Sustainable Water Resources Management Research Articles

Geospatial and geophysical insights for groundwater potential zones mapping and aquifer evaluation at Wadi Abu Marzouk in El-Nagila, Egypt

This study employs an integration of remote sensing, geographic information systems (GIS), and geophysical techniques to delineate groundwater potential zones (GWPZ). This multidisciplinary approach significantly enhances the precision and reliability of groundwater potential zone mapping. Eight criteria were introduced into the analytic hierarchy process (AHP) to identify GWPZs in Wadi Abu Marzouk by applying a weighted overlay analysis of all criteria layers. The criteria weights were derived by using a pairwise-comparison technique, while the accuracy of the weightage process was calculated by the consistency ratio as 0.06. As revealed in the GWPZ analysis, the northern and northwestern regions have the highest groundwater potentiality. Thirty-five vertical electrical soundings (VES) and four electrical resistivity tomography (ERT) profiles were measured across the study area. The interpretation of geophysical data revealed the presence of a water-bearing layer at depths varying between 27 and 51 m from the ground surface. Its resistivity values indicate the existence of freshwater in the northern and northwestern parts, which highly matches the GWPZ analysis results. However, the southern parts of the area are dominated by saltwater. The integration between geospatial techniques, geophysics, and hydrogeology forms a robust scientific approach, with invaluable insights for sustainable water resource management.

Biopolymeric Nanocomposites for Wastewater Remediation: An Overview on Recent Progress and Challenges.

Essential for human development, water is increasingly polluted by diverse anthropogenic activities, containing contaminants like organic dyes, acids, antibiotics, inorganic salts, and heavy metals. Conventional methods fall short, prompting the exploration of advanced, cost-effective remediation. Recent research focuses on sustainable adsorption, with nano-modifications enhancing adsorbent efficacy against persistent waterborne pollutants. This review delves into recent advancements (2020-2023) in sustainable biopolymeric nanocomposites, spotlighting the applications of biopolymers like chitosan in wastewater remediation, particularly as adsorbents and filtration membranes along with their mechanism. The advantages and drawbacks of various biopolymers have also been discussed along with their modification in synthesizing biopolymeric nanocomposites by combining the benefits of biodegradable polymers and nanomaterials for enhanced physiochemical and mechanical properties for their application in wastewater treatment. The important functions of biopolymeric nanocomposites by adsorbing, removing, and selectively targeting contaminants, contributing to the purification and sustainable management of water resources, have also been elaborated on. Furthermore, it outlines the reusability and current challenges for the further exploration of biopolymers in this burgeoning field for environmental applications.

Assessing Groundwater Recharge in the Wabe River Catchment, Central Ethiopia, through a GIS-Based Distributed Water Balance Model

The utilization of groundwater has emerged as an indispensable asset in facilitating economic advancement, preserving ecological integrity, and responding to the challenges posed by climate change, especially in regions characterized by aridity and semi-aridity. The sustainable management of water resources requires an assessment of the geographical and temporal patterns of groundwater recharge. The present study employed the GIS-based WetSpass-M model to model the water balance components by utilizing hydro-meteorological and biophysical data from the Wabe catchment, which spans an area of 1840 km2 in central Ethiopia, for a long time. The objective of this study was to assess the long-term average annual and seasonal groundwater recharge for the catchment area utilizing the WetSpass-M model. The input data were collected through remote sensing data and surveys in the field. The model was employed to gain insights into the process of groundwater recharge in a particular region and to facilitate effective management, prudent utilization, and sustainable planning of water resources in the long run. Water balance components were estimated using seasonal fluctuations in evapotranspiration, surface runoff, and groundwater recharge. The Wabe catchment’s summer, winter, and mean long-term yearly groundwater recharge were determined to be 125.5 mm, 78.98 mm, and 204.51 mm, respectively. The model indicates that summer seasons account for 86.5% of the mean annual precipitation, while winter seasons account for 13.5%. On the other hand, the groundwater system percolates 14.8% of the total annual rainfall (1374.26 mm). While evapotranspiration accounts for 51% of total precipitation and surface runoff accounts for 34.1%, the Wabe catchment’s mean annual evapotranspiration and surface runoff values are simulated at 701.11 mm and 485.58 mm, respectively. The findings suggest the use of the WetSpass-M model to precisely calculate the water balance components within the Wabe catchment.

Water and Us: tales and hands-on laboratories to educate about sustainable and nonconflictual water resources management

Abstract. Climate change and water security are among the grand challenges of the 21st century, but literacy on these matters among high-school students is often unsystematic and/or detached from the real world. This study aims to introduce the educational objectives, methods, and early results of “Water and Us”, a three-module initiative that can contribute to advancing water education in a warming climate by focusing on the natural and anthropogenic water cycle, climate change, and emerging water conflicts. The method of Water and Us revolves around storytelling to aid understanding and generate new knowledge, learning by doing, a flipped-classroom environment, and a constant link to examples from the real world (such as ongoing droughts across the world or seeds of conflict regarding transnational river basins). Water and Us was established in 2021–2022 and, during that school year, involved ≥200 students as part of a proof of concept to test the complete didactic approach using small-scale experiments. Results from ≥40 h of proof-of-concept events confirmed the effectiveness of this approach with respect to conveying the essential elements of the natural and anthropogenic water cycle, the most commonly recurring concepts related to climate change and water as well as the possible conflicts and solutions related to water scarcity in a warming climate. The Water and Us team remains interested in networking with colleagues and potential recipients to upscale and further develop this work.

Limited comparability of global and local estimates of environmental flow requirements to sustain river ecosystems

Environmental flows (e-flows) are a central element of sustainable water resource management to mitigate the detrimental impacts of hydrological alteration on freshwater ecosystems and their benefits to people. Many nations strive to protect e-flows through policy, and thousands of local-scale e-flows assessments have been conducted globally, leveraging data and knowledge to quantify how much water must be provided to river ecosystems, and when, to keep them healthy. However, e-flows assessments and implementation are geographically uneven and cover a small fraction of rivers worldwide. This hinders globally consistent target-setting, monitoring and evaluation for international agreements to curb water scarcity and biodiversity loss. Therefore, dozens of models have been developed over the past two decades to estimate the e-flows requirements of rivers seamlessly across basins and administrative boundaries at a global scale. There has been little effort, however, to benchmark these models against locally derived e-flows estimates, which may limit confidence in the relevance of global estimates. The aim of this study was to assess whether current global methods reflect e-flows estimates used on the ground, by comparing global and local estimates for 1194 sites across 25 countries. We found that while global approaches broadly approximate the bulk volume of water that should be precautionarily provided to sustain aquatic ecosystems at the scale of large basins or countries, they explain a remarkably negligible 0%–1% of the global variability in locally derived estimates of the percentage of river flow that must be protected at a given site. Even when comparing assessments for individual countries, thus controlling for differences in local assessment methods among jurisdictions, global e-flows estimates only marginally compared (R 2 ⩽ 0.31) to local estimates. Such a disconnect between global and local assessments of e-flows requirements limits the credibility of global estimates and associated targets for water use. To accelerate the global implementation of e-flows requires further concerted effort to compile and draw from the thousands of existing local e-flows assessments worldwide for developing a new generation of global models and bridging the gap from local to global scales.

A Critical Review of Climate Change Impacts on Groundwater Resources: A Focus on the Current Status, Future Possibilities, and Role of Simulation Models

The Earth’s water resources, totalling 1.386 billion cubic kilometres, predominantly consist of saltwater in oceans. Groundwater plays a pivotal role, with 99% of usable freshwater supporting 1.5–3 billion people as a drinking water source and 60–70% for irrigation. Climate change, with temperature increases and altered precipitation patterns, directly impacts groundwater systems, affecting recharge, discharge, and temperature. Hydrological models are crucial for assessing climate change effects on groundwater, aiding in management decisions. Advanced hydrological models, incorporating data assimilation and improved process representation, contribute to understanding complex systems. Recent studies employ numerical models to assess climate change impacts on groundwater recharge that could help in the management of groundwater. Groundwater vulnerability assessments vary with the spatial and temporal considerations, as well as assumptions in modelling groundwater susceptibility. This review assesses the vulnerability of groundwater to climate change and stresses the importance of accurate assessments for sustainable water resource management. It highlights challenges in assumptions related to soil and aquifer properties, multiple stressors, adaptive capacity, topography and groundwater contamination processes, gradual sea level rise scenarios, and realistic representations of the region of study. With the advancements in hydrological modelling, including the integration of uncertainty quantification and remote sensing data, artificial intelligence could assist in the efforts to improve models for assessing the impacts of climate change on hydrological modelling.

Recent Precipitation Trends in Six Districts of the Ken River Basin of Bundelkhand Region, India

The future development and sustainable management of water resources will be greatly influenced by the trend analysis of precipitation. This paper focuses on the analysis of rainfall trends in the Bundelkhand region, particularly in six districts covering the Ken basin. Mann-Kendall test was employed to identify potential trends, and the Sen’s slope estimator was utilized to quantify the magnitude of change during 1990 to 2020. Given that a significant portion of rainfall occurs during the southwest monsoon season, the study included both seasonal (monsoon) and annual analyses. The findings indicated a decreasing trend in precipitation for both the monsoon season and the annual scale, although many districts exhibited insignificant trends. The outcomes of this study offer valuable insights for agriculture, related sectors, and contribute to the food and energy security considerations for the six districts in the Bundelkhand region and regions with similar physiography.

International Experience in the Use of Transboundary Water Resources and Issues of its Regulation

The article analyzes the ecological problems of regulating the use of transboundary waters and its protection. The contents of the documents accepted by the international community were studied. At the same time, the state environmental policy of the Republic of Uzbekistan regarding transboundary waters and the tasks it has set for itself have been studied, and suggestions for their improvement have been given. The methods used in this research were interviews and surveys where interviews were conducted with key stakeholders, including government officials, local activists, and the general public in Uzbekistan. Use surveys to collect quantitative data about public perception and awareness regarding changing views about the value of water. In summary, effective international cooperation, clear legal regulations, the establishment of a monitoring commission, and comprehensive protection measures are essential for the sustainable management of transboundary water resources in Central Asia.

Review of Recent Developments in Hydrologic Forecast Merging Techniques

Accurate forecasting in hydrologic modeling is crucial for sustainable water resource management across various sectors, where predicting extreme flow phases holds particular significance due to their severe impact on the territory. Due to the inherent uncertainties in hydrologic forecasting, relying solely on a single rainfall–runoff model may not provide reliable predictions. To address this challenge, over the years, researchers have developed and applied hydrologic forecast merging (HFM) techniques that combine multiple models or ensembles to enhance forecast accuracy, reduce uncertainty, and increase confidence in the forecast. This review summarizes the progress in HFM techniques since the early 1990s and covers developments and applications in flow simulation, uncertainty analysis, monthly and seasonal streamflow predictions, ensemble forecasts, flood forecasting, and climate change analysis. The findings indicate that while HFM techniques outperform individual models regarding forecasting efficiency, their performance across applications is not uniform. Among the different methods, Bayesian model averaging (BMA) is the most popular due to its ability to reduce uncertainty and provide accurate and reliable forecasts in deterministic and probabilistic simulations. With their application simplicity, regression techniques are also robust and efficient as they perform competitively well across different model-merging applications. While specific techniques, such as model-dependent weighted averaging and neural network methods, effectively reduce forecast uncertainty, there is still room for improving forecast accuracy across different lead times. Future research can focus on advanced HFM techniques for estimating optimal weights in time-varying domains and overcoming limitations, like simulating low flows in seasonally dry catchments.

Response of Matching Degree between Precipitation and Maize Water Requirement to Climate Change in China

The synchronicity of rain and heat in the summer of China’s monsoon region provides sufficient water and heat resources for maize growth. However, the intra-annual distribution of precipitation and the probability of extreme precipitation have been inevitably altered by the ongoing climate change, thus affecting the matching degree between precipitation and crop water requirements (MDPCWR). Evaluating the extent to which the MDPCWR will change in the future is of great importance for food security and the sustainable management of water resources. In this study, considering that different growth stages of crops have different sensitivities to water stress, the AquaCrop model was used to calculate the MDPCWR more accurately. In addition, a cumulative distribution function-transform (CDF-t) method was used to remove the bias of 11 global climate models (GCMs) under two typical emission scenarios (SSP2-4.5 and SSP5-8.5) from phase six of the Coupled Model Intercomparison Project (CMIP6). A comprehensive investigation was conducted on how maize growth, water consumption, and the MDPCWR will respond to future climate change with CO2 concentration enrichment in the Huang–Huai–Hai (3H) region in China by driving a well-tested AquaCrop model with the bias-corrected GCMs outputs. The results indicate the following: (1) The CDF-t method can effectively remove seasonal bias, and it also performs well in eliminating the bias of extreme climate events. (2) Under the SSP2-4.5 scenario, the average maximum temperature will increase by 1.31 °C and 2.44 °C in 2021–2050 and 2051–2080, respectively. The average annual precipitation will increase up to 96.8 mm/year, but it will mainly occur in the form of heavy rain. (3) The increased maize evapotranspiration rate does not compensate for the decreased crop water requirement (up to −32 mm/year), due to a shorter growth cycle. (4) The farmland cultivation layer is not able to hold a significant amount of precipitation, due to the increased frequency of heavy rains, resulting in increased irrigation water requirements for maize over the next two periods, with the maximum value of 12 mm/year. (5) Under different scenarios, the projected future MDPCWR will decrease by 9.3–11.6% due to changes in precipitation patterns and crop water requirements, indicating that it will be more difficult for precipitation to meet the water demand of maize growing in the 3H region. The results can provide comprehensive information to understand the impact of climate change on the agricultural water balance and improve the regional strategy for water resource utilization in the 3H region.

The effect of organic pollution on the seasonal dynamics of water quality in a semi-arid zone: case of the Hammam Boughrara Dam, Tlemcen (Algeria).

The present study aims to assess the impact of human activities on the water quality of the Hammam Boughrara dam. It also highlights the crucial importance of sustainable management of water resources in the face of persistent challenges related to various forms of pollution. The study is based on an exhaustive database covering a period spread over 16 years, with monthly measurements of organic pollution indicator parameters, namely BOD5, COD, [Formula: see text],[Formula: see text], [Formula: see text], [Formula: see text], Organic Matter (OM), TDS, Dissolved Oxygen (DO) and pH. The box plots showed an asymmetric distribution of almost all the parameters, with significant seasonal variations in the interquartile (IQR) range. The IQR ranges for [Formula: see text] extends from 0.575 mg/l (summer) to 4.445 mg/l (spring), and for [Formula: see text] from 1.3075 mg/l (autumn) to 1.8625 mg/l (spring). This led to the use of the Spearman method for the analysis of correlations between different parameters. The seasonal study of the five categories of water quality, according to the Organic Pollution Index (OPI), revealed considerable organic pollution. At the 1% significance level, the seasonal correlation between OPI and [Formula: see text] varies between -0.71 and -0.85, while that with [Formula: see text] fluctuates between -0.69 and -0.86. During the period analyzed, the COD/BOD Ratio (CBR) reveals two dominant categories with seasonal variations, i.e. the Moderately Biodegradable Effluents (MBE), with 96 cases, reaching 29 in autumn and 20 in spring. The Difficult to Biodegrade or Non-Biodegradable Effluents (DBE or NBE) category records 94 cases, with a maximum frequency of 26 in winter and minimum of 21 in autumn. These results therefore show the persistence of organic pollution, which had an impact on water quality over the four seasons and throughout the period studied. The results indicate persistent organic pollution affecting water quality. Therefore, prompt actions and sustainable strategies are deemed necessary to mitigate these harmful impacts and to ensure the sustainability of the water resource.

Near real-time retrieval of lake surface water temperature using Himawari-8 satellite imagery and machine learning techniques: a case study in the Yangtze River Basin

Lake Surface Water Temperature (LSWT) is essential for understanding and regulating various processes in lake ecosystems. Remote sensing for large-scale aquatic monitoring offers valuable insights, but its limitations call for a dynamic LSWT monitoring model. This study developed multiple machine learning models for LSWT retrieval of four representative freshwater lakes in the Yangtze River Basin using Himawari-8 (H8) remote sensing imagery and in-situ data. Based on the in situ monitoring dataset in Lake Chaohu, the dynamic LSWT retrieval models were effectively configured and validated to perform H8-based remote sensing inversion. The test results showed that six models provided satisfactory LSWT retrievals, with the Back Propagation (BP) neural network model achieving the highest accuracy with an R-squared (R2) value of 0.907, a Root Mean Square Error (RMSE) of 2.52°C, and a Mean Absolute Error (MAE) of 1.68°C. Furthermore, this model exhibited universality, performing well in other lakes within the Yangtze River Basin, including Taihu, Datonghu and Dongtinghu. The ability to derive robust LSWT estimates confirms the feasibility of real-time LSWT retrieval using synchronous satellites, offering a more efficient and accurate approach for LSWT monitoring in the Yangtze River Basin. Thus, this proposed model would serve as a valuable tool to support the implementation of more informed policies for aquatic environmental conservation and sustainable water resource management, addressing challenges such as climate change, water pollution, and ecosystem restoration.

Mapping Groundwater Potential (GWP) in the Al-Ahsa Oasis, Eastern Saudi Arabia Using Data-Driven GIS Techniques

Searching for new sources of water is becoming one of the most important aspects of scientific research, especially in areas prone to drought, like Saudi Arabia. The study aim was to delineate groundwater potential zones within the Oasis of Al-Ahsa, in Saudi Arabia’s eastern region, and to identify the optimum factors that control the availability of groundwater zones. This was achieved through examining the effect of ten environmental variables on groundwater recharge, namely: slope, topographic wetness index (TWI), land cover (LC), elevation, lineament density (Ld), drainage density (Dd), rainfall, geology, and soil texture. The variables were prepared from a variety of data sources, including spatial data (i.e., DEM and Landsat-8 image), in addition to other complementing data sources for appropriate parameters extraction. Two weighted overlay methods were used, namely the simple additive weight (SAW) as well as the optimum index factor (OIF) in order to categorize the optimal set of parameters for computing GWP and identifying its zones. Two GWP maps were obtained and validated through comparison with the locations of existing wells at GWP zones. The study findings have assured the cogency of the SAW map, where it was found that nearly 45–48% of the resultant zones were characterized as in the “moderate” class, whereas around 21–37% of the entire zones area were classified within the “high” class. The soil texture parameter was determined as being the most influencing parameter for GWP mapping followed by the “geology” parameter; however, the “lineament density” (Ld) was the least important factor. Furthermore, the OIF method has facilitated the identification of the optimal parameter combination for delineating groundwater potential (GWP) zones, which included “Ld”, “land cover”, and “TWI”. The study findings and methodology can serve as a potential model for other similar regions, supporting sustainable water resource management locally as well as globally.

Drought response and recovery mechanisms of grapevine rootstocks grafted to a common Vitis vinifera scion

As grapevine production is converting into irrigated systems worldwide, understanding rootstock-scion interactions at different stages of moderate drought can help to better manage water resources and the choice of rootstock. This study compared the physio-morphological drought response and recovery of a drought-sensitive (Riparia Gloire (Vitis riparia)) and a drought-tolerant rootstock (Ramsey (Vitis champinii)) grafted with Cabernet Sauvignon (Vitis vinifera), and the self-grafted control in a pot study. Ramsey had lower root-to-shoot ratio but higher performance of the root system under drought, explained by the lower root tissue density and tip suberization and higher VviPIP2;1 aquaporin expression, and faster recovery of root hydraulic conductivity and stomatal conductance after re-watering than Riparia. Riparia maintained better water status under moderate drought by early root suberization, but it was less able to restore water uptake capacity and support scion growth and leaf gas exchange after re-watering. This study shows a suite of rootstock traits that improve scion growth in response to moderate drought. Thus, these results identify traits for breeding programs and the selection of rootstocks for sustainable management of water resources under irrigated production.

Ecology of Saline Watersheds: An Investigation of the Functional Communities and Drivers of Benthic Fauna in Typical Water Bodies of the Irtysh River Basin.

In this study, we investigated how changes in salinity affect biodiversity and function in 11 typical water bodies in the Altai region. The salinity of the freshwater bodies ranged from 0 to 5, the brackish water salinities ranged from 5 to 20, and the hypersaline environments had salinities > 20. We identified 11 orders, 34 families, and 55 genera in 3061 benthic samples and classified them into 10 traits and 32 categories. Subsequently, we conducted Mantel tests and canonical correlation analysis (CCA) and calculated biodiversity and functional diversity indices for each sampling site. The results indicated that biodiversity and the proportion of functional traits were greater in freshwater environments than in saline environments and decreased gradually with increasing salinity. Noticeable shifts in species distribution were observed in high-salinity environments and were accompanied by specific functional traits such as swimming ability, smaller body sizes, and air-breathing adaptations. The diversity indices revealed that the species were more evenly distributed in high-diversity environments under the influence of salinity. In contrast, in high-salinity environments, only a few species dominated. The results suggested that increasing salinity accelerated the evolution of benthic communities, leading to reduced species diversity and functional homogenization. We recommend enhancing the monitoring of saline water resources and implementing sustainable water resource management to mitigate the impact of salinity stress on aquatic communities in response to climate-induced soil and water salinization.

The role of state institutions of Kyrgyzstan in the formation of water resources management policy

This article explores the importance of the activities of government agencies in the development and implementation of water resources management strategies. Analyzing the functions and powers of government institutions, the authors discuss their influence on the formation of legislation, the development of water resources management strategies and monitoring their implementation. The article also examines current problems and challenges faced by government institutions in this area, and also suggests ways to solve them to ensure sustainable management of water resources in Kyrgyzstan. Particular attention is paid to the role of government institutions in regulating access to water resources, as well as in developing strategies to ensure sustainable use of water resources in a changing climate. The results of the study may be useful for forming recommendations for improving water resources management policies in Kyrgyzstan.

Physiochemical Characteristics Analysis of Garrah River Water at Shahjahanpur, Ganga River Basin, Uttar Pradesh, India

This study focuses on the physiochemical analysis of the Garrah River in Shahjahanpur, within the Ganga River Basin, Uttar Pradesh, India. The research evaluates the impact of various pollutants, including industrial and municipal sewage, on the river's water quality. Water samples were collected from three locations along the river, representing different pollution levels. The analysis included parameters such as pH, dissolved oxygen (DO), total suspended solids (TSS), color, odor, electrical conductivity, temperature, chemical oxygen demand (COD), salinity, and the concentrations of various elements. The findings showed variations in water quality parameters, with DO, TSS, COD, and heavy metals indicating significant pollution, particularly downstream. Color and odor also suggested pollution from nearby industries. The study revealed that some parameters exceeded WHO standards for drinking water, raising concerns about health risks from exposure to contaminants like chromium. Urgent actions are required to treat municipal sewage and industrial effluents before discharging into the Garrah River. This research highlights the need for ongoing monitoring and sustainable management of water resources in the Ganga River Basin to protect the ecosystem and local communities. It underscores the importance of improving water quality in the region.

Promotion of Socio-Environmental Sustainability by Water Utilities: Optimal Budget’s Estimation and Results’ Analysis of Varying Company Size

Sustainable management of water resources cannot ignore environmental aspects, let alone social and economic ones. To curb water waste, and groundwater pollution and promote equitable access to the resource, water utilities are required to implement a series of initiatives to promote environmental and social sustainability. In this paper, an optimization model is proposed to define the budget that water utilities should allocate to promote socio-environmental sustainability, optimally conveying their message and achieving the right trade-off between capital invested and audience reached. The optimization problem is solved using a nonlinear programming model. The application of the model shows that both big and small water companies should invest an amount that can increase the visibility of sustainability’s promotional message by 20%. However, this amount is about 0.2% of turnover for large utilities and about 17% for small utilities. The model can be a useful tool for both budgeting and incentivizing sustainable practices.

Managerial agility and digital transformation of hydraulic basins: A case study of the Guir Hydraulic Basin Agency

This study aims to examine the impact of managerial agility on decision-making and water resources management within the Guir Hydraulic Basin Agency, focusing on digital approaches. Using a primarily quantitative approach, a questionnaire was administered to assess the perception of digital transformation success and the role of managerial agility among staff within the agency. The results underscore the pivotal role of managerial agility in optimizing water resources within the Hydraulic Basin Agency. The perceived success of digital transformation efforts, alongside the emphasis on collaborative decision-making and agile leadership, highlights the significance of this managerial approach. Furthermore, the recognition of digital training and cross-functional collaboration underscores the multifaceted impact of managerial agility on fostering sustainable water management practices. Agile communication emerges as crucial for aligning stakeholders with digital transformation objectives, thereby reinforcing the integral role of managerial agility in driving efficiency and sustainability in water resources management.

Sustainable Water Resources Management: Groundwater Recharge Potential in the Mesuji-Tulang Bawang River Basin

Sustainable Water Resources Management: Groundwater Recharge Potential in the Mesuji-Tulang Bawang River Basin