (WRM) following three pillars: (1) A historical review over the past 20,000 years indicating that WRM depends on the interplay between Humans and Nature. This is in constant change over time, and depending on socio-economic and climate conditions, it oscillates between two opposites: conflict and cooperation. Three clusters have been identified, showing a different timeline pattern of dominance: (a) Nature dominating Humans (Naturalistic), (b) Nature–Humans in cooperation and competition (Dualistic), and (c) Humans dominating Nature (Anthropocentric). (2) Clarification of why a WRM model can improve water security through the Governance–Policy–Science Nexus. (3) Suggestion of a novel WRM model based on conflict identification (eristic component) and dialectical conflict resolution. Two types of conflicts have been distinguished: (a) Human vs. Human and (b) Human vs. Nature when the laws of nature are not respected. The dialectical tool operates by exchanging rational arguments to unify opposite objectives for harmonizing Humans with Natural laws. A case study of flood mitigation in Crete Island illustrates the Eristic–Dialectical methodology.

Use of water accounts based indicators for water management in India

AbstractIn India, water accounts on a river basin scale are not prepared regularly, mainly due to the unavailability of data on consumptive uses in various economic sectors at that scale. This research paper demonstrates an approach to prepare water accounts for the Mahanadi river basin in eastern India, which experiences climate‐induced hydrological extremes using the demographic, economic, hydrological, and geohydrological data available at different administrative and geographical scales. Further, selected water accounts derived indicators were computed to identify critical elements that need to be altered for improving water resources management at the river basin scale. The results show that the total inflow during the wet year exceeds 24%–26% in comparison to the normal and dry years. In turn, 23% and 24% of the inflow get drains to the sea in a dry and normal year, respectively, with agriculture accounting for the lion's share of the blue water consumed, about 57%–60% in all the years. The river has a huge dilution capacity, and, except for the biological oxygen demand in a dry year, the value of all other selected water quality parameters (nitrogen and electrical conductivity) is within the acceptable limits established by law. Reducing water consumption in irrigated crops during summer, controlling evaporation from the reservoirs, and considering nitrogen concentration and electrical conductivity in the existing approach to determine polluted river stretches in India are identified as crucial actions for improving water management in the basin. Further, assessment of water consumption and environmental flow requirement is identified as important decision factors to guide future water reallocation among riparian states.

Numerical modeling as a support tool for groundwater permits in the state of Bahia, Brazil

The western region of Bahia State is an important agricultural frontier in Brazil, generating a large increase in requests for groundwater usage in the last decades, mainly through large capacity water wells tapping the Urucuia Aquifer System (UAS). This study aims to develop a groundwater numerical model using the Visual MODFLOW software and the additional packages MODPATH and ZONEBUDGET to evaluate the effects of intensive groundwater pumping in eight possible scenarios of two areas (Central and Eastern) in the Alto Grande - São Desidério rivers sub-basin. Drawdown ranging from 4 to 20 m was observed in the different areas and scenarios. The analysis of the local flow path lines showed that the wells have an area of influence that captures part of the groundwater flow. The water balance indicated that the total volume pumped in the sub-basin did not reach 10% of the recharge in any scenario, considering the entire model domain. The high concentration of irrigation pumping wells in restricted areas resulted in a significant impact on the aquifer, reaching up to 84.6% of the local recharge, a value that is far above what is considered sustainable for the region. Results show that the eastern area is more susceptible to drawdown and changes in flow path lines by pumping. The applied method has proven to be useful to predict the effects of water abstraction on the aquifer before the implementation of projects, improving water resources management. Long-range forecasts and taking into account possible climate changes are also some of the advantages of the method, though it depends on reliable field hydrological and climate data.

Optimizing Solution in Decision Supporting System for River Basin Management Consisting of a Reservoir System

Decision support systems tackle problems and require systematic planning. They consider physical data, hydrological data, and sediment levels to achieve efficiency and adaptability in various situations. Therefore, this research aims to identify alternative engineering choices for the management of a river basin with a single reservoir system. Optimization techniques, including marine predator algorithm (MPA), genetic algorithm (GA), genetic programming (GP), tabu search (TS), and flower pollination algorithm (FPA), were applied to find the optimal reservoir rule curves using a reservoir simulation model. The study focused on the Ubolratana Reservoir in Thailand’s Khon Kaen Province, considering historic inflow data, water demand, hydrologic and physical data, and sedimentation volume. Four scenarios were considered: normal water scarcity, high water scarcity, normal excess water, and high excess water. The optimal rule curves derived from the reservoir simulation model, incorporating sedimentation and hedging rule (HR) criteria, were found to be the best engineering choices. In the normal and high water scarcity scenarios, they minimized the average water shortage to 95.558 MCM/year, with the lowest maximum water shortage 693.000 MCM/year. Similarly, in the normal and high excess water scenarios, the optimal rule curves minimized the average excess water, resulting in a minimum overflow of 1087.810 MCM/year and the lowest maximum overflow 4105.660 MCM/year. These findings highlight the effectiveness of integrating optimization techniques and a reservoir simulation model to obtain the optimal rule curves. By considering sedimentation and incorporating HR criteria, the selected engineering alternatives demonstrated their ability to minimize water shortage and excess water. This contributes to improved water resource management and decision-making in situations of scarcity and excess.

Potential Effects of Climate Change on Agricultural Water Resources in Riyadh Region, Saudi Arabia

The water supply in Saudi Arabia is already depleted. Climate change will exacerbate the demand for these resources. This paper examines how climate change affects the water demands of Saudi Arabia’s most important food crops: wheat, clover, vegetables, and dates. To reduce the adverse climate change impacts on these crops’ productivity, as well as their irrigation water requirements (IWR), a number of adaptation techniques were investigated. The study was carried out for the Ar Riyadh region, Saudi Arabia, with a cultivated area of 179,730 ha. In this study, five climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for two Shared Socio-economic Pathways (SSPs), SSP2-4.5 and SSP5-8.5, were used to forecast and investigate the potential impacts of climate change on agricultural water resources in the Al-Riyadh Region of Saudi Arabia. To simulate IWRs under the present and projected climate change scenarios, CROPWAT8.0 was used. The results showed that the maximum increase ratio in 2100 under SSP2-4.5 and SSP5-8.5, respectively, will be 4.46% and 12.11% higher than in the current case (2020). The results showed that the projected maximum temperatures in 2100 will be increased by 4.46% and 12.11%, respectively, under SSP2-4.5 and SSP5-8.5, compared to the current case (2020), supporting past research on the Arabian Peninsula that revealed that both short- and long-term temperature increases are anticipated to be considerable. Under SSP2-4.5 and SSP5-8.5, the projected ETo was found to be increased by 2.18% and 6.35% in 2100, respectively. Given that evapotranspiration closely mirrors the temperature behavior in the study region from June to August, our data suggest that crop and irrigation demand may increase in the mid to long term. The findings indicate that Riyadh, Saudi Arabia’s capital and commercial hub, will require more water to irrigate agricultural land because of the expanding ETo trend. Under SSP2-4.5 and SSP5-8.5, the projected growth irrigation water requirement (GIWR) will be increased by 3.1% and 6.7% in 2100, respectively. Under SSP5-8.5, crop areas of wheat, clover, dates, maize, citrus, tomato, potato, and other vegetables in Ar Riyadh will decrease by 6.56%, 7.17%, 5.90%, 6.43%, 5.47%, 6.99%, 5.21%, and 5.5%, respectively, in 2100. Conversely, under SSP2-4.5, the crop areas will decrease by 3.10%, 3.67%, 2.35%, 3.83%, 2.32%, 4.18%, 1.72%, and 2.38% in 2100, respectively. This research could aid in clarifying the adverse climate change impacts on GIWR in Ar Riyad, as well as improving water resource management planning.

A Spatiotemporal Characterization of Water Resource Conditions and Demands as Influenced by the Hydrogeologic Framework of the Willcox Groundwater Basin, Southeastern Arizona, USA

In the Willcox Groundwater Basin (WGB), increasing rates of agricultural groundwater withdrawal have led to significant regional groundwater level decline, threatening the basin’s long-term water resource security. Updated characterization of the basin’s water resource conditions and agricultural water demand is critically important for informing groundwater resource management efforts. We developed the hydrogeologic framework of the WGB and linked groundwater level data with land cover classification data to provide a spatiotemporal assessment of water resource conditions and agricultural development in the WGB. A correlation analysis evaluated the degree of association between the basin’s mean annual depth-to-groundwater and agricultural land cover extent. Results of this study indicate that between 2008 and 2021, agricultural land cover in the WGB increased by 29%. The average rate of groundwater level change in the basin’s measured wells was calculated at −13.8 m between 2006 and 2021. We found a strong correlation between the basin’s mean annual measured depth-to-groundwater and the annual agricultural land cover extent, further reinforcing the understanding of agricultural water use in the basin as a principal driver of groundwater level decline. The methodological framework employed proved a simple and effective way to assess groundwater resources as influenced by geology and land use. The outcomes of this study provide critical information toward improved water resources management by providing an integrated understanding of local hydrogeology, groundwater level variability, and changes in agricultural land cover in arid inland basins such as those found in Arizona, USA.

Investigating technology opportunities toward improved Colorado water monitoring: Insights from key informant interviews and stakeholder surveys

Prolonged drought conditions in the western United States have prompted an interest in improved water resource management. In the past two decades, Colorado has experienced decreasing precipitation and increasing temperatures, causing persistent meteorological and agricultural drought. In times of limited water resources, more precise water accounting and water conservation is often required. We investigated technological and monitoring gaps in Colorado water resource management using a sequential explanatory mix-method approach, including key informant interviews and a survey study. Key informant interviews gave insight into water monitoring concerns and informed a state-wide survey on monitoring gaps and water resource challenges. Qualitative and quantitative analysis of interview transcripts and survey results found that the most critical monitoring gaps for water managers in Colorado are: (1) streamflow forecasting and improved understanding of Colorado snowpack, (2) expanding groundwater and soil moisture monitoring, (3) wildfire impacts on watershed health, (4) improved accuracy and reliability of data sources, and (5) addressing these gaps while maintaining an emphasis on community collaboration. Challenges for Colorado managers varied by stakeholder basin and sector but included changes in hydrologic systems due to the effects of extended drought, climate change, and related anthropogenic impacts and negative impacts of intensifying wildfire seasons on water quality and watershed health.

Hydrogeology of Karst and Metapelitic Domains of the Semi-Arid Vieira River Watershed (Brazil)—A Contribution to Groundwater Resource Management

Water scarcity is a problem in Brazil’s northern semi-arid domain. Montes Claros is the most populated Minas Gerais city in this context, and its socio-economic problems are related to water consumption and management. Aiming to help assess these problems, this study presents a new hydrogeological characterization. The 3D geological model was developed using drilling data from 125 public wells, field campaigns and satellite images for hydrogeological interpretation. The area has two main different aquifer systems underlying the Vieira River Watershed. The first is a karstic fissured aquifer, located in the Lagoa do Jacaré limestone Formation. The second is fissured aquifer systems in metapelites from the Serra da Santa Helena and Serra da Saudade Formations, which are characterized by low hydraulic transmissivity and locally higher specific capacity zones related to their structural features or carbonate intercalations. Monitoring data from new manual and automatic methods carried out in 16 selected points highlight that variations are related to (1) hydrogeological domains, (2) oscillations related to interference from neighboring wells, and (3) seasonal variation and irregular pluviometry in the region. This is important information that can help update our hydrogeological knowledge, provide information on surface and groundwater flow dynamics, and improve water resource management, with the aim of ensuring sustainability in exploitation.

Analysis of spatial and temporal trend of hydro-climatic parameters in the Kilombero River Catchment, Tanzania

Inadequate knowledge on actual water availability, have raised social-economic conflicts that necessitate proper water management. This requires a better understanding of spatial–temporal trends of hydro-climatic variables as the main contributor to available water for use by sectors of economy. The study has analysed the trend of hydro-climatic variables viz. precipitation, temperature, evapotranspiration and river discharge. One downstream river gauge station was used for discharge data whereas a total of 9 daily observed and 29 grided satellite stations were used for climate data. Climate Hazards Group InfraRed Precipitation was used for precipitation data and Observational-Reanalysis Hybrid was used for Temperature data. Mann–Kendall Statistical test, Sen’s slope estimator and ArcMap Inverse Distance Weighted Interpolation functionality were employed for temporal, magnitude and spatial trend analysis respectively. Results confirmed that, spatially, there are three main climatic zones in the study area viz. Udzungwa escarpment, Kilombero valley and Mahenge escarpment. On temporal analysis, with exception of the declining potential evapotranspiration trend, all other variables are on increase. This is with catchment rates of 2.08 mm/year, 0.05 °C/year, 0.02 °C/year, 498.6 m3/s/year and − 2.27 mm/year for precipitation, Tmax, Tmin, river discharge and PET respectively. Furthermore, rainfalls start late by a month (November) while temperatures picks earlier by September and October for Tmax and Tmin respectively. Water availability matches farming season. However, it is recommended to improve water resources management practices to limit flow impairment as expansions in sectors of economy are expected. Furthermore, landuse change analysis is recommended to ascertain actual trend and hence future water uptake.

IMPACT OF AGRICULTURAL TRAINING COURSES ON APPLYING MODERN AND EFFICIENT IRRIGATION METHODS AMONG FARMERS IN TABRIZ, IRAN (TREATMENT EFFECT APPROACH)

Purpose: Many experts believe that the lack of an efficient water management system in agriculture has made it essential to redesign new irrigation models adopted in many successful countries across the world. Improving water productivity in the agriculture sector is undoubtedly one of the crucial measures taken to improve water resource management. Water productivity in Iran's agriculture is about one-fifth of the global standard. Many assume that accurate training courses for farmers or granting production facilities and loans for agriculturists are beneficial steps to use efficient and effective irrigation methods and a subsequent considerable saving in water consumption.
 Design/methodology/approach: This study aims to apply the Treatment Effect Approach to examine the impact of academic or promotional training courses for irrigation efficiency on the application of modern and efficient irrigation methods, by farmers. To do this, 132 trained farmers were assigned to the treatment or test groups, and 212 untrained farmers in Tabriz were assigned to the control group in the crop year 2020. 
 Findings: Results indicated a positive and significant impact of agriculture education and training courses on the probability of using efficient irrigation techniques. In other words, agriculture knowledge increases the probability of using modern irrigation methods up to 344.25. 
 Originality: It is suggested that agricultural policies must grant loans and facilities to agriculturists or those farmers who have received purposeful training courses about the application of efficient irrigation methods.

Improving global hydrological simulations through bias-correction and multi-model blending

There is an immediate need to develop accurate and reliable global hydrological forecasts in light of the future vulnerability to hydrological hazards and water scarcity under a changing climate. As a part of the World Meteorological Organization’s (WMO) Global Hydrological Status and Outlook System (HydroSOS) initiative, we investigated different approaches to blending multi-model simulations for developing holistic operational global forecasts. The ULYSSES (mULti-model hYdrological SeaSonal prEdictionS system) dataset, to be published as “Global seasonal forecasts and reforecasts of river discharge and related hydrological variables ensemble from four state-of-the-art land surface and hydrological models” is used in this study. The first step for improving these forecasts is to investigate ways to improve the model simulations, as global models are not calibrated for local conditions. The analysis was performed over 119 different catchments worldwide for the baseline period of 1981–2019 for three variables: evapotranspiration, surface soil moisture and streamflow. This study evaluated blending approaches with a performance metric based (weighted) averaging of the multi-model simulations, using the catchment’s Kling-Gupta Efficiency (KGE) for the variable to define the weight. Hydrological model simulations were also bias-corrected to improve the multi-model blending output. Weighted blending in conjunction with bias-correction provided the best improvement in performance for the catchments investigated. Applying modelled weights during blending original simulations improved performance over ungauged catchments. The results indicate that there is potential to successfully and easily implement the bias-corrected weighted blending approach to improve operational forecasts globally. This work can be used to improve water resources management and hydrological hazard mitigation, especially in data-sparse regions.

New Software for the Techno–Economic Analysis of Small Hydro Power Plants

Project SMART (Strategies to Promote Small-Scale Hydro Electricity Production in Europe) from the Intelligent Energy Europe (IEE) program, in which 7 institutions from 5 European states participate, pointed to the important barriers for the expansion of small hydro power plants (SHP) in Europe. One of the main barriers is the lack of suitable methodology and software able to create a clear view of the SHP potential in the given territory, as well as a complete techno-economic analysis for certain locations. Worldwide, there are a certain number of software for this purpose, and will be presented in this paper. However, in practical application for concrete cases, they show certain disadvantages. For example, one software is not able to take into account all the specifics of watercourses and plants; another does not have the option of selecting all types of turbines; in others, the calculation models are based on a limited number of equations that do not describe all possible cases; in some, economic analysis is oversimplified, etc. The aim of this paper is to develop software that is more comprehensive than any existing software. A new software for the techno-economic analysis of SHP is developed using Python and will be presented in this paper. The software is very useful for experts in the field of SHP, but also much wider, for decision-makers, potential investors, and stakeholders, especially in developing countries. It will improve water resources management, disseminate opportunities to investors, and increase the interest of stakeholders to invest in SHP, resulting in their wider use. The software is tested on location for SHP in the Republic of Croatia by comparison with the results obtained by the usual classical calculation. The agreement of the results is satisfactory.

Environmental controls on transpiration of Schima superba trees with different tree sizes under ten years’ climate fluctuations in south subtropics, China

Transpiration is an important component of the hydrological cycle for forest ecosystems. Long-term studies on how climate fluctuations influence canopy transpiration, as well as regulation mechanisms, are still lacking in southern subtropics. Based on a ten-year sap flow monitoring, we analyzed the long-term patterns of tree water use and environmental regulation of transpiration for a Schima superba forest under climate fluctuations. Results showed that the sap flux density (JS) and whole-tree transpiration (Et) in wet seasons were higher than those in dry seasons. Stand transpiration (Eg) upscaled from JS varied significantly among the experimental years and 11.9–33.6% of annual precipitation were transpired by the canopy. Extreme meteorological events increased transpiration anomalies during the decade. Large trees took up the most proportion of stand transpiration and exhibited greater sensitivities to environmental factors than medium and small trees. Evaporative demands had a higher effect on whole tree water use (Qd) than water supply due to adequate precipitation in this area. The variation partitioning analysis indicated that Qd was mainly influenced by energy factor (net radiation and sunshine duration), while the effect of precipitation on Qd was the lowest among all environmental factors. Furthermore, the shared effects of vapor pressure deficit (VPD) and energy factor accounted for the biggest portion of the variance of Qd. These results revealed the influence of environmental factors on forest transpiration in subtropics, and provided valuable implications for predicting the hydrological dynamics under future global climate scenarios, thus improving water resources management in catchments.

Development of Multi-Inflow Prediction Ensemble Model Based on Auto-Sklearn Using Combined Approach: Case Study of Soyang River Dam

Accurate prediction of dam inflows is essential for effective water resource management and dam operation. In this study, we developed a multi-inflow prediction ensemble (MPE) model for dam inflow prediction using auto-sklearn (AS). The MPE model is designed to combine ensemble models for high and low inflow prediction and improve dam inflow prediction accuracy. We investigated the impact of datasets assigned to flow regimes on the ensemble composition and compared the performance of the MPE model to an AS-based ensemble model developed using a conventional approach. Our findings showed that the MPE model outperformed the conventional model in predicting dam inflows during flood and nonflood periods, reducing the root mean square error (RMSE) and mean absolute error (MAE) by 22.1% and 24.9% for low inflows, and increasing the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) by 21.9% and 35.8%, respectively. These results suggest that the MPE model has the potential to improve water resource management and dam operation, benefiting both the environment and society. Overall, the methodology of this study is expected to contribute to the development of a robust ensemble model for dam inflow prediction in regions with high climate variability.

Spatial–temporal variations in vegetation with changing water stress in the Kongqi River basin, China

AbstractIdentifying dominant water stress on vegetation growth over the arid basins is essential to better understand ecosystems and water interactions, which are fundamental in managing regional water resources. The Kongqi River basin is an ecologically sensitive area with limited water resources in the northern part of Tarim Basin in northwest China. How is the spatial distribution of vegetation controlled by natural conditions and anthropogenic regulation of water resources is a concern for ecology system protection. This study explores the spatio–temporal variations in the remote‐sensing vegetation index across the basin and identifies water stress forces with the Mann–Kendall trend test and linear regression analysis. Results show that the controls of vegetation change are different among geomorphological units over the past 20 years. In the northern mountains, the increasing vegetation trend mainly responds to climate change, particularly to increased precipitation. In contrast, in the plain area, the vegetation change is controlled by changes in hydrologic and anthropogenic water stresses. A significant rise in surface water and groundwater utilization counteracts the negative effect of the increasing hydrologic water stress in the upstream oasis. However, the increasing anthropogenic water stress contributed to more than 50% of vegetation decay in the downstream area during 2004–2015. The ecological water conveyance beginning in 2016 has promoted vegetation restoration, but the effect decreased with distance to the upstream area and showed a delay in response. This study provides evidence for ecological consequence of anthropogenic water stress that is beneficial to improve water resources management and ecosystem restoration.

Using the Global Navigation Satellite System and Precipitation Data to Establish the Propagation Characteristics of Meteorological and Hydrological Drought in Yunnan, China

AbstractAnalyzing the spatiotemporal characteristics and evolution of meteorological and hydrological droughts can reproduce the process of drought propagation, which helps reduce the impact of droughts and improve water resources management. While emerging studies have attempted to build drought severity index based on the cutting‐edge space geodetic observations, few have focused the propagation characteristics of meteorological to hydrological drought using geodetic data. In this paper, using global navigation satellite systems (GNSS) observations together with precipitation data, we systematically investigated drought propagation in the Yunnan province, Southwest China. We first identified seven meteorological and seven hydrological droughts in Yunnan from January 2011 to May 2021, and the meteorological drought was mainly concentrated in northern Yunnan lasting for 1–11 months. By contrast, hydrological droughts were more severe and larger than meteorological droughts, lasting for 2–16 months. The drought propagation time was 2–7 months, short in the southwest but long in the northeast. Water vapor, precipitation, and water storage demonstrated a spatiotemporal pattern of uneven distribution, with the red river fault (RRF) as the boundary, and their phase difference also presented notable regional differences, indicating that the RRF not only influences spatial variation of water resources but also affects drought propagation.