Water Resources Management Model Research Articles

Rainfall-runoff Modelling Using MIKE11 NAM Model for Ravishankar Sagar Catchment, Chhattisgarh, India

Estimating rainfall-runoff within a catchment is inherently intricate and crucial for water resource planning via hydrological evaluations. The study focuses on utilizing the MIKE 11 NAM model to simulate rainfall-runoff dynamics within the Ravishankar Sagar Reservoir catchment in the Chhattisgarh state. In order to ensure accurate estimation, data on stream flows from 2004 to 2015 was used for calibration, and from 2016 to 2020 was used for validation. The MIKE 11 NAM model accurately predicted daily runoff and adequately reproduced the hydrological response of the Ravishankar Sagar watershed to rainfall. The calibrated model outputs were good to employ in the water resources management model, specifically for MIKE BASIN. During calibration, the optimal values of the nine NAM model parameters were determined and subsequently employed in the simulation. The reliability of the MIKE 11 NAM model was assessed for the study area using the Coefficient of Determination (R2) and the Nash–Sutcliffe Efficiency Index (EI). The sensitivity analysis helped to determine the most important model parameters. R2 values of 0.730 and 0.704 were obtained from the model's calibration and validation, respectively. With an Efficiency Index of 81%, the model demonstrated its efficiency and ability to forecast runoff for Ravishankar Sagar Reservoir over an extended period. This study helps to manage the water resource and to improve the reservoir operation policy for the reservoir.

Community participation and effective water management: A study on water user organizations (WUOs) in Thailand

This study examines the factors enhancing the effectiveness of Water User Organizations (WUOs) in Thailand, spotlighting the integration of geo-informatics and community involvement in water management. Employing a community-based participatory research approach, we assessed the impact of advanced technological tools and increased community engagement on WUOs' operations and sustainability. Our methodology included surveys, interviews, and an analysis of water management practices before and after geo-informatics implementation. Findings reveal a significant increase in community participation and an improvement in water management knowledge. The use of geo-informatics led to notable advancements in water allocation efficiency and conflict resolution, directly contributing to the financial sustainability of WUOs. Specifically, the application of geo-informatics facilitated more accurate and timely water resource allocation, evidenced by enhanced community engagement metrics and the resolution of longstanding conflicts. These results underscore the value of combining geo-informatics with community-driven approaches to water management, offering valuable insights for policymakers and practitioners. The study advocates for policies that support the adoption of technological innovations and promote community-centric governance, providing a scalable model for sustainable water resource management. This approach not only improves the functionality and sustainability of WUOs but also sets a precedent for holistic water governance practices globally.

Incipient Salinization: A Case Study of the Spring of Asclepieion in Lentas (Ancient Lebena), Crete

Sanctuaries devoted to Asclepius were established and operated for almost a thousand years in various Greek and Roman cities throughout the Mediterranean region. The Asclepieion sanctuary in Lentas (formerly known as Ancient Lebena) in Crete was famous for receiving water from a sacred spring. In Ancient Lebena, Levinaion was a famous centre for hydrotherapy, physiotherapy, and a psychiatric hospital. In the present paper, we aim to assess the hydrochemical status of this sacred spring that holds a prominent position in archaeological and historical studies. The main objectives of this study are: Initially, to present supervisory evidence (archaeological, geological, hydrochemical) of an area that was a water resource management model for many centuries, carrying out therapeutic work. The second objective is to present and compare hydrochemical data in the last century, i.e., from 1915 to 2021. The third objective is to highlight and warn of an incipient saltwater intrusion in the area along the Lentas coast. The fourth objective is to propose an alternative and sustainable form of water resources management in the region that requires the study and rational utilization of the sporadic small water springs in the region. Our study focuses on a basic hydrochemical analysis of spring and borehole water in the remains of Levinaion in the Lentas region, and their comparison with sparse historical data of the sacred spring water, aiming to interpret the impact of the changes in the spring water resources that occurred in recent decades due to urban modernization. Our results highlight (i) visible fluctuations in chemical composition of borehole water samples; (ii) a neutral to alkaline pH in borehole waters and an alkaline pH in spring waters; (iii) undetectable arsenic in Lentas borehole water, unlike historical data of Lentas spring water; (iv) low values of dissolved radon in Lentas borehole water and the spring water of Kefalovrysa; and (v) a timeless constant and hypothermic nature of the water of both the sacred spring and borehole of Lentas, and also of the Kefalovrysa spring. The recorded historical data, i.e., from 1915 to 1957, due to the absence of substantial anthropogenic activity in the area, can be used as reference values (natural background levels, NBLs) for the Lentas area. Our findings emerge with the need to bring again the flowing spring water of the sacred spring of Lentas in its original form through sustainable management and re-discover its beneficial therapeutical effects.

Identification of hydrologically homogenous watersheds and climate-vegetation dynamics in the Blue Nile Basin of Ethiopia

Abstract Identification of hydrologically homogenous watersheds in the Upper Blue Nile Basin of Ethiopia is challenging due to the large number of watersheds and the lack of consistent and reliable data. Traditional methods, such as expert-based classification, are time-consuming, subjective, and often not reproducible. Therefore, this study aims to identify homogenous gauged watersheds using hydrometeorological and remote sensing data. In this study 76 watersheds were delineated from a 30-m digital elevation model (SRTM-DEM). Twelve watershed characteristics were selected to aid the classification process. Three homogenous climate regions were identified using rainfall data from 42 stations, and for each homogeneous climate region, gauged watersheds were identified. Principal component analysis (PCA) and K-means clustering were used for classification. The PCA reduced 12 watershed characteristics into three principal components using a threshold of 80% accounted variance and eigenvalues greater than one. K-means clustering classified the 76 watersheds into nine homogenous clusters. In the classified regions, vegetation dynamics within three decades have also been analyzed. This helped identify trends in vegetation cover and its spatial and temporal dynamics. The results of the investigation will potentially be used for runoff prediction of ungauged watersheds and for water resource management models in the future.

Integrated approach to water resource management in Mashhad Plain, Iran: actor analysis, cognitive mapping, and roadmap development.

Iran's Mashhad Plain faces a severe water crisis due to the excessive exploitation of groundwater, leading to the depletion of its aquifer. While water demand management is recognized as a superior solution compared to supply projects, its implementation presents notable challenges. This study addresses the urgent necessity to curtail water demand in the Mashhad Plain by alleviating conflicts among various stakeholders, including water resource managers and consumers. Initially, the research identifies key water resource actors who collaborate in devising a comprehensive roadmap and conceptual model for efficient water resource management. An analysis uncovers significant conflicts among actors, representing approximately 6% of identified issues, with minor conflicts in 30% of cases. Encouragingly, stakeholders demonstrate potential for consensus on the remaining conflict items, with specific actors emerging as pivotal in conflict resolution. Efficient water resource management in regions facing scarcity, diverse interests, and sustainability challenges demands a multifaceted strategy. Future endeavors involve developing a dynamic system model to simulate policy impacts and strengthen conflict resolution efforts. This research introduces a roadmap-driven approach aimed at resolving conflicts and implementing water demand management in the Mashhad Plain. It emphasizes the critical need to address water scarcity challenges while effectively mitigating conflicts among water resource stakeholders.

An integrated water resources management model considering carbon source and sink under uncertainty: A case study of agricultural water-dominated basin

The global drive for carbon neutrality promotion through integrated water resource management (IWRM) in the face of burgeoning water demand is of great importance. This study developed an interval fuzzy-credibility chance-constrained multi-objective programming (IFCMP) model for water resources-carbon system (WCS) planning, which not only accounts for multiple uncertainties within system parameters, such as interval, fuzzy, and stochastic, but also effectively balances the conflicting objectives of water scarcity, benefits, emissions, and carbon sinks. The IFCMP-WCS model was applied to an agricultural water-dominated zone in the Tarim River Basin, China. Multiple water-allocation scenarios were examined, encompassing five prefecture-level cities, five departments, and three planning years. The results indicated that: (1) the water deficit was increasing over time, limited by water supply capacity, reaching 0–3.49 × 109 m3 in 2035; (2) as water allocation rises, system benefits and pollutant emissions increase, with the agricultural sector contributing the most economic benefits and pollutant emission; (3) the Tarim River Basin is an important carbon sink area, with the net carbon sink increasing from 8781.7–10,771.1 × 103 to 8851.1–10,937.9 × 103 tonnes during the planning horizon; (4) compared to single-objective models, the IFCMP-WCS model can offer more applicable water resource management options. These findings provide useful information for decision-making regarding IWRM and enhancing the net carbon sink in the Tarim River Basin.

Dynamic probabilistic analytical modeling for estimating rainfall–runoff transformation rates in drylands

Abstract Precipitation-runoff changes used in the development of precipitation-runoff models depict general runoff mechanisms in physical precipitation-runoff processes. For this purpose, it must be able to adequately express the characteristics of the physical system. Similar to other water resources management models, analytical-probabilistic models may be developed with different levels of complexity according to different types of rainfall–runoff developments. In this research, a log-normal probabilistic model was used to estimate the return period of rainfall and Soil and Water Assessment Tool (SWAT) software was used to convert rainfall values into discharge and runoff height in agricultural lands. The slope and the level of plant shade cover were considered the two basic factors in the estimation of the subsurface flow used in agriculture. Slopes of less than 0.015 and land cover level of more than 70% of extreme points were obtained to ensure subsurface water sources and prevent erosion.

A multi-decadal national scale assessment of reference evapotranspiration methods in continental and temperate climate zones of South Korea

Agricultural water resource management and hydrological models rely heavily on reference evapotranspiration (ET0), which is typically calculated using FAO-56 Penman-Monteith (FPM) method. However, FPM is restricted in its applicability by comprehensive meteorological data requirements, motivating identification of alternative approaches for estimating ET0 that require fewer meteorological inputs. This study compares 30 empirical models for estimating ET0 over 50 years (1972–2021; at daily scale) at 30 stations spanning continental (22 stations) and temperate (8 stations) climate zones across South Korea. Candidate empirical models were categorized based on their composition (temperature-based (n = 5), radiation-based (n = 15), temperature-radiation-based (n = 2), and mass-transfer-based (n = 8)) and complexity with models requiring between one and four meteorological variables. Model performance did not vary significantly across mapped climate zones (i.e., continental vs. temperate), and more complex models (i.e., those requiring 4 meteorological inputs) did not necessarily yield better prediction. Temperature-radiation-based models were consistently effective, whereas the models based on mass-transfer were always poor. Given the lack of long-term spatially extensive meteorological data in most developing countries in continental and temperate climate zones, this study establishes best practices for estimating ET0 using empirical models, which will aid water resources management decision-making in regions with limited meteorological data.

Assessment of L-band InSAR snow estimation techniques over a shallow, heterogeneous prairie snowpack

Snow water equivalent (SWE) is a critical input for weather, climate, and water resource management models at local to global scales. Despite its importance, global SWE measurements that are accurate, consistent, and at sufficiently high spatiotemporal resolutions are not currently available. L-band interferometric synthetic aperture radar (InSAR) techniques have been used to measure SWE at local to regional scales, and two upcoming L-band SAR satellite missions have renewed interest in these techniques to provide regular SWE measurements at the global scale. However, previous research demonstrating the capabilities of L-band InSAR-SWE measurement has been limited to mountain or tundra snowpack regimes. Here we examine the feasibility of applying the same techniques over a prairie snowpack, which are typically characterized by shallow snow depths (mean snow depth of 0.22 m in this study), exposed agricultural vegetation, and high spatial variability over short distances. Our study area in central Montana, USA (47.060, -109.951) was a validation site for NASA SnowEx 2021, as part of the UAVSAR snow timeseries. Airborne L-band SAR imagery was acquired by the UAVSAR platform while concurrent snow measurements were collected using uncrewed aerial vehicle (UAV)-based LiDAR, UAV-based photogrammetry, and ground-based manual techniques. This validation dataset enables an investigation of the effects of sub-pixel snow cover heterogeneity and exposed agricultural vegetation stubble on SAR data and the resulting SWE estimations. Results based on repeated application of the Kolmogorov–Smirnov test show that UAVSAR VV phase change is sensitive to differences in snow cover but relatively unaffected by differences in agricultural stubble height. However, we did not find similarly definitive results when we used the same phase change data to estimate SWE. Although broad spatial patterns were similar in both LiDAR-derived and InSAR-derived SWE estimates, considerable differences in the two estimates were apparent in areas with large sub-pixel snow depth variability. Our results indicate that additional work is necessary to derive accurate SWE estimates in prairie environments. Regular measurements from L-band SAR satellites will provide an excellent opportunity to refine InSAR-based snow estimation techniques over shallow, heterogeneous snowpacks.

Impact of Sedimentation and Bathymetry of Selected Small Reservoirs on the Priority Water-Linked Sectors in the Zambezi River Basin

This study was conducted within the Zambezi River Basin to ascertain the bathymetry and sedimentation of selected reservoirs, evaluate their seasonal hydrological regimes, pinpoint the causes of reservoir siltation, and determine how the bathymetry and siltation impacted water-related industries and policy choices. Hydrological field measurements using a hydrographic survey boat, document studies, and interviews were used to collect the data. The 3D spatial analyst tools in ArcGIS 10.3 and hypsometric curves were used to analyze bathymetric data. Thematic analysis was used to analyze qualitative interview data. Findings indicated that sedimentation was a problematic phenomenon spatial-temporally and, it triggered a significant decrease in the storage capacities of the reservoirs. The study noted that catchments with small reservoirs were vulnerable to severe water stress, particularly from July through the beginning of the next rainy season in December. Over 90% of the local population and water-related industries were facing substantial risks of economic water shortages and may continue to face more water challenges amidst escalating climatic changes. The problem could be addressed by coping mechanisms such as alternative livelihoods, water harvesting, and water shedding. This study proposes an Integrated Water Resources Management Framework, which may help incorporate water education to bring about behavioural change against drivers of sedimentation. The proposed sediment and water resources management model serves as a multidisciplinary and transdisciplinary tool that could be used to address siltation concerns. This work has also shown the significance of bathymetric surveys of small reservoirs as a basis for policy context and regulations on managing water resources.

Multicriteria land cover design via coupled hydrologic and multi-sector water management models

We investigate how hydrologic-land feedbacks and a hydrologic-water management linkage impact land cover arrangements optimized within a multiobjective land cover design framework. The framework integrates a spatially-distributed and physically-based hydrologic model, for simulating surface and subsurface flow and land processes, with a network-based multi-sector water resources management and allocation model. Both models used (Parflow, Pywr) are open-source. The framework is applied to a hillslope problem to identify land cover patterns that optimize trade-offs between water, food, energy and environment objectives. Results show trade-offs depend on land cover composition and the spatial arrangement of land covers within the catchment. Total runoff volume and peak flow of runoff was found to change 3 and 2-fold, respectively, between optimized solutions as land cover composition and spatial patterns were altered to satisfy different combinations of objectives. At the same time, up to a 15% reduction in the total runoff volume and an 8% reduction in the peak flow of runoff were observed within optimized land cover patterns having equal composition but different spatial arrangements. This emphasizes the impact on hydrologic behavior of the spatial location of land covers within a catchment. The emergence of patterns in land cover distribution for different trade-offs between objectives is driven by feedback mechanisms between subsurface hydrology and land processes, which are implicitly linked to the properties of each land cover and the interactions between neighboring land covers through lateral groundwater flow. The study demonstrates the added benefits of coupling distributed hydrologic models with water management simulation for multisector multicriteria land cover planning.

What are the Sustainable Water Policies in Central Regions of Iran? An Integrated Water Resource Management Model

The efficient and optimal management of water resources is of great importance due to the strong dependence of human life on water. Also, the availability and utilization of the existing water resources in regions with water shortages, such as the Middle East, impose high social, economic, and environmental costs. Therefore, water resource management policies should incorporate all aspects of supply, allocation, control, and monitoring of resources. This study provides a dynamic simulation model for water resource management in the Yazd province of Iran to examine the effect of different policies on the other variables and choose the most suitable policies over time. For this purpose, we used a system dynamics approach to propose an integrated water resources management model, considering a comprehensive view of different aspects. The proposed model included over 230 influential variables in water resources, along with economic, demographic, technological, agricultural, industrial, public policy-making, water demand-supply, and virtual water volume subsystems. After we validate the model, we define three scenarios (optimistic, baseline, and pessimistic) and four policy packages (i.e., business as usual, focusing on economic development, focusing on sustainable development based on ecological balance, and focusing on water conservation) in the time horizons of 10, 20, and 50 years. The simulation results indicated that we require a reform in the Yazd economic development strategies through policies such as changing the cropping pattern and reducing water-consuming industries. Moreover, water supply enhancement by raising the inter-basin transfer of water alone cannot be an effective solution for reducing the water shortage in Yazd province and may even worsen the water shortage in the long run. We conclude that the “Focus on Water Conservation” policy is the best solution to reduce water shortage. The results of the baseline scenario show that adopting the FWC policy changes the increasing trend of water shortage in the province and decreases them from more than 53 billion m3 in the “Business as Usual” policy to less than 20 billion m3 in the year 2040. As the FWC would decrease more than 10 billion m3 of the virtual water level imbalance compared to BAU policy and make more investments in water efficiency plans, it preserves the current resources of water in the long run.

Investigation of water allocation using integrated water resource management approaches in the Zayandehroud River basin, Iran

The Zayandehroud River is the largest river in the Gavkhouni basin, Iran. Water management in this basin is beset by poor water-allocation policies that do not adequately meet diverse demands (potable, agriculture, industry, and environmental demands). The Gavkhouni basin suffers from water scarcity and unmet water demands; especially with respect to environmental requirements. Water allocation considering appropriate priorities for all demands would be a major improvement for environmental protection in the Gavhouni basin. The application of the environmental flow in Integrated Water Resource Management offers practical options for water management in the Gavkhouni basin. Environmental flow describes the quantity, timing, and quality of water flow required to sustain freshwater, estuarine ecosystems, the human livelihoods, and well-being. A water resources management model is developed in this study for the purpose of improved water management in the Gavkhouni basin. The model involves six stages. The first stage implements a survey of resources and water use. The Environmental flow is calculated in the second stage with the hydraulic method and the Hydrologic Engineering Center- River Analysis System. The third stage applies the calculated environmental flow to the Integrated Water Resource Management approach by means of the Water Evaluation and Planning model. The fourth stage creates seven possible management scenarios in the Water Evaluation and Planning model to be applied in the period ending in the year 2041. These scenarios are ranked in the fifth stage with a multi-criteria decision-making method. The sixth stage applies the best management scenario in the study region. This study's results indicate that the annual drinking water demand under current conditions would rise from 547.6 to 760.2 Mm3 by 2041. The annual industrial water demand is estimated to increase from 213.7 to 400.5 Mm3, and the agricultural water demand is projected to remain constant at 1789.1 Mm3 per yr. The annual drinking water, environmental, industrial, and agricultural unmet demands are estimated to increase from 68.1, 106.5, 73.4, and 470 to 130.1, 186.1, 141.4, and 480 Mm3, respectively. The considered scenarios are (i) change in water supply priority, (ii) change in the population growth trend, (iii) change in return flow and water loss management utilization, (iv) change in the amount of water transferred to the Gavkhouni basin, (v) change of demand management (consumption per capita reduction), (vi) change of agricultural conditions, and (vii) change of industrial conditions. The change in water supply priority and the change in the volume of water transferred to the Gavkhouni basin scenarios are found to be of the highest priority. The best management alternative is chosen with four types of ranking (i.e., water allocation priorities) in which the ranking (i.e., drinking, Industrial, agricultural, environmental unmet water) and fourth ranking (i.e., environmental, drinking, industrial, agricultural Unmet water) are recommended as the best approach.

Assessment of Water Balance of Deme Watershed, Omo-Gibe Basin, Ethiopia Using SWAT Model and ARC-GIS for Water Resources Management

To deal with water management issues, one must analyse and quantify the different elements of hydrologic processes taking place within the area of interest. Obviously, this analysis must be carried out on a watershed basis because all these process are taking place within individual micro watersheds. Only after understanding the spatial and temporal variation and the interaction of these hydrologic components one can scientifically formulate strategies for water conservation. To achieve this goal the choice and use of an appropriate watershed model is a must. All the thematic maps and attribute information of the watershed have been collected from various Government agencies. SWAT model has been set up for the Deme watershed by inputting the digital thematic maps, physical properties of soil and climatic parameters. Total area of the watershed corresponding to the outlet chosen at Deme watershed is 11284.35km ² and its elevation varies from 1138 to 3269m. Calibration and validation of the model have been done by comparing the river flow prediction with the observed values. Nash Sutcliff Efficiency (NSE), coefficient of determination (R ²) and Percent bias (PBIAS) has given very high values for the calibration 0.75, 0.75 and -0.7% respectively and validation 0.73, 0.74 and 6.3% respectively. The calibrated model has been used to predict the important hydrologic processes. The water balance components of Deme watershed resulted PET 388.5mm, Evaporation and transpiration 293.8mm, Precipitation 1147.5mm, Average curve number 76.38, Surface runoff 189.7mm, Revap from shallow aquifer 7.7mm, Percolation to shallow aquifer 37.59mm, Lateral flow 624.33mm and Recharge to deep aquifer 0.28mm. The study has revealed that SWAT model can effectively be used in the simulation of river flow and for predicting the water balance of a watershed. Water balance information of the basin is of great use in planning water conservation, drainage and flood control.

Climate Uncertainty Modelling in Integrated Water Resources Management: Review

Integrated water resources management is exposed to the effects of several risks (climatic, socio-economic, and political). Currently, climate change represents one of the greatest risks for many countries around the world and the agricultural sector in particular. In the literature, climate change is sufficiently researched but there are scarce studies that deal with the theme of risk in agricultural water management and in particular the management under climate change. In the paper, we first define out the characteristics and particularity of climate change risk and then we point the different approaches and methods for taking into consideration for climate change risk in the integrated water resources management models for the agriculture sector. In this work, we aim to appraise the quantification of uncertainties in systems modelling in watersheds and discuss various water resource management and operation models.

Climate services for water utilities: Lessons learnt from the case of the urban water supply to Valencia, Spain

Climate change projections in many regions of the world show a critical reduction in precipitation and a significant rise in temperatures in the next decades. This change may affect the operation of water utilities in arid and semi-arid parts of the globe. The Mediterranean region is particularly vulnerable to the impacts of climate change on water resources. In this paper, we reflect on the challenges that the water utility sector may experience during the upcoming decades to continue providing its essential service under the new climate scenario. Our reasoning is based on the lessons learned during the co-creation of a climate service with the water utility company of Valencia (Spain) within the framework of the EU ERA4CS project INNOVA. The joint vision of climate, water management researchers and water utility operators resulted in a multi-scale framework for evaluating the vulnerability of the water utility to climate change. The modelling framework couples water quantity and quality and their interaction in a chain of models. The proposed framework forced all parties to consider the issue of the temporal and spatial scales, and the importance of choosing and defining the boundaries of the problem. The analytical framework has three distinct elements: (1) a combination of climate projections; (2) hydrological and water resource management model of the river basin system; (3) reservoir management and water quality model. Two Representative Concentration Pathways (RCP) 4.5 and 8.5 were considered in two timeframes for the analysis: the short term (2020–2040) and the medium term (2041–2069). The results show a significant reduction in water availability combined with an increased frequency and intensity of phytoplankton blooms and anoxia episodes. These changes result in the deterioration of the reservoir trophic state, shifting from ultraoligotrophic-oligotrophic (control period) to oligotrophic-mesotrophic (RCP 8.5). The example shows how the combination of models on different scales and the involvement of experts in the co-creation process can result in a customized climate service that provides valuable information to water utility operators that can be used to reduce the system’s vulnerability to climate change.

Development of a Hydrodynamic Model for Regulating Water Drainage of Reservoir and Water Resources Management, Lamtakong Watershed of Thailand

The goal of this research was to develop a hydrodynamic model (HDD-M) for water resource management in the Lamtakong Watershed (LTKW), as well as to simulate three scenarios: 1) Current land use conditions in 2021, 2) Forecasting predicted land-use changes in 2024, and 3) Water drainage regulation of the Lamtakong Reservoir (LTKR) for water resource management in 2024. The Soil and Water Assessment Tool (SWAT) model and Geographic Information System (GIS) program were used to estimate and simulate the amount of Surface Runoff (S), Sediment Yield (SED), Carbonaceous Biochemical Oxygen Demand concentration (CBOD), and Nitrate concentration (NO3) based on a comparison of simulated and observed data. In scenario 1, the S, SED, CBOD, and NO3 were calculated to be 238.44 million cubic meters (MCM), 840,613.68 tons per year, 2.38 mg/L, and 7.36 mg/L, respectively. In the second scenario, the S decreased to 14.75 MCM, whereas SED, CBOD, and NO3 increased to 56,757.48 tons, 0.56 mg/L, and 0.79 mg/L, respectively, when compared to scenario 1, (Scenario 2). Scenario 3 demonstrated that during the dry season of November to June, the standards of surface water were CBOD and NO3, and that increasing LTKR drainage can help prevent the deterioration of water yields. As a result, the HDD-M, which includes the reservoir's controlling water drainage, may need to be considered to satisfy water resource management goals.

Stackelberg equilibrium water allocation patterns in shallow groundwater area under uncertainties

• Establishing a multi-level water resource management model applicable in shallow groundwater area. • Considering process-based crops growth model (detailed water and salt movement). • Introducing uncertainties into multi-level programming model. The hierarchical agricultural water resource management problem in shallow groundwater area is expected to be solved through establishing a practical and feasible mathematical model. This study proposes a multi-level programming model with considerations of process-based crops growth model and uncertainties. The model is solved by a fuzzy approach that ensures the decision-making proceeds from top to bottom sequentially and the leader supervises the solution search direction. The leeway given by each level decision maker expands the decision-making space and lets Stackelberg equilibrium solution more satisfactory. The model is applied in Hetao Irrigation District in China. After optimization, the Stackelberg equilibrium water allocation pattern and satisfaction degrees of each level decision makers can be identified. Summarized conclusions are as follows: (1) under uncertainties of available water, the water diversion is allocated in a similar pattern, while the groundwater allocation has larger variabilities; (2) when available water decreases, local farmers can improve crop production through modifying or optimizing irrigation water amount in each growth period; (3) the combined use of water diversion and groundwater is expected to become an effective approach for achieving a win–win situation between government managers and local farmers. The proposed model performs well in generating Stackelberg equilibrium solutions satisfied by multi-level decision makers. It can be extended to provide decision makers a more complete decision support system and also has potential to be applied in other similar areas.

Global hydroclimatic drivers of terrestrial water storage changes in different climates

The Gravity Recovery and Climate Experiment (GRACE) mission provides an unprecedented way to assess terrestrial water storage changes (TWSC) worldwide. However, hydroclimatic drivers of GRACE-derived TWSC in different climates have not been systematically examined, which hinders its applications in water resources management and hydrological model development. In this study, we derived the monthly TWSC using the GRACE dataset, and analyzed its partial correlations with precipitation (P), evapotranspiration (ET), runoff (R), and temperature (T) from 2003 to 2019 under the Köppen-Geiger world climate classification system. Relative contributions of the four hydroclimatic elements (P, ET, R, and T) to TWSC were quantified using the hierarchical partitioning method. The results indicate that P mainly controls TWSC in tropical climates, hot semi-arid climate, and temperate and continental climates with dry winter. ET is the primary driver of TWSC in mid- and high-latitude regions that feature temperate and continental climates with no dry season, subarctic climates, and polar climates. T mainly influences TWSC in cold arid climates, temperate and continental climates with dry summer or no dry season, and ice cap climate. However, TWSC in many arid climates near the Tropic of Cancer and the Tropic of Capricorn are not well explained by all four hydroclimatic variables according to their non-significant partial correlations. Large trends in annual TWSC are found in South America, western Canada, eastern contiguous United States, and Africa, which are likely due to marked changes in P based on their similar spatial pattern. In particular, decreasing TWSC are found in most continental climates, which manifests a deterioration of water resources availability in these regions. Overall, our results clarify the major hydroclimatic drivers of TWSC in different climates at a global scale, which may help improve TWSC modeling and prediction through a judicious selection of explanatory hydroclimatic variables in different climates.

Spatial multivariate selection of climate indices for precipitation over India

Large-scale interdependent teleconnections influence precipitation at various spatio-temporal scales. Selecting the relevant climate indices based on geographical location is important. Therefore, this study focuses on the spatial multivariate selection of climate indices influencing precipitation variability over India, using the partial least square regression and variable importance of projection technique. 17 climate indices and gridded precipitation dataset (0.25 × 0.25°) from the Indian Meteorological Department for 1951–2020 at a monthly scale are considered. Results show that among all the indices, Nino 4, Nino 1 + 2, Trans Nino Index, Atlantic Multidecadal Oscillation (AMO), quasi-biennial oscillation (QBO), Arctic oscillation (AO), and North Atlantic Oscillation (NAO) have a significant influence on precipitation over India. Further, within homogenous regions, it is found that the Southern Oscillation Index and Nino 3.4 are selected majorly in the South Peninsular compared to other regions. The NAO/AO show a similar pattern and was found to be relevant in the Northeast region (>89%). AMO is selected mainly in Northwest, and West Central (>80%), AMO and QBO at about 70% of grid locations over Central Northeast India. It is to be noted that the number of climate indices identified varies spatially across the study region. Overall, the study highlights identifying the relevant climate indices would aid in developing improved predictive and parsimonious models for agriculture planning and water resources management