Effective Management Of Water Resources Research Articles

An Investigation of Hydrological Drought Characteristics in Kızılırmak Basin, Türkiye: Impacts and Trends

Drought is a natural disaster that is generally defined as precipitations which are significantly below the precipitation recorded in normal times. Drought has been classified as meteorological, hydrological, agricultural, and socio-economic by many researchers. Hydrological drought takes place when deficiencies in the surface and ground waters occur as a result of the long-term lack of precipitation. In this study, a hydrological drought analysis has been performed for Kızılırmak Basin which is the second biggest basin of Turkey by using streamflow drought index (SDI) and innovative trend analysis (ITA) for the time scales of 1, 3, 6, 9, 12-month. Monthly mean streamflow records of 7 stations are obtained from the General Directorate of State Hydraulic Works (DSİ). Drought severity and drought duration which is two important drought characteristics have been calculated for each time scale with their occurrence term. Results have shown that Mild Drought and Wet (SDI≥0) have the highest percentage of occurrences. Using Run Theory, the longest lasted and highest drought has been noted in the SDI-12-time scale of E15A017 station with 149.72 and 103 months as severity and duration, respectively. From the highest severity and longest lasted droughts, it is seen that starting with 2000, the basin is exposed to the highest occurrence of droughts. ITA results have shown that in most of the SDI series of any time scale a trend is existent and these trends are mostly decreasing trends. Therefore, the results of this have shown that the basin needs to be kept from the potential effects of droughts with effective water resources management plan.

Targeting of rainwater harvesting structures using geospatial tools and analytical hierarchy process (AHP) in the semi-arid region of Rajasthan (India).

Burgeoning population growth and subsequent demand for freshwater, besides competition among irrigation, domestic, and industrial sectors, coupled with a changing climate, have necessitated prudent and effective management of water resources. Rainwater harvesting (RWH) is considered one of the most effective strategies for water management. However, the location and design of RWH structures are essential for proper implementation, operation, and maintenance. An attempt has been made in this study to locate the most suitable site for RWH structure and design using one of the robust multi-criteria decision analysis techniques, viz. analytic hierarchy process, using geospatial tools in the Gambhir watershed, Rajasthan, India. High-resolution Sentinel-2A data and a digital elevation model of the Advanced Land Observation Satellite were used in this study. Five biophysical parameters, viz. land use and land cover, slope, soil texture, surface runoff, and drainage density, were considered to identify suitable locations for RWH structures. It was observed that runoff is the prime factor in determining the location of RWH structures compared to other parameters. It was revealed that 75.54 km2 (13% of the total area) was very highly suited for the construction of RWH structures, while 114.56 km2 (19%) was highly suitable. A total of 43.77 km2 (7%) of land was determined to be unsuitable for the construction of any type of RWH structure. Farm ponds, check dams, and percolation ponds were suggested for the study area. Furthermore, Boolean logic was used to target a particular type of RWH structure. The study indicated that a total of 25 farm ponds, 14 check dams, and 16 percolation ponds can be constructed at identified locations in the watershed. Water resource development maps of the watershed generated using an analytical approach would be useful for policymakers and hydrologists for targeting and implementing RWH structures in the study watershed.

Trends and Variability in Flood Magnitude: A Case Study of the Floods in the Qilian Mountains, Northwest China

Analyzing trends in flood magnitude changes, and their underlying causes, under climate change, is a key challenge for the effective management of water resources in arid and semi-arid regions, particularly for inland rivers originating in the Qilian Mountains (QMs). Sen’s slope estimator and the Mann–Kendall test were used to investigate the spatial and temporal trends in flood magnitude, based on the annual maximum peak discharge (AMPD) and Peaks Over Threshold magnitude (POT3M) flood series, of twelve typical rivers, from 1970 to 2021. The results showed that, in the AMPD series, 42% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends; in the POT3M series, 25% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends. The regional differences in the QMs from east to west were that, rivers in the eastern region (e.g., Gulang, Zamu, and Xiying rivers) showed significantly decreasing trends in the AMPD and POT3M series; most rivers in the central region had non-significant trends, while the Shule river in the western region showed a significantly increasing trend. Temperatures and precipitation showed a fluctuating increasing trend after 1987, which were the main factors contributing to the change in flood magnitude trends of the AMPD and POT3M flood series in the QMs. Regional differences in precipitation, precipitation intensity, and the ratio of glacial meltwater in the eastern, central and western regions, resulted in the differences in flood magnitude trends between the east and west.

Spatio-temporal change monitoring for surface water on the Qinghai-Tibet Plateau from 1990 to 2020 using remote sensing

Detecting and analyzing changes of water resources is critical for human survival and societal development in the Qinghai Tibet Plateau (QTP). We implemented the cosine similarity method to complete the migration of samples and achieve a more accurate random forest classifier (mean Kappa = 0.872) for each period. Based on these classifiers and 45,370 Landsat images, we estimated the surface water distribution of the QTP for six periods between 1990 and 2020 based on the Google Earth Engine platform. The results indicate that the QTP has a surface water area of 57,229 ± 3,248 km2 (1990–1995), 58,444 ± 3,248 km2 (1996–2000), 67,319 ± 3,704 km2 (2001–2005), 67,399 ± 2,798 km2 (2006–2010), 70,286 ± 3,033 km2 (2011–2015), 75,176 ± 2,785 km2 (2016–2020), that the area of water rose by ap-proximately 31.3% and continued to increase. The area of permanent water remained constant between 1990 and 2020 at 47,280 km2. On the QTP, the change in water area can be split into four regions: rapid increase (Qiangtang Plateau), slow increase (eastern basins), decrease (northern and northeastern basins), and relatively stable (southern basins). About 186,408 km2 area of land is significantly losing water bodies, while about 589,567 km2 area of land is significantly gaining water bodies. This study provides higher accuracy temporal distribution data of water bodies in the Qinghai-Tibet Plateau, and quantitatively evaluates the area changes of water bodies from multiple spatial scales. Research provides an important scientific reference for hydrological research and effective management of water resources in important rivers in the QTP.

Geochemical characterization, its controlling factors, and comparison between the upstream and downstream segments of the Himalayan Satluj River basin, India

Satluj River Basin (SRB) has special economic significance, representing the country's most incredible hydro-structure with fresh water, a primary source of irrigation and hydroelectric power in Northern India. Therefore, SRB's geochemical characterization is vital for hydropower and agricultural sustainability. This study provides a preliminary characterization of the hydrogeochemical processes controlling the natural water evolution in SRB by observing the spatial variation and qualitative assessment of solute chemistry (major ions and trace/heavy elements) in the Satluj river, associated tributaries, and groundwater. Hydrochemical characteristics displayed the predominance of geogenic weathering processes with carbonates dissolution and silicate weathering as end members that could explain all the geochemical variability within the SRB. The results reveal that the chemical signature of the upstream segment is possibly influenced more by carbonate weathering than silicate weathering, and the trends reverse in the downstream section with the increasing influence of silicate weathering. Dissolved heavy metals (HMs) such as Mn, Cr, Fe, Co, Ni, Cu, Zn, As, Cd, and Pb showed large fluctuations among upstream and downstream sampling sites, indicating diverse environmental conditions. Human health risk assessment (HHRA) studies revealed less or no potential noncarcinogenic via HMs, except for the downstream stretch of tributaries inferring increased non-cancerous risk. Moreover, the HHRA with HMs (Cr, As, Cd, and Pb) manifested high carcinogenic risks for adults and children across the SRB. The finding of this study could be the baseline dataset for assessing the future status, effective management, and better utilization of water resources of the SRB.

ESTIMATION OF WHEAT CROP PRODUCTIVITY OF DISTRICT NAWAB SHAH USING METRIC EEFLUX IMAGERY

Water scarcity and food security are global concerns, which require morefood production from less water. Therefore, for effective management of water resources and improved food production, identification of Crop water Productivity (CWP) is of prime importance. Current study was conducted at Center for Advanced Studies in Water, Mehran University of Engineering and Technology, Jamshoro, Pakistan during year 2020 estimates CWP of wheat during the Rabi season (winter season) in the Nawab Shah District of Sindh (located in Rorhi canal command area) using Mapping Evapotranspiration at High Resolution with internalized calibration (METRIC) - Earth Engine Flux (EEFLUX) application. Cloud corrections were applied where cloud cover was approximately 50% and missing data were interpolated. Actual evapotran spiration (ETa ) for each season (initial, development, mid and late, required for estimating CWP) were calculated from reference evapotranspiration (ETr ) by evapotranspiration factor (ETr F) which were available at the Food and Agriculture Organization (FAO) website, using geographical information system software package (ARC-GIS). Total ETa for the entire season came out to be 367.57 mm. Inshort, wheat crop productivity can be assessed by using matric EEFLUX imagery

Yield and yield quality characteristics of two varieties of sweet potato under different watering intervals ​

Climate change significantly impacts sweet potato production because of the high potential for drought conditions. Understanding the regional impacts of climate change on the irrigation interval is important for effective water resource management. This study aims at determining the influence of the irrigation interval on the drought tolerance responses of two new sweet potato varieties from Universitas Padjadjaran. The experiment was arranged in a randomized block design (RBD) with two factors. The first factor was two varieties of sweet potato i.e. Awachy-1 (Orange-Fleshed) and Biang (Purple-Fleshed); and the second factor was the irrigation interval (1, 3, 5 and 7 days). This research was conducted in a screen house of Ciparanje experimental field station, Universitas Padjadjaran Jatinangor. Experimental results showed no interaction between the irrigation intervals and the varieties on the sweet potato's yield components and nutritional content. Biang provided the most optimal result regarding the number of tubers and dry mass, despite being watered once every three days. Biang also produced a higher number of tubers, shorter sweet potato length and higher dry weight than Awachy-1 in every irrigation interval. Biang also showed a higher value for nutritional content than Awachy 1 on total soluble solids, sugar and carbohydrate content. The optimal water usage to store the root yield of Biang and Awachy-1 is one to three days of irrigation intervals on the sweet potato’s tuber diameter and the plant's dry weight. However, the irrigation interval that most significantly improved the weight of the tuber was one day, while the increased nutritional content of the tuber was three days. Biang and Awachy-1 cultivars could survive under drought conditions, although some yield components had decreased. These results suggested that the varieties or watering interval affected sweet potato growth and yield components.

Variability in trends of streamflow and precipitation in the Narmada River Basin over the past four decades

AbstractHydrological climate variables such as precipitation, temperature, humidity, evapotranspiration, infiltration, and streamflow provide useful information for the effective planning, design, and management of water resources. In the present study, monthly precipitation and streamflow data were analyzed to assess the variability in trends of precipitation over the Upper Narmada Basin (UNB), Middle Narmada Basin (MNB), and Lower Narmada Basin (LNB) for 41 years (1981–2021) using the widely accepted Mann–Kendall Test (MKT), Innovative Trend Analysis (ITA), and magnitude by Sen's Slope estimator, thereby extending further by a decade, the last study by Thomas and others in 2015. The inclusion of more factors affecting the streamflow in response to the rainfall often makes the model very complex and unreliable. In the present study, to overcome this limitation, a simple yet most definite correlation was established between rainfall and streamflow, which can serve as a meaningful indicator of basin behavior. Poor correlation was observed for the UNB and the MNB compared to the LNB, which may be attributed to the presence of tributaries. The result of this study will be helpful to policymakers and water resource managers to plan and adopt suitable schemes of water conservation and management in the Narmada basin.

Modeling of Flow Rate at Sukkur Barrage using Artificial Neural Networks (ANNs)

Modeling of flow discharge plays a significant role in effective planning, sustainable usage, development, and management of water resources in short (hourly) and long-term (monthly) temporal categories. Since the inception of managing water resources, various techniques such as conceptual, metric, and physical models have been introduced all of these require a large amount of data, labor, and expense to be incorporated to obtain reliable results, due to which Artificial Intelligence methods were introduced that require less amount of data, time, expense and as well as experience to model flow discharge. In this research study, an attempt was made by employing two different artificial neural network techniques feedforward neural networks (FFNN), and time-lagged neural networks (TLNN) to model and predict the river flow discharge at daily and monthly timescale. 2010 and 503 no. of observations were used for model calibration and validation in daily time scale while 557 and 139 observations were used in monthly timescale. The result of the study revealed that the FFNN modeling approach has captured the daily and monthly stream flow variability very well than the TLNN model with R2 of 0.91 on the daily and 0.71 on the monthly time scale while R2 for the TLNN model was 0.79, and 0.34 for daily and monthly timescale. This indicates that the FFNN technique requires less no. of observations and is more reliable than TLNN and can be used to model river flow.

Evaluation of Precipitation Estimates from Remote Sensing and Artificial Neural Network Based Products (PERSIANN) Family in an Arid Region

Accurate and continuous rainfall monitoring is essential for effective water resources management, especially in arid and semi-arid regions such as the United Arab Emirates (UAE). Significant spatio-temporal precipitation variation in the UAE necessitates the use of the latest techniques to measure rainfall intensity accurately. This study investigates the consistency and applicability of four satellite precipitation products, namely PERSIANN, PERSIANN-CCS, PERSIANN-CDR, and PDIR-Now, over the UAE. Daily time series data from 2011 to 2020 were analyzed using various statistical measures and climate indices to develop the belief in the products and for their inter-comparison. The analysis revealed that the average probability of detection (POD) for PDIR and CDR was the highest, with values ranging from 0.7–0.9 and 0.6–0.9, respectively. Similarly, CDR has a better Heidke Skill Score (HSS) with an average value of 0.26. CDR outperformed its counterparts with an average correlation coefficient value of 0.70 vs. 0.65, 0.40, and 0.34 for PDIR, CCS, and PERSIANN, respectively. Precipitation indices analysis revealed that all the products overestimated the number of consecutive wet days by 15–20%, while underestimating consecutive dry days by 5–10%. The quantitative estimations indicate that all the products were matching with the gauge values during the wet months (January–April), while they showed significant overestimation during the dry months. CDR and PDIR were in close agreement with the gauge data in terms of maximum daily rainfall with an error of less than 10% for both products. As compared to others, PERSIANN-CDR provided better estimates, particularly in terms of capturing extreme rainfall events and spatial distribution of rainfall. This study provides the first comprehensive evaluation of four PERSIANN family products based on recent daily rainfall data of UAE. The findings can provide future insights into the applicability and improvement of PERSIANN products in arid and semi-arid regions.

A novel framework for water accounting and auditing for efficient management of industrial water use

The importance of industrial water resource management has increased owing to the increasingly significant issues of global water scarcity and water environmental degradation, which results in the need for more precise data as well as more advanced management strategies. The majority of industrial water resource management frameworks currently in use fall short in their attempts to perform microscopic section accounting and analysis and are unable to fully obtain and effectively implement product information regarding water. This unquestionably made it more challenging to pinpoint the effects of production pollution, accomplish efficient water conservation in industry, and raise the bar for meticulous management of water resources. Therefore, this paper proposes a novel framework for water accounting and auditing that combines traditional water accounting and water mass balance for measuring, evaluating, and diagnosing water flowing in various production links as well as water finance, to facilitate the effective management of industrial water resources and their integration with enterprise benefits management. Specifically, the framework suggests a new accounting structure that successfully connects the conventional water accounting system with the exact quantitative and economic accounting of industrial production links by revamping the title and substance of water accounting. As opposed to traditional water accounting and industrial water mass balance analysis, this will further improve the system's ability to track internal, intricate production links and the economics of industrial water management, respectively. The case study shows that this framework has considerable benefits for industrial companies in terms of water efficiency, product structure, and cleaner production, which better fits the goal of creating a water-saving society and the global industrial water resources management strategy.

Dam inflow prediction using large-scale climate variability and deep learning approach: a case study in South Korea

AbstractAccurate prediction of dam inflows is essential for effective water resources management in terms of both water quantity and quality. This study aims to develop a Long Short-Term Memory (LSTM) deep learning-based monthly dam inflow prediction model using large-scale climate indices. Six climate indices, Atlantic multidecadal oscillation (AMO), El Niño–southern oscillations (ENSO), North Atlantic oscillation (NAO), Pacific decadal oscillation (PDO), Niño 3.4, and Southern Oscillation Index (SOI) for the period of 1981–2020, were used as input variables of the model. The proposed model was trained with 29 years of data (1981–2009) and tested with 12 years of data (2009–2020). We investigated 29 input data combinations to evaluate the predictive performance according to different input datasets. The model showed the average values of metrics ranged from 0.5 to 0.6 for CC and from 40 to 80 cm for root mean square error (RMSE) at three dams. The prediction results from the model showed lower performance as the lead time increased. Also, each dam showed different prediction results for different seasons. For example, Soyangriver/Daecheong dams have better accuracy in prediction for the wet season than the dry season, whereas the Andong dam has a high prediction ability during the dry season. These investigations can be used for better efficient dam management using a data-driven approach.

Hydrogeochemical and Stable Isotope Data of the Groundwater of a Multi-Aquifer System in the Maknessy Basin (Mediterranean Area, Central Tunisia)

The Maknessy plain in central Tunisia is one of the most important agricultural basins in Tunisia. Given the semi-arid climate conditions, the irrigation of cultivated crops relies principally on the abstraction from groundwater resources. The assessment of the quality of the used water for agricultural purposes is crucial for safe production. Thus, the objective of this work is to assess the physicochemical quality of the irrigation water resources in this catchment area using a combined chemical, isotopic, and statistical approach. The waters analyzed are represented by two types of groundwater, mainly calcium hyper chloride and calcium sulfate. A multivariate statistical analysis (PCA and HCA) and a geochemical approach have been applied to study water quality as a function of chemical parameters, showing that the EC and TDS are the parameters influencing water quality. The stable isotopic compositions of the sampled waters range from −7.53 to −4.90% vs. VSMOW and from −53.6 to −32.2% vs. VSMOW for δ18O and δ2H; they show the exchange between groundwater and rock and the evaporation effect. The isotopic data form three groups such as recent water, paleowater, and mixing water indicate the evaporation effect and interaction of the groundwater, and confirm that this aquifer has been recharged by current rainwater. So, these aquifers were recharged by precipitation derived from a mixture of cloud masses from the Atlantic Ocean and the Mediterranean Sea. The findings of this research are of important relevance for effective water resources management in this agro-based region. Indeed, the increased exploitation of these resources will induce a continuous reduction in the available resources and progressive degradation of the used water quality that may adversely impact the safe agricultural production and the economic resilience of the local population.

Future climate and its potential impact on the spatial and temporal hydrological regime in the Koshi Basin, Nepal

Study regionKoshi River basin, Eastern Nepal. Study focusClimate change is increasingly evident as the global surface temperature is warming with erratic rainfall patterns across the globe. In this regard, the Koshi Basin in the Himalayan region is also impacted, and it is important to understand the spatio-temporal details of the impact in the basin under future climate change. This study assessed the potential climate change and its impact on the hydrological regime using the Soil and Water Assessment Tool (SWAT) and Indicators of Hydrological Alteration (IHA) based on RCP4.5 and RCP8.5 of ensemble downscaled CMIP5 GCM runs. New hydrological insights for this regionResults show the upper part of the basin warming faster than the lower part, the pre-monsoon season warming more than other seasons. There is no clear uniform trend in precipitation. However, the southeastern part of the basin will get more precipitation. Sub-basins will get more precipitation during the post-monsoon under RCP4.5, and during the monsoon under RCP8.5. The annual water availability will not decline but water availability within seasons and regions is projected to be highly variable. There is also a change in the spatial pattern of river discharge and the western part of the basin is likely to experience more impact. Therefore, these findings will be valuable in identifying how particular sub-basins within the Koshi Basin will be impacted by climate change and in stipulating effective planning and management of water resources for the future.

Assessment of Runoff Components of River Flow in the Karakoram Mountains, Pakistan, during 1995–2010

Glaciers are generally believed to be subjugating by global warming but the Karakoram glaciers are reportedly maintaining their balance. Earlier studies in the Karakoram and its sub-basins have mostly addressed a short span of time and used complex models to understand the phenomenon. Thus, this study is based on a long-term trend analysis of the computed runoff components using satellite data with continuous spatial and temporal coverage incorporated into a simple degree day Snowmelt Runoff Model (SRM). The trends of melt runoff components can help us understanding the future scenarios of the glaciers in the study area. The SRM was calibrated against the recorded river flows in the Hunza River Basin (HRB). Our simulations showed that runoff contribution from rain, snow, and glaciers are 14.4%, 34.2%, and 51.4%, respectively during 1995–2010. The melting during the summer has slightly increased, suggesting overall but modest glacier mass loss which consistent with a few recent studies. The annual stream flows showed a rising trend during the 1995–2010 period, while, rainfall and temperatures showed contrasting increasing/decreasing behavior in the July, August, and September months during the same period. The average decreasing temperatures (0.08 °C per annum) in July, August, and September makes it challenging and unclear to explain the reason for this rising trend of runoff but a rise in precipitation in the same months affirms the rise in basin flows. At times, the warmer rainwater over the snow and glacier surfaces also contributed to excessive melting. Moreover, the uncertainties in the recorded hydrological, meteorological, and remote sensing data due to low temporal and spatial resolution also portrayed contrasting results. Gradual climate change in the HRB can affect river flows in the near future, requiring effective water resource management to mitigate any adverse impacts. This study shows that assessment of long-term runoff components can be a good alternative to detect changes in melting glaciers with minimal field observations.

РОЗВИТОК НАУКОВОГО ЗАБЕЗПЕЧЕННЯ ВОДНИХ МЕЛІОРАЦІЙ НА ЗРОШУВАНИХ ЗЕМЛЯХ УКРАЇНИ: ІСТОРІОГРАФІЯ ПЕРІОДУ НЕЗАЛЕЖНОСТІ

It was established that during the period of Ukraine’s independence, historiography began to play the role of an integration factor, maintaining the appropriate level of scientific knowledge, preserving and supplementing the methodological apparatus of modern historical science. It has been found that in recent decades, a number of meaningful scientific works have been published, which contain systematized factual material on the development of scientific support for water reclamation on irrigated lands of Ukraine, a thorough analysis of scientific technologies and their theoretical generalizations. It was determined that the historical works of the period of Ukraine’s independence are characterized by the multi-facetedness and content of generalizations, the objectivity of approaches to the study of the evolution of the scientific-organizational foundations of the use of water resources for land irrigation. Historical works highlight the evolution of certain scientific directions, theories, concepts and technologies regarding the improvement of water reclamation in agrarian production on irrigated lands; development of scientific foundations of effective management of water resources for agricultural land reclamation; the contribution of higher education institutions, and scientific-research institutions and research teams to the development of scientific technologies for the conservation and balanced use of water resources in irrigated farming; the evolution of the working and practical implementation of water reclamation on irrigated lands in the context of the activities of well-known agrarian scientists of Ukraine. It was established that at the beginning of the 21st century, thanks to the cooperation of Ukrainian and foreign scientists, the working and implementation of innovative technologies for the ecologically safe use of water and land resources gained significant development and has great prospects, especially in conditions of climate change. An own position has been formed regarding the choice of the most accurate and scientifically based reflection of the historical development of scientific support for water reclamation on irrigated lands of Ukraine, which is updated in the conditions of global challenges and threats today.

Расчет коэффициента естественной зарегулированности стока рек Калининградской области по результатам наблюдений 2020 г.

Effective management of water resources in the river basin is impossible without information about the intra-annual distribution of runoff and its regularities. To analyze the intra-annual distribution of river discharge, graphs of the change in flow over time and curves for the provision of average daily discharges are used. The share of the basic runoff in the year under consideration is estimated using the coefficient of natural flow regulation (CNFR). The CNFR is taken into account when solving engineering and scientific problems. The value of CNFR is determined according to the graph of the supply curve for average daily expenses or by another approximate method. This article uses a previously developed method for calculating CNFR in the Mathcad environment. The values of CNFR for the rivers of the Kaliningrad region are calculated based on the results of observations of average daily discharges in 2020 obtained from the Automated Information System for State Monitoring of Water Bodies of the Russian Federation for eight hydrological posts. It has been established that 2020 in the Kaliningrad region was characterized by low water content. Under these conditions, the CNFR of the rivers of the region turned out to be noticeably higher than that of the rivers of the North-West of Russia. The exception was the rivers Instruch and Zlaya. It is determined that CNFR has a close stochastic relationship with the ratio of the average and maximum flow of this river. The growth trend of CNFR can be traced with an increase in the area of the catchment area.

Near-term forecasting of water reservoir storage capacities using long short-term memory

Abstract Predicting reservoir storage capacities is an important planning activity for effective conservation and water release practices. Weather events such as drought and precipitation impact water storage capacities in reservoirs. Predictive insights on reservoir storage levels are beneficial for water planners and stakeholders in effective water resource management. A deep learning (DL) neural network (NN) based reservoir storage prediction approach is proposed that learns from climate, hydrological, and storage information within the reservoir’s associated watershed. These DL models are trained and evaluated for 17 reservoirs in Texas, USA. Using the trained models, reservoir storage predictions were validated with a test data set spanning 2 years. The reported results show promise for longer-term water planning decisions.

Ecological integrity of a medium‐sized river of a lake basin towards ecosystem health management

AbstractThis study demonstrates the use of a multi‐metric Fish Index of Biotic Integrity (FIBI) for assessment of ecological health of a medium‐sized river, under a gradient of human disturbances in the Kenyan side of the Lake Victoria Basin (LVB). Development of the index is based on water quality, river habitat quality and fish community attributes. The river was sampled from 2019 to 2020 during wet and dry seasons of the year at nine selected sites along its length based on the level of human disturbance. A total of nine metrics representing the structural and functional organization of fish communities were qualified using the separation power of Mann–Whitney U test (p < .05). Metric values at unimpaired, intermediate, impaired and no‐fish sites were used to establish the scoring criteria using inter‐quartile ranges. A 1, 3, 5 scoring system representing high, fair and slight deviation from the best site, respectively, was used in the final FIBI development. River mouth station had the highest FIBI score of 43, with extensive natural riparian buffer vegetation (>20 m) and 18 fish species implying least human disturbance. The midstream section had intermediate FIBI scores of 34–36, with wide natural riparian buffer vegetation (10–20 m) and 6–9 fish species that represented moderate human disturbance. The upstream section had the least FIBI score of 0, with no fish and narrow riparian buffer vegetation (<5 m) that indicated notable degradation. This study presents the preliminary results of using fish and habitat metrics for development of an Index of Biotic Integrity (IBI) for a medium‐sized river in a lake basin, as a decision‐making support tool for effective management and conservation of water resources. The study recommends restoration of river habitat quality for improved ecological integrity of rivers in the Lake Victoria Basin.

A fuzzy based model for rainfall prediction

Of all the current challenges faced by Jordan, the most severe is the inadequacy of the water supply. The country is almost entirely reliant on rainfall, whose pattern, however, is highly variable in terms of its frequency, regularity, and quantity. Evidently, therefore, the ability to anticipate rainfall accurately is critically important for the effective planning and management of water resources in Jordan, and particularly in agricultural areas. Influenced by a range of factors such as temperature, relative humidity, and wind speed, rainfall is a stochastic process. This paper suggests the use of a fuzzy model that draws upon data gathered at 26 stations situated in a range of locations throughout Jordan. The model is capable of forecasting seasonal rainfall relating to a specific station. Its ability to deliver predictions with an acceptable degree of accuracy has been demonstrated, and it can be concluded from this that the fuzzy technique can provide a model that is capable of efficiently forecasting seasonal rainfall.