*Article* **Soil Erosion and Sediment Load Management Strategies for Sustainable Irrigation in Arid Regions**

**Muhammad Tousif Bhatti 1,\* , Muhammad Ashraf 2,\* and Arif A. Anwar <sup>1</sup>**


**Abstract:** Soil erosion is a serious environmental issue in the Gomal River catchment shared by Pakistan and Afghanistan. The river segment between the Gomal Zam dam and a diversion barrage (~40 km) brings a huge load of sediments that negatively affects the downstream irrigation system, but the sediment sources have not been explored in detail in this sub-catchment. The analysis of flow and sediment data shows that the significant sediment yield is still contributing to the diversion barrage despite the Gomal Zam dam construction. However, the sediment share at the diversion barrage from the sub-catchment is much larger than its relative size. A spatial assessment of erosion rates in the sub-catchment with the revised universal soil loss equation (RUSLE) shows that most of the sub-catchment falls into very severe and catastrophic erosion rate categories (>100 t h−1y −1 ). The sediment entry into the irrigation system can be managed both by limiting erosion in the catchment and trapping sediments into a hydraulic structure. The authors tested a scenario by improving the crop management factor in RUSLE as a catchment management option. The results show that improving the crop management factor makes little difference in reducing the erosion rates in the sub-catchment, suggesting other RUSLE factors, and perhaps slope is a more obvious reason for high erosion rates. This research also explores the efficiency of a proposed settling reservoir as a sediment load management option for the flows diverted from the barrage. The proposed settling reservoir is simulated using a computer-based sediment transport model. The modeling results suggest that a settling reservoir can reduce sediment entry into the irrigation network by trapping 95% and 25% for sand and silt particles, respectively. The findings of the study suggest that managing the sub-catchment characterizing an arid region and having steep slopes and barren mountains is a less compelling option to reduce sediment entry into the irrigation system compared to the settling reservoir at the diversion barrage. Managing the entire catchment (including upstream of Gomal Zam dam) can be a potential solution, but it would require cooperative planning due to the transboundary nature of the Gomal river catchment. The output of this research can aid policy and decision-makers to sustainably manage sediment erosion issues of the irrigation network.

**Keywords:** soil erosion; sediment yield; RUSLE; sediment transport modeling; Gomal River; arid regions

### **1. Introduction**

Soil erosion in catchments occurs in various forms such as sheet, rill, gully, river bed and bank erosion, and landslides that contribute sediments to the water bodies. The rate of erosion is primarily determined by the erosive events (e.g., short duration and high-intensity rainfall events), soil type, and characteristics of the terrain [1]. The impacts of accelerated soil erosion processes can be severe, not only through land degradation and fertility loss but through a conspicuous number of off-site effects such as sedimentation, siltation, and eutrophication of waterways or enhanced flooding [2]. Soil erosion rates are exacerbated for the arid and semi-arid regions due to barren mountains with scattered vegetation that provide direct exposure to heavy rainfall. For example, 50% of the soil loss

**Citation:** Bhatti, M.T.; Ashraf, M.; Anwar, A.A. Soil Erosion and Sediment Load Management Strategies for Sustainable Irrigation in Arid Regions. *Sustainability* **2021**, *13*, 3547. https://doi.org/10.3390/ su13063547

Academic Editors: Muhammad Sultan, Yuguang Zhou, Redmond R. Shamshiri and Aitazaz A. Farooque

Received: 6 February 2021 Accepted: 17 March 2021 Published: 23 March 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

occurs in Pakistan during the monsoon season [3] causing huge sediment load diverted into the irrigation canals. Also, landslides and debris flow from the catchment increase the sediment load in the river flows. The eroded sediments finally deposit in reservoirs, stream channels, irrigation canals, and water conveyance structures and reduce the capacities of these water bodies to perform their prime functions and often requires costly treatments [1,4].

Soil erosion and the fate of eroded sediments are widely recognized as one of the major environmental concerns worldwide. The results of soil erosion rate for the year 2012 published in a global study [5] show that South America, Africa, and Asia had respectively 8.3%, 7.7%, and 7.6% of the continental area in high erosion rate classes (>10 t ha−1yr−<sup>1</sup> ). In the global map of soil erosion rates in [5], the northern parts of Pakistan (where the study area of this research lies) fall in the range of vulnerable to high erosion rates (>50 t ha−1yr−<sup>1</sup> ).

Sustainable irrigation requires appropriate soil erosion and sediment load management options and strategies both at the catchment level and the diversion structures. The catchment management options such as improved vegetation, slope stabilization, etc. are often considered preferred solutions to limit soil erosion rates as opposed to the structural measures for its control. However, in some cases, it becomes impractical to achieve anticipated benefits of the catchment management interventions amid factors such as; steep terrain, transboundary nature, urgency and severity of the challenges, etc. Another critical factor to consider is the feasibility of implementing such interventions.

Significant sediment entry from river flows may reduce the discharge capacity of irrigation canals up to 40% due to the settlement of coarse particles [6]. Many remedial measures have been suggested by different researchers to reduce the sediment load in canals, e.g., 41% using silt excluder [7], up to 40% using submerged vanes [8], and 40–45% using the vortex tube sediment extractor [9]. These structural measures only remove the coarser sediment in the canals; therefore, settling basins are assumed more appropriate options of sediment control for both coarser and finer particles [10]. Dredging of deposited sediment from irrigation networks also requires considerable effort and cost that farmers often have to put in. Similarly, the control of sediment load at the diversion structure depends on the feasibility of the proposed solution [11]. Hence, before making investment decisions, it is more practical to identify the targeted areas (i.e., hotspot analysis) in the case of opting for catchment management options. In the case of remedial measures (e.g., a hydraulic structure proposed to control sediment entry) the simulation model can be useful to predict the impacts of the proposed intervention on sustainable irrigation supplies.

Pakistan and Afghanistan share three main rivers, namely the Kabul, Kurram, and Gomal rivers. The Gomal river is the smallest among these three in terms of average annual inflow, but it is an essential source of livelihood for the downstream users in the Khyber Pakhtunkhwa (KP) province of Pakistan. The combined average flow of Kabul, Kurram, and Gomal rivers is 23.58 Gm<sup>3</sup> yr−<sup>1</sup> , out of which the Gomal river contributes 4.1% (0.974 Gm<sup>3</sup> yr−<sup>1</sup> ). The physical infrastructures in the Gomal river catchment on the Pakistan side comprise a storage dam, two powerhouses, a diversion barrage, and a canal irrigation system to irrigate more than 77,000 ha of agricultural land.

Afghanistan is the upstream riparian on all shared rivers with Pakistan, including the Gomal river. The eroded sediment from the catchment in Afghanistan finds its fate in the reservoir of the Gomal Zam (GZ) dam and periodically sluiced in the downstream river reach. In the absence of a joint river management agreement between Pakistan and Afghanistan, integrated catchment management intervention cannot be introduced effectively. There is also no data-sharing mechanism between the two catchment-sharing countries.

The Gomal river brings a considerable amount of sediments to the diversion barrage, as shown in Figure 1. This sediment is a combination of soil eroded by rainfall in the sub-catchment below the GZ dam and the sediment generated in the catchment upstream of the GZ dam. Hydro-meteorological monitoring is very limited in the catchment area. Furthermore, the sediment flushing operation at the GZ dam is ad hoc, and its concentration

in the outflows is not monitored. All this makes the catchment of the Gomal river a datasparse catchment. When sediment-laden flow enters into the irrigation canal network, the sediments settle down in the channels and impede the conveyance capacity of the canals. This deprives the downstream users of their due share and gives rise to social unrest and conflicts. tration in the outflows is not monitored. All this makes the catchment of the Gomal river a data-sparse catchment. When sediment-laden flow enters into the irrigation canal network, the sediments settle down in the channels and impede the conveyance capacity of the canals. This deprives the downstream users of their due share and gives rise to social unrest and conflicts.

The Gomal river brings a considerable amount of sediments to the diversion barrage, as shown in Figure 1. This sediment is a combination of soil eroded by rainfall in the sub-catchment below the GZ dam and the sediment generated in the catchment upstream of the GZ dam. Hydro-meteorological monitoring is very limited in the catchment area. Furthermore, the sediment flushing operation at the GZ dam is ad hoc, and its concen-

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**Figure 1.** Sediment conditions at the diversion barrage. (**a**) High sediments concentration at downstream of the under sluice sections of the barrage as a result of flushing from GZ dam during 9–10 May 2019; (**b**) View of the main canal from canal head regulator on 10 May 2019. **Figure 1.** Sediment conditions at the diversion barrage. (**a**) High sediments concentration at downstream of the under sluice sections of the barrage as a result of flushing from GZ dam during 9–10 May 2019; (**b**) View of the main canal from canal head regulator on 10 May 2019.

> The decisions to manage erosion rates in the catchment and eroded sediments in the water conveyance system are informed by the erosion/sediment assessment studies. These assessments help identify catchment areas with high soil erosion susceptibility and a clear understanding of the system's operation. The revised universal soil loss equation (RUSLE) is commonly used to assess soil erosion rates. Soil loss predictions are frequently unrealistic because the methods used to estimate the soil loss equation's factors are empirically derived. Therefore, the methodology section emphasizes the selection of suitable methods to determine RUSLE's factors. Few studies have identified the impact of RUSLE factors on soil loss. For example, both ref [12,13] concurred in their findings that the topographic factor is the most significant factor among others, affecting the soil erosion rates. On the other hand, ref [14] has found that improving the support practice factor by adopting terracing showed a reduction in sediment yields. Previous studies show that no one rule fits all when investing in catchment management interventions. The decisions to manage erosion rates in the catchment and eroded sediments in the water conveyance system are informed by the erosion/sediment assessment studies. These assessments help identify catchment areas with high soil erosion susceptibility and a clear understanding of the system's operation. The revised universal soil loss equation (RUSLE) is commonly used to assess soil erosion rates. Soil loss predictions are frequently unrealistic because the methods used to estimate the soil loss equation's factors are empirically derived. Therefore, the methodology section emphasizes the selection of suitable methods to determine RUSLE's factors. Few studies have identified the impact of RUSLE factors on soil loss. For example, both ref [12,13] concurred in their findings that the topographic factor is the most significant factor among others, affecting the soil erosion rates. On the other hand, ref [14] has found that improving the support practice factor by adopting terracing showed a reduction in sediment yields. Previous studies show that no one rule fits all when investing in catchment management interventions.

> Many studies that employ the RUSLE equation limit their analysis to improve the estimation of potential soil erosion. The input factors in RULSE can be estimated by using values from the literature or adapted for empirical and statistical data in combination with geographic information system (GIS) software [15], and this remains the focus of most of the studies. Many studies that employ the RUSLE equation limit their analysis to improve the estimation of potential soil erosion. The input factors in RULSE can be estimated by using values from the literature or adapted for empirical and statistical data in combination with geographic information system (GIS) software [15], and this remains the focus of most of the studies.

> This paper contributes to the science and application related to soil erosion as it is a critical problem worldwide, and especially in dryland areas. The paper first identifies the sources of sediment in a segment of the Gomal river (between GZ dam and the diversion barrage) in Pakistan. The incoming sediment limits supply in the irrigation system downstream and creates huge maintenance problems. A novel contribution of this study is its solution-oriented approach to the prevailing problem of sedimentation in the water conveyance system. There could be many possible solutions, but this paper has analyzed in detail a catchment management option (preventive) and a structural option (remedial). The analysis consists of erosion rates estimation and their severity level in the This paper contributes to the science and application related to soil erosion as it is a critical problem worldwide, and especially in dryland areas. The paper first identifies the sources of sediment in a segment of the Gomal river (between GZ dam and the diversion barrage) in Pakistan. The incoming sediment limits supply in the irrigation system downstream and creates huge maintenance problems. A novel contribution of this study is its solution-oriented approach to the prevailing problem of sedimentation in the water conveyance system. There could be many possible solutions, but this paper has analyzed in detail a catchment management option (preventive) and a structural option (remedial). The analysis consists of erosion rates estimation and their severity level in the sub-catchment of the Gomal river using a computer-based empirical model. The study is focused on the sub-catchment because it is not transboundary and, therefore, management options can be introduced, monitored, and evaluated with relative ease. The analysis expands on predicting the impact of improved vegetation in the sub-catchment (i.e., crop management factor of RUSLE) as a catchment management option. Finally, a sediment transport model

is used to determine the sediment trapping efficiency of a hypothetical settling reservoir at the diversion barrage.

## **2. Materials and Methods**

### *2.1. The Study Area*

Afghanistan and Pakistan share the catchment of the Gomal river. The Gomal river originates in the mountains of Ghazni province of Afghanistan and enters the South Waziristan district of KP, Pakistan. The total catchment area at Gomal Zam (GZ) dam is 33,950 km<sup>2</sup> , about 70% of the area lies within Pakistan, and the remaining lies in Afghanistan.

The Government of Pakistan constructed the GZ dam (32◦5 05500 N 69◦5205300 E) in South Waziristan district (formerly the South Waziristan Agency of the Federally Administered Tribal Area) with the financial assistance of the United States Agency for International Development (USAID). The construction of the dam started in August 2001 and was completed in April 2011. The dam impounds the Gomal River in a reservoir with 1.41 km<sup>3</sup> storage capacity. The primary purpose of the dam is to supply water to irrigate 77,295 ha of land through a newly built irrigation system in the Tank and Dera Ismail Khan districts of Khyber Pakhtunkhwa province of Pakistan. The additional benefits of the dam are flood control and a modest amount of hydroelectric power generation (17.4 MW).

The Gomal river traverses around 40 km downstream of the dam site where a barrage is constructed near the town of Kot Murtaza, to divert the river flows into the irrigation system. The sub-catchment of this river segment (herein referred to as sub-catchment) is shown in Figure 2. The sub-catchment undergoes erosion and imparts sediments into the river stream, which find their way to the diversion barrage and enters into the canal irrigation system. This not only challenges the management of the irrigation system but also places significant demands on the operations and maintenance budget of the irrigation system.

Figure 2 shows the location and pictures of the GZ dam and diversion barrage. The diversion barrage is 140 m long and 7 m high. Three gates divert water into the main canal; in addition to that, four under sluice gates are also provided as shown in Figure 1a. The barrage is designed to pass a flood of 5200 m<sup>3</sup> s −1 safely. The primary purpose of the GZ dam is to irrigate 77,295 ha of land in two districts of Khyber Pakhtunkhwa province i.e., D I Khan and Tank districts. For this purpose, an irrigation system consisting of the diversion barrage, 60.5 km long main canal, and 206 km of distribution canals have been constructed. The irrigation system is operational since November 2014, except for the portion fed by a branch canal named Waran Canal. A flow and sediment monitoring station is located approximately 2.5 km upstream of the diversion barrage, as shown in Figure 2.

At the diversion barrage, the river inflow is a combination of the flows released from the GZ dam and runoff from the sub-catchment. The area of this sub-catchment is ~450 km<sup>2</sup> constituting only 1.3% of the entire catchment of the Gomal river. This sub-catchment constitutes the study area for detailed analysis in this research.

The sub-catchment is mostly barren, with no essential utilities for human settlements. The community living in the command area of the irrigation system depends entirely on the water from the Gomal river not only for irrigated agriculture but in some parts also for domestic uses.

The existing dam operation is such that water is released from the tailrace of two hydroelectric power units at the GZ dam into the Gomal River. The main spillway has never been operated because water levels in the reservoir have not yet reached the spillway crest level. A low-level outlet is provided in the main dam to flush the sediments, which is operated on an ad hoc basis. This bottom outlet at an elevation of 680 m above mean sea level (dead storage level is 711 m) was designed for flushing out deposited sediments in the reservoir during monsoon, but one of the hydroelectric power units has never worked and, therefore, part of the water demand (8–10 m<sup>3</sup> s −1 ) is supplied through this bottom outlet.

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**Figure 2.** Map of the Gomal river sub-catchment. **Figure 2.** Map of the Gomal river sub-catchment.

*2.2. Data and Methods*  2.2.1. Annual Sediment Yield in Gomal River The long-term annual sediment yield data (1960–2015) was analyzed to find the cumulative trend at the monitoring station before and after the construction of the GZ dam. The monitoring station is located 2.5 km upstream of the diversion barrage site, and hence the sediment yield at this location includes the contribution from the entire catchment of the Gomal river, including the sub-catchment. The monitoring station is maintained by the Water and Power Development Authority (WAPDA) of Pakistan, which is responsible for the collection and analysis of sediment data. Moreover, it is The mean annual rainfall in the sub-catchment is 276 mm yr−<sup>1</sup> . The rainfall events are typically of high intensity, generate significant runoff, and bring with them eroded sediments. Erosion in this sub-catchment is often considered as a leading source of sediment [16] and, therefore, efforts for watershed management and conservation practices are emphasized as a potential solution to this issue of soil erosion [17]. The sediments from the catchment upstream of the GZ dam are trapped in the reservoir behind the dam and flushed through the low-level outlet. This sediment contribution is not quantified and monitored systematically; therefore, the only data available for analysis are at the monitoring station near the diversion barrage.

### *2.2. Data and Methods*

### 2.2.1. Annual Sediment Yield in Gomal River

The long-term annual sediment yield data (1960–2015) was analyzed to find the cumulative trend at the monitoring station before and after the construction of the GZ dam. The monitoring station is located 2.5 km upstream of the diversion barrage site, and hence the sediment yield at this location includes the contribution from the entire catchment of the Gomal river, including the sub-catchment. The monitoring station is maintained by the Water and Power Development Authority (WAPDA) of Pakistan, which is responsible for the collection and analysis of sediment data. Moreover, it is noteworthy that only suspended sediment samples are collected by WAPDA using depth-integrated samplers (DH-48).

### 2.2.2. Assessment of Erosion Rates

The universal soil loss equation (USLE) was developed in 1965 [18] to estimate the rate of soil loss. This empirical equation was improved and revised in 1995, since then it has been known as the RUSLE [1] and has been applied in numerous catchments worldwide. RUSLE is not intended to estimate the sediment yield (as the amount of sediment reaching or passing a point of interest in a given period) instead; its application is limited to calculate the annual soil loss rate. However, the sediment delivery ratio (SDR) method can be used to link soil erosion with sediment delivery to the stream. With the RUSLE model, the average annual rate of soil loss for a catchment of interest can be predicted for any number of scenarios in association with cropping systems, management techniques, and erosion control practices [19]. Therefore, many studies have applied RUSLE to estimate soil loss rates and identification of high-risk areas, e.g., [20–22]. It has become the most widely used approach during an 80-year history of erosion modeling applied in 109 countries [23]. Alewell et al. [23] point out the limitations of USLE-type modeling that it does not address larger rills or gully erosion but is restricted to sheet/interrill and small rill erosion only. Due to these limitations, some researchers, e.g., reference [24] have criticized RUSLE for using it in predicting sediment delivery ratios.

In this research, RUSLE is applied to the sub-catchment of the Gomal river to assess erosion rate and test an improved vegetation scenario.

$$A = \text{RKLSCP} \tag{1}$$

where *A* denotes average annual soil loss (t ha−<sup>1</sup> y −1 ), *R* is rainfall-runoff erosivity factor (MJ mm ha−<sup>1</sup> h <sup>−</sup><sup>1</sup> yr−<sup>1</sup> ), *K* is soil erodibility factor (Mg ha h ha−<sup>1</sup> MJ−<sup>1</sup> mm−<sup>1</sup> ), *LS* is topographic factor, *C* is crop management factor (ranges from zero to 1), and *P* is conservation support practice factor (ranges from zero to 1).

Soil loss predictions using RUSLE yield varying results because the methods used to estimate the factors in Equation (1) are empirically derived. The regional applicability of the RUSLE requires the sub-factors to be adjusted and modified based on the specific characteristics of the study site [25]. Some studies have attempted to evaluate the impact of different RUSLE factors on soil loss. For example, reference [12] found the land slope (*LS*) as the factor most significant factor affecting soil erosion. The authors in [12] conclude that severe erosion occurs along the drainage channels due to steep bank slopes. Similarly, ref [13] found that the land slope (*LS*) factor is that with most influence on soil erosion, followed by *P*, *K*, *C,* and *R*. The support practice *P* may also be an important factor when the management of soil erosion from the catchment is considered [14].

Assessment of soil loss using RUSLE approach requires a careful selection of methods determining its factors. A recent study by [25] reviews the different factors of USLE and RUSLE, and analyses how various studies around the world have adapted the equations to local conditions.

Rainfall-Runoff Erosivity Factor *R*

The factor *R* considers the erosion due to rainfall and runoff, which is the function of long-term rainfall kinetic energy and maximum 30-min intensity [1,26]. For this study, precipitation data were collected from Tank meteorological station (32◦1202300 N, 70◦2303000 E) maintained by the Water and Power Development Authority (WAPDA). The meteorological station does not have an automatic recording rain-gauge, and hence high-intensity rainfall data of considerable length was not available. The rainfall data for the period of 2014–2016 was collected to estimate *R* using an appropriate empirical equation for the study area. Many regional studies have suggested empirical equations (see in [25]) that can be adopted to estimate *R* using monthly rainfall data. The advantage of considering these empirical equations is that they do not necessitate long-term and high-resolution rainfall data and are suitable for use in data-sparse catchments like the Gomal river catchment. Table 1 lists down a few of these empirical equations, which we considered to calculate *R* but finally adopted the empirical equation by [27] in this research. A comparison of *R* calculated with the empirical equations (as shown in Table 1) with the *R* from the global rainfall erosivity dataset is presented in the Results and Discussion section. The global rainfall erosivity dataset is collected from the Joint Research Centre, European Soil Data Centre (ESDAC) (https://esdac.jrc.ec.europa.eu/, accessed on 30 June 2019).

**Table 1.** Different empirical relationships for calculation of rainfall-runoff erosivity factor *R.*


In Table 1, MFI is the modified Fournier index calculated as in Equation (2).

$$\text{MFI} = \sum\_{i=1}^{12} \frac{\text{P}\_i^2}{\text{P}} \tag{2}$$

where p<sup>i</sup> is the monthly rainfall in mm, and p is the annual rainfall in mm.
