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There is great uncertainty about the future effects of climate change on the global economic, social, environmental, and water sectors. This paper focuses on watershed vulnerabilities to climate change by coupling a distributed hydrological model with artificial neural networks and spatially distributed indicators for the use of a predictive model of such vulnerability. The analyses are complemented by a Monte Carlo evaluation of the uncertainty associated with the projections of the global circulation models, including how such uncertainty impacts the vulnerability forecast. To test the proposal, the paper uses current and future vulnerabilities of the Turbio River watershed, located in the semi-arid zone of Guanajuato (Mexico). The results show that nearly 50% of the watershed currently has medium and high vulnerabilities, and only the natural areas in the watershed show low vulnerabilities. In the future, an increase from medium to high vulnerability is expected to occur in urban and agricultural areas of the basin, with an associated uncertainty of ±15 mm in the projected precipitation. [ABSTRACT FROM AUTHOR]

In recent years, a new discipline known as Explainable Artificial Intelligence (XAI) has emerged, which has followed the growing trend experienced by Artificial Intelligence over the last decades. There are, however, important gaps in the adoption of XAI in hydrology research, in terms of application studies in the southern hemisphere, or in studies associated with snowmelt-driven streamflow prediction in arid regions, to mention a few. This paper seeks to contribute to filling these knowledge gaps through the application of XAI techniques in snowmelt-driven streamflow prediction in a basin located in the arid region of north-central Chile in South America. For this, two prediction models were built using the Random Forest algorithm, for one and four months in advance. The models show good prediction performance in the training set for one (RMSE:1.33, R2: 0.94, MAE:0.55) and four (RMSE: 5.67, R2:0.94, MAE: 1.51) months in advance. The selected interpretation techniques (importance of the variable, partial dependence plot, accumulated local effects plot, Shapley values and local interpretable model-agnostic explanations) show that hydrometeorological variables in the vicinity of the basin are more important than climate variables and this occurs both for the dataset level and for the months with the lowest streamflow records. The importance of the XAI approach adopted in this study is discussed in terms of its contribution to the understanding of hydrological processes, as well as its role in high-stakes decision-making. [ABSTRACT FROM AUTHOR]

Integration of renewable energy sources and water production technologies is a must when facing water scarcity problems in semiarid regions, such as Mediterranean regions. The use of additional water resources and production methods, such as reclaimed water and, more specifically, desalinated water, means present and necessary water resources to introduce in the water balances to attend to water demands within a global warming and droughting scenario. These solutions have the inconvenience of energy/power needs and costs. However, the development of renewable energies like photovoltaic solar energy, with lower and lower costs and greater efficiency, makes these economically feasible facilities, reaching competitive production costs for marine or sea desalinated water by around 50% of reduction in energy costs and 20–30% of savings in final water production cost. This paper presents a practical project or action focused on the integration of renewable energies and new water resources by introducing a Photovoltaic Energy Plant (PVEP) as an energy source to feed a Seawater Desalination Treatment Plant (SWDTP). The PV facility is designed to cover all the energy demanded using the SWDTP during the day, and even studying the possibility of selling the energy production exceeds and injecting them into the energy supply network, covering the needs of buying energy needed during the high period where there is no photovoltaic energy production. Thus, savings related to energy costs and even incomes coming from energy sales mean an important reduction in operation costs or expenditures (OPEX), which makes economically feasible and sustainable the investment and the final price of water produced within the Mutxamel SWDTP. The final reduction cost in water desalination reaches 25% on average. [ABSTRACT FROM AUTHOR]

Water is the most important resource for human, animal, and vegetal life. Recently, the use of artificial intelligence techniques, such as Random Forest, has been combined with other techniques, such as models of logical–mathematical reasoning, to generate predictive water quality models. In this study, a rule-based inference technique to generate water quality labels is described, using historical physicochemical parameter data on seven water monitoring stations in Loa River, collected by the Chilean Ministry of the Environment. Next, a predictive model of water quality status was created, using Random Forest, physicochemical parameters, and expert knowledge. The validation of Random Forest results is described using three quality indicators from the machine learning model: accuracy (acc), precision (p), and recall (r). This paper describes dataset preparation, the refinement of the threshold values used for the physicochemical parameters most significant in the class, and the predictive model labeling water quality. The models obtained yielded the following mean values: acc = 0.897, p = 89.73, and r = 0.928. The ML model reported here is novel since no previous studies of this kind predict the water quality of Loa River, located in an extremely arid zone. This study also helps to create specific knowledge to predict freshwater quality. [ABSTRACT FROM AUTHOR]

The global climate shows an obvious warming trend, and the impact on water resources is increasing. Abrupt temperature change and warming hiatus are two important states of temperature change. The quantitative impacts of temperature change and warming hiatus on surface runoff remain unclear. Based on the measured runoff data from 60 representative hydrological stations in China from 1956 to 2016 and the Water Balance Model developed by the Research Center for Climate Change (RCCC-WBC), this paper analyzes the quantitative impacts of abrupt temperature change and warming hiatus on surface runoff. The results showed that the effects of three types of abrupt temperature changes on runoff in different basins in China are significantly different. The effects of abrupt temperature changes and warming stagnation on runoff in northern China are greater than those in southern China, and the effects of abrupt temperature changes and warming stagnation on runoff in the upper, middle, and lower reaches of the same basin are also different. Before the abrupt change in temperature, the influence of temperature on the surface runoff was less than 9%, and the influence of temperature on the runoff in some southern areas was weaker, only affecting less than 3% of the runoff. When the temperature changes abruptly, the influence of air temperature on the surface runoff in a small part of the arid region is up to 30%. The abrupt change in mean maximum temperature has both positive and negative driving effects on runoff in China, and the negative driving effect is concentrated in the areas with abrupt warming, affecting about 8% of the runoff on average. The average influence of abrupt mean temperature change on runoff in China is about 10%, and the area with a large influence on runoff change is concentrated in the area north of 40° N. The abrupt change in temperature in the middle and lower reaches of the Yellow River Basin has a great influence on the runoff change, up to 13%. The maximum impact of abrupt mean minimum temperature on runoff is concentrated in Northeast China, ranging from 9% to 12%. During the period of temperature stagnation, air temperature and runoff showed an obvious reverse trend. During this period, the average negative influence of drastic changes in air temperature on runoff was about 15%, but precipitation and runoff still maintained a good consistency, which may be due to the effect of other influencing factors which offset the negative driving effect of air temperature. [ABSTRACT FROM AUTHOR]

In arid regions with scarce water resources, lakes play an extremely vital role in maintaining the ecological environment. Therefore, the Chinese government has launched an ecological water conveyance project in the Tarim River basin in Xinjiang with the aim of restoring the ecological environment of the area. In previous studies, there was no complete evaluation system used to quantify changes in the ecological environment of arid regions after ecological water conveyance. In this paper, Lake Taitema was selected as the study area, which is both a terminal lake in the Tarim River basin and an object of the ecological water conveyance project. This study utilized Landsat TM/OLI satellite remote sensing images and MODIS datasets to build a remote sensing ecological index model and systematically evaluated the changes in the ecological environment and land use types in the Taitema Lake area. A structural equation model was constructed to analyze the correlation between the area of Taitema Lake and its driving factors. The results show that over the selected 20 years, the proportion of pixels with an upward trend (Zc > 0) of the RSEI was 56.5%, while the proportion of pixels with a downward trend (Zc < 0) of the RSEI was 43.5%. The area proportion of regions with poor ecological environment quality decreased by about 40%, and the area proportions of regions with moderate, good, and excellent ecological environment quality increased by 29.7%, 10%, and 0.6%, respectively. By comparing the land use data from 2000 and 2020, the proportion of grassland increased by 6%, the proportion of water area increased by 4.4%, and the proportion of unused land decreased by 9.6%. In summary, after the implementation of the ecological water conveyance project, the ecological environment quality of the Lake Taitema area gradually improved, and ecological water conveyance was the main driving factor of the area change in Lake Taitema. [ABSTRACT FROM AUTHOR]

In the last three decades, water shortages have become more common and have left an increasing and significant mark on the world economy. The lack of water in arid and semi-arid regions, along with the interest in water security in areas where the demand for water exceeds its availability, has caused water reuse to be considered as an alternative source in these areas and has prompted the authorities to change from the usual linear, take–make–use management approach to the circular management of resource preservation. This new approach to sustainable management, using the management of reduction, reuse, recycling, and recovery, is called the circular economy (CE). However, although the potential for the reuse of treated wastewater is still insipient, CE in the water sector has gained a lot of attention lately. The aim of this paper is to systematically examine existing research published in the last five years on CE implementation in the water and wastewater sector. A sample of 64 articles was found through interactive keyword selection. Using the dynamic reading technique, data were extracted, and articles were classified according to five research motivations, which include, political, economic, legal, institutional, technical, and environmental. Most publications were from institutions in Europe, followed by North America and Asia. A similar trend was observed in terms of the distribution by authors, countries, and regions. [ABSTRACT FROM AUTHOR]

Xinjiang is a typical continental arid climate zone and ecologically fragile zone. Drought has caused damage to the local social economy, agricultural production, and the ecological environment. However, the study of drought is more difficult due to the complex topography and the lack of monitoring information. In this paper, based on the meteorological data of 94 meteorological stations in Xinjiang from 1961 to 2020, we used the precipitation and potential evapotranspiration (ET0) to calculate the aridity index (AI); the Mann–Kendall test, Morlet wavelet analysis, and Kriging interpolation were used to identify the trend, period, and spatial distribution. The results showed that (1) the average change rate of the precipitation in Xinjiang was 8.58 mm/10a, the average change rate of the ET0 was −14.84 mm/10a, and the average change rate of the AI was −1.94/10a; (2) the periods of precipitation, ET0, and AI in Xinjiang were 39, 29, and 14 years, respectively, and the abrupt changes occurred in 1986, 1971, and 1987, respectively; (3) The Moran index of precipitation and temperature are 0.41 and 0.33, respectively, indicating that precipitation and temperature in Xinjiang are positively correlated in spatial distribution and have spatial clustering characteristics; and the z-values are both greater than 2.58 (p < 0.01), indicating that the spatial autocorrelation of precipitation and temperature in Xinjiang is significant. This study can provide a reference for the diagnosis of the meteorological drought mechanism and the coping with climate change in Xinjiang. [ABSTRACT FROM AUTHOR]

Global warming has led to an increase in interest in river hydrology. Water surface slope is a basic parameter of river morphology and is critical in understanding riverine ecosystems. The Yarlung Zangbo River is an important international river. Scientific understanding of its hydrology has been severely limited by its harsh topography and the sparse distribution of measurement stations. This paper describes the first attempt to use ICESat-2 satellite altimetry data to calculate river water slope and introduces a new technique for studying river hydrology. Water level data for different stretches of the Yarlung Zangbo River were obtained from high spatial resolution ICESat-2 altimetry data. The data were analyzed to determine the water surface slope of the Yarlung Zangbo River, and variation in the water surface slope was examined for several river sections. The water surface slope of the Yarlung Zangbo River was greatest in summer and autumn and least in winter and spring. There may be seasonal cyclic changes in the water surface slope. The range for water surface slope was large and the difference in extremes is significant; the maximum average water surface slope was 1935.17 cm/km and the minimum water surface slope was 0.08 cm/km. The water surface slope of the Yarlung Zangbo River can be characterized as small in the upper and middle reaches and large in the lower reaches; it is related to dry and wet conditions determined by topography and climate. The upper and middle reaches of the Yarlung Zangbo River are semi-arid and the lower reaches of the Yarlung Zangbo River span three climate zones: semi-arid, semi-humid and humid. In addition, the water level information measured by ICESat-2 data is basically similar to the water level information measured by Hydroweb data, except that the water level information of individual virtual stations is quite different due to special reasons. It was found that ICESat-2 data had higher-accuracy water level data results and more river location information. Therefore, ICESat-2 satellite altimetry data can provide a baseline reference for the study of the Yarlung Zangbo River hydrology, and the technique used is applicable to other rivers. [ABSTRACT FROM AUTHOR]

Lakes are sensitive indicators of climatic change and are important resources for regional economic development. In recent years, there have been many studies related to the changes in lake area and lake volume. However, further studies are still required to understand the responses of lakes to climatic change and human activities. This paper utilizes lakes in the Qaidam Basin, an inland arid region of China, as the object of study and investigates the characteristics of variability in lake changes and its driving forces by combining multi-source remote sensing, model simulations and historical data. We first analyzed the spatiotemporal pattern of climatic change in the basin under the background of global warming. The response of lake water volume to climatic change and human activities is then discussed. Finally, the main factors that affect the change in lake water volume in different regions of the basin are delineated. The water volume of lakes in the Qaidam Basin increased by 3.81 km3 from 1990 to 2020. Particularly since the 21st century, the water volume of lakes has increased rapidly, and an increasingly abrupt change appeared around 2015. The increases in precipitation and vegetation area are the main and secondary factors that led to the increase in total lake water volume in the basin, respectively. However, the main influencing factors still vary in different regions. The impact of air temperature, evaporation, and changes in the cropland area on the change in lake water volume is generally not obvious. Human activities, such as the development of salt lakes and damming, have led to substantial changes in the spatial pattern of lakes in the middle of the basin and are associated with the replacement, genesis, and disappearance of Yiliping Lake, Yahu Lake and West Taijinar Lake, respectively. This study reveals the changing characteristics of climate and lake water volume in inland arid basins in China, which are highly important to understand the responses of lakes to climatic change and human activities, and provides a scientific basis for the rational development and utilization of lake resources in arid basins. [ABSTRACT FROM AUTHOR]

The water harvesting potential of atmospheric water generators (AWGs) in high-altitude semiarid regions can be diminutive relative to the water generation capacity. Operational parameters for the dehumidification process can be augmented to increase atmospheric water in the defined zone available for harvesting. In this paper, the feasibility of augmenting the microclimates of AWGs at the point of air extraction through an evaporative cooling system (ECS) was investigated. Water yield and capacity utilisation were measured from two AWGs piloted on a plant in Ga-Rankuwa, South Africa. This was implemented between December 2019 and May 2021. The study revealed that although the ECS did impact the operating parameters through decreasing temperature and increasing relative humidity (p < 0.05), variance in water yield was not significant (p > 0.05). Capacity utilisation of the AWGs remained below 50% after augmentation. Cooling efficiency of the ECS ranged between 1.4–74.5%. Energy expenditures of 0.926 kWh/L and 0.576 kWh/L for AWGs 1 and 2 were required under pristine conditions, respectively. Under the modified conditions, energy expenditure decreased to 0.855 kWh/L for AWG 1, but increased/L to 0.676 kWh for AWG 2. ECS is deduced to not be a feasible intervention for augmenting water harvesting potential for AWGs in this semiarid zone. [ABSTRACT FROM AUTHOR]

Southwest Asia has different climate types including arid, semiarid, Mediterranean, and temperate regions. Due to the complex interactions among components of the Earth system, forecasting precipitation is a difficult task in such large regions. The aim of this paper is to propose a learning approach, based on artificial neural network (ANN) and random forest (RF) algorithms for post-processing the output of forecasting models, in order to provide a multi-model ensemble forecasting of monthly precipitation in southwest Asia. For this purpose, four forecasting models, including GEM-NEMO, NASA-GEOSS2S, CanCM4i, and COLA-RSMAS-CCSM4, included in the North American multi-model ensemble (NMME) project, are considered for the ensemble algorithms. Since each model has nine different lead times, a total of 108 different ANN and RF models are trained for each month of the year. To train the proposed ANN an RF models, the ERA5 reanalysis dataset is employed. To compare the performance of the proposed algorithms, four performance evaluation criteria are calculated for each model. The results indicate that the performance of the ANN and RF post-processing is better than that of the individual NMME models. Moreover, RF outperformed ANN for all lead times and months of the year. [ABSTRACT FROM AUTHOR]

Glacier mass balance can visually indicate the degree of glacier response to climate change. The mountain glaciers are an essential source of recharge for rivers in arid regions and play a vital role in maintaining regional ecological stability and production life. This paper drives a spatially distributed degree-day model using multi-source remote sensing data such as MOD11C3 and TRMM3B43 to simulate the mass balance in the Tianshan Mountains' south and north slope basins. The spatiotemporal heterogeneity of the mass balance was compared and attributed using a Geographical detector. The results show that: (1) The glaciers in the north and south basins are mainly distributed at an altitude of 3900–4300 m, and the total glacier area accounts for 85.71%. The number of less than 1 km2 glaciers is the most in the whole region. (2) During the study period, the glaciers in the north and south basins were negative (−465.95 mm w.e.) an entire interannual change rate was −28.36 mm w.e./a. The overall trend of ablation can be divided into two stages: from 2000 to 2010a, the persistence increased, and from 2010 to 2016a, the volatility decreased. (3) In the attribution of mass balance, the factors affecting glacier mass balance can be divided into two parts: climate and topography. The cumulative contribution rate of climate factors in Kaidu is nearly 20% higher than that of topographic factors, but the contribution rate of climate factors in Manas is only 7.3% higher. Therefore, the change of glacier mass balance in the Kaidu river basin is more driven by climate factors, while the glacier mass balance in the Manas river basin is more affected by the combination of climate and topographic factors. (4) The climate accumulation is the dominant factor in the Manas river basin (69.55%); for the ablation area, the Kaidu river basin is dominated by climate (70.85%), and the Manas river basin is dominated by topographic factors (54.11%). Due to the driving force of climate and topographic factors and the different coupling modes, glacier mass balance's spatiotemporal heterogeneity in the north and south slope basins is caused. This study contributes to analyzing the mechanism of regional changes in the glacier mass balance. It provides a scientific basis for investigating the characteristics of water resource changes and water resource regulation in the north and south slope basins of the Tianshan Mountains. [ABSTRACT FROM AUTHOR]

Marshlands in arid and semi-arid areas are considered constantly changing environments due to unsecured water supplies as a result of high evapotranspiration and limited and highly variable rainfall. Classification of marshlands in these regions and mapping of their land cover is not an easy task and maps need to be upgraded frequently. Satellites provide enormous amounts of information and data for the continuous monitoring of changes. The aim of this paper is to introduce an approach using multispectral satellite imagery that was adopted to classify and monitor the Al Hammar Marsh (Iraq) over several years and to suggest a relationship between the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI), and the Normalized Difference Water Index (NDWI), using Landsat 8 data with a resolution of 30 m × 30 m, validated with Sentinel-2 datasets at 10 m × 10 m. Six land cover classes were used: (1) open water, (2) dry area, (3) dense vegetation, (4) medium-density vegetation, (5) sparse vegetation, and (6) wet soil. Three indices, NDWI, NDMI, and NDVI, were chosen for the automatic classification of each pixel and the creation of a time series of land cover maps. The proposed method can efficiently classify and monitor marshlands and can be used to study different marshlands by adjusting the thresholds for NDVI, NDMI, and NDWI. Overall, the correlation for all classes (R) between Landsat 8 and Sentinel-2 is about 0.78. Thus, this approach will help to preserve marshes through improved water management. [ABSTRACT FROM AUTHOR]

Evaluation and modeling of soil water infiltration are essential to all aspects of water resources management and the design of hydraulic structures. Nonetheless, research focused on experimental studies of infiltration rates in arid and semi-arid regions under unknown boundary conditions remains minimal. This paper investigates the characteristics of the spatial variability of infiltration over a semi-arid rural basin of Algeria. The experiments were conducted using a portable double-ring infiltrometer filled at an equal volume of approximately 100 L of water for each of the 25 catchment locations. Soil moisture contents at the proximity of each test location were evaluated in the laboratory as per the standard NF P94–050 protocol. The experimental results are used to produce the catchment infiltration curves using three statistically fitted infiltration models, namely Horton, Kostiakov, and Philip models. The reliability of the models was assessed using four performance criteria. The statistical regressions of the fitted models suggest that the Horton model is the most suitable to assess the infiltration rate over the catchment with mean coefficients of Nash = 0.963, CC = 0.985, RMSE = 1.839 (cm/h), and Bias = 0.241. The superiority of the Horton model suggests that the initial and final infiltration rates, primarily affected by soil type, initial soil moistures, and land cover, are important predictors of the modeling process over the Madjez Ressoul catchment. The results also infer that the applicability of other models to the different types of undeveloped soils in the study area requires advanced field investigations. This finding will support the understanding of the hydrologic processes over semi-arid basins, especially in advising crop irrigation schemes and methods and managing the recurring flood and drought over the country. [ABSTRACT FROM AUTHOR]

Drylands regions of the world face difficult issues in maintaining water resources to meet current demands which will intensify in the future with population increases, infrastructure development, increased agricultural water demands, and climate change impacts on the hydrologic system. New water resources evaluation and management methods will be needed to assure that water resources in drylands are optimally managed in a sustainable manner. Development of water management and conservation methods is a multi-disciplinary endeavor. Scientists and engineers must collaborate and cooperate with water managers, planners, and politicians to successfully adopt new strategies to manage water not only for humans, but to maintain all aspects of the environment. This particularly applies to drylands regions where resources are already limited and conflicts over water are occurring. Every aspect of the hydrologic cycle needs to be assessed to be able to quantify the available water resources, to monitor natural and anthropogenic changes, and to develop flexible policies and management strategies that can change as conditions dictate. Optimal, sustainable water management is achieved by cooperation and not conflict, thereby necessitating the need for high quality scientific research and input into the process. [ABSTRACT FROM AUTHOR]

The supply of raw water to the inhabitants of metropolises is not a trivial problem, and involves many challenges, both in terms of the quantity and quality of this water. When these metropolises are located in semiarid regions, this challenge takes on enormous proportions, and in many situations, there are no sustainable solutions, especially in times of global climate change. One hypothesis to try to mitigate this problem in coastal cities is the underwater adduction of rivers. The objective of this paper was to make the abstraction of drinking water in the mouths of great rivers near semi-arid regions. This water would be led by a pipeline below the water level and would follow the route of the seacoast, where the energy to move the water would be supplied by an axial hydraulic pump embedded in the pipeline by water-cooled electric motors driven by the energy generated from offshore wind turbines. Estimates have been made for the four metropolises in semi-arid regions: Fortaleza-Brazil, Dalian-China, Tel Aviv-Israel, and Gaza-Palestine, where it was possible to calculate economic viability through the Present Worth Value, the internal rate of return, and payback. The results indicated that Fortaleza had economic viability under restrictions. Dalian proved the ideal result. Tel Aviv and Gaza both had great economic viability, but only if Egypt agreed to supply water from the Nile. This paper proved that the management of the water supply for human consumption through the underwater adduction of rivers could be achieved with real clearance for any deficits in the volume of water that due to global climate change are becoming more frequent. [ABSTRACT FROM AUTHOR]

Understanding how natural variation in flow regimes influences stream ecosystem structure and function is critical to the development of effective stream management policies. Spatial variation in flow regimes among streams is reasonably well understood for streams in mesic regions, but a more robust characterization of flow regimes in arid regions is needed, especially to support biological monitoring and assessment programs. In this paper, we used long-term (41 years) records of mean daily streamflow from 287 stream reaches in the arid and semi-arid western USA to develop and compare several alternative flow-regime classifications. We also evaluated how accurately we could predict the flow-regime classes of ungauged reaches. Over the 41-year record examined (water years 1972–2013), the gauged reaches varied continuously from always having flow > zero to seldom having flow. We predicted ephemeral and perennial reaches with less error than reaches with an intermediate number of zero-flow days or years. We illustrate application of our approach by predicting the flow-regime classes at ungauged reaches in Arizona, USA. Maps based on these predictions were generally consistent with qualitative expectations of how flow regimes vary spatially across Arizona. These results represent a promising step toward more effective assessment and management of streams in arid regions. [ABSTRACT FROM AUTHOR]

The growing interest in groundwater as a sustainable resource for water supply regulation is noteworthy. Just as surface reservoirs in many countries are primarily designed to manage seasonal fluctuations throughout the year, aquifers possess significant reserves, making them particularly well suited for interannual regulation, especially during droughts. In the face of climate change, this form of regulation may increasingly highlight the importance of groundwater resources. For instance, the temporary use of groundwater reserves through intensive pumping in arid or semiarid regions, compensating for seasonal or interannual variations in natural water recharge, can significantly affect aquifers. The exploitation of groundwater reserves may lead to adverse effects over time, eventually being deemed overexploitation and subject to environmental or even legal issues. This work assesses the interannual regulation capacity of aquifers and estimates the groundwater renewal rates and periods for aquifers according to river basins. We first present the mathematical background and development of a method to assess the hydrodynamic volumes (renewable groundwater reserves) in large regions. This method builds on prior knowledge of the distribution functions of spring water contributions based on their discharge and for lithological groups exhibiting similar hydrogeological behavior. Furthermore, it establishes a relationship between spring discharges and hydrodynamic volumes, facilitating the integration of the latter based on discharge. Although proposed for Spain, the method can also be implemented to other regions where data are available. [ABSTRACT FROM AUTHOR]

The classification of stream flow regimes has been a subject of study for over a half century in the fields of hydrology, geomorphology, ecology, and water resources management. But with the most recent Supreme Court decision on jurisdictional Waters of the United States (WOTUS) and the 2023 Conforming Rule, the answer to the question of which waters are relatively permanent has increased in importance and urgency. One state where this question is salient is Arizona, where approximately 95% of its streams are nonperennial. In this study, we use long-term (>30 years) daily discharge records from Arizona to assess semi-natural flow regimes of arid streams within the context of the 2023 Conforming Rule. Using flow percentile distributions, we distinguished flow permanency—ephemeral vs. intermittent vs. perennial—for 70 stream reaches distributed throughout the state. Ephemeral streams had a median flow of 0 cms and a 75th percentile flow permanence less than 25% (i.e., less than 3 months of flow for every 7.5 out of 10 years). On the other end of the spectrum, perennial streams had a 90th percentile flow permanence of 100%. In the middle, intermittent streams had a 75th percentile flow permanence greater than 25% and a 90th percentile flow permanence less than 100%. We also assessed the effect of the recent megadrought (since 1994) on flow permanency. As a result of the megadrought, four perennial streams transitioned to intermittent, four intermittent streams transitioned to ephemeral, and one perennial stream became ephemeral. The flow classification we present here is specific to Arizona streams but could be useful to other arid regions seeking to answer the question of which streams are relatively permanent in a typical year. [ABSTRACT FROM AUTHOR]

Reservoir sediment severely impacts water supply in water-scarce regions, making reservoir dredging an urgent global issue. The investment required for deep-water dredging far exceeds that for dry land dredging. Therefore, against the backdrop of the national water network construction, this study focuses on a typical inter-basin water transfer project in Northern China. To increase the proportion of dry land dredging volume and save costs, this study uses compensation reservoirs to replace the emptied reservoir in undertaking water supply tasks as a constraint. Single-objective optimization models for single reservoirs and multi-objective optimization models for reservoir groups are established, using game theory comprehensive subjective and objective weighting methods to select the optimal solution. The following conclusions are drawn from comparing the water supply effects under various emptying sequences: the optimal sequence for emptying reservoirs should be determined through precise quantitative analysis; as the dredging is completed, the water supply tends to stabilize; the satisfaction with the water supply and the variance of the water shortage rate are primarily related to reservoirs with a large inflow and storage capacity; dredging occurs according to the descending order of the storage capacity of reservoirs; and the startup proportion of pump stations shows an increasing trend. [ABSTRACT FROM AUTHOR]

Addressing soil salinity in irrigated drylands is tightly linked with water and land management decisions thus requiring interdisciplinary engagement. The salinity mapping approaches in Central Asia are undertaken through field sampling and laboratory analysis, which is a time consuming process. As a consequence, salinity maps are not available on time to estimate water requirements to cope with varying levels of soil salinity. Reducing the time lag between assessment and delivery of such maps would enable authorities to determine in advance appropriate water volumes for leaching the salts before and during the growing season. Research initiated in Uzbekistan context explored transdisciplinary and participatory approach to innovation development with local stakeholders. As one of the innovations, an electromagnetic induction meter (EM), a tool for rapid salinity assessment, was chosen and jointly with local salinity mapping related institutions tested, validated, and local capacities for its use developed. This paper redraws this process of innovation-focused stakeholder interaction and transdisciplinary research and discusses it with reference to ongoing debates on participatory and/or transdisciplinary innovation research. The existence of strong path dependencies within implementation oriented organizations could be observed, meaning that the innovation demands many changes to the existing system. Furthermore, the encountered challenges of participatory, transdisciplinary research in the hierarchically shaped setting of post-soviet Uzbekistan are illustrated in selected qualitative field notes and assessed. For improved joint learning and research in a transdisciplinary team, feedback cycles of mutual learning and critical reflection of how to theoretically and practically work in a transdisciplinary manner turned out to be crucial and not to be underestimated. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (PET) is an important factor that needs to be considered in regional water management and allocation; thus, the reasonable estimation of PET is an important topic in hydrometeorology and other related fields. There is evidence that increased CO2 concentration alters the physiological properties of vegetation and thus affects PET. In this study, changes in PET with and without the CO2 effect over China is investigated using seven CMIP6-GCMs outputs under seven shared socioeconomic pathways (SSPs) based scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5), as well as the contribution rate of CO2 on PET in different climatic regions. Changes in estimated PET based on modified Penman–Monteith (PM) method that considers the CO2 effect is compared with the traditional PM method to examine how PET quantity varies (differences) between these two approaches. The results show that the PET values estimated by the two methods explored opposite trends in 1961–2014 over entire China; it decreases with consideration of CO2 but increases without consideration of CO2. In the future, overall PET is projected to increase under all scenarios during 2015–2100 for China and its three sub-regions. PET generally tends to grow slower when CO2 is taken into account (modified PM approach), than when it is not (traditional PM method). In terms of differences in the estimated PET by the two methods, the difference between the two adopted methods increased in China and its sub-regions for the 1961–2014 period. In the future, the difference in estimated PET is anticipated to continuously increase under SSP3-7.0 and SSP5-8.5. Spatially, a much greater extent of difference is found in the arid region. Across the arid region, the PET difference is projected to be the highest at 138% in the mid-term (2041–2060) with respect to the 1995–2014 period, whereas it tends to increase slower in the long-term period (2081–2100). Importantly, CO2 is found to be the most dominant factor (−154.2% contribution) to have a great effect on PET changes across the arid region. Our findings suggest that ignorance of CO2 concentration in PET estimation will result in significant overestimation of PET in the arid region. However, consideration of CO2 in PET estimation will be beneficial for formulating strategies on future water resource management and sustainable development at the local scale. [ABSTRACT FROM AUTHOR]

The potential of generalized deep learning models developed for crop water estimation was examined in the current study. This study was conducted in a semiarid region of India, i.e., Karnataka, with daily climatic data (maximum and minimum air temperatures, maximum and minimum relative humidity, wind speed, sunshine hours, and rainfall) of 44 years (1976–2020) for twelve locations. The Extreme Gradient Boosting (XGBoost), Gradient Boosting (GB), and Random Forest (RF) are three ensemble deep learning models that were developed using all of the climatic data from a single location (Bengaluru) from January 1976 to December 2017 and then immediately applied at eleven different locations (Ballari, Chikmaglur, Chitradurga, Devnagiri, Dharwad, Gadag, Haveri, Koppal, Mandya, Shivmoga, and Tumkuru) without the need for any local calibration. For the test period of January 2018–June 2020, the model's capacity to estimate the numerical values of crop water requirement (Penman-Monteith (P-M) ETo values) was assessed. The developed ensemble deep learning models were evaluated using the performance criteria of mean absolute error (MAE), average absolute relative error (AARE), coefficient of correlation (r), noise to signal ratio (NS), Nash–Sutcliffe efficiency (ɳ), and weighted standard error of estimate (WSEE). The results indicated that the WSEE values of RF, GB, and XGBoost models for each location were smaller than 1 mm per day, and the model's effectiveness varied from 96% to 99% across various locations. While all of the deep learning models performed better with respect to the P-M ETo approach, the XGBoost model was able to estimate ETo with greater accuracy than the GB and RF models. The XGBoost model's strong performance was also indicated by the decreased noise-to-signal ratio. Thus, in this study, a generalized mathematical model for short-term ETo estimates is developed using ensemble deep learning techniques. Because of this type of model's accuracy in calculating crop water requirements and its ability for generalization, it can be effortlessly integrated with a real-time water management system or an autonomous weather station at the regional level. [ABSTRACT FROM AUTHOR]

Conservation tillage technology possesses substantial potential to enhance agricultural production efficiency and tackle issues such as wind erosion and land degradation in semi-arid regions. The integration of no-tillage and straw mulching technologies in the conventional aeolian semi-arid agricultural zones of western Liaoning, China, has led to notable improvements in crop yield and soil quality. However, a comprehensive assessment of the mechanisms and kinetics involved in soil nutrient variations is yet to be conducted. During a two-year study period, we assessed four tillage systems in the aeolian semi-arid regions of Northern China: no-tillage with full straw mulching (NTFS), no-tillage with half straw mulching (NTHS), no-tillage without straw mulching (NT), and conventional tillage (CT). The investigation focused on examining nutrient conditions, enhancing photosynthetic activity, and increasing maize yield while improving water use efficiency (WUE). Our findings emphasize the beneficial impact of combining no-tillage and straw mulching on enhancing soil water retention, resulting in a notable rise in soil moisture levels during the crucial growth phases of maize. This approach also positively influenced soil nutrient levels, particularly in the 0–20 cm layer, fostering an environment conducive to maize cultivation. In terms of ecological benefits, no-tillage with straw mulching curtailed soil sediment transport and wind erosion, notably at 30–40 cm heights, aiding in the ecological protection of the region. The yield and WUE were substantially higher under NTFS and NTHS than under CT, with NTHS demonstrating the most significant gains in yield (14.5% to 16.6%) and WUE (18.3% to 21.7%) throughout the study period. A TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) analysis confirmed NTHS as the optimal treatment, achieving the highest scores for soil water, nutrient availability, wind erosion control, maize photosynthesis, yield, and WUE, thus emerging as the most effective conservation tillage strategy for sustainable agriculture in aeolian semi-arid regions. [ABSTRACT FROM AUTHOR]

As an important indicator for assessing regional water resources, the study of the spatiotemporal evolution and driving factors of water resources carrying capacity (WRCC) is essential for achieving sustainable water resource utilization. This study focuses on Yulin City, a typical arid region located on the Loess Plateau in northwestern China. By constructing an evaluation index system for regional WRCC and combining an improved fuzzy comprehensive evaluation model with the TOPSIS evaluation model, a comprehensive WRCC evaluation model is established. Additionally, Geodetector is used to explore the main driving factors behind the evolution of regional WRCC. This multidimensional analytical framework aims to deeply analyze the dynamic evolution trends of WRCC and the driving mechanisms of different factors in its spatiotemporal changes. The results indicate that (1) from 2011 to 2020, the overall WRCC of Yulin City showed a trend of positive improvement, with Shenmu, Yuyang, and Fugu areas performing the best, and by 2020, more than half of the counties had achieved Grade 3 or above; (2) the spatial variability of WRCC in Yulin City was more significant than its temporal changes; and (3) in terms of driving mechanisms, the northern six counties gradually shifted from traditional economic-driven factors to ecological and environmental drivers, whereas the southern six counties remained constrained by economic factors. Overall, water resource factors remain the primary driving force for the socio-economic development and environmental sustainability of the entire Yulin City. The study provides valuable information for water resource allocation and differentiated management in arid regions. [ABSTRACT FROM AUTHOR]

Water shortages are serious in northwest China due to the level of social and economic development, engineering, resource shortages, and other factors being restricted, so the conflict between supply and demand for water resources is prominent in different regions and different water use sectors. Therefore, Pingliang City was selected as the research object in this study. The membership function was introduced, and an interactive algorithm to correct model parameters based on the fairness constraint was derived. An uncertain multi-objective fuzzy programming model was also established. The results show that the optimal allocation of water will be 38,051.9~40,740 × 104 m3 and 39,938.4~41,317.5 × 104 m3 under a normal year (p = 50%) and a dry year (p = 75%) in 2025, respectively, and the corresponding water shortage rates will be 4.2% and 6.7%. In 2035, the optimal water allocation will be 45,644.1~49,245.9 × 104 m3 and 46,442.4~50,044.2 × 104 m3 and the water shortage rates will be 7.0% and 7.0%, respectively. The proportion of groundwater supply will decrease by 8.8% and 13.8% in 2025 and 2035 after the optimal allocation, the proportion of surface water supply will increase by 9.6% and 12.2%, and the proportion of reclaimed water will increase by −0.78% and 2.1%, respectively. The results can provide a technical reference for the development and utilization of water resources in other cities and similar areas in semi-arid regions. [ABSTRACT FROM AUTHOR]

This study investigates the Batha endorheic basin in Chad, situated east of the Lake Chad basin in the arid to semi-arid Sahelian zone. This region has not yet undergone comprehensive geological and hydrogeological studies. More broadly, the transition zone between semi-arid and arid climates has been minimally explored. This research aims to evaluate the resources and dynamics of this multi-layered system using a combined geology-hydrogeology-hydrochemistry-isotopes approach. The multilayer system includes sedimentary layers (Quaternary, Pliocene, and Eocene) over a crystalline basement. A piezometric investigation of the system shows a general SE–NW groundwater, indicating an interconnection between all layers. Hydrochemical analyses identifies four main facies (calcium-bicarbonate, sodium-bicarbonate, sulphate-sodium, and mixed), primarily controlled by water–rock interaction with secondary influences from base-exchange and evaporation. Saturation indices indicate that these waters are close to equilibrium with the calcite-Mg phases, gaylussite and gypsum. Stable isotopes (oxygen-18 and deuterium) categorize groundwater into three groups: ancient water, recent and older meteoric water mixtures affected by evaporation, and mixtures more heavily impacted by evaporation. Tritium contents reveal three groups: current rainwater, modern water, and sub-modern water. These results indicate that ionic and isotopic differentiations cannot be strictly linked to specific layers, confirming the interconnected nature of the Batha system. The observed heterogeneity is mainly influenced by lithological and climatic variations. This study, though still limited, enhances significantly the understanding of the basin's functioning and supports the rational exploitation of its vital resources for the Batha area's development. Future investigations to complete the present study are highlighted. [ABSTRACT FROM AUTHOR]

Residential areas in developing arid and semi-arid countries are highly vulnerable to flooding, and water shortages have forced their inhabitants to live close to rivers. While climate change is expected to cause more extreme weather conditions in the future, adopting private loss-reduction measures can diminish flood risk. Although the number of flood models has grown significantly for developing arid and semi-arid lands, these models suffer from being incapable of performing micro-scale flood risk analysis and including household behaviors. This research work presents a novel socio-economic simulation model in the framework of flood risk management (FRM) to couple household adaptive responses with flood risk analysis. Agent-based modeling (ABM) embeds human behaviors in a flood-simulating environment. The focus of this research is the upper Kan catchment in Iran with a long history of severe flash flooding. Our results show the ability of the developed framework to address household participation in FRM activities through private precautionary measures. Moreover, the results indicate the importance of presenting such micro-level behaviors in flood modeling for a more realistic flood risk assessment. It is also demonstrated that household adaptation in a continuous way can lead to less flood risks in the region, even under climate change and the future economy. Finally, the results reveal that the remaining and diminished regional flood risks are influenced by the behavioral framework through which the individuals make decisions in adopting flood-loss-reduction measures. A similar pattern is, however, observed in household contributions over time among the discussed behavioral approaches. [ABSTRACT FROM AUTHOR]

Processes driving nutrient retention in stormwater green infrastructure (SGI) are not well quantified in water-limited biomes. We examined the role of plant diversity and physiochemistry as drivers of microbial community physiology and soil N dynamics post precipitation pulses in a semi-arid region experiencing drought. We conducted our study in bioswales receiving experimental water additions and a montane meadow intercepting natural rainfall. Pulses of water generally elevated soil moisture and pH, stimulated ecoenzyme activity (EEA), and increased the concentration of organic matter, proteins, and N pools in both bioswale and meadow soils. Microbial community growth was static, and N assimilation into biomass was limited across pulse events. Unvegetated plots had greater soil moisture than vegetated plots at the bioswale site, yet we detected no clear effect of plant diversity on microbial C:N ratios, EEAs, organic matter content, and N pools. Differences in soil N concentrations in bioswales and the meadow were most directly correlated to changes in organic matter content mediated by ecoenzyme expression and the balance of C, N, and P resources available to microbial communities. Our results add to growing evidence that SGI ecological function is largely comparable to neighboring natural vegetated systems, particularly when soil media and water availability are similar. [ABSTRACT FROM AUTHOR]

This study implemented and assessed, over a period of four weeks, a full-scale constructed wetland designed to collect and treat the greywater for a rural household located in an arid environment typical of Africa's Sahel region. The system was constructed from local materials and consisted of a shower room, a receiving basin, a pre-treatment filter, and a subsurface horizontal flow wetland planted with Chrysopogon zizanioides. Results showed the overall removal of organic matter was greater than 90%, and orthophosphate and ammonium were reduced by 73% and 60%, respectively, allowing for the treated water to retain some embedded nutrients. The removal efficiency of fecal bacteria varied from 3.41 (enterococci) to 4.19 (fecal coliforms) log10 units which meets World Health Organization Guidelines for restricted irrigation. Our assessment of the full-scale household constructed wetland technology adds to the relatively low number of constructed wetland studies conducted outside a laboratory setting. Furthermore, it supports efforts to promote safe reuse of an underutilized resource at the rural household level in Sub-Saharan Africa and other arid regions in the developing world, supporting prospects for using treated greywater for agricultural reuse in regions that experience water scarcity, climate variability, and land degradation. [ABSTRACT FROM AUTHOR]

Soils and water are major resources that drive a country's economy, and therefore should be conserved and utilized sustainably. However, in Kenya, these two resources are facing huge depletion and degradation due to anthropogenic factors and climate change. Bamboo species, especially on large plantations, can significantly alter ecological, hydrological, and biogeochemical processes in the long term. This study aimed to evaluate the effects of different species of bamboo and tree plantations on important soil–water processes like infiltration, bulk density, runoff, and soil loss in Kenya. The research was conducted at two sites (Gede in Arabuko Sokoke forest and at Baolala, in Kilifi County) managed by the Kenya Forestry Research Institute (KEFRI). The Arabuko Sokoke forest has a hot–humid coastal climate, while Baolala is a hot semi-arid area with little precipitation. The study involved measurement of soil–water infiltration rates using infiltrometers, installing runoff plots to quantify surface runoff and sediment loss, and analyzing soil properties like bulk density for growing periods for different bamboo and tree species. At the Gede forest site, the 30-year-old Thyrsostachys siamensis and Bambusa bambos plantations recorded the highest infiltration rates. Mature bamboo plantations of T. siamensis and B. bambos recorded higher infiltration rates compared to mature plantations of E. camaldulensis and G. arborea. It was observed that the bamboo plantations manifested lower soil bulk density compared to bare land, which recorded the highest bulk density. At Boalala, infiltration rates were significantly higher in the bamboo species compared to grassland and bare land. The painted bamboo (B. vulgaris vittata) had a slightly higher water infiltration rate compared to B. vulgaris. Runoff and erosion patterns reinforced the benefits of more mature bamboo plantations as well. There was a significant correlation between amount of runoff and collected soil loss through erosion. The data showed reductions in surface runoff volumes and sediment loss as the bamboo plantations aged compared to younger species. Therefore, by enhancing infiltration and reducing runoff and erosion, well-managed bamboo plantations can protect valuable soil resources, improve water recharge, and support sustainable land use over the long term. In conclusion, this study showed the strong potential of bamboo as a soil and water conservation tool in Kenya. [ABSTRACT FROM AUTHOR]

Landscape has significant effects on hydrological processes in a watershed. In the Sudano-Sahelian area, watersheds are subjected to a quick change in landscape patterns due to the human footprint, and the exact role of the actual landscape features in the modification of the hydrological process remains elusive. This study tends to assess the effects of landscape on the genesis of the runoff in the Mayo Mizao watershed. To achieve this goal, 62 infiltration tests were performed at different points and depths (5 cm and 20 cm) using the double-ring method and the Porchet method. The results show that the combination of many factors (soil type, land use, and farming practices) can guide the hydraulic conductivity behavior of soils. For example, at 5 cm depths, clayey-evolved soils, such as vertisols and halomorphic soils, inhibit infiltration, as opposed to non-evolved mineral soils, such as lithosols and clayey-sandy soils. However, at 20 cm depths, gray soils with halomorphic tendencies followed by vertisols have a low sensitivity to infiltration, as opposed to soils derived from loose materials and halomorphic soils. For a given soil type, rainfed crops are the primary land use that runs against infiltration. However, the effect of tillage varies according to the soil type. Finally, given the extent of vertisols and halomorphic soils in the Far North region of Cameroon in general, and in the Mayo Mizao watershed in particular, and regarding the increase in cultivated areas, a probable reduction in the infiltration capacity of soils in this region is to be expected in the medium term. The results of this study can be used as a basis for land-use planning and sustainable watershed management in semi-arid tropical zones. [ABSTRACT FROM AUTHOR]

Comprehensive evaluations of global precipitation datasets are imperative for gaining insights into their performance and potential applications. However, the existing evaluations of global precipitation datasets are often constrained by limitations regarding the datasets, specific regions, and hydrological models used for hydrologic predictions. The accuracy and hydrological utility of eight precipitation datasets (including two gauged-based, five reanalysis and one merged precipitation datasets) were evaluated on a daily timescale from 1982 to 2015 in this study by using 2404 rain gauges, 2508 catchments, and four lumped hydrological models under varying climatic conditions worldwide. Specifically, the characteristics of different datasets were first analyzed. The accuracy of precipitation datasets at the site and regional scale was then evaluated with daily observations from 2404 gauges and two high-resolution gridded gauge-interpolated regional datasets. The effectiveness of precipitation datasets in runoff simulation was then assessed by using 2058 catchments around the world in combination with four conceptual hydrological models. The results show that: (1) all precipitation datasets demonstrate proficiency in capturing the interannual variability of the annual mean precipitation, but with magnitudes deviating by up to 200 mm/year among the datasets; (2) the precipitation datasets directly incorporating daily gauge observations outperform the uncorrected precipitation datasets. The Climate Precipitation Center dataset (CPC), Global Precipitation Climatology Center dataset (GPCC) and multi-source weighted-ensemble precipitation V2 (MSWEP V2) can be considered the best option for most climate regions regarding the accuracy of precipitation datasets; (3) the performance of hydrological models driven by different datasets is climate dependent and is notably worse in arid regions (with median Kling–Gupta efficiency (KGE) ranging from 0.39 to 0.65) than in other regions. The MSWEP V2 posted a stable performance with the highest KGE and Nash–Sutcliffe Efficiency (NSE) values in most climate regions using various hydrological models. [ABSTRACT FROM AUTHOR]

Drought is the most complex natural hazard that can occur over large spatial scales and during long time periods. It affects more people than any other natural hazard, particularly in areas with a dry climate, such as the semiarid region of the Brazilian Northeast (NEB), which is the world's most populated dry area. In this work, we analyzed trends and the spatial distribution of drought characteristics (frequency, affected area, and intensity) based on the Standardized Precipitation Index (SPI) on annual (SPI-12) and seasonal (SPI-3) scales. The study used monthly precipitation data recorded between 1962 and 2012 at 133 meteorological stations in Pernambuco State, Brazil, which is located in the eastern part of the NEB and has more than 80% of its territory characterized by a semiarid climate. The regions of Sertão, Agreste, and Zona da Mata of Pernambuco were considered for comparison. The Mann–Kendall and Sen's slope tests were used to detect the trend and determine its magnitude, respectively. The results indicated that annual droughts in the state of Pernambuco became more frequent from the 1990s onwards, with summer having the greatest spatial coverage, followed by winter, autumn, and spring. Sertão presented a greater number of stations with a significant positive trend in drought frequency. Regarding the drought-affected area, global events occurred in a greater number of years on an annual scale and during the summer. Trend analysis pointed to an increase in areas with drought events on both scales. As for the drought intensity, the entire state of Pernambuco experienced drought events with high intensity during the autumn. The relationship between drought characteristics indicated an increase in the affected area as the result of an increase in drought intensity. [ABSTRACT FROM AUTHOR]

Water vapor adsorption on soil, a crucial non-rainfall water resource in arid regions, warrants further experimental investigation, particularly on two typical land surfaces: bare soil and gravel. This study examined the formation characteristics and influencing factors of vapor adsorption in an arid region of Northwestern China. Observations and analyses were conducted on adsorption and evaporation measurements taken by two small weighing lysimeters (SLSs); soil temperature at a depth of 5 cm; surface temperature; relative humidity; and air temperature at a height of 30 cm above the ground from 2019 to 2020. The adsorbed water in this area was more abundant at night and less abundant during the day, with a stable nightly adsorption rate of 0.013 mm/h. Adsorption was more frequent in spring and winter (from January to June and November to December), accounting for about 90% of the total annual adsorption. In 2019 and 2020, the ratio values of adsorption to evaporation were 0.16 and 0.10 for bare soil, and 0.10 and 0.12 for gravel, respectively. Adsorption was more likely to occur when the soil moisture content was less than 13%; the highest adsorption frequency was close to 20% when the RH was between 75 and 95%; low soil temperatures were more conducive to the occurrence of adsorption. The effect of temperature differences (Ta−Ts) on adsorption was stronger than that of relative humidity. The adsorption frequency generally showed a bimodal change with increasing temperature difference, but the effect of temperature differences was less effective for gravel than bare soil. When the relative humidity was high and the temperature difference was weakly positive, the maximum adsorption intensity could reach 0.18 mm/h. [ABSTRACT FROM AUTHOR]

Arid regions are susceptible to flash floods and severe drought periods, therefore there is a need for accurate and gap-free rainfall data for the design of flood mitigation measures and water resource management. Nevertheless, arid regions may suffer from a shortage of precipitation gauge data, whether due to improper gauge coverage or gaps in the recorded data. Several alternatives are available to compensate for deficiencies in terrestrial rain gauge records, such as satellite data or utilizing geostatistical interpolation. However, adequate assessment of these alternatives is mandatory to avoid the dramatic effect of using improper data in the design of flood protection works and water resource management. The current study covers 75% of the Kingdom of Saudi Arabia's area and spans the period from 1967 to 2014. Seven satellite precipitation datasets with daily, 3-h, and 30-min temporal resolutions, along with 43 geostatistical interpolation techniques, are evaluated as supplementary data to address the gaps in terrestrial gauge records. The Normalized Root Mean Square Error by the mean value of observation (NRMSE) is selected as a ranking criterion for the evaluated datasets. The geostatistical techniques outperformed the satellite datasets with 0.69 and 0.8 NRMSE for the maximum and total annual records, respectively. The best performance was found in the areas with the highest gauge density. PERSIANN-CDR and GPM IMERG V7 satellite datasets performed better than other satellite datasets, with 0.8 and 0.82 NRMSE for the maximum and total annual records, respectively. The spatial distributions of maximum and total annual precipitation for every year from 1967 to 2014 are generated using geostatistical techniques. Eight Probability Density Functions (PDFs) belonging to the Gamma, Normal, and Extreme Value families are assessed to fit the gap-filled datasets. The PDFs are ranked according to the Chi-square test results and Akaike information criterion (AIC). The Gamma, Extreme Value, and Normal distribution families had the best fitting over 56%, 34%, and 10% of the study area gridded data, respectively. Finally, the selected PDF at each grid point is utilized to generate the maximum annual precipitation for 2, 5, 10, 25, 50, and 100-year rasters that can be used directly as a gridded precipitation input for hydrological studies. [ABSTRACT FROM AUTHOR]

Global changes in drought and wetness and their future trends in arid regions have recently become a major focus of research attention. The Tarim River Basin (TRB) in Xinjiang, China, is among the most climate-sensitive regions in the world. This study uses data from the past 60 years (1962–2021) to analyze the spatial and temporal features of drought and wetness conditions in the TRB, calculating the Standardized Precipitation Evapotranspiration Index (SPEI). Trend detection for SPEI is performed using the BEAST mutation test, identification of drought events using the theory of operations, and spatial and temporal analyses of dry and wet changes using Empirical Orthogonal Function (EOF) decomposition. Additionally, the CMIP6 dataset is used to estimate future changes. The study results indicate the following: (1) From 1962 to 1998, the TRB exhibited a "warm and wet" trend that suddenly shifted from "wet-to-dry" in 1998 and subsequently transitioned to a pronounced "warm and dry" trend. (2) After the "wet-to-dry" shift, the frequency of drought events noticeably increased. The northern section of the basin witnessed more frequent drought events, albeit with lower severity, while the southern part had fewer occurrences but with higher severity. The spatial distribution of drought event frequency and severity is inconsistent. (3) The EOF decomposition results for SPEI-variable fields at 1-, 3-, and 6-month time scales show that the cumulative variance contribution rate of the first three principal spatial modal feature vectors exceeds 70%. The spatial distribution of the modes includes a consistent pattern across the entire basin, a north–south opposite pattern, and an east–west opposite pattern. (4) The future trend of drought in the TRB is expected to intensify, manifesting a spatial pattern characterized by dryness in the middle of the basin and wetness around the periphery. These research findings can provide support for decisions addressing regional drought risks. [ABSTRACT FROM AUTHOR]

A better understanding of the effects of climate change and land use/cover change (LUCC) on streamflow promotes the long-term water planning and management in the arid regions of northwestern China. In this paper, the Soil and Water Assessment Tool (SWAT) and a separation approach were used to evaluate and separate the effects of climate change and LUCC on streamflow in the Xiying River basin. The SWAT model was calibrated by the hydro-meteorological data from 1980-1989 to obtain the optimum parameters, which were validated by the subsequent application to the period between 1990-2008. Moreover, streamflow under several scenarios with different climate change and land use conditions in 1990-2008 and 2010-2069 were further investigated. Results indicate that, in the period of 1990-2008, the streamflow was dominated by climate change (i.e., changes in precipitation and temperature), which led to a 102.8% increase in the mean annual streamflow, whereas LUCC produced a decrease of 2.8%. Furthermore, in the future period of 2010-2039, the mean annual streamflow will decrease by 5.4% and 4.5% compared with the data of 1961-1990 under scenarios A2 and B2, respectively, while it will decrease by 21.2% and 16.9% in the period of 2040-2069, respectively. [ABSTRACT FROM AUTHOR]

This paper presents a modeling application of surface runoff using the Hydrologic Modelling System (HEC-HMS). A case study was carried out for the Jianghe watershed, a typical semi-arid and sub-humid geo-climatic region in northern China. Two modeling schemes using different descriptive sub-mechanism models provided by HEC-HMS for runoff volume, direct runoff and routing (channel flow) were investigated. The modeling results were compared with historical observation data. This work shows that HEC-HMS can be a suitable modeling tool for specific situations in China. With the appropriate selection of the sub-mechanism models, HEC-HMS can be applied to various situations, including the typical semi-arid and sub-humid conditions in northern China. [ABSTRACT FROM AUTHOR]

Arid and semi-arid ecosystems are characterized by patchy vegetation and variable resource availability. The interplant spaces of these ecosystems are very often covered by cyanobacteria-dominated biocrusts, which are the primary colonizers of terrestrial ecosystems and key in facilitating the succession of other biocrust organisms and plants. Cyanobacterial biocrusts regulate the horizontal and vertical fluxes of water, carbon and nutrients into and from the soil and play crucial hydrological, geomorphological and ecological roles in these ecosystems. In this paper, we analyze the influence of cyanobacterial biocrusts on water balance components (infiltration-runoff, evaporation, soil moisture and non-rainfall water inputs (NRWIs)) in representative semiarid ecosystems in southeastern Spain. The influence of cyanobacterial biocrusts, in two stages of their development, on runoff-infiltration was studied by rainfall simulation and in field plots under natural rainfall at different spatial scales. Results showed that cover, exopolysaccharide content, roughness, organic carbon, total nitrogen, available water holding capacity, aggregate stability, and other properties increased with the development of the cyanobacterial biocrust. Due to the effects on these soil properties, runoff generation was lower in well-developed than in incipient-cyanobacterial biocrusts under both simulated and natural rainfall and on different spatial scales. Runoff yield decreased at coarser spatial scales due to re-infiltration along the hillslope, thus decreasing hydrological connectivity. Soil moisture monitoring at 0.03 m depth revealed higher moisture content and slower soil water loss in plots covered by cyanobacterial biocrusts compared to bare soils. Non-rainfall water inputs were also higher under well-developed cyanobacterial biocrusts than in bare soils. Disturbance of cyanobacterial biocrusts seriously affected the water balance by increasing runoff, decreasing soil moisture and accelerating soil water loss, at the same time that led to a very significant increase in sediment yield. The recovery of biocrust cover after disturbance can be relatively fast, but its growth rate is strongly conditioned by microclimate. The results of this paper show the important influence of cyanobacterial biocrust in modulating the different processes supporting the capacity of these ecosystems to provide key services such as water regulation or erosion control, and also the important impacts of their anthropic disturbance. [ABSTRACT FROM AUTHOR]

A correct determination of irrigation water requirements necessitates an adequate estimation of reference evapotranspiration (ETo). In this study, monthly ETo is estimated using artificial neural network (ANN) models. Eleven combinations of long-term average monthly climatic data of air temperature (min and max), wind speed (WS), relative humidity (RH), and solar radiation (SR) recorded at nine different weather stations in Tunisia are used as inputs to the ANN models to calculate ETo given by the FAO-56 PM (Penman–Monteith) equation. This research study proposes to: (i) compare the FAO-24 BC, Riou, and Turc equations with the universal PM equation for estimating ETo; (ii) compare the PM method with the ANN technique; (iii) determine the meteorological parameters with the greatest impact on ETo prediction; and (iv) determine how accurate the ANN technique is in estimating ETo using data from nearby weather stations and compare it to the PM method. Four statistical criteria were used to evaluate the model's predictive quality: the determination coefficient (R2), the index of agreement (d), the root mean square error (RMSE), and the mean absolute error (MAE). It is quite evident that the Blaney–Criddle, Riou, and Turc equations underestimate or overestimate the ETo values when compared to the PM method. Values of ETo underestimation ranged from 1.9% to 66.1%, while values of overestimation varied from 0.9% to 25.0%. The comparisons revealed that the ANN technique could be adeptly utilized to model ETo using the available meteorological data. Generally, the ANN technique performs better on the estimates of ETo than the conventional equations studied. Among the meteorological parameters considered, maximum temperature was identified as the most significant climatic parameter in ETo modeling, reaching values of R and d of 0.936 and 0.983, respectively. The research showed that trained ANNs could be used to yield ETo estimates using new data from nearby stations not included in the training process, reaching high average values of R and d values of 0.992 and 0.997, respectively. Very low values of MAE (0.233 mm day−1) and RMSE (0.326 mm day−1) were also obtained. [ABSTRACT FROM AUTHOR]

Water, being the basic resource for life on earth, is of great importance in arid and semi-arid regions, which face the direct impacts of climate change. This study aims to solve water scarcity for Baranti Plain farmers by constructing concrete canals using modern technology. The Baranti Plain is located approximately 25 km north of Erbil in Iraq and spans an area of 445 km2. The Great Zap River flows through its northern region, with an average discharge of about 400 m3 per second. In response to the challenges faced in this area, the Ministry of Agriculture and Water Resources collaborated with the Food and Agriculture Organization (FAO) to gather essential data. This extensive dataset, covering the period from 2000 to 2021, particularly focuses on ground-level monitoring in September. Notably, the region experienced a significant decline in groundwater levels, totaling 23 m on average. Additionally, there was a 7.8% increase of urban expansion, and the number of wells increased from 257 in 2006 to 600 in 2021. To counter the diminishing groundwater levels and facilitate agricultural irrigation, a proposal was introduced to harness the waters of the Great Zap River. This plan involves channeling the river waters to the plain through a network of concrete canals known as the Baranati Project Plain. For precise planning, a digital elevation model (DEM) with a 12.5 m resolution was procured to analyze the area using GIS. This investigation revealed a height difference of 130 m between the Great Zap River and the Baranti Plain. Subsequently, the area was segmented into four zones based on its suitability for the project: highest, medium, low, and unsuitable. Notably, the combined areas of high, medium, and low suitability encompass 68% of the entire study region. The project's next phase used a flow calculator to determine the channel's shape, area, slope, and water requirements. The final phase involved analyzing annual rainfall data from three meteorological stations (Bastora, Ankawa, and Khabat), showing an average annual rainfall of 396 mm. The project has the capacity to irrigate more than 30,000 hectares of land, benefiting more than 1200 farmers. It is expected to stop the use of over 600 wells for irrigation and potentially raise groundwater levels by about 2.5 m annually. Our work revealed that addressing groundwater depletion requires implementing canals, rainwater harvesting, farmer education, modern irrigation, drilling restrictions, and supporting water. [ABSTRACT FROM AUTHOR]

With the increasing water scarcity and the demand for sustainable agriculture, precise estimation of crop evapotranspiration (ET) is crucial for effective irrigation management, crop yield assessment, and equitable water distribution, particularly in semi-arid regions. In this study, a large aperture scintillometer (LAS) was used to validate the remote sensing-based ET model SETMI (Spatial Evapotranspiration Modeling Interface) in an irrigated maize-wheat cropping system in a semi-arid region at the ICAR-Indian Agricultural Research Institute, New Delhi. Results obtained by the SETMI model depicted modeled surface energy fluxes compared well with LAS field data, showing a very high R2 (0.83–0.95) and NRMSE (8–29%). The SETMI model performed better in the case of the maize crop than the wheat crop in field experiments. Further, the SETMI model was employed at the regional level using high-resolution Sentinel-2 to estimate the regional water productivity of wheat crops over a semi-arid region in India. The estimated regional, seasonal wheat actual ET mainly ranged between 101 mm and 325 mm. The regional wheat water productivity varied from 0.9 kg m−3 to 2.20 kg m−3. Our research reveals that the SETMI model can give reliable estimates of regional wheat water productivity by examining its spatial and temporal fluctuations and facilitating the creation of regional benchmark values. [ABSTRACT FROM AUTHOR]

Water resource management scenarios have become more crucial for arid to semi-arid regions. Their application prerequisites rigorous hydrological modelling approaches since data are usually exposed to uncertainties and inaccuracies. In this work, Soil Water Assessment Tool (SWAT), an open source semi-distributed, continuous-time, process-based physical hydrological model is used to model hydrological processes and eventually calculate groundwater recharge estimations in Seybouse basin, Northeast Algeria. The model uses estimated rainfall to calibrate the model with observed discharge from hydrometric stations. Model calibration and validation are performed over four hydrometric stations located in the basin. Uncertainty analysis and sensitivity analysis supported the calibration period. SUFI-2 algorithm is used for uncertainty estimations along with a global sensitivity analysis prior to calibration simulations. Simulated flood hydrographs showed generally good accuracy with few misfits on the peaks. The model obtained satisfactory and consistent calibration and validation results for which the Nash score varied from 0.5 to 0.7 for calibration and from −0.1 to 0.6 for validation and R2 from 0.6 to 0.7 for calibration and 0.03 to 0.8 for validation. Moreover, estimated water budget values show strong similarities with the observed values found in the literature. The present work shows that the rigorously calibrated and validated SWAT model can simulate hydrological processes as well as major high and low flows using estimated rainfall data. [ABSTRACT FROM AUTHOR]

Analyzing the evolution of regional habitat quality is an important means to assess the impact of engineering activities on ecosystems. Taking Xiangyu in the Feng River Basin as the study area, the land use change in 1985 and 2022 was analyzed, and the habitat quality and degradation degree were evaluated by using the Integrated Assessment and Tradeoff of Ecosystem Services (InVEST) model. The results showed that from 1985 to 2022, the transfer of land use types in Xiangyu mainly occurred on dry land, bare land, forest land, and industrial land. The area of dry land and bare land converted into industrial land is 10,825.15 m2 and 249,123.09 m2, respectively, and affected by the measures of returning farmland to forest and grassland in Shaanxi Province, the area transferred to forest land reached 371,471.87 m2, mainly from dry land and bare land. The continuous expansion of industrial land led to a significant decline in habitat quality, and the areas with high habitat degradation were concentrated in forest land in a large range, which indicated that forest land was vulnerable to industrial land expansion. Land use change and human engineering activities are the main factors affecting the ecological environment, and limiting the expansion rate of industrial land is the key to protecting the ecological environment. [ABSTRACT FROM AUTHOR]

Interest in artificial recharge of groundwater using pretreated wastewater continues to increase, especially in semi-arid countries. After the artificial recharge and natural treatment, the water could be extracted through boreholes pumping for direct irrigation. The selection of suitable locations for artificial recharge should be based on hydrogeological conditions, economic evaluation and environmental considerations. Clogging of boreholes that are used for artificial recharge is a serious problem and requires proper planning to reduce it. This paper deals with the investigation of the possibilities and prospects of aquifer recharge via boreholes using treated wastewater. Firstly, the aquifer recharge techniques, the proposed criteria of waste and the clogging effect are presented. Secondly, the possibility of application of artificial recharge in the South-Eastern Mesaoria aquifer of Cyprus is examined. Based on hydrogeological results, artificial recharge using tertiary treated wastewater via boreholes is one of the options available for increasing the groundwater reserves of this aquifer. The recycled water will infiltrate through gravel pack, providing favorable conditions for ventilation and laminar flow due to small water flow velocity. The treatment works include the removal of the fat, oil and grease (FOG) and cyanides (CN-) content in order to meet the upper acceptable limits. [ABSTRACT FROM AUTHOR]

In this paper, the authors use remote-sensing images to monitor the water quality of reservoirs located in the semiarid region of Northeast Brazil. Sentinel-2 MSI TOA Level 1C reflectance images were used to remotely estimate the concentration of chlorophyll-a (chl-a), the main indicator of the trophic state of aquatic environments, in five reservoirs in the state of Ceará, Brazil. A three-spectral band retrieval model was calibrated using 171 water samples, collected from November 2015 through July 2018 in 5 reservoirs. For validation, 71 additional samples, collected from August 2018 through December 2019, were used to ensure a robust accuracy assessment. The TOA Level 1C products performed very well, achieving a relative RMSE of 28% and R2 = 0.80. Data on wind direction and speed, solar radiation and reservoir volume were used to generate a conceptual model to analyze the behavior of chl-a in the surface waters of the Castanhão reservoir. During 2019, the reservoir water quality showed strong variation, with concentration fluctuating from 30 to 95 µg/L We showed that the end of the dry season is marked by strong eutrophic conditions corresponding to very low water inflows into the reservoir. During the rainy season there is a large decrease in the chl-a concentration following the increase of the lake water storage. During the following dry season, satellite data show a progressive improvement of the trophic state controlled by wind intensity that promotes a better mixing of the reservoir waters and inhibiting the development of most phytoplankton. [ABSTRACT FROM AUTHOR]

Sediment transport in rivers is a nonlinear natural phenomenon, which can harm the environment and hydraulic structures and is one of the main reasons for the dams' siltation. In this paper, the following artificial intelligence approaches were used to simulate the suspended sediment load (SSL) during periods of flood events in the northeastern Algerian river basins: artificial neural network combined with particle swarm optimization (ANN-PSO), adaptive neuro-fuzzy inference system combined with particle swarm optimization (ANFIS-PSO), random forest (RF), and long short-term memory (LSTM). The comparison of the prediction accuracies of such different intelligent system approaches revealed that ANN-PSO, RF, and LSTM satisfactorily simulated the nonlinear process of SSL. Carefully comparing the results, the ANN-PSO model showed a slight superiority over the RF and LSTM models, with RMSE = 67.2990 kg/s in the Chemourah basin and RMSE = 55.8737 kg/s in the Gareat el tarf basin. [ABSTRACT FROM AUTHOR]

To reduce downstream ecological damage, it is crucial to analyze water and salt sources in saline–alkali farmland drainage and optimize soil salt discharge. This study employs statistical, hydrochemical, and isotope methods to identify controlling factors and characteristics in water bodies during winter irrigation. The results show average TDS values of 0.59, 6.40, and 4.14 g/L for irrigation, phreatic, and drainage water. Irrigation and phreatic water mainly belong to the HCO3-Ca·Mg·Na and Cl·SO4-Na·Mg types. Na+/(Na+ + Ca2+) and Cl−/(Cl− + HCO3−) values suggest the rock–water interaction and evaporation influences in irrigation water, while evaporation primarily controls phreatic water. The main salt types include NaCl, MgSO4, Na2CO3, and CaCO3 for irrigation water and NaCl, MgSO4, Na2SO4, and CaCO3 for phreatic water. These findings lay a research basis for analyzing water and salt sources in farmland drainage during winter irrigation in saline–alkali land. [ABSTRACT FROM AUTHOR]